qualitative research approaches examples

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

Knowledge Base

Methodology

What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

How does social media shape body image in teenagers?
How do children and adults interpret healthy eating in the UK?
What factors influence employee retention in a large organization?
How is anxiety experienced around the world?
How can teachers integrate social issues into science curriculums?

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Qualitative research approaches
Approach	What does it involve?
Grounded theory	Researchers collect rich data on a topic of interest and develop theories .
	Researchers immerse themselves in groups or organizations to understand their cultures.
Action research	Researchers and participants collaboratively link theory to practice to drive social change.
Phenomenological research	Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.
Narrative research	Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

Academic style
Vague sentences
Style consistency

See an example

qualitative research approaches examples

Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

Observations: recording what you have seen, heard, or encountered in detailed field notes.
Interviews: personally asking people questions in one-on-one conversations.
Focus groups: asking questions and generating discussion among a group of people.
Surveys : distributing questionnaires with open-ended questions.
Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
You take field notes with observations and reflect on your own experiences of the company culture.
You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative data analysis
Approach	When to use	Example
	To describe and categorize common words, phrases, and ideas in qualitative data.	A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.
	To identify and interpret patterns and themes in qualitative data.	A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.
	To examine the content, structure, and design of texts.	A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.
	To study communication and how language is used to achieve effects in specific contexts.	A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Prevent plagiarism. Run a free check.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

Chi square goodness of fit test
Degrees of freedom
Null hypothesis
Discourse analysis
Control groups
Mixed methods research
Non-probability sampling
Quantitative research
Inclusion and exclusion criteria

Research bias

Rosenthal effect
Implicit bias
Cognitive bias
Selection bias
Negativity bias
Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organization to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organize your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Bhandari, P. (2023, June 22). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved August 21, 2024, from https://www.scribbr.com/methodology/qualitative-research/

Is this article helpful?

Pritha Bhandari

Other students also liked, qualitative vs. quantitative research | differences, examples & methods, how to do thematic analysis | step-by-step guide & examples, get unlimited documents corrected.

✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

How to Order

Research Paper Guide

Types Of Qualitative Research

8 Types of Qualitative Research - Overview & Examples

16 min read

What is Qualitative Research?

Qualitative research is a robust and flexible methodology used to explore and understand complex phenomena in-depth.

Unlike quantitative research , qualitative research dives into the rich and complex aspects of human experiences, behaviors, and perceptions.

At its core, this type of research question seek to answer for:

Why do people think or behave a certain way?
What are the underlying motivations and meanings behind actions?
How do individuals perceive and interpret the world around them?

This approach values context, diversity, and the unique perspectives of participants.

Rather than seeking generalizable findings applicable to a broad population, qualitative research aims for detailed insights, patterns, and themes that come from the people being studied.

Characteristics of Qualitative Research

Qualitative research possesses the following characteristics:

Subjective Perspective: Qualitative research explores subjective experiences, emphasizing the uniqueness of human behavior and opinions.
In-Depth Exploration: It involves deep investigation, allowing a comprehensive understanding of specific phenomena.
Open-Ended Questions: Qualitative research uses open-ended questions to encourage detailed, descriptive responses.
Contextual Understanding: It emphasizes the importance of understanding the research context and setting.
Rich Descriptions: Qualitative research produces rich, descriptive findings that contribute to a nuanced understanding of the topic.

Types of Qualitative Research Methods

Researchers collect data on the targeted population, place, or event by using different types of qualitative research analysis.

Each qualitative research method offers a distinct perspective, enabling researchers to reveal concealed meanings, patterns, and valuable insights.

Below are the most commonly used qualitative research types for writing a paper.

Ethnographic Research Method

	To describe and understand cultural characteristics within human societies.
	Gathering existing knowledge and insights from academic and historical sources. Immersion in the environment where the target audience resides, living with and interacting with subjects. Data collection through extensive observation and direct engagement.
	The analysis phase aims to describe the fundamental parameters of the culture under study.
	Comprehensive descriptions of social norms, values, customs, and practices within the studied culture.

Ethnography, a subfield of anthropology, provides a scientific approach to examining human societies and cultures. It ranks among the most widely employed qualitative research techniques.

In ethnographic field notes, researchers actively engage with the environment and live alongside the focus group.

This immersive interaction allows researchers to gain insights into the objectives, motivations, challenges, and distinctive cultural attributes of the individuals under study.

Key cultural characteristics that ethnography helps to illustrate encompass:

Geographical Location
Religious Practices
Tribal Systems
Shared Experiences

Unlike traditional survey and interview-based research methods, ethnographers don't rely on structured questioning.

Instead, they become observers within the community, emphasizing participant observation over an extended period. However, it may also be appropriate to complement observations with interviews of individuals who possess knowledge of the culture.

Ethnographic research can present challenges if the researcher is unfamiliar with the social norms and language of the group being studied.

Furthermore, interpretations made by outsiders may lead to misinterpretations or confusion. Therefore, thorough validation of data is essential before presenting findings.

An effective way to understand customer needs is by observing their daily activities and interactions with a product. This approach doesn't necessitate formulating hypotheses for testing but instead requires immersion in the subjects' social lives.

Narrative Method

Collect data in the form of a cohesive story.

Examining the sequence of events and conducting interviews to describe the significant influences that have shaped an individual's life.

Analyzing various life situations and opportunities that have played a role in the individual's narrative.

Presenting a short narrative that includes themes, conflicts, and challenges.

The narrative research design unfolds over an extended period to compile data, much like crafting a cohesive story. Similar to a narrative structure, it begins with a starting point and progresses through various life situations.

In this method, researchers engage in in-depth interviews and review relevant documents. They explore events that have had a significant impact on an individual's personality and life journey. Interviews may occur over weeks, months, or even years, depending on the depth and scope of the narrative being studied.

The outcome of narrative research is the presentation of a concise story that captures essential themes, conflicts, and challenges. It provides a holistic view of the individual's experiences, both positive and negative, which have shaped their unique narrative.

The narrative method finds practical application in the business world. It can help in understanding the diverse challenges faced by a target audience. Moreover, it can be leveraged to foster innovation and guide the development of products and solutions that resonate with the audience's narrative.

Phenomenological Method

	To describe experiences, events, or situations from various perspectives.
	Collecting data through interviews, observations, surveys, and document analysis. Articulating the experiences related to the phenomenon under study.
	Classifying data and exploring experiences beyond conscious awareness.
	Creation of a database that presents findings from the subject's viewpoint.

The term "phenomenological" pertains to the study of phenomena, which can encompass events, situations, or experiences.

This method is ideal for examining a subject from multiple perspectives and contributing to existing knowledge, with a particular focus on subjective experiences.

Researchers employing the phenomenological method use various data collection techniques, including interviews, site visits, observations, surveys, and document reviews.

These methods help gather rich and diverse data about the phenomenon under investigation.

A central aspect of this technique is capturing how participants experience events or activities, delving into their subjective viewpoints. Ultimately, the research results in the creation of a thematic database that validates the findings and offers insights from the subject's perspective.

The phenomenological research method is valuable for understanding why students are increasingly opting for online courses. It allows researchers to explore the reasons behind this trend from the subjective experiences of students, providing valuable insights into their motivations and preferences.

Grounded Theory Method

To develop theories, identify social developments, and understand ways to address them.

Gathering data through interviews, observations, literature reviews, and document analysis.

Developing theories through a systematic process of data collection, coding, and theory formation.

The development of theories is supported by relevant examples drawn from the collected data.

A grounded theory approach differs from a phenomenological study in that it seeks to explain, provide reasons for, or develop theories behind an event or phenomenon.

It serves as a means to construct new theories by systematically collecting and analyzing data related to a specific phenomenon.

Researchers employing the grounded theory method utilize a variety of data collection techniques, including observation, interviews, literature review , and the analysis of relevant documents.

The focus of content analysis is not individual behaviors but a specific phenomenon or incident.

This method typically involves various coding techniques and large sample sizes to identify themes and develop more comprehensive theories.

Businesses can employ this method to conduct surveys and gain insight into why consumers choose their products or services. The data collected through such surveys can aid companies in enhancing and maintaining customer satisfaction and loyalty.

Case Study Research

	To provide a detailed description of an experience, person, event, or place.
	Gaining a deep understanding of the subject through firsthand experiences and engagement.
	Analyzing the experiences and insights gained from the case study.
	Delivering an in-depth and comprehensive description of the subject under study.

The case study approach entails a comprehensive examination of a subject over an extended period, with a focus on providing detailed insights into the subject, which can be an event, person, business, or place.

Data for case studies is collected from diverse sources, including interviews, direct observation, historical records, and documentation.

Case studies find applications across various disciplines, including law, education, medicine, and the sciences. They can serve both descriptive and explanatory purposes, making them a versatile research methodology .

Researchers often turn to the case study method when they want to explore:

'How' and 'why' research questions
Behaviors under observation
Understanding a specific phenomenon
The contextual factors influencing the phenomena

Businesses can effectively showcase their solutions and problem-solving capabilities through case studies. Let's consider a scenario where Company AB introduces new UX designs in an agile environment. This case study can offer valuable insights for other companies seeking similar enhancements.

Historical Method

	To describe and examine past events for a better understanding of present patterns and the ability to predict future scenarios.

	Analyzing the collected data by assessing its credibility and considering conflicting evidence.
	Presenting the research findings in the form of a biography or scholarly paper.

The historical method aims to describe and analyze past events, offering insights into present patterns and the potential to predict future scenarios.

Researchers formulate research questions based on a hypothetical idea and then rigorously test this idea using multiple historical resources.

Key steps in the historical method include:

Developing a research idea
Identifying appropriate sources such as archives and libraries
Ensuring the reliability and validity of these sources
Creating a well-organized research outline
Systematically collecting research data

The analysis phase involves critically assessing the collected data, accepting or rejecting it based on credibility, and identifying any conflicting evidence.

Ultimately, the outcomes of the historical method are presented in the form of a biography or a scholarly paper that provides a comprehensive account of the research findings.

Businesses can harness the historical method by examining past ad campaigns and the demographics they target. This historical data can inform the creation of new ads and help tailor qualitative market research strategies for better outcomes.

Action Research

	To improve and address practical issues, problems, or challenges in real-world settings by taking action and conducting research simultaneously.

	The outcomes of action research include practical solutions, improved practices, and enhanced understanding of the issue.

Action research is a dynamic research approach focused on addressing practical challenges in real-world settings while simultaneously conducting research to improve the situation.

It follows a cyclic process, starting with the identification of a specific issue or problem in a particular context.

The key steps in action research include:

Planning and implementing actions to address the issue
Collecting data during the action phase to understand its impact
Reflecting on the data and analyzing it to gain insights
Adjusting the action plan based on the analysis

This process may be iterative, with multiple cycles of action and reflection.

The outcomes of action research are practical solutions and improved practices that directly benefit the context in which the research is conducted. Additionally, it leads to a deeper and more nuanced understanding of the issue under investigation.

In education, action research can be used by teachers to identify and address classroom challenges. For instance, a teacher may recognize that a particular teaching method is not effectively engaging students. Through action research, the teacher can develop and implement new teaching strategies, collect data on their effectiveness, analyze the results, and refine the teaching approach to enhance student learning outcomes.

Focus Groups

	To gather qualitative data by engaging a small group of participants in a structured discussion on a specific topic or research question.

	Analyzing the data collected from the focus group discussion to identify themes, patterns, and insights.
	The outcomes of focus groups include rich qualitative data that provide a deeper understanding of the research topic or question.

Focus groups are a qualitative research method used to gather in-depth insights and perspectives on a specific topic or research question.

This approach involves assembling a small group of participants who possess relevant knowledge or experiences related to the research focus.

Key steps in the focus group method include:

Selecting participants
Moderating the discussion
Structuring the conversation around open-ended questions
Collecting data through audio or video recordings and note-taking

The discussion is dynamic and interactive, encouraging participants to share their thoughts, experiences, and opinions.

The analysis phase involves reviewing the data collected from the focus group discussion to identify common themes, patterns, and valuable insights. Focus groups provide rich qualitative data that offer a deeper and more nuanced understanding of the research topic or question.

In the development of a new mobile app, a focus group can be organized with potential users to gather feedback on user interface design and functionality. Participants in the focus group can share their preferences, concerns, and suggestions, providing valuable input to improve the app's usability and appeal.

Tough Essay Due? Hire Tough Writers!

Types of Data Analysis in Qualitative Research

Qualitative research employs different data analysis methods, each suited to specific research goals:

Thematic Analysis: Identifies recurring themes or concepts within data.
Content Analysis: Systematically categorizes and quantifies text or media content.
Narrative Analysis: Focuses on storytelling and narrative elements in data.
Grounded Theory Analysis: Develops or refines theories based on data.
Discourse Analysis: Examines language and communication patterns.
Framework Analysis: Organizes data using predefined categories.
Visual Analysis: Interprets visual data like photos or videos.
Cross-case Analysis: Compares patterns across multiple cases.

The choice depends on research questions and data type, enhancing understanding and insights.

Benefits of Qualitative Research

Qualitative research offers valuable advantages, including:

Flexibility: Adaptable to various research questions and settings.
Holistic Approach: Explores multiple dimensions of phenomena.
Theory Development: Contributes to theory creation or refinement.
Participant Engagement: Fosters active participant involvement.
Complements Quantitative Research: Provides a comprehensive understanding.

All in all, different types of qualitative research methodology can assist in understanding the behavior and motivations of people. Similarly, it will also help in generating original ideas and formulating a better research problem.

However, not everyone can write a good research paper. Thus, if you get stuck at any stage, you can get professional help.

MyPerfectWords.com is the best paper writing service, where you can hire a professional writer for all your ' do my essay ' requests.

We assure you that you will receive high-quality paper at the most reasonable rates.

Contact our team with your " pay for my research paper " queries. We are available 24/7!

Write Essay Within 60 Seconds!

Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

Paper Due? Why Suffer? That’s our Job!

Keep reading

Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years. Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student). In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication). But both of these approaches are necessary for the beginner student. This textbook will have sections dedicated to the process as well as the techniques of qualitative research. This is a true “comprehensive” book for the beginning student. In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction. It covers aspects of research design and research communication as well as methods employed. Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines. And, let’s face it. Textbooks can be boring. I hope readers find this to be a little different. I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research. Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines. These short accounts by practitioners should help inspire students. So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that? This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation. We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us. Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does. Or because that is what “mothers” do by tradition. Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life. Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research. Empirical research is research (investigation) based on evidence. Conclusions can then be drawn from observable data. This observable data can also be “tested” or checked. If the data cannot be tested, that is a good indication that we are not doing research. Note that we can never “prove” conclusively, through observable data, that our mothers love us. We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.” Faith and tradition and authority work differently. Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe. That is why I say that scientific empirical research is a historically specific approach to understand the world. You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church. Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2] For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities. All used the scientific method of observation and testing to advance knowledge. Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority. Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions. New fields of sociology, economics, political science, and anthropology emerged. The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development. Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?” Well, this is actually not really how a researcher would frame the question, as it is too specific to your case. It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother. A social science researcher might ask, “do mothers love their children?” Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration. All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell. If we don’t tell the world, we don’t know the world. We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses. All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not. To be honest, any simple statement will fail to capture the power and depth of qualitative research. One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world. To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe. They take us, as readers, into the time and place of the observation so that we know what it was like to have been there. They capture and communicate someone else’s experience of the world in his or her own words. Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues. Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study. I do a lot of research about first-generation and working-college college students. Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads? A qualitative researcher might ask, how does the college experience differ for first-generation college students? What is it like to carry a lot of debt, and how does this impact the ability to complete college on time? Both sets of questions are important, but they can only be answered using specific tools tailored to those questions. For the former, you need large numbers to make adequate comparisons. For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.” A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader. Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another. In some ways, this can seem like reading particularly insightful novels. But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied. Most of this textbook will be spent conveying those rules and guidelines. Let’s take a look, first, however, at three examples of what the end product looks like. I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book. They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time. I will also provide some information on how these books came to be and the length of time it takes to get them into book version. It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona. In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012. Actually, the dissertation was completed in 2012 but the work that was produced that took several years. The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ). You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title. You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.” It’s a study about “how” people do something – in this case, how they deal with aging and death. This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill. These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ). What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods. We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business. It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4] He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender. So, he set up a research design that would allow him to observe differences. He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American). He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other. He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods. As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention. It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about. It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times . The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that. It helped show how inequality affects people’s everyday lives. For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US. Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does. Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota. Trained as a sociologist, she has written a number of books about gender, race, and power. Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms. Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment. The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs. She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality. Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior. It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles. My students often have a very difficult time with the fictional accounts she includes. But they serve an important communicative purpose here. They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means. By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions. I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts. In fact, the use of fiction in our work remains controversial. When used, it must be clearly identified as a presentation device, as Pierce did. I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied. We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them. This is normal human behavior , in other words. This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings. Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates. I include it here as an example of mixed methods, and for the use of supplementary archival research. I’ve done a lot of research over the years on first-generation, low-income, and working-class college students. I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general. As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it. And when I entered graduate school, I realized with dismay that there were very few people like me there. I worried about becoming too different from my family and friends back home. And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on. And so I wrote my dissertation and first two books about working-class college students. These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ). But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college? Do working-class students fare as well as their peers? I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated. To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty. These private colleges tend to have more money and resources so they can provide financial aid to low-income students. They also attract some very wealthy students. Because they enroll students across the class spectrum, I would be able to draw comparisons. I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation). This is what we call a “mixed methods” approach because we use both quantitative and qualitative data. The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school). But the survey analyses could not explain why these differences existed. For that, I needed to talk to people and ask them about their motivations and aspirations. I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond. Specifically, I identified three versions of gameplay. Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school. They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad. This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector. In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital. They did this by joining fraternities and sororities and playing club sports. This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs. Finally, low-income, first-generation, and working-class students were often adrift. They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college. They spent time working and studying rather than partying or building their resumes. All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college. But these three versions of gameplay led to distinct outcomes that advantaged some students over others. I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher. They also help explain why qualitative research is so important. Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit. For that, we need tools that allow us to listen and make sense of what people tell us and show us. That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods. The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study). The second half reviews various data collection and data analysis techniques. Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other. That said, each chapter can be read on its own for assistance with a particular narrow topic. In addition to the chapters, a helpful glossary can be found in the back of the book. Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process. How does one begin a study? What is an appropriate research question? How is the study to be done – with what methods ? Involving what people and sites? Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals. Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world. What is it possible for us to know about how other people think or why they behave the way they do? What does it mean to say something is a “fact” or that it is “well-known” and understood? Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research). Qualitative researchers have adopted various epistemological approaches. Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection. In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of. If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data. The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect. For that reason, it is important to pull out that lens (articulate the research question) before you get started. In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging. It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor). Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question. Developing a good research question is thus crucial to effective design and a successful outcome. Chapter 4 will provide pointers on how to do this. Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling . After you have developed a research question and have a general idea of how you will collect data (Observations? Interviews?), how do you go about actually finding people and sites to study? Although there is no “correct number” of people to interview , the sample should follow the research question and research design. Unlike quantitative research, qualitative research involves nonprobability sampling. Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research. Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting. As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend. As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us . Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have. Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked. As a practical matter, it should also be read closely with chapters 6 and 8. Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm. There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us. Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused. Because each research project is unique, the standards of care for each study are unique. Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances. Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research. If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance. Minimizing the harm in one area may require possible harm in another. Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) . Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects . Every institution that receives funding from the federal government has an IRB. IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research. This group review serves an important role in the protection of the rights and welfare of human research subjects. Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive. Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research. Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature. Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams). What any of us finds and reports back becomes part of a much larger body of knowledge. Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute. When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds). But there had been a lot published by professors who had grown up working class and made it through college despite the odds. These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed. Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection. Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos. Techniques can be effectively combined, depending on the research question and the aims and goals of the study. Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed. Chapters 11 through 17 cover various data collection techniques and approaches. Chapters 18 and 19 provide a very simple overview of basic data analysis. Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research. This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival). An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available. Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation. Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group. Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant). Focus groups explicitly use group interaction to assist in the data collection. They are best used to collect data on a specific topic that is non-personal and shared among the group. For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020. Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation . Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed. For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions. Chapter 13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world. Clifford Geertz called this “deep hanging out.” Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people. These interactions and conversations may take place over months or even years. As can be expected, there are some costs to this technique, as well as some very large rewards when done competently. Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist . A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews. Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here. There are several advantages and some disadvantages to taking this route. Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects). Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time. Fortunately, humans leave many traces and we can often answer questions we have by examining those traces. Special collections and archives can be goldmines for social science research. This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis . Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here. Content analysis involves interpreting meaning from a body of text. This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post. I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed. Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest. In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue. This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations. Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns. What is a code and how does it work? What are the different ways of coding data, and when should you use them? What is a codebook, and why do you need one? What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized. These later rounds of coding are essential to getting the most out of the data we’ve collected. As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process. By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results. Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting. Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project. Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality. Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them. And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students. This is for two reasons. First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you. Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond). It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation. Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
Really work on design. Doing qualitative research effectively takes a lot of planning. Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here! Do not expect your first interview to be perfect. You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too. This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple. And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases? Having a plan in hand will also help prevent you from collecting too much extraneous data.
Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences. For example, is an “n” of 1 really sufficient? Yes! But not everyone will agree.
Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research). Do it because you are convinced it is right for your goals, aims, and research questions.
Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process. Even though qualitative research often involves human subjects, it can be pretty lonely. A lot of times you will feel like you are working without a net. You have to create one for yourself. Take care of yourself.
And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation. There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
Historians are a special case here. Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research. History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here. Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data. Examples of common methods in qualitative research are interviews , observations , and documentary analysis . One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms. See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation. The positing of a hypothesis is often the first step in quantitative research but not in qualitative research. Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study. This will form the anchor of the research design, collection, and analysis. Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations. Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research. Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study. In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge. For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer. See, e.g., constructivism , subjectivism, and objectivism .

An approach that refutes the possibility of neutrality in social science research. All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13). In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context. Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative. In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from. Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research. Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings. This remains true even when dealing with historical archives and other content. Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research: (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography.

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview. The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences. It is sometimes referred to as an “in-depth” interview. See also interview and interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork . The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer). This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness. In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity). The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding. Calling someone a “positivist” is often intended as an insult. See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions. Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography . These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said. They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages. See coding frame and codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction. This approach was pioneered by the sociologists Glaser and Strauss (1967). The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences. Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB. The protocol serves as the recipe for the conduct of the research activity. It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research. Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

Knowledge Base
Methodology
What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

How does social media shape body image in teenagers?
How do children and adults interpret healthy eating in the UK?
What factors influence employee retention in a large organisation?
How is anxiety experienced around the world?
How can teachers integrate social issues into science curriculums?

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

Qualitative research approaches
Approach	What does it involve?
Grounded theory	Researchers collect rich data on a topic of interest and develop theories .
	Researchers immerse themselves in groups or organisations to understand their cultures.
	Researchers and participants collaboratively link theory to practice to drive social change.
Phenomenological research	Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences.
Narrative research	Researchers examine how stories are told to understand how participants perceive and make sense of their experiences.

Prevent plagiarism, run a free check.

Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

Observations: recording what you have seen, heard, or encountered in detailed field notes.
Interviews: personally asking people questions in one-on-one conversations.
Focus groups: asking questions and generating discussion among a group of people.
Surveys : distributing questionnaires with open-ended questions.
Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
You take field notes with observations and reflect on your own experiences of the company culture.
You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative data analysis
Approach	When to use	Example
	To describe and categorise common words, phrases, and ideas in qualitative data.	A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps.
	To identify and interpret patterns and themes in qualitative data.	A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity.
	To examine the content, structure, and design of texts.	A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade.
	To study communication and how language is used to achieve effects in specific contexts.	A political scientist could use discourse analysis to study how politicians generate trust in election campaigns.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

Limited generalisability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .

Labour-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

There are five common approaches to qualitative research :

Grounded theory involves collecting data in order to develop new theories.
Ethnography involves immersing yourself in a group or organisation to understand its culture.
Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
Phenomenological research involves investigating phenomena through people’s lived experiences.
Action research links theory and practice in several cycles to drive innovative changes.

There are various approaches to qualitative data analysis , but they all share five steps in common:

Prepare and organise your data.
Review and explore your data.
Develop a data coding system.
Assign codes to the data.
Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Bhandari, P. (2023, January 30). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved 21 August 2024, from https://www.scribbr.co.uk/research-methods/introduction-to-qualitative-research/

Is this article helpful?

Pritha Bhandari

Educational resources and simple solutions for your research journey

What is Qualitative Research? Methods, Types, Approaches and Examples

Qualitative research is a type of method that researchers use depending on their study requirements. Research can be conducted using several methods, but before starting the process, researchers should understand the different methods available to decide the best one for their study type. The type of research method needed depends on a few important criteria, such as the research question, study type, time, costs, data availability, and availability of respondents. The two main types of methods are qualitative research and quantitative research. Sometimes, researchers may find it difficult to decide which type of method is most suitable for their study. Keeping in mind a simple rule of thumb could help you make the correct decision. Quantitative research should be used to validate or test a theory or hypothesis and qualitative research should be used to understand a subject or event or identify reasons for observed patterns.

Qualitative research methods are based on principles of social sciences from several disciplines like psychology, sociology, and anthropology. In this method, researchers try to understand the feelings and motivation of their respondents, which would have prompted them to select or give a particular response to a question. Here are two qualitative research examples :

Two brands (A & B) of the same medicine are available at a pharmacy. However, Brand A is more popular and has higher sales. In qualitative research , the interviewers would ideally visit a few stores in different areas and ask customers their reason for selecting either brand. Respondents may have different reasons that motivate them to select one brand over the other, such as brand loyalty, cost, feedback from friends, doctor’s suggestion, etc. Once the reasons are known, companies could then address challenges in that specific area to increase their product’s sales.
A company organizes a focus group meeting with a random sample of its product’s consumers to understand their opinion on a new product being launched.

Table of Contents

What is qualitative research? 1

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data. The findings of qualitative research are expressed in words and help in understanding individuals’ subjective perceptions about an event, condition, or subject. This type of research is exploratory and is used to generate hypotheses or theories from data. Qualitative data are usually in the form of text, videos, photographs, and audio recordings. There are multiple qualitative research types , which will be discussed later.

Qualitative research methods 2

Researchers can choose from several qualitative research methods depending on the study type, research question, the researcher’s role, data to be collected, etc.

The following table lists the common qualitative research approaches with their purpose and examples, although there may be an overlap between some.


Narrative	Explore the experiences of individuals and tell a story to give insight into human lives and behaviors. Narratives can be obtained from journals, letters, conversations, autobiographies, interviews, etc.	A researcher collecting information to create a biography using old documents, interviews, etc.
Phenomenology	Explain life experiences or phenomena, focusing on people’s subjective experiences and interpretations of the world.	Researchers exploring the experiences of family members of an individual undergoing a major surgery.
Grounded theory	Investigate process, actions, and interactions, and based on this grounded or empirical data a theory is developed. Unlike experimental research, this method doesn’t require a hypothesis theory to begin with.	A company with a high attrition rate and no prior data may use this method to understand the reasons for which employees leave.
Ethnography	Describe an ethnic, cultural, or social group by observation in their naturally occurring environment.	A researcher studying medical personnel in the immediate care division of a hospital to understand the culture and staff behaviors during high capacity.
Case study	In-depth analysis of complex issues in real-life settings, mostly used in business, law, and policymaking. Learnings from case studies can be implemented in other similar contexts.	A case study about how a particular company turned around its product sales and the marketing strategies they used could help implement similar methods in other companies.

Types of qualitative research 3,4

The data collection methods in qualitative research are designed to assess and understand the perceptions, motivations, and feelings of the respondents about the subject being studied. The different qualitative research types include the following:

In-depth or one-on-one interviews : This is one of the most common qualitative research methods and helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event. These interviews are usually conversational and encourage the respondents to express their opinions freely. Semi-structured interviews, which have open-ended questions (where the respondents can answer more than just “yes” or “no”), are commonly used. Such interviews can be either face-to-face or telephonic, and the duration can vary depending on the subject or the interviewer. Asking the right questions is essential in this method so that the interview can be led in the suitable direction. Face-to-face interviews also help interviewers observe the respondents’ body language, which could help in confirming whether the responses match.
Document study/Literature review/Record keeping : Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
Focus groups : Usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic. Focus groups ensure constructive discussions to understand the why, what, and, how about the topic. These group meetings need not always be in-person. In recent times, online meetings are also encouraged, and online surveys could also be administered with the option to “write” subjective answers as well. However, this method is expensive and is mostly used for new products and ideas.
Qualitative observation : In this method, researchers collect data using their five senses—sight, smell, touch, taste, and hearing. This method doesn’t include any measurements but only the subjective observation. For example, “The dessert served at the bakery was creamy with sweet buttercream frosting”; this observation is based on the taste perception.

Qualitative research : Data collection and analysis

Qualitative data collection is the process by which observations or measurements are gathered in research.
The data collected are usually non-numeric and subjective and could be recorded in various methods, for instance, in case of one-to-one interviews, the responses may be recorded using handwritten notes, and audio and video recordings, depending on the interviewer and the setting or duration.
Once the data are collected, they should be transcribed into meaningful or useful interpretations. An experienced researcher could take about 8-10 hours to transcribe an interview’s recordings. All such notes and recordings should be maintained properly for later reference.
Some interviewers make use of “field notes.” These are not exactly the respondents’ answers but rather some observations the interviewer may have made while asking questions and may include non-verbal cues or any information about the setting or the environment. These notes are usually informal and help verify respondents’ answers.

2. Qualitative data analysis

This process involves analyzing all the data obtained from the qualitative research methods in the form of text (notes), audio-video recordings, and pictures.
Text analysis is a common form of qualitative data analysis in which researchers examine the social lives of the participants and analyze their words, actions, etc. in specific contexts. Social media platforms are now playing an important role in this method with researchers analyzing all information shared online.

There are usually five steps in the qualitative data analysis process: 5

Prepare and organize the data
Transcribe interviews
Collect and document field notes and other material
Review and explore the data
Examine the data for patterns or important observations
Develop a data coding system
Create codes to categorize and connect the data
Assign these codes to the data or responses
Review the codes
Identify recurring themes, opinions, patterns, etc.
Present the findings
Use the best possible method to present your observations

The following table 6 lists some common qualitative data analysis methods used by companies to make important decisions, with examples and when to use each. The methods may be similar and can overlap.


Content analysis	To identify patterns in text, by grouping content into words, concepts, and themes; that is, determine presence of certain words or themes in some text	Researchers examining the language used in a journal article to search for bias
Narrative analysis	To understand people’s perspectives on specific issues. Focuses on people’s stories and the language used to tell these stories	A researcher conducting one or several in-depth interviews with an individual over a long period
Discourse analysis	To understand political, cultural, and power dynamics in specific contexts; that is, how people express themselves in different social contexts	A researcher studying a politician’s speeches across multiple contexts, such as audience, region, political history, etc.
Thematic analysis	To interpret the meaning behind the words used by people. This is done by identifying repetitive patterns or themes by reading through a dataset	Researcher analyzing raw data to explore the impact of high-stakes examinations on students and parents

Characteristics of qualitative research methods 4

Unstructured raw data : Qualitative research methods use unstructured, non-numerical data , which are analyzed to generate subjective conclusions about specific subjects, usually presented descriptively, instead of using statistical data.
Site-specific data collection : In qualitative research methods , data are collected at specific areas where the respondents or researchers are either facing a challenge or have a need to explore. The process is conducted in a real-world setting and participants do not need to leave their original geographical setting to be able to participate.
Researchers’ importance : Researchers play an instrumental role because, in qualitative research , communication with respondents is an essential part of data collection and analysis. In addition, researchers need to rely on their own observation and listening skills during an interaction and use and interpret that data appropriately.
Multiple methods : Researchers collect data through various methods, as listed earlier, instead of relying on a single source. Although there may be some overlap between the qualitative research methods , each method has its own significance.
Solving complex issues : These methods help in breaking down complex problems into more useful and interpretable inferences, which can be easily understood by everyone.
Unbiased responses : Qualitative research methods rely on open communication where the participants are allowed to freely express their views. In such cases, the participants trust the interviewer, resulting in unbiased and truthful responses.
Flexible : The qualitative research method can be changed at any stage of the research. The data analysis is not confined to being done at the end of the research but can be done in tandem with data collection. Consequently, based on preliminary analysis and new ideas, researchers have the liberty to change the method to suit their objective.

When to use qualitative research 4

The following points will give you an idea about when to use qualitative research .

When the objective of a research study is to understand behaviors and patterns of respondents, then qualitative research is the most suitable method because it gives a clear insight into the reasons for the occurrence of an event.
A few use cases for qualitative research methods include:
New product development or idea generation
Strengthening a product’s marketing strategy
Conducting a SWOT analysis of product or services portfolios to help take important strategic decisions
Understanding purchasing behavior of consumers
Understanding reactions of target market to ad campaigns
Understanding market demographics and conducting competitor analysis
Understanding the effectiveness of a new treatment method in a particular section of society

A qualitative research method case study to understand when to use qualitative research 7

Context : A high school in the US underwent a turnaround or conservatorship process and consequently experienced a below average teacher retention rate. Researchers conducted qualitative research to understand teachers’ experiences and perceptions of how the turnaround may have influenced the teachers’ morale and how this, in turn, would have affected teachers’ retention.

Method : Purposive sampling was used to select eight teachers who were employed with the school before the conservatorship process and who were subsequently retained. One-on-one semi-structured interviews were conducted with these teachers. The questions addressed teachers’ perspectives of morale and their views on the conservatorship process.

Results : The study generated six factors that may have been influencing teachers’ perspectives: powerlessness, excessive visitations, loss of confidence, ineffective instructional practices, stress and burnout, and ineffective professional development opportunities. Based on these factors, four recommendations were made to increase teacher retention by boosting their morale.

Advantages of qualitative research 1

Reflects real-world settings , and therefore allows for ambiguities in data, as well as the flexibility to change the method based on new developments.
Helps in understanding the feelings or beliefs of the respondents rather than relying only on quantitative data.
Uses a descriptive and narrative style of presentation, which may be easier to understand for people from all backgrounds.
Some topics involving sensitive or controversial content could be difficult to quantify and so qualitative research helps in analyzing such content.
The availability of multiple data sources and research methods helps give a holistic picture.
There’s more involvement of participants, which gives them an assurance that their opinion matters, possibly leading to unbiased responses.

Disadvantages of qualitative research 1

Large-scale data sets cannot be included because of time and cost constraints.
Ensuring validity and reliability may be a challenge because of the subjective nature of the data, so drawing definite conclusions could be difficult.
Replication by other researchers may be difficult for the same contexts or situations.
Generalization to a wider context or to other populations or settings is not possible.
Data collection and analysis may be time consuming.
Researcher’s interpretation may alter the results causing an unintended bias.

Differences between qualitative research and quantitative research 1


Purpose and design	Explore ideas, formulate hypotheses; more subjective	Test theories and hypotheses, discover causal relationships; measurable and more structured
Data collection method	Semi-structured interviews/surveys with open-ended questions, document study/literature reviews, focus groups, case study research, ethnography	Experiments, controlled observations, questionnaires and surveys with a rating scale or closed-ended questions. The methods can be experimental, quasi-experimental, descriptive, or correlational.
Data analysis	Content analysis (determine presence of certain words/concepts in texts), grounded theory (hypothesis creation by data collection and analysis), thematic analysis (identify important themes/patterns in data and use these to address an issue)	Statistical analysis using applications such as Excel, SPSS, R
Sample size	Small	Large
Example	A company organizing focus groups or one-to-one interviews to understand customers’ (subjective) opinions about a specific product, based on which the company can modify their marketing strategy	Customer satisfaction surveys sent out by companies. Customers are asked to rate their experience on a rating scale of 1 to 5

Frequently asked questions on qualitative research

Q: how do i know if qualitative research is appropriate for my study .

A: Here’s a simple checklist you could use:

Not much is known about the subject being studied.
There is a need to understand or simplify a complex problem or situation.
Participants’ experiences/beliefs/feelings are required for analysis.
There’s no existing hypothesis to begin with, rather a theory would need to be created after analysis.
You need to gather in-depth understanding of an event or subject, which may not need to be supported by numeric data.

Q: How do I ensure the reliability and validity of my qualitative research findings?

A: To ensure the validity of your qualitative research findings you should explicitly state your objective and describe clearly why you have interpreted the data in a particular way. Another method could be to connect your data in different ways or from different perspectives to see if you reach a similar, unbiased conclusion.

To ensure reliability, always create an audit trail of your qualitative research by describing your steps and reasons for every interpretation, so that if required, another researcher could trace your steps to corroborate your (or their own) findings. In addition, always look for patterns or consistencies in the data collected through different methods.

Q: Are there any sampling strategies or techniques for qualitative research ?

A: Yes, the following are few common sampling strategies used in qualitative research :

1. Convenience sampling

Selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.

2. Purposive sampling

Participants are grouped according to predefined criteria based on a specific research question. Sample sizes are often determined based on theoretical saturation (when new data no longer provide additional insights).

3. Snowball sampling

Already selected participants use their social networks to refer the researcher to other potential participants.

4. Quota sampling

While designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

Q: What ethical standards need to be followed with qualitative research ?

A: The following ethical standards should be considered in qualitative research:

Anonymity : The participants should never be identified in the study and researchers should ensure that no identifying information is mentioned even indirectly.
Confidentiality : To protect participants’ confidentiality, ensure that all related documents, transcripts, notes are stored safely.
Informed consent : Researchers should clearly communicate the objective of the study and how the participants’ responses will be used prior to engaging with the participants.

Q: How do I address bias in my qualitative research ?

A: You could use the following points to ensure an unbiased approach to your qualitative research :

Check your interpretations of the findings with others’ interpretations to identify consistencies.
If possible, you could ask your participants if your interpretations convey their beliefs to a significant extent.
Data triangulation is a way of using multiple data sources to see if all methods consistently support your interpretations.
Contemplate other possible explanations for your findings or interpretations and try ruling them out if possible.
Conduct a peer review of your findings to identify any gaps that may not have been visible to you.
Frame context-appropriate questions to ensure there is no researcher or participant bias.

We hope this article has given you answers to the question “ what is qualitative research ” and given you an in-depth understanding of the various aspects of qualitative research , including the definition, types, and approaches, when to use this method, and advantages and disadvantages, so that the next time you undertake a study you would know which type of research design to adopt.

References:

McLeod, S. A. Qualitative vs. quantitative research. Simply Psychology [Accessed January 17, 2023]. www.simplypsychology.org/qualitative-quantitative.html
Omniconvert website [Accessed January 18, 2023]. https://www.omniconvert.com/blog/qualitative-research-definition-methodology-limitation-examples/
Busetto L., Wick W., Gumbinger C. How to use and assess qualitative research methods. Neurological Research and Practice [Accessed January 19, 2023] https://neurolrespract.biomedcentral.com/articles/10.1186/s42466-020-00059
QuestionPro website. Qualitative research methods: Types & examples [Accessed January 16, 2023]. https://www.questionpro.com/blog/qualitative-research-methods/
Campuslabs website. How to analyze qualitative data [Accessed January 18, 2023]. https://baselinesupport.campuslabs.com/hc/en-us/articles/204305675-How-to-analyze-qualitative-data
Thematic website. Qualitative data analysis: Step-by-guide [Accessed January 20, 2023]. https://getthematic.com/insights/qualitative-data-analysis/
Lane L. J., Jones D., Penny G. R. Qualitative case study of teachers’ morale in a turnaround school. Research in Higher Education Journal . https://files.eric.ed.gov/fulltext/EJ1233111.pdf
Meetingsnet website. 7 FAQs about qualitative research and CME [Accessed January 21, 2023]. https://www.meetingsnet.com/cme-design/7-faqs-about-qualitative-research-and-cme
Qualitative research methods: A data collector’s field guide. Khoury College of Computer Sciences. Northeastern University. https://course.ccs.neu.edu/is4800sp12/resources/qualmethods.pdf

Editage All Access is a subscription-based platform that unifies the best AI tools and services designed to speed up, simplify, and streamline every step of a researcher’s journey. The Editage All Access Pack is a one-of-a-kind subscription that unlocks full access to an AI writing assistant, literature recommender, journal finder, scientific illustration tool, and exclusive discounts on professional publication services from Editage.

Based on 22+ years of experience in academia, Editage All Access empowers researchers to put their best research forward and move closer to success. Explore our top AI Tools pack, AI Tools + Publication Services pack, or Build Your Own Plan. Find everything a researcher needs to succeed, all in one place –  Get All Access now starting at just $14 a month !  

What are the Best Research Funding Sources

Inductive vs. Deductive Research Approach

Integrations

What's new?

In-Product Prompts

Participant Management

Interview Studies

Prototype Testing

Card Sorting

Tree Testing

Live Website Testing

Automated Reports

Templates Gallery

Choose from our library of pre-built mazes to copy, customize, and share with your own users

Browse all templates

Financial Services

Tech & Software

Product Designers

Product Managers

User Researchers

By use case

Concept & Idea Validation

Wireframe & Usability Test

Content & Copy Testing

Feedback & Satisfaction

Content Hub

Educational resources for product, research and design teams

Explore all resources

Question Bank

Maze Research Success Hub

Guides & Reports

Help Center

Future of User Research Report

The Optimal Path Podcast

Qualitative research examples: How to unlock, rich, descriptive insights

User Research

Aug 19, 2024 • 17 minutes read

Qualitative research examples: How to unlock, rich, descriptive insights

Qualitative research uncovers in-depth user insights, but what does it look like? Here are seven methods and examples to help you get the data you need.

Armin Tanovic

Behind every what, there’s a why . Qualitative research is how you uncover that why. It enables you to connect with users and understand their thoughts, feelings, wants, needs, and pain points.

There’s many methods for conducting qualitative research, and many objectives it can help you pursue—you might want to explore ways to improve NPS scores, combat reduced customer retention, or understand (and recreate) the success behind a well-received product. The common thread? All these metrics impact your business, and qualitative research can help investigate and improve that impact.

In this article, we’ll take you through seven methods and examples of qualitative research, including when and how to use them.

Qualitative UX research made easy

Conduct qualitative research with Maze, analyze data instantly, and get rich, descriptive insights that drive decision-making.

7 Qualitative research methods: An overview

There are various qualitative UX research methods that can help you get in-depth, descriptive insights. Some are suited to specific phases of the design and development process, while others are more task-oriented.

Here’s our overview of the most common qualitative research methods. Keep reading for their use cases, and detailed examples of how to conduct them.

Method
User interviews
Focus groups
Ethnographic research
Qualitative observation
Case study research
Secondary research
Open-ended surveys			to extract descriptive insights.

1. User interviews

A user interview is a one-on-one conversation between a UX researcher, designer or Product Manager and a target user to understand their thoughts, perspectives, and feelings on a product or service. User interviews are a great way to get non-numerical data on individual experiences with your product, to gain a deeper understanding of user perspectives.

Interviews can be structured, semi-structured, or unstructured . Structured interviews follow a strict interview script and can help you get answers to your planned questions, while semi and unstructured interviews are less rigid in their approach and typically lead to more spontaneous, user-centered insights.

When to use user interviews

Interviews are ideal when you want to gain an in-depth understanding of your users’ perspectives on your product or service, and why they feel a certain way.

Interviews can be used at any stage in the product design and development process, being particularly helpful during:

The discovery phase: To better understand user needs, problems, and the context in which they use your product—revealing the best potential solutions
The design phase: To get contextual feedback on mockups, wireframes, and prototypes, helping you pinpoint issues and the reasons behind them
Post-launch: To assess if your product continues to meet users’ shifting expectations and understand why or why not

How to conduct user interviews: The basics

Draft questions based on your research objectives
Recruit relevant research participants and schedule interviews
Conduct the interview and transcribe responses
Analyze the interview responses to extract insights
Use your findings to inform design, product, and business decisions

💡 A specialized user interview tool makes interviewing easier. With Maze Interview Studies , you can recruit, host, and analyze interviews all on one platform.

User interviews: A qualitative research example

Let’s say you’ve designed a recruitment platform, called Tech2Talent , that connects employers with tech talent. Before starting the design process, you want to clearly understand the pain points employers experience with existing recruitment tools'.

You draft a list of ten questions for a semi-structured interview for 15 different one-on-one interviews. As it’s semi-structured, you don’t expect to ask all the questions—the script serves as more of a guide.

One key question in your script is: “Have tech recruitment platforms helped you find the talent you need in the past?”

Most respondents answer with a resounding and passionate ‘no’ with one of them expanding:

“For our company, it’s been pretty hit or miss honestly. They let just about anyone make a profile and call themselves tech talent. It’s so hard sifting through serious candidates. I can’t see any of their achievements until I invest time setting up an interview.”

You begin to notice a pattern in your responses: recruitment tools often lack easily accessible details on talent profiles.

You’ve gained contextual feedback on why other recruitment platforms fail to solve user needs.

2. Focus groups

A focus group is a research method that involves gathering a small group of people—around five to ten users—to discuss a specific topic, such as their’ experience with your new product feature. Unlike user interviews, focus groups aim to capture the collective opinion of a wider market segment and encourage discussion among the group.

When to use focus groups

You should use focus groups when you need a deeper understanding of your users’ collective opinions. The dynamic discussion among participants can spark in-depth insights that might not emerge from regular interviews.

Focus groups can be used before, during, and after a product launch. They’re ideal:

Throughout the problem discovery phase: To understand your user segment’s pain points and expectations, and generate product ideas
Post-launch: To evaluate and understand the collective opinion of your product’s user experience
When conducting market research: To grasp usage patterns, consumer perceptions, and market opportunities for your product

How to conduct focus group studies: The basics

Draft prompts to spark conversation, or a series of questions based on your UX research objectives
Find a group of five to ten users who are representative of your target audience (or a specific user segment) and schedule your focus group session
Conduct the focus group by talking and listening to users, then transcribe responses
Analyze focus group responses and extract insights
Use your findings to inform design decisions

The number of participants can make it difficult to take notes or do manual transcriptions. We recommend using a transcription or a specialized UX research tool , such as Maze, that can automatically create ready-to-share reports and highlight key user insights.

Focus groups: A qualitative research example

You’re a UX researcher at FitMe , a fitness app that creates customized daily workouts for gym-goers. Unlike many other apps, FitMe takes into account the previous day’s workout and aims to create one that allows users to effectively rest different muscles.

However, FitMe has an issue. Users are generating workouts but not completing them. They’re accessing the app, taking the necessary steps to get a workout for the day, but quitting at the last hurdle.

Time to talk to users.

You organize a focus group to get to the root of the drop-off issue. You invite five existing users, all of whom have dropped off at the exact point you’re investigating, and ask them questions to uncover why.

A dialog develops:

Participant 1: “Sometimes I’ll get a workout that I just don’t want to do. Sure, it’s a good workout—but I just don’t want to physically do it. I just do my own thing when that happens.”

Participant 2: “Same here, some of them are so boring. I go to the gym because I love it. It’s an escape.”

Participant 3: “Right?! I get that the app generates the best one for me on that specific day, but I wish I could get a couple of options.”

Participant 4: “I’m the same, there are some exercises I just refuse to do. I’m not coming to the gym to do things I dislike.”

Conducting the focus groups and reviewing the transcripts, you realize that users want options. A workout that works for one gym-goer doesn’t necessarily work for the next.

A possible solution? Adding the option to generate a new workout (that still considers previous workouts)and the ability to blacklist certain exercises, like burpees.

3. Ethnographic research

Ethnographic research is a research method that involves observing and interacting with users in a real-life environment. By studying users in their natural habitat, you can understand how your product fits into their daily lives.

Ethnographic research can be active or passive. Active ethnographic research entails engaging with users in their natural environment and then following up with methods like interviews. Passive ethnographic research involves letting the user interact with the product while you note your observations.

When to use ethnographic research

Ethnographic research is best suited when you want rich insights into the context and environment in which users interact with your product. Keep in mind that you can conduct ethnographic research throughout the entire product design and development process —from problem discovery to post-launch. However, it’s mostly done early in the process:

Early concept development: To gain an understanding of your user's day-to-day environment. Observe how they complete tasks and the pain points they encounter. The unique demands of their everyday lives will inform how to design your product.
Initial design phase: Even if you have a firm grasp of the user’s environment, you still need to put your solution to the test. Conducting ethnographic research with your users interacting with your prototype puts theory into practice.

How to conduct ethnographic research:

Recruit users who are reflective of your audience
Meet with them in their natural environment, and tell them to behave as they usually would
Take down field notes as they interact with your product
Engage with your users, ask questions, or host an in-depth interview if you’re doing an active ethnographic study
Collect all your data and analyze it for insights

While ethnographic studies provide a comprehensive view of what potential users actually do, they are resource-intensive and logistically difficult. A common alternative is diary studies. Like ethnographic research, diary studies examine how users interact with your product in their day-to-day, but the data is self-reported by participants.

⚙️ Recruiting participants proving tough and time-consuming? Maze Panel makes it easy, with 400+ filters to find your ideal participants from a pool of 3 million participants.

Ethnographic research: A qualitative research example

You're a UX researcher for a project management platform called ProFlow , and you’re conducting an ethnographic study of the project creation process with key users, including a startup’s COO.

The first thing you notice is that the COO is rushing while navigating the platform. You also take note of the 46 tabs and Zoom calls opened on their monitor. Their attention is divided, and they let out an exasperated sigh as they repeatedly hit “refresh” on your website’s onboarding interface.

You conclude the session with an interview and ask, “How easy or difficult did you find using ProFlow to coordinate a project?”

The COO answers: “Look, the whole reason we turn to project platforms is because we need to be quick on our feet. I’m doing a million things so I need the process to be fast and simple. The actual project management is good, but creating projects and setting up tables is way too complicated.”

You realize that ProFlow ’s project creation process takes way too much time for professionals working in fast-paced, dynamic environments. To solve the issue, propose a quick-create option that enables them to move ahead with the basics instead of requiring in-depth project details.

4. Qualitative observation

Qualitative observation is a similar method to ethnographic research, though not as deep. It involves observing your users in a natural or controlled environment and taking notes as they interact with a product. However, be sure not to interrupt them, as this compromises the integrity of the study and turns it into active ethnographic research.

When to qualitative observation

Qualitative observation is best when you want to record how users interact with your product without anyone interfering. Much like ethnographic research, observation is best done during:

Early concept development: To help you understand your users' daily lives, how they complete tasks, and the problems they deal with. The observations you collect in these instances will help you define a concept for your product.
Initial design phase: Observing how users deal with your prototype helps you test if they can easily interact with it in their daily environments

How to conduct qualitative observation:

Recruit users who regularly use your product
Meet with users in either their natural environment, such as their office, or within a controlled environment, such as a lab
Observe them and take down field notes based on what you notice

Qualitative observation: An qualitative research example

You’re conducting UX research for Stackbuilder , an app that connects businesses with tools ideal for their needs and budgets. To determine if your app is easy to use for industry professionals, you decide to conduct an observation study.

Sitting in with the participant, you notice they breeze past the onboarding process, quickly creating an account for their company. Yet, after specifying their company’s budget, they suddenly slow down. They open links to each tool’s individual page, confusingly switching from one tab to another. They let out a sigh as they read through each website.

Conducting your observation study, you realize that users find it difficult to extract information from each tool’s website. Based on your field notes, you suggest including a bullet-point summary of each tool directly on your platform.

5. Case study research

Case studies are a UX research method that provides comprehensive and contextual insights into a real-world case over a long period of time. They typically include a range of other qualitative research methods, like interviews, observations, and ethnographic research. A case study allows you to form an in-depth analysis of how people use your product, helping you uncover nuanced differences between your users.

When to use case studies

Case studies are best when your product involves complex interactions that need to be tracked over a longer period or through in-depth analysis. You can also use case studies when your product is innovative, and there’s little existing data on how users interact with it.

As for specific phases in the product design and development process:

Initial design phase: Case studies can help you rigorously test for product issues and the reasons behind them, giving you in-depth feedback on everything between user motivations, friction points, and usability issues
Post-launch phase: Continuing with case studies after launch can give you ongoing feedback on how users interact with the product in their day-to-day lives. These insights ensure you can meet shifting user expectations with product updates and future iterations

How to conduct case studies:

Outline an objective for your case study such as examining specific user tasks or the overall user journey
Select qualitative research methods such as interviews, ethnographic studies, or observations
Collect and analyze your data for comprehensive insights
Include your findings in a report with proposed solutions

Case study research: A qualitative research example

Your team has recently launched Pulse , a platform that analyzes social media posts to identify rising digital marketing trends. Pulse has been on the market for a year, and you want to better understand how it helps small businesses create successful campaigns.

To conduct your case study, you begin with a series of interviews to understand user expectations, ethnographic research sessions, and focus groups. After sorting responses and observations into common themes you notice a main recurring pattern. Users have trouble interpreting the data from their dashboards, making it difficult to identify which trends to follow.

With your synthesized insights, you create a report with detailed narratives of individual user experiences, common themes and issues, and recommendations for addressing user friction points.

Some of your proposed solutions include creating intuitive graphs and summaries for each trend study. This makes it easier for users to understand trends and implement strategic changes in their campaigns.

6. Secondary research

Secondary research is a research method that involves collecting and analyzing documents, records, and reviews that provide you with contextual data on your topic. You’re not connecting with participants directly, but rather accessing pre-existing available data. For example, you can pull out insights from your UX research repository to reexamine how they apply to your new UX research objective.

Strictly speaking, it can be both qualitative and quantitative—but today we focus on its qualitative application.

When to use secondary research

Record keeping is particularly useful when you need supplemental insights to complement, validate, or compare current research findings. It helps you analyze shifting trends amongst your users across a specific period. Some other scenarios where you need record keeping include:

Initial discovery or exploration phase: Secondary research can help you quickly gather background information and data to understand the broader context of a market
Design and development phase: See what solutions are working in other contexts for an idea of how to build yours

Secondary research is especially valuable when your team faces budget constraints, tight deadlines, or limited resources. Through review mining and collecting older findings, you can uncover useful insights that drive decision-making throughout the product design and development process.

How to conduct secondary research:

Outline your UX research objective
Identify potential data sources for information on your product, market, or target audience. Some of these sources can include: a. Review websites like Capterra and G2 b. Social media channels c. Customer service logs and disputes d. Website reviews e. Reports and insights from previous research studies f. Industry trends g. Information on competitors
Analyze your data by identifying recurring patterns and themes for insights

Secondary research: A qualitative research example

SafeSurf is a cybersecurity platform that offers threat detection, security audits, and real-time reports. After conducting multiple rounds of testing, you need a quick and easy way to identify remaining usability issues. Instead of conducting another resource-intensive method, you opt for social listening and data mining for your secondary research.

Browsing through your company’s X, you identify a recurring theme: many users without a background in tech find SafeSurf ’s reports too technical and difficult to read. Users struggle with understanding what to do if their networks are breached.

After checking your other social media channels and review sites, the issue pops up again.

With your gathered insights, your team settles on introducing a simplified version of reports, including clear summaries, takeaways, and step-by-step protocols for ensuring security.

By conducting secondary research, you’ve uncovered a major usability issue—all without spending large amounts of time and resources to connect with your users.

7. Open-ended surveys

Open-ended surveys are a type of unmoderated UX research method that involves asking users to answer a list of qualitative research questions designed to uncover their attitudes, expectations, and needs regarding your service or product. Open-ended surveys allow users to give in-depth, nuanced, and contextual responses.

When to use open-ended surveys

User surveys are an effective qualitative research method for reaching a large number of users. You can use them at any stage of the design and product development process, but they’re particularly useful:

When you’re conducting generative research : Open-ended surveys allow you to reach a wide range of users, making them especially useful during initial research phases when you need broad insights into user experiences
When you need to understand customer satisfaction: Open-ended customer satisfaction surveys help you uncover why your users might be dissatisfied with your product, helping you find the root cause of their negative experiences
In combination with close-ended surveys: Get a combination of numerical, statistical insights and rich descriptive feedback. You’ll know what a specific percentage of your users think and why they think it.

How to conduct open-ended surveys:

Design your survey and draft out a list of survey questions
Distribute your surveys to respondents
Analyze survey participant responses for key themes and patterns
Use your findings to inform your design process

Open-ended surveys: A qualitative research example

You're a UX researcher for RouteReader , a comprehensive logistics platform that allows users to conduct shipment tracking and route planning. Recently, you’ve launched a new predictive analytics feature that allows users to quickly identify and prepare for supply chain disruptions.

To better understand if users find the new feature helpful, you create an open-ended, in-app survey.

The questions you ask your users:

“What has been your experience with our new predictive analytics feature?"
“Do you find it easy or difficult to rework your routes based on our predictive suggestions?”
“Does the predictive analytics feature make planning routes easier? Why or why not?”

Most of the responses are positive. Users report using the predictive analytics feature to make last-minute adjustments to their route plans, and some even rely on it regularly. However, a few users find the feature hard to notice, making it difficult to adjust their routes on time.

To ensure users have supply chain insights on time, you integrate the new feature into each interface so users can easily spot important information and adjust their routes accordingly.

💡 Surveys are a lot easier with a quality survey tool. Maze’s Feedback Surveys solution has all you need to ensure your surveys get the insights you need—including AI-powered follow-up and automated reports.

Qualitative research vs. quantitative research: What’s the difference?

Alongside qualitative research approaches, UX teams also use quantitative research methods. Despite the similar names, the two are very different.

Here are some of the key differences between qualitative research and quantitative research .

Research type
Qualitative research			.
Quantitative research

Before selecting either qualitative or quantitative methods, first identify what you want to achieve with your UX research project. As a general rule of thumb, think qualitative data collection for in-depth understanding and quantitative studies for measurement and validation.

Conduct qualitative research with Maze

You’ll often find that knowing the what is pointless without understanding the accompanying why . Qualitative research helps you uncover your why.

So, what about how —how do you identify your 'what' and your 'why'?

The answer is with a user research tool like Maze.

Maze is the leading user research platform that lets you organize, conduct, and analyze both qualitative and quantitative research studies—all from one place. Its wide variety of UX research methods and advanced AI capabilities help you get the insights you need to build the right products and experiences faster.

Frequently asked questions about qualitative research examples

What is qualitative research?

Qualitative research is a research method that aims to provide contextual, descriptive, and non-numerical insights on a specific issue. Qualitative research methods like interviews, case studies, and ethnographic studies allow you to uncover the reasoning behind your user’s attitudes and opinions.

Can a study be both qualitative and quantitative?

Absolutely! You can use mixed methods in your research design, which combines qualitative and quantitative approaches to gain both descriptive and statistical insights.

For example, user surveys can have both close-ended and open-ended questions, providing comprehensive data like percentages of user views and descriptive reasoning behind their answers.

Is qualitative or quantitative research better?

The choice between qualitative and quantitative research depends upon your research goals and objectives.

Qualitative research methods are better suited when you want to understand the complexities of your user’s problems and uncover the underlying motives beneath their thoughts, feelings, and behaviors. Quantitative research excels in giving you numerical data, helping you gain a statistical view of your user's attitudes, identifying trends, and making predictions.

What are some approaches to qualitative research?

There are many approaches to qualitative studies. An approach is the underlying theory behind a method, and a method is a way of implementing the approach. Here are some approaches to qualitative research:

Grounded theory: Researchers study a topic and develop theories inductively
Phenomenological research: Researchers study a phenomenon through the lived experiences of those involved
Ethnography: Researchers immerse themselves in organizations to understand how they operate

Skip to main content
Skip to primary sidebar
Skip to footer
QuestionPro

Solutions Industries Gaming Automotive Sports and events Education Government Travel & Hospitality Financial Services Healthcare Cannabis Technology Use Case AskWhy Communities Audience Contactless surveys Mobile LivePolls Member Experience GDPR Positive People Science 360 Feedback Surveys
Resources Blog eBooks Survey Templates Case Studies Training Help center

Home Market Research

Qualitative Research Methods: Types, Analysis + Examples

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses. The interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience makes decisions can help derive conclusions in market research.

What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication .

This method is about “what” people think and “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that more men are visiting this store. One good method to determine why women were not visiting the store is conducting an in-depth interview method with potential customers.

For example, after successfully interviewing female customers and visiting nearby stores and malls, the researchers selected participants through random sampling . As a result, it was discovered that the store didn’t have enough items for women.

So fewer women were visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store because there were more male products than female ones.

Gather research insights

Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods, such as in-depth interviews, focus groups, ethnographic research, content analysis, and case study research that are usually used.

The results of qualitative methods are more descriptive, and the inferences can be drawn quite easily from the obtained data .

Qualitative research methods originated in the social and behavioral research sciences. Today, our world is more complicated, and it is difficult to understand what people think and perceive. Online research methods make it easier to understand that as it is a more communicative and descriptive analysis .

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples :

1. One-on-one interview

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method is that it provides a great opportunity to gather precise data about what people believe and their motivations . If the researcher is well experienced, asking the right questions can help him/her collect meaningful data. If they should need more information, the researchers should ask such follow-up questions that will help them collect more information.

These interviews can be performed face-to-face or on the phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face, it gives a better opportunity to read the respondents’ body language and match the responses.

2. Focus groups

A focus group is also a commonly used qualitative research method used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why, ” “what,” and “how” questions. One advantage of focus groups is you don’t necessarily need to interact with the group in person. Nowadays, focus groups can be sent an online survey on various devices, and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to other online qualitative research methods. Typically, they are used to explain complex processes. This method is very useful for market research on new products and testing new concepts.

3. Ethnographic research

Ethnographic research is the most in-depth observational research method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments, which could be anywhere from an organization to a city or any remote location. Here, geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings firsthand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and time-consuming method and solely depends on the researcher’s expertise to analyze, observe, and infer the data.

4. Case study research

T he case study method has evolved over the past few years and developed into a valuable quality research method. As the name suggests, it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences, and similar. This method may look difficult to operate; however , it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There, one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, environmental analysis , nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc.

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or research problems . These are real-time data and rarely bring the participants out of the geographic locations to collect information.
Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source .
This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

Qualitative research method case study

Let’s take the example of a bookstore owner who is looking for ways to improve their sales and customer outreach. An online community of members who were loyal patrons of the bookstore were interviewed and related questions were asked and the questions were answered by them.

At the end of the interview, it was realized that most of the books in the stores were suitable for adults and there were not enough options for children or teenagers.

By conducting this qualitative research the bookstore owner realized what the shortcomings were and what were the feelings of the readers. Through this research now the bookstore owner can now keep books for different age categories and can improve his sales and customer outreach.

Such qualitative research method examples can serve as the basis to indulge in further quantitative research , which provides remedies.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

Developing a new product or generating an idea.
Studying your product/brand or service to strengthen your marketing strategy.
To understand your strengths and weaknesses.
Understanding purchase behavior.
To study the reactions of your audience to marketing campaigns and other communications.
Exploring market demographics, segments, and customer care groups.
Gathering perception data of a brand, company, or product.

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

Their analytical objectives
Types of questions asked
Types of data collection instruments
Forms of data they produce
Degree of flexibility


Analytical objectives	This research method focuses on describing individual experiences and beliefs.	Quantitative research method focuses on describing the characteristics of a population.
Types of questions asked	ions
Data collection Instrument	Use semi-structured methods such as in-depth interviews, focus groups, and	Use highly structured methods such as structured observation using and
Form of data produced	Descriptive data	Numerical data
Degree of flexibility	Participant responses affect how and which questions researchers ask next	Participant responses do not influence or determine how and which questions researchers ask next

LEARN MORE ABOUR OUR SOFTWARE FREE TRIAL

MORE LIKE THIS

Customer Experience Lessons from 13,000 Feet — Tuesday CX Thoughts

Aug 20, 2024

Insight: Definition & meaning, types and examples

Aug 19, 2024

Employee Loyalty: Strategies for Long-Term Business Success

Jotform vs SurveyMonkey: Which Is Best in 2024

Aug 15, 2024

18 Qualitative Research Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

Learn about our Editorial Process

qualitative research examples and definition, explained below

Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets.

It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).

Methods of qualitative research encompass a wide range of techniques, from in-depth personal encounters, like ethnographies (studying cultures in-depth) and autoethnographies (examining one’s own cultural experiences), to collection of diverse perspectives on topics through methods like interviewing focus groups (gatherings of individuals to discuss specific topics).

Qualitative Research Examples

1. ethnography.

Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology , this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.

Ethnographic research is characterized by extended observation of the group, often through direct participation, in the participants’ environment. An ethnographer typically lives with the study group for extended periods, intricately observing their everyday lives (Khan, 2014).

It aims to present a complete, detailed and accurate picture of the observed social life, rituals, symbols, and values from the perspective of the study group.


The key advantage of ethnography is its depth; it provides an in-depth understanding of the group’s behaviour, lifestyle, culture, and context. It also allows for flexibility, as researchers can adapt their approach based on their observations (Bryman, 2015)	There are issues regarding the subjective interpretation of data, and it’s time-consuming. It also requires the researchers to immerse themselves in the study environment, which might not always be feasible.

Example of Ethnographic Research

Title: “ The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity “

Citation: Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Overview: This study by Evans (2010) provides a rich narrative of young adult male identity as experienced in everyday life. The author immersed himself among a group of young men, participating in their activities and cultivating a deep understanding of their lifestyle, values, and motivations. This research exemplified the ethnographic approach, revealing complexities of the subjects’ identities and societal roles, which could hardly be accessed through other qualitative research designs.

Read my Full Guide on Ethnography Here

2. Autoethnography

Definition: Autoethnography is an approach to qualitative research where the researcher uses their own personal experiences to extend the understanding of a certain group, culture, or setting. Essentially, it allows for the exploration of self within the context of social phenomena.

Unlike traditional ethnography, which focuses on the study of others, autoethnography turns the ethnographic gaze inward, allowing the researcher to use their personal experiences within a culture as rich qualitative data (Durham, 2019).

The objective is to critically appraise one’s personal experiences as they navigate and negotiate cultural, political, and social meanings. The researcher becomes both the observer and the participant, intertwining personal and cultural experiences in the research.


One of the chief benefits of autoethnography is its ability to bridge the gap between researchers and audiences by using relatable experiences. It can also provide unique and profound insights unaccessible through traditional ethnographic approaches (Heinonen, 2012).	The subjective nature of this method can introduce bias. Critics also argue that the singular focus on personal experience may limit the contributions to broader cultural or social understanding.

Example of Autoethnographic Research

Title: “ A Day In The Life Of An NHS Nurse “

Citation: Osben, J. (2019). A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography. The Journal of Autoethnography for Health & Social Care. 1(1).

Overview: This study presents an autoethnography of a day in the life of an NHS nurse (who, of course, is also the researcher). The author uses the research to achieve reflexivity, with the researcher concluding: “Scrutinising my practice and situating it within a wider contextual backdrop has compelled me to significantly increase my level of scrutiny into the driving forces that influence my practice.”

Read my Full Guide on Autoethnography Here

3. Semi-Structured Interviews

Definition: Semi-structured interviews stand as one of the most frequently used methods in qualitative research. These interviews are planned and utilize a set of pre-established questions, but also allow for the interviewer to steer the conversation in other directions based on the responses given by the interviewee.

In semi-structured interviews, the interviewer prepares a guide that outlines the focal points of the discussion. However, the interview is flexible, allowing for more in-depth probing if the interviewer deems it necessary (Qu, & Dumay, 2011). This style of interviewing strikes a balance between structured ones which might limit the discussion, and unstructured ones, which could lack focus.


The main advantage of semi-structured interviews is their flexibility, allowing for exploration of unexpected topics that arise during the interview. It also facilitates the collection of robust, detailed data from participants’ perspectives (Smith, 2015).	Potential downsides include the possibility of data overload, periodic difficulties in analysis due to varied responses, and the fact they are time-consuming to conduct and analyze.

Example of Semi-Structured Interview Research

Title: “ Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review “

Citation: Puts, M., et al. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Overview: Puts et al. (2014) executed an extensive systematic review in which they conducted semi-structured interviews with older adults suffering from cancer to examine the factors influencing their adherence to cancer treatment. The findings suggested that various factors, including side effects, faith in healthcare professionals, and social support have substantial impacts on treatment adherence. This research demonstrates how semi-structured interviews can provide rich and profound insights into the subjective experiences of patients.

4. Focus Groups

Definition: Focus groups are a qualitative research method that involves organized discussion with a selected group of individuals to gain their perspectives on a specific concept, product, or phenomenon. Typically, these discussions are guided by a moderator.

During a focus group session, the moderator has a list of questions or topics to discuss, and participants are encouraged to interact with each other (Morgan, 2010). This interactivity can stimulate more information and provide a broader understanding of the issue under scrutiny. The open format allows participants to ask questions and respond freely, offering invaluable insights into attitudes, experiences, and group norms.


One of the key advantages of focus groups is their ability to deliver a rich understanding of participants’ experiences and beliefs. They can be particularly beneficial in providing a diverse range of perspectives and opening up new areas for exploration (Doody, Slevin, & Taggart, 2013).	Potential disadvantages include possible domination by a single participant, groupthink, or issues with confidentiality. Additionally, the results are not easily generalizable to a larger population due to the small sample size.

Example of Focus Group Research

Title: “ Perspectives of Older Adults on Aging Well: A Focus Group Study “

Citation: Halaweh, H., Dahlin-Ivanoff, S., Svantesson, U., & Willén, C. (2018). Perspectives of older adults on aging well: a focus group study. Journal of aging research .

Overview: This study aimed to explore what older adults (aged 60 years and older) perceived to be ‘aging well’. The researchers identified three major themes from their focus group interviews: a sense of well-being, having good physical health, and preserving good mental health. The findings highlight the importance of factors such as positive emotions, social engagement, physical activity, healthy eating habits, and maintaining independence in promoting aging well among older adults.

5. Phenomenology

Definition: Phenomenology, a qualitative research method, involves the examination of lived experiences to gain an in-depth understanding of the essence or underlying meanings of a phenomenon.

The focus of phenomenology lies in meticulously describing participants’ conscious experiences related to the chosen phenomenon (Padilla-Díaz, 2015).

In a phenomenological study, the researcher collects detailed, first-hand perspectives of the participants, typically via in-depth interviews, and then uses various strategies to interpret and structure these experiences, ultimately revealing essential themes (Creswell, 2013). This approach focuses on the perspective of individuals experiencing the phenomenon, seeking to explore, clarify, and understand the meanings they attach to those experiences.


An advantage of phenomenology is its potential to reveal rich, complex, and detailed understandings of human experiences in a way other research methods cannot. It encourages explorations of deep, often abstract or intangible aspects of human experiences (Bevan, 2014).	Phenomenology might be criticized for its subjectivity, the intense effort required during data collection and analysis, and difficulties in replicating the study.

Example of Phenomenology Research

Title: “ A phenomenological approach to experiences with technology: current state, promise, and future directions for research ”

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development, 59 , 487-510.

Overview: A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

6. Grounded Theory

Definition: Grounded theory is a systematic methodology in qualitative research that typically applies inductive reasoning . The primary aim is to develop a theoretical explanation or framework for a process, action, or interaction grounded in, and arising from, empirical data (Birks & Mills, 2015).

In grounded theory, data collection and analysis work together in a recursive process. The researcher collects data, analyses it, and then collects more data based on the evolving understanding of the research context. This ongoing process continues until a comprehensive theory that represents the data and the associated phenomenon emerges – a point known as theoretical saturation (Charmaz, 2014).


An advantage of grounded theory is its ability to generate a theory that is closely related to the reality of the persons involved. It permits flexibility and can facilitate a deep understanding of complex processes in their natural contexts (Glaser & Strauss, 1967).	Critics note that it can be a lengthy and complicated process; others critique the emphasis on theory development over descriptive detail.

Example of Grounded Theory Research

Title: “ Student Engagement in High School Classrooms from the Perspective of Flow Theory “

Citation: Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158–176.

Overview: Shernoff and colleagues (2003) used grounded theory to explore student engagement in high school classrooms. The researchers collected data through student self-reports, interviews, and observations. Key findings revealed that academic challenge, student autonomy, and teacher support emerged as the most significant factors influencing students’ engagement, demonstrating how grounded theory can illuminate complex dynamics within real-world contexts.

7. Narrative Research

Definition: Narrative research is a qualitative research method dedicated to storytelling and understanding how individuals experience the world. It focuses on studying an individual’s life and experiences as narrated by that individual (Polkinghorne, 2013).

In narrative research, the researcher collects data through methods such as interviews, observations , and document analysis. The emphasis is on the stories told by participants – narratives that reflect their experiences, thoughts, and feelings.

These stories are then interpreted by the researcher, who attempts to understand the meaning the participant attributes to these experiences (Josselson, 2011).


The strength of narrative research is its ability to provide a deep, holistic, and rich understanding of an individual’s experiences over time. It is well-suited to capturing the complexities and intricacies of human lives and their contexts (Leiblich, Tuval-Mashiach, & Zilber, 2008).	Narrative research may be criticized for its highly interpretive nature, the potential challenges of ensuring reliability and validity, and the complexity of narrative analysis.

Example of Narrative Research

Title: “Narrative Structures and the Language of the Self”

Citation: McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative . American Psychological Association.

Overview: In this innovative study, McAdams et al. (2006) employed narrative research to explore how individuals construct their identities through the stories they tell about themselves. By examining personal narratives, the researchers discerned patterns associated with characters, motivations, conflicts, and resolutions, contributing valuable insights about the relationship between narrative and individual identity.

8. Case Study Research

Definition: Case study research is a qualitative research method that involves an in-depth investigation of a single instance or event: a case. These ‘cases’ can range from individuals, groups, or entities to specific projects, programs, or strategies (Creswell, 2013).

The case study method typically uses multiple sources of information for comprehensive contextual analysis. It aims to explore and understand the complexity and uniqueness of a particular case in a real-world context (Merriam & Tisdell, 2015). This investigation could result in a detailed description of the case, a process for its development, or an exploration of a related issue or problem.


Case study research is ideal for a holistic, in-depth investigation, making complex phenomena understandable and allowing for the exploration of contexts and activities where it is not feasible to use other research methods (Crowe et al., 2011).	Critics of case study research often cite concerns about the representativeness of a single case, the limited ability to generalize findings, and potential bias in data collection and interpretation.

Example of Case Study Research

Title: “ Teacher’s Role in Fostering Preschoolers’ Computational Thinking: An Exploratory Case Study “

Citation: Wang, X. C., Choi, Y., Benson, K., Eggleston, C., & Weber, D. (2021). Teacher’s role in fostering preschoolers’ computational thinking: An exploratory case study. Early Education and Development , 32 (1), 26-48.

Overview: This study investigates the role of teachers in promoting computational thinking skills in preschoolers. The study utilized a qualitative case study methodology to examine the computational thinking scaffolding strategies employed by a teacher interacting with three preschoolers in a small group setting. The findings highlight the importance of teachers’ guidance in fostering computational thinking practices such as problem reformulation/decomposition, systematic testing, and debugging.

Read about some Famous Case Studies in Psychology Here

9. Participant Observation

Definition: Participant observation has the researcher immerse themselves in a group or community setting to observe the behavior of its members. It is similar to ethnography, but generally, the researcher isn’t embedded for a long period of time.

The researcher, being a participant, engages in daily activities, interactions, and events as a way of conducting a detailed study of a particular social phenomenon (Kawulich, 2005).

The method involves long-term engagement in the field, maintaining detailed records of observed events, informal interviews, direct participation, and reflexivity. This approach allows for a holistic view of the participants’ lived experiences, behaviours, and interactions within their everyday environment (Dewalt, 2011).


A key strength of participant observation is its capacity to offer intimate, nuanced insights into social realities and practices directly from the field. It allows for broader context understanding, emotional insights, and a constant iterative process (Mulhall, 2003).	The method may present challenges including potential observer bias, the difficulty in ensuring ethical standards, and the risk of ‘going native’, where the boundary between being a participant and researcher blurs.

Example of Participant Observation Research

Title: Conflict in the boardroom: a participant observation study of supervisory board dynamics

Citation: Heemskerk, E. M., Heemskerk, K., & Wats, M. M. (2017). Conflict in the boardroom: a participant observation study of supervisory board dynamics. Journal of Management & Governance , 21 , 233-263.

Overview: This study examined how conflicts within corporate boards affect their performance. The researchers used a participant observation method, where they actively engaged with 11 supervisory boards and observed their dynamics. They found that having a shared understanding of the board’s role called a common framework, improved performance by reducing relationship conflicts, encouraging task conflicts, and minimizing conflicts between the board and CEO.

10. Non-Participant Observation

Definition: Non-participant observation is a qualitative research method in which the researcher observes the phenomena of interest without actively participating in the situation, setting, or community being studied.

This method allows the researcher to maintain a position of distance, as they are solely an observer and not a participant in the activities being observed (Kawulich, 2005).

During non-participant observation, the researcher typically records field notes on the actions, interactions, and behaviors observed , focusing on specific aspects of the situation deemed relevant to the research question.

This could include verbal and nonverbal communication , activities, interactions, and environmental contexts (Angrosino, 2007). They could also use video or audio recordings or other methods to collect data.


Non-participant observation can increase distance from the participants and decrease researcher bias, as the observer does not become involved in the community or situation under study (Jorgensen, 2015). This method allows for a more detached and impartial view of practices, behaviors, and interactions.	Criticisms of this method include potential observer effects, where individuals may change their behavior if they know they are being observed, and limited contextual understanding, as observers do not participate in the setting’s activities.

Example of Non-Participant Observation Research

Title: Mental Health Nurses’ attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units: A non-participant observation study

Citation: Sreeram, A., Cross, W. M., & Townsin, L. (2023). Mental Health Nurses’ attitudes towards mental illness and recovery‐oriented practice in acute inpatient psychiatric units: A non‐participant observation study. International Journal of Mental Health Nursing .

Overview: This study investigated the attitudes of mental health nurses towards mental illness and recovery-oriented practice in acute inpatient psychiatric units. The researchers used a non-participant observation method, meaning they observed the nurses without directly participating in their activities. The findings shed light on the nurses’ perspectives and behaviors, providing valuable insights into their attitudes toward mental health and recovery-focused care in these settings.

11. Content Analysis

Definition: Content Analysis involves scrutinizing textual, visual, or spoken content to categorize and quantify information. The goal is to identify patterns, themes, biases, or other characteristics (Hsieh & Shannon, 2005).

Content Analysis is widely used in various disciplines for a multitude of purposes. Researchers typically use this method to distill large amounts of unstructured data, like interview transcripts, newspaper articles, or social media posts, into manageable and meaningful chunks.

When wielded appropriately, Content Analysis can illuminate the density and frequency of certain themes within a dataset, provide insights into how specific terms or concepts are applied contextually, and offer inferences about the meanings of their content and use (Duriau, Reger, & Pfarrer, 2007).


The application of Content Analysis offers several strengths, chief among them being the ability to gain an in-depth, contextualized, understanding of a range of texts – both written and multimodal (Gray, Grove, & Sutherland, 2017) – see also: .	Content analysis is dependent on the descriptors that the researcher selects to examine the data, potentially leading to bias. Moreover, this method may also lose sight of the wider social context, which can limit the depth of the analysis (Krippendorff, 2013).

Example of Content Analysis

Title: Framing European politics: A content analysis of press and television news .

Citation: Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50 (2), 93-109.

Overview: This study analyzed press and television news articles about European politics using a method called content analysis. The researchers examined the prevalence of different “frames” in the news, which are ways of presenting information to shape audience perceptions. They found that the most common frames were attribution of responsibility, conflict, economic consequences, human interest, and morality.

Read my Full Guide on Content Analysis Here

12. Discourse Analysis

Definition: Discourse Analysis, a qualitative research method, interprets the meanings, functions, and coherence of certain languages in context.

Discourse analysis is typically understood through social constructionism, critical theory , and poststructuralism and used for understanding how language constructs social concepts (Cheek, 2004).

Discourse Analysis offers great breadth, providing tools to examine spoken or written language, often beyond the level of the sentence. It enables researchers to scrutinize how text and talk articulate social and political interactions and hierarchies.

Insight can be garnered from different conversations, institutional text, and media coverage to understand how topics are addressed or framed within a specific social context (Jorgensen & Phillips, 2002).


Discourse Analysis presents as its strength the ability to explore the intricate relationship between language and society. It goes beyond mere interpretation of content and scrutinizes the power dynamics underlying discourse. Furthermore, it can also be beneficial in discovering hidden meanings and uncovering marginalized voices (Wodak & Meyer, 2015).	Despite its strengths, Discourse Analysis possesses specific weaknesses. This approach may be open to allegations of subjectivity due to its interpretive nature. Furthermore, it can be quite time-consuming and requires the researcher to be familiar with a wide variety of theoretical and analytical frameworks (Parker, 2014).

Example of Discourse Analysis

Title: The construction of teacher identities in educational policy documents: A critical discourse analysis

Citation: Thomas, S. (2005). The construction of teacher identities in educational policy documents: A critical discourse analysis. Critical Studies in Education, 46 (2), 25-44.

Overview: The author examines how an education policy in one state of Australia positions teacher professionalism and teacher identities. While there are competing discourses about professional identity, the policy framework privileges a narrative that frames the ‘good’ teacher as one that accepts ever-tightening control and regulation over their professional practice.

Read my Full Guide on Discourse Analysis Here

13. Action Research

Definition: Action Research is a qualitative research technique that is employed to bring about change while simultaneously studying the process and results of that change.

This method involves a cyclical process of fact-finding, action, evaluation, and reflection (Greenwood & Levin, 2016).

Typically, Action Research is used in the fields of education, social sciences , and community development. The process isn’t just about resolving an issue but also developing knowledge that can be used in the future to address similar or related problems.

The researcher plays an active role in the research process, which is normally broken down into four steps:

developing a plan to improve what is currently being done
implementing the plan
observing the effects of the plan, and
reflecting upon these effects (Smith, 2010).


Action Research has the immense strength of enabling practitioners to address complex situations in their professional context. By fostering reflective practice, it ignites individual and organizational learning. Furthermore, it provides a robust way to bridge the theory-practice divide and can lead to the development of best practices (Zuber-Skerritt, 2019).	Action Research requires a substantial commitment of time and effort. Also, the participatory nature of this research can potentially introduce bias, and its iterative nature can blur the line between where the research process ends and where the implementation begins (Koshy, Koshy, & Waterman, 2010).

Example of Action Research

Title: Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing. Journal of Research in Childhood Education , 34 (2), 277-287.

Overview: This was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Read my Full Guide on Action Research Here

14. Semiotic Analysis

Definition: Semiotic Analysis is a qualitative method of research that interprets signs and symbols in communication to understand sociocultural phenomena. It stems from semiotics, the study of signs and symbols and their use or interpretation (Chandler, 2017).

In a Semiotic Analysis, signs (anything that represents something else) are interpreted based on their significance and the role they play in representing ideas.

This type of research often involves the examination of images, sounds, and word choice to uncover the embedded sociocultural meanings. For example, an advertisement for a car might be studied to learn more about societal views on masculinity or success (Berger, 2010).


The prime strength of the Semiotic Analysis lies in its ability to reveal the underlying ideologies within cultural symbols and messages. It helps to break down complex phenomena into manageable signs, yielding powerful insights about societal values, identities, and structures (Mick, 1986).	On the downside, because Semiotic Analysis is primarily interpretive, its findings may heavily rely on the particular theoretical lens and personal bias of the researcher. The ontology of signs and meanings can also be inherently subject to change, in the analysis (Lannon & Cooper, 2012).

Example of Semiotic Research

Title: Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia

Citation: Symes, C. (2023). Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia. Semiotica , 2023 (250), 167-190.

Overview: This study examines school badges in New South Wales, Australia, and explores their significance through a semiotic analysis. The badges, which are part of the school’s visual identity, are seen as symbolic representations that convey meanings. The analysis reveals that these badges often draw on heraldic models, incorporating elements like colors, names, motifs, and mottoes that reflect local culture and history, thus connecting students to their national identity. Additionally, the study highlights how some schools have shifted from traditional badges to modern logos and slogans, reflecting a more business-oriented approach.

15. Qualitative Longitudinal Studies

Definition: Qualitative Longitudinal Studies are a research method that involves repeated observation of the same items over an extended period of time.

Unlike a snapshot perspective, this method aims to piece together individual histories and examine the influences and impacts of change (Neale, 2019).

Qualitative Longitudinal Studies provide an in-depth understanding of change as it happens, including changes in people’s lives, their perceptions, and their behaviors.

For instance, this method could be used to follow a group of students through their schooling years to understand the evolution of their learning behaviors and attitudes towards education (Saldaña, 2003).


One key strength of Qualitative Longitudinal Studies is its ability to capture change and continuity over time. It allows for an in-depth understanding of individuals or context evolution. Moreover, it provides unique insights into the temporal ordering of events and experiences (Farrall, 2006).	Qualitative Longitudinal Studies come with their own share of weaknesses. Mainly, they require a considerable investment of time and resources. Moreover, they face the challenges of attrition (participants dropping out of the study) and repeated measures that may influence participants’ behaviors (Saldaña, 2014).

Example of Qualitative Longitudinal Research

Title: Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study

Citation: Hackett, J., Godfrey, M., & Bennett, M. I. (2016). Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study. Palliative medicine , 30 (8), 711-719.

Overview: This article examines how patients and their caregivers manage pain in advanced cancer through a qualitative longitudinal study. The researchers interviewed patients and caregivers at two different time points and collected audio diaries to gain insights into their experiences, making this study longitudinal.

Read my Full Guide on Longitudinal Research Here

16. Open-Ended Surveys

Definition: Open-Ended Surveys are a type of qualitative research method where respondents provide answers in their own words. Unlike closed-ended surveys, which limit responses to predefined options, open-ended surveys allow for expansive and unsolicited explanations (Fink, 2013).

Open-ended surveys are commonly used in a range of fields, from market research to social studies. As they don’t force respondents into predefined response categories, these surveys help to draw out rich, detailed data that might uncover new variables or ideas.

For example, an open-ended survey might be used to understand customer opinions about a new product or service (Lavrakas, 2008).

Contrast this to a quantitative closed-ended survey, like a Likert scale, which could theoretically help us to come up with generalizable data but is restricted by the questions on the questionnaire, meaning new and surprising data and insights can’t emerge from the survey results in the same way.


The key advantage of Open-Ended Surveys is their ability to generate in-depth, nuanced data that allow for a rich, . They provide a more personalized response from participants, and they may uncover areas of investigation that the researchers did not previously consider (Sue & Ritter, 2012).	Open-Ended Surveys require significant time and effort to analyze due to the variability of responses. Furthermore, the results obtained from Open-Ended Surveys can be more susceptible to subjective interpretation and may lack statistical generalizability (Fielding & Fielding, 2008).

Example of Open-Ended Survey Research

Title: Advantages and disadvantages of technology in relationships: Findings from an open-ended survey

Citation: Hertlein, K. M., & Ancheta, K. (2014). Advantages and disadvantages of technology in relationships: Findings from an open-ended survey. The Qualitative Report , 19 (11), 1-11.

Overview: This article examines the advantages and disadvantages of technology in couple relationships through an open-ended survey method. Researchers analyzed responses from 410 undergraduate students to understand how technology affects relationships. They found that technology can contribute to relationship development, management, and enhancement, but it can also create challenges such as distancing, lack of clarity, and impaired trust.

17. Naturalistic Observation

Definition: Naturalistic Observation is a type of qualitative research method that involves observing individuals in their natural environments without interference or manipulation by the researcher.

Naturalistic observation is often used when conducting research on behaviors that cannot be controlled or manipulated in a laboratory setting (Kawulich, 2005).

It is frequently used in the fields of psychology, sociology, and anthropology. For instance, to understand the social dynamics in a schoolyard, a researcher could spend time observing the children interact during their recess, noting their behaviors, interactions, and conflicts without imposing their presence on the children’s activities (Forsyth, 2010).


The predominant strength of Naturalistic Observation lies in : it allows the behavior of interest to be studied in the conditions under which it normally occurs. This method can also lead to the discovery of new behavioral patterns or phenomena not previously revealed in experimental research (Barker, Pistrang, & Elliott, 2016).	The observer may have difficulty avoiding subjective interpretations and biases of observed behaviors. Additionally, it may be very time-consuming, and the presence of the observer, even if unobtrusive, may influence the behavior of those being observed (Rosenbaum, 2017).

Example of Naturalistic Observation Research

Title: Dispositional mindfulness in daily life: A naturalistic observation study

Citation: Kaplan, D. M., Raison, C. L., Milek, A., Tackman, A. M., Pace, T. W., & Mehl, M. R. (2018). Dispositional mindfulness in daily life: A naturalistic observation study. PloS one , 13 (11), e0206029.

Overview: In this study, researchers conducted two studies: one exploring assumptions about mindfulness and behavior, and the other using naturalistic observation to examine actual behavioral manifestations of mindfulness. They found that trait mindfulness is associated with a heightened perceptual focus in conversations, suggesting that being mindful is expressed primarily through sharpened attention rather than observable behavioral or social differences.

Read my Full Guide on Naturalistic Observation Here

18. Photo-Elicitation

Definition: Photo-elicitation utilizes photographs as a means to trigger discussions and evoke responses during interviews. This strategy aids in bringing out topics of discussion that may not emerge through verbal prompting alone (Harper, 2002).

Traditionally, Photo-Elicitation has been useful in various fields such as education, psychology, and sociology. The method involves the researcher or participants taking photographs, which are then used as prompts for discussion.

For instance, a researcher studying urban environmental issues might invite participants to photograph areas in their neighborhood that they perceive as environmentally detrimental, and then discuss each photo in depth (Clark-Ibáñez, 2004).


Photo-Elicitation boasts of its ability to facilitate dialogue that may not arise through conventional interview methods. As a visual catalyst, it can support interviewees in articulating their experiences and emotions, potentially resulting in the generation of rich and insightful data (Heisley & Levy, 1991).	There are some limitations with Photo-Elicitation. Interpretation of the images can be highly subjective and might be influenced by cultural and personal variables. Additionally, ethical concerns may arise around privacy and consent, particularly when photographing individuals (Van Auken, Frisvoll, & Stewart, 2010).

Example of Photo-Elicitation Research

Title: Early adolescent food routines: A photo-elicitation study

Citation: Green, E. M., Spivak, C., & Dollahite, J. S. (2021). Early adolescent food routines: A photo-elicitation study. Appetite, 158 .

Overview: This study focused on early adolescents (ages 10-14) and their food routines. Researchers conducted in-depth interviews using a photo-elicitation approach, where participants took photos related to their food choices and experiences. Through analysis, the study identified various routines and three main themes: family, settings, and meals/foods consumed, revealing how early adolescents view and are influenced by their eating routines.

Features of Qualitative Research

Qualitative research is a research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

Some key features of this method include:

Naturalistic Inquiry: Qualitative research happens in the natural setting of the phenomena, aiming to understand “real world” situations (Patton, 2015). This immersion in the field or subject allows the researcher to gather a deep understanding of the subject matter.
Emphasis on Process: It aims to understand how events unfold over time rather than focusing solely on outcomes (Merriam & Tisdell, 2015). The process-oriented nature of qualitative research allows researchers to investigate sequences, timing, and changes.
Interpretive: It involves interpreting and making sense of phenomena in terms of the meanings people assign to them (Denzin & Lincoln, 2011). This interpretive element allows for rich, nuanced insights into human behavior and experiences.
Holistic Perspective: Qualitative research seeks to understand the whole phenomenon rather than focusing on individual components (Creswell, 2013). It emphasizes the complex interplay of factors, providing a richer, more nuanced view of the research subject.
Prioritizes Depth over Breadth: Qualitative research favors depth of understanding over breadth, typically involving a smaller but more focused sample size (Hennink, Hutter, & Bailey, 2020). This enables detailed exploration of the phenomena of interest, often leading to rich and complex data.

Qualitative vs Quantitative Research

Qualitative research centers on exploring and understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

It involves an in-depth approach to the subject matter, aiming to capture the richness and complexity of human experience.

Examples include conducting interviews, observing behaviors, or analyzing text and images.

There are strengths inherent in this approach. In its focus on understanding subjective experiences and interpretations, qualitative research can yield rich and detailed data that quantitative research may overlook (Denzin & Lincoln, 2011).

Additionally, qualitative research is adaptive, allowing the researcher to respond to new directions and insights as they emerge during the research process.

However, there are also limitations. Because of the interpretive nature of this research, findings may not be generalizable to a broader population (Marshall & Rossman, 2014). Well-designed quantitative research, on the other hand, can be generalizable.

Moreover, the reliability and validity of qualitative data can be challenging to establish due to its subjective nature, unlike quantitative research, which is ideally more objective.


	Research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013)	Research method dealing with numbers and statistical analysis (Creswell & Creswell, 2017)
	Interviews, text/image analysis (Fugard & Potts, 2015)	Surveys, lab experiments (Van Voorhis & Morgan, 2007)
	Yields rich and detailed data; adaptive to new directions and insights (Denzin & Lincoln, 2011)	Enables precise measurement and analysis; findings can be generalizable; allows for replication (Ali & Bhaskar, 2016)
	Findings may not be generalizable; labor-intensive and time-consuming; reliability and validity can be challenging to establish (Marshall & Rossman, 2014)	May miss contextual detail; depends heavily on design and instrumentation; does not provide detailed description of behaviors, attitudes, and experiences (Mackey & Gass, 2015)

Compare Qualitative and Quantitative Research Methodologies in This Guide Here

In conclusion, qualitative research methods provide distinctive ways to explore social phenomena and understand nuances that quantitative approaches might overlook. Each method, from Ethnography to Photo-Elicitation, presents its strengths and weaknesses but they all offer valuable means of investigating complex, real-world situations. The goal for the researcher is not to find a definitive tool, but to employ the method best suited for their research questions and the context at hand (Almalki, 2016). Above all, these methods underscore the richness of human experience and deepen our understanding of the world around us.

Angrosino, M. (2007). Doing ethnographic and observational research. Sage Publications.

Areni, C. S., & Kim, D. (1994). The influence of in-store lighting on consumers’ examination of merchandise in a wine store. International Journal of Research in Marketing, 11 (2), 117-125.

Barker, C., Pistrang, N., & Elliott, R. (2016). Research Methods in Clinical Psychology: An Introduction for Students and Practitioners. John Wiley & Sons.

Baxter, P. & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13 (4), 544-559.

Berger, A. A. (2010). The Objects of Affection: Semiotics and Consumer Culture. Palgrave Macmillan.

Bevan, M. T. (2014). A method of phenomenological interviewing. Qualitative health research, 24 (1), 136-144.

Birks, M., & Mills, J. (2015). Grounded theory: A practical guide . Sage Publications.

Bryman, A. (2015) . The SAGE Handbook of Qualitative Research. Sage Publications.

Chandler, D. (2017). Semiotics: The Basics. Routledge.

Charmaz, K. (2014). Constructing grounded theory. Sage Publications.

Cheek, J. (2004). At the margins? Discourse analysis and qualitative research. Qualitative Health Research, 14(8), 1140-1150.

Clark-Ibáñez, M. (2004). Framing the social world with photo-elicitation interviews. American Behavioral Scientist, 47(12), 1507-1527.

Creswell, J. W. (2013). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage Publications.

Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology, 11(100), 1-9.

Denzin, N. K., & Lincoln, Y. S. (2011). The Sage Handbook of Qualitative Research. Sage.

Dewalt, K. M., & Dewalt, B. R. (2011). Participant observation: A guide for fieldworkers. Rowman Altamira.

Doody, O., Slevin, E., & Taggart, L. (2013). Focus group interviews in nursing research: part 1. British Journal of Nursing, 22(1), 16-19.

Durham, A. (2019). Autoethnography. In P. Atkinson (Ed.), Qualitative Research Methods. Oxford University Press.

Duriau, V. J., Reger, R. K., & Pfarrer, M. D. (2007). A content analysis of the content analysis literature in organization studies: Research themes, data sources, and methodological refinements. Organizational Research Methods, 10(1), 5-34.

Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Farrall, S. (2006). What is qualitative longitudinal research? Papers in Social Research Methods, Qualitative Series, No.11, London School of Economics, Methodology Institute.

Fielding, J., & Fielding, N. (2008). Synergy and synthesis: integrating qualitative and quantitative data. The SAGE handbook of social research methods, 555-571.

Fink, A. (2013). How to conduct surveys: A step-by-step guide . SAGE.

Forsyth, D. R. (2010). Group Dynamics . Wadsworth Cengage Learning.

Fugard, A. J. B., & Potts, H. W. W. (2015). Supporting thinking on sample sizes for thematic analyses: A quantitative tool. International Journal of Social Research Methodology, 18 (6), 669–684.

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine de Gruyter.

Gray, J. R., Grove, S. K., & Sutherland, S. (2017). Burns and Grove’s the Practice of Nursing Research E-Book: Appraisal, Synthesis, and Generation of Evidence. Elsevier Health Sciences.

Greenwood, D. J., & Levin, M. (2016). Introduction to action research: Social research for social change. SAGE.

Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17 (1), 13-26.

Heinonen, T. (2012). Making Sense of the Social: Human Sciences and the Narrative Turn. Rozenberg Publishers.

Heisley, D. D., & Levy, S. J. (1991). Autodriving: A photoelicitation technique. Journal of Consumer Research, 18 (3), 257-272.

Hennink, M. M., Hutter, I., & Bailey, A. (2020). Qualitative Research Methods . SAGE Publications Ltd.

Hsieh, H. F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research, 15 (9), 1277–1288.

Jorgensen, D. L. (2015). Participant Observation. In Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource. John Wiley & Sons, Inc.

Jorgensen, M., & Phillips, L. (2002). Discourse Analysis as Theory and Method . SAGE.

Josselson, R. (2011). Narrative research: Constructing, deconstructing, and reconstructing story. In Five ways of doing qualitative analysis . Guilford Press.

Kawulich, B. B. (2005). Participant observation as a data collection method. Forum: Qualitative Social Research, 6 (2).

Khan, S. (2014). Qualitative Research Method: Grounded Theory. Journal of Basic and Clinical Pharmacy, 5 (4), 86-88.

Koshy, E., Koshy, V., & Waterman, H. (2010). Action Research in Healthcare . SAGE.

Krippendorff, K. (2013). Content Analysis: An Introduction to its Methodology. SAGE.

Lannon, J., & Cooper, P. (2012). Humanistic Advertising: A Holistic Cultural Perspective. International Journal of Advertising, 15 (2), 97–111.

Lavrakas, P. J. (2008). Encyclopedia of survey research methods. SAGE Publications.

Lieblich, A., Tuval-Mashiach, R., & Zilber, T. (2008). Narrative research: Reading, analysis and interpretation. Sage Publications.

Mackey, A., & Gass, S. M. (2015). Second language research: Methodology and design. Routledge.

Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Sage publications.

McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative. American Psychological Association.

Merriam, S. B., & Tisdell, E. J. (2015). Qualitative Research: A Guide to Design and Implementation. Jossey-Bass.

Mick, D. G. (1986). Consumer Research and Semiotics: Exploring the Morphology of Signs, Symbols, and Significance. Journal of Consumer Research, 13 (2), 196-213.

Morgan, D. L. (2010). Focus groups as qualitative research. Sage Publications.

Mulhall, A. (2003). In the field: notes on observation in qualitative research. Journal of Advanced Nursing, 41 (3), 306-313.

Neale, B. (2019). What is Qualitative Longitudinal Research? Bloomsbury Publishing.

Nolan, L. B., & Renderos, T. B. (2012). A focus group study on the influence of fatalism and religiosity on cancer risk perceptions in rural, eastern North Carolina. Journal of religion and health, 51 (1), 91-104.

Padilla-Díaz, M. (2015). Phenomenology in educational qualitative research: Philosophy as science or philosophical science? International Journal of Educational Excellence, 1 (2), 101-110.

Parker, I. (2014). Discourse dynamics: Critical analysis for social and individual psychology . Routledge.

Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage Publications.

Polkinghorne, D. E. (2013). Narrative configuration in qualitative analysis. In Life history and narrative. Routledge.

Puts, M. T., Tapscott, B., Fitch, M., Howell, D., Monette, J., Wan-Chow-Wah, D., Krzyzanowska, M., Leighl, N. B., Springall, E., & Alibhai, S. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Qu, S. Q., & Dumay, J. (2011). The qualitative research interview . Qualitative research in accounting & management.

Ali, J., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60 (9), 662–669.

Rosenbaum, M. S. (2017). Exploring the social supportive role of third places in consumers’ lives. Journal of Service Research, 20 (1), 26-42.

Saldaña, J. (2003). Longitudinal Qualitative Research: Analyzing Change Through Time . AltaMira Press.

Saldaña, J. (2014). The Coding Manual for Qualitative Researchers. SAGE.

Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158-176.

Smith, J. A. (2015). Qualitative Psychology: A Practical Guide to Research Methods . Sage Publications.

Smith, M. K. (2010). Action Research. The encyclopedia of informal education.

Sue, V. M., & Ritter, L. A. (2012). Conducting online surveys . SAGE Publications.

Van Auken, P. M., Frisvoll, S. J., & Stewart, S. I. (2010). Visualising community: using participant-driven photo-elicitation for research and application. Local Environment, 15 (4), 373-388.

Van Voorhis, F. L., & Morgan, B. L. (2007). Understanding Power and Rules of Thumb for Determining Sample Sizes. Tutorials in Quantitative Methods for Psychology, 3 (2), 43–50.

Wodak, R., & Meyer, M. (2015). Methods of Critical Discourse Analysis . SAGE.

Zuber-Skerritt, O. (2018). Action research for developing educational theories and practices . Routledge.

Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 101 Hidden Talents Examples
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 15 Green Flags in a Relationship
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 15 Signs you're Burnt Out, Not Lazy
Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 15 Toxic Things Parents Say to their Children

Qualitative research: methods and examples

Last updated

13 April 2023

Reviewed by

Qualitative research involves gathering and evaluating non-numerical information to comprehend concepts, perspectives, and experiences. It’s also helpful for obtaining in-depth insights into a certain subject or generating new research ideas.

As a result, qualitative research is practical if you want to try anything new or produce new ideas.

There are various ways you can conduct qualitative research. In this article, you'll learn more about qualitative research methodologies, including when you should use them.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

What is qualitative research?

Qualitative research is a broad term describing various research types that rely on asking open-ended questions. Qualitative research investigates “how” or “why” certain phenomena occur. It is about discovering the inherent nature of something.

The primary objective of qualitative research is to understand an individual's ideas, points of view, and feelings. In this way, collecting in-depth knowledge of a specific topic is possible. Knowing your audience's feelings about a particular subject is important for making reasonable research conclusions.

Unlike quantitative research , this approach does not involve collecting numerical, objective data for statistical analysis. Qualitative research is used extensively in education, sociology, health science, history, and anthropology.

Types of qualitative research methodology

Typically, qualitative research aims at uncovering the attitudes and behavior of the target audience concerning a specific topic. For example, “How would you describe your experience as a new Dovetail user?”

Some of the methods for conducting qualitative analysis include:

Focus groups

Hosting a focus group is a popular qualitative research method. It involves obtaining qualitative data from a limited sample of participants. In a moderated version of a focus group, the moderator asks participants a series of predefined questions. They aim to interact and build a group discussion that reveals their preferences, candid thoughts, and experiences.

Unmoderated, online focus groups are increasingly popular because they eliminate the need to interact with people face to face.

Focus groups can be more cost-effective than 1:1 interviews or studying a group in a natural setting and reporting one’s observations.

Focus groups make it possible to gather multiple points of view quickly and efficiently, making them an excellent choice for testing new concepts or conducting market research on a new product.

However, there are some potential drawbacks to this method. It may be unsuitable for sensitive or controversial topics. Participants might be reluctant to disclose their true feelings or respond falsely to conform to what they believe is the socially acceptable answer (known as response bias).

Case study research

A case study is an in-depth evaluation of a specific person, incident, organization, or society. This type of qualitative research has evolved into a broadly applied research method in education, law, business, and the social sciences.

Even though case study research may appear challenging to implement, it is one of the most direct research methods. It requires detailed analysis, broad-ranging data collection methodologies, and a degree of existing knowledge about the subject area under investigation.

Historical model

The historical approach is a distinct research method that deeply examines previous events to better understand the present and forecast future occurrences of the same phenomena. Its primary goal is to evaluate the impacts of history on the present and hence discover comparable patterns in the present to predict future outcomes.

Oral history

This qualitative data collection method involves gathering verbal testimonials from individuals about their personal experiences. It is widely used in historical disciplines to offer counterpoints to established historical facts and narratives. The most common methods of gathering oral history are audio recordings, analysis of auto-biographical text, videos, and interviews.

Qualitative observation

One of the most fundamental, oldest research methods, qualitative observation , is the process through which a researcher collects data using their senses of sight, smell, hearing, etc. It is used to observe the properties of the subject being studied. For example, “What does it look like?” As research methods go, it is subjective and depends on researchers’ first-hand experiences to obtain information, so it is prone to bias. However, it is an excellent way to start a broad line of inquiry like, “What is going on here?”

Record keeping and review

Record keeping uses existing documents and relevant data sources that can be employed for future studies. It is equivalent to visiting the library and going through publications or any other reference material to gather important facts that will likely be used in the research.

Grounded theory approach

The grounded theory approach is a commonly used research method employed across a variety of different studies. It offers a unique way to gather, interpret, and analyze. With this approach, data is gathered and analyzed simultaneously. Existing analysis frames and codes are disregarded, and data is analyzed inductively, with new codes and frames generated from the research.

Ethnographic research

Ethnography is a descriptive form of a qualitative study of people and their cultures. Its primary goal is to study people's behavior in their natural environment. This method necessitates that the researcher adapts to their target audience's setting.

Thereby, you will be able to understand their motivation, lifestyle, ambitions, traditions, and culture in situ. But, the researcher must be prepared to deal with geographical constraints while collecting data i.e., audiences can’t be studied in a laboratory or research facility.

This study can last from a couple of days to several years. Thus, it is time-consuming and complicated, requiring you to have both the time to gather the relevant data as well as the expertise in analyzing, observing, and interpreting data to draw meaningful conclusions.

Narrative framework

A narrative framework is a qualitative research approach that relies on people's written text or visual images. It entails people analyzing these events or narratives to determine certain topics or issues. With this approach, you can understand how people represent themselves and their experiences to a larger audience.

Phenomenological approach

The phenomenological study seeks to investigate the experiences of a particular phenomenon within a group of individuals or communities. It analyzes a certain event through interviews with persons who have witnessed it to determine the connections between their views. Even though this method relies heavily on interviews, other data sources (recorded notes), and observations could be employed to enhance the findings.

Qualitative research methods (tools)

Some of the instruments involved in qualitative research include:

Document research: Also known as document analysis because it involves evaluating written documents. These can include personal and non-personal materials like archives, policy publications, yearly reports, diaries, or letters.

Focus groups: This is where a researcher poses questions and generates conversation among a group of people. The major goal of focus groups is to examine participants' experiences and knowledge, including research into how and why individuals act in various ways.

Secondary study: Involves acquiring existing information from texts, images, audio, or video recordings.

Observations: This requires thorough field notes on everything you see, hear, or experience. Compared to reported conduct or opinion, this study method can assist you in getting insights into a specific situation and observable behaviors.

Structured interviews : In this approach, you will directly engage people one-on-one. Interviews are ideal for learning about a person's subjective beliefs, motivations, and encounters.

Surveys: This is when you distribute questionnaires containing open-ended questions

Free AI content analysis generator

Make sense of your research by automatically summarizing key takeaways through our free content analysis tool.

What are common examples of qualitative research?

Everyday examples of qualitative research include:

Conducting a demographic analysis of a business

For instance, suppose you own a business such as a grocery store (or any store) and believe it caters to a broad customer base, but after conducting a demographic analysis, you discover that most of your customers are men.

You could do 1:1 interviews with female customers to learn why they don't shop at your store.

In this case, interviewing potential female customers should clarify why they don't find your shop appealing. It could be because of the products you sell or a need for greater brand awareness, among other possible reasons.

Launching or testing a new product

Suppose you are the product manager at a SaaS company looking to introduce a new product. Focus groups can be an excellent way to determine whether your product is marketable.

In this instance, you could hold a focus group with a sample group drawn from your intended audience. The group will explore the product based on its new features while you ensure adequate data on how users react to the new features. The data you collect will be key to making sales and marketing decisions.

Conducting studies to explain buyers' behaviors

You can also use qualitative research to understand existing buyer behavior better. Marketers analyze historical information linked to their businesses and industries to see when purchasers buy more.

Qualitative research can help you determine when to target new clients and peak seasons to boost sales by investigating the reason behind these behaviors.

Qualitative research: data collection

Data collection is gathering information on predetermined variables to gain appropriate answers, test hypotheses, and analyze results. Researchers will collect non-numerical data for qualitative data collection to obtain detailed explanations and draw conclusions.

To get valid findings and achieve a conclusion in qualitative research, researchers must collect comprehensive and multifaceted data.

Qualitative data is usually gathered through interviews or focus groups with videotapes or handwritten notes. If there are recordings, they are transcribed before the data analysis process. Researchers keep separate folders for the recordings acquired from each focus group when collecting qualitative research data to categorize the data.

Qualitative research: data analysis

Qualitative data analysis is organizing, examining, and interpreting qualitative data. Its main objective is identifying trends and patterns, responding to research questions, and recommending actions based on the findings. Textual analysis is a popular method for analyzing qualitative data.

Textual analysis differs from other qualitative research approaches in that researchers consider the social circumstances of study participants to decode their words, behaviors, and broader meaning.

Learn more about qualitative research data analysis software

When to use qualitative research

Qualitative research is helpful in various situations, particularly when a researcher wants to capture accurate, in-depth insights.

Here are some instances when qualitative research can be valuable:

Examining your product or service to improve your marketing approach

When researching market segments, demographics, and customer service teams

Identifying client language when you want to design a quantitative survey

When attempting to comprehend your or someone else's strengths and weaknesses

Assessing feelings and beliefs about societal and public policy matters

Collecting information about a business or product's perception

Analyzing your target audience's reactions to marketing efforts

When launching a new product or coming up with a new idea

When seeking to evaluate buyers' purchasing patterns

Qualitative research methods vs. quantitative research methods

Qualitative research examines people's ideas and what influences their perception, whereas quantitative research draws conclusions based on numbers and measurements.

Qualitative research is descriptive, and its primary goal is to comprehensively understand people's attitudes, behaviors, and ideas.

In contrast, quantitative research is more restrictive because it relies on numerical data and analyzes statistical data to make decisions. This research method assists researchers in gaining an initial grasp of the subject, which deals with numbers. For instance, the number of customers likely to purchase your products or use your services.

What is the most important feature of qualitative research?

A distinguishing feature of qualitative research is that it’s conducted in a real-world setting instead of a simulated environment. The researcher is examining actual phenomena instead of experimenting with different variables to see what outcomes (data) might result.

Can I use qualitative and quantitative approaches together in a study?

Yes, combining qualitative and quantitative research approaches happens all the time and is known as mixed methods research. For example, you could study individuals’ perceived risk in a certain scenario, such as how people rate the safety or riskiness of a given neighborhood. Simultaneously, you could analyze historical data objectively, indicating how safe or dangerous that area has been in the last year. To get the most out of mixed-method research, it’s important to understand the pros and cons of each methodology, so you can create a thoughtfully designed study that will yield compelling results.

Should you be using a customer insights hub?

Do you want to discover previous research faster?

Do you share your research findings with others?

Do you analyze research data?

Start for free today, add your research, and get to key insights faster

Editor’s picks

Last updated: 18 April 2023

Last updated: 27 February 2023

Last updated: 5 February 2023

Last updated: 16 April 2023

Last updated: 16 August 2024

Last updated: 9 March 2023

Last updated: 30 April 2024

Last updated: 12 December 2023

Last updated: 11 March 2024

Last updated: 4 July 2024

Last updated: 6 March 2024

Last updated: 5 March 2024

Last updated: 13 May 2024

Latest articles

Related topics, .css-je19u9{-webkit-align-items:flex-end;-webkit-box-align:flex-end;-ms-flex-align:flex-end;align-items:flex-end;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-flex-direction:row;-ms-flex-direction:row;flex-direction:row;-webkit-box-flex-wrap:wrap;-webkit-flex-wrap:wrap;-ms-flex-wrap:wrap;flex-wrap:wrap;-webkit-box-pack:center;-ms-flex-pack:center;-webkit-justify-content:center;justify-content:center;row-gap:0;text-align:center;max-width:671px;}@media (max-width: 1079px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}}@media (max-width: 799px){.css-je19u9{max-width:400px;}.css-je19u9>span{white-space:pre;}} decide what to .css-1kiodld{max-height:56px;display:-webkit-box;display:-webkit-flex;display:-ms-flexbox;display:flex;-webkit-align-items:center;-webkit-box-align:center;-ms-flex-align:center;align-items:center;}@media (max-width: 1079px){.css-1kiodld{display:none;}} build next, decide what to build next, log in or sign up.

Get started for free

Qualitative vs Quantitative Research Methods & Data Analysis

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human. Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms.

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
The research aims for objectivity (i.e., without bias) and is separated from the data.
The design of the study is determined before it begins.
For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
Useful for testing and validating already constructed theories.
Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

Mixed methods research
Designing qualitative research
Methods of data collection and analysis
Introduction to quantitative and qualitative research
Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
Qualitative research in health care: Analysing qualitative data
Qualitative data analysis: the framework approach
Using the framework method for the analysis of
Qualitative data in multi-disciplinary health research
Content Analysis
Grounded Theory
Thematic Analysis

Home » Qualitative Data – Types, Methods and Examples

Qualitative Data – Types, Methods and Examples

Table of Contents

Qualitative Data

Definition:

Qualitative data is a type of data that is collected and analyzed in a non-numerical form, such as words, images, or observations. It is generally used to gain an in-depth understanding of complex phenomena, such as human behavior, attitudes, and beliefs.

Types of Qualitative Data

There are various types of qualitative data that can be collected and analyzed, including:

Interviews : These involve in-depth, face-to-face conversations with individuals or groups to gather their perspectives, experiences, and opinions on a particular topic.
Focus Groups: These are group discussions where a facilitator leads a discussion on a specific topic, allowing participants to share their views and experiences.
Observations : These involve observing and recording the behavior and interactions of individuals or groups in a particular setting.
Case Studies: These involve in-depth analysis of a particular individual, group, or organization, usually over an extended period.
Document Analysis : This involves examining written or recorded materials, such as newspaper articles, diaries, or public records, to gain insight into a particular topic.
Visual Data : This involves analyzing images or videos to understand people’s experiences or perspectives on a particular topic.
Online Data: This involves analyzing data collected from social media platforms, forums, or online communities to understand people’s views and opinions on a particular topic.

Qualitative Data Formats

Qualitative data can be collected and presented in various formats. Some common formats include:

Textual data: This includes written or transcribed data from interviews, focus groups, or observations. It can be analyzed using various techniques such as thematic analysis or content analysis.
Audio data: This includes recordings of interviews or focus groups, which can be transcribed and analyzed using software such as NVivo.
Visual data: This includes photographs, videos, or drawings, which can be analyzed using techniques such as visual analysis or semiotics.
Mixed media data : This includes data collected in different formats, such as audio and text. This can be analyzed using mixed methods research, which combines both qualitative and quantitative research methods.
Field notes: These are notes taken by researchers during observations, which can include descriptions of the setting, behaviors, and interactions of participants.

Qualitative Data Analysis Methods

Qualitative data analysis refers to the process of systematically analyzing and interpreting qualitative data to identify patterns, themes, and relationships. Here are some common methods of analyzing qualitative data:

Thematic analysis: This involves identifying and analyzing patterns or themes within the data. It involves coding the data into themes and subthemes and organizing them into a coherent narrative.
Content analysis: This involves analyzing the content of the data, such as the words, phrases, or images used. It involves identifying patterns and themes in the data and examining the relationships between them.
Discourse analysis: This involves analyzing the language and communication used in the data, such as the meaning behind certain words or phrases. It involves examining how the language constructs and shapes social reality.
Grounded theory: This involves developing a theory or framework based on the data. It involves identifying patterns and themes in the data and using them to develop a theory that explains the phenomenon being studied.
Narrative analysis : This involves analyzing the stories and narratives present in the data. It involves examining how the stories are constructed and how they contribute to the overall understanding of the phenomenon being studied.
Ethnographic analysis : This involves analyzing the culture and social practices present in the data. It involves examining how the cultural and social practices contribute to the phenomenon being studied.

Qualitative Data Collection Guide

Here are some steps to guide the collection of qualitative data:

Define the research question : Start by clearly defining the research question that you want to answer. This will guide the selection of data collection methods and help to ensure that the data collected is relevant to the research question.
Choose data collection methods : Select the most appropriate data collection methods based on the research question, the research design, and the resources available. Common methods include interviews, focus groups, observations, document analysis, and participatory research.
Develop a data collection plan : Develop a plan for data collection that outlines the specific procedures, timelines, and resources needed for each data collection method. This plan should include details such as how to recruit participants, how to conduct interviews or focus groups, and how to record and store data.
Obtain ethical approval : Obtain ethical approval from an institutional review board or ethics committee before beginning data collection. This is particularly important when working with human participants to ensure that their rights and interests are protected.
Recruit participants: Recruit participants based on the research question and the data collection methods chosen. This may involve purposive sampling, snowball sampling, or random sampling.
Collect data: Collect data using the chosen data collection methods. This may involve conducting interviews, facilitating focus groups, observing participants, or analyzing documents.
Transcribe and store data : Transcribe and store the data in a secure location. This may involve transcribing audio or video recordings, organizing field notes, or scanning documents.
Analyze data: Analyze the data using appropriate qualitative data analysis methods, such as thematic analysis or content analysis.
I nterpret findings : Interpret the findings of the data analysis in the context of the research question and the relevant literature. This may involve developing new theories or frameworks, or validating existing ones.
Communicate results: Communicate the results of the research in a clear and concise manner, using appropriate language and visual aids where necessary. This may involve writing a report, presenting at a conference, or publishing in a peer-reviewed journal.

Qualitative Data Examples

Some examples of qualitative data in different fields are as follows:

Sociology : In sociology, qualitative data is used to study social phenomena such as culture, norms, and social relationships. For example, a researcher might conduct interviews with members of a community to understand their beliefs and practices.
Psychology : In psychology, qualitative data is used to study human behavior, emotions, and attitudes. For example, a researcher might conduct a focus group to explore how individuals with anxiety cope with their symptoms.
Education : In education, qualitative data is used to study learning processes and educational outcomes. For example, a researcher might conduct observations in a classroom to understand how students interact with each other and with their teacher.
Marketing : In marketing, qualitative data is used to understand consumer behavior and preferences. For example, a researcher might conduct in-depth interviews with customers to understand their purchasing decisions.
Anthropology : In anthropology, qualitative data is used to study human cultures and societies. For example, a researcher might conduct participant observation in a remote community to understand their customs and traditions.
Health Sciences: In health sciences, qualitative data is used to study patient experiences, beliefs, and preferences. For example, a researcher might conduct interviews with cancer patients to understand how they cope with their illness.

Application of Qualitative Data

Qualitative data is used in a variety of fields and has numerous applications. Here are some common applications of qualitative data:

Exploratory research: Qualitative data is often used in exploratory research to understand a new or unfamiliar topic. Researchers use qualitative data to generate hypotheses and develop a deeper understanding of the research question.
Evaluation: Qualitative data is often used to evaluate programs or interventions. Researchers use qualitative data to understand the impact of a program or intervention on the people who participate in it.
Needs assessment: Qualitative data is often used in needs assessments to understand the needs of a specific population. Researchers use qualitative data to identify the most pressing needs of the population and develop strategies to address those needs.
Case studies: Qualitative data is often used in case studies to understand a particular case in detail. Researchers use qualitative data to understand the context, experiences, and perspectives of the people involved in the case.
Market research: Qualitative data is often used in market research to understand consumer behavior and preferences. Researchers use qualitative data to gain insights into consumer attitudes, opinions, and motivations.
Social and cultural research : Qualitative data is often used in social and cultural research to understand social phenomena such as culture, norms, and social relationships. Researchers use qualitative data to understand the experiences, beliefs, and practices of individuals and communities.

Purpose of Qualitative Data

The purpose of qualitative data is to gain a deeper understanding of social phenomena that cannot be captured by numerical or quantitative data. Qualitative data is collected through methods such as observation, interviews, and focus groups, and it provides descriptive information that can shed light on people’s experiences, beliefs, attitudes, and behaviors.

Qualitative data serves several purposes, including:

Generating hypotheses: Qualitative data can be used to generate hypotheses about social phenomena that can be further tested with quantitative data.
Providing context : Qualitative data provides a rich and detailed context for understanding social phenomena that cannot be captured by numerical data alone.
Exploring complex phenomena : Qualitative data can be used to explore complex phenomena such as culture, social relationships, and the experiences of marginalized groups.
Evaluating programs and intervention s: Qualitative data can be used to evaluate the impact of programs and interventions on the people who participate in them.
Enhancing understanding: Qualitative data can be used to enhance understanding of the experiences, beliefs, and attitudes of individuals and communities, which can inform policy and practice.

When to use Qualitative Data

Qualitative data is appropriate when the research question requires an in-depth understanding of complex social phenomena that cannot be captured by numerical or quantitative data.

Here are some situations when qualitative data is appropriate:

Exploratory research : Qualitative data is often used in exploratory research to generate hypotheses and develop a deeper understanding of a research question.
Understanding social phenomena : Qualitative data is appropriate when the research question requires an in-depth understanding of social phenomena such as culture, social relationships, and experiences of marginalized groups.
Program evaluation: Qualitative data is often used in program evaluation to understand the impact of a program on the people who participate in it.
Needs assessment: Qualitative data is often used in needs assessments to understand the needs of a specific population.
Market research: Qualitative data is often used in market research to understand consumer behavior and preferences.
Case studies: Qualitative data is often used in case studies to understand a particular case in detail.

Characteristics of Qualitative Data

Here are some characteristics of qualitative data:

Descriptive : Qualitative data provides a rich and detailed description of the social phenomena under investigation.
Contextual : Qualitative data is collected in the context in which the social phenomena occur, which allows for a deeper understanding of the phenomena.
Subjective : Qualitative data reflects the subjective experiences, beliefs, attitudes, and behaviors of the individuals and communities under investigation.
Flexible : Qualitative data collection methods are flexible and can be adapted to the specific needs of the research question.
Emergent : Qualitative data analysis is often an iterative process, where new themes and patterns emerge as the data is analyzed.
Interpretive : Qualitative data analysis involves interpretation of the data, which requires the researcher to be reflexive and aware of their own biases and assumptions.
Non-standardized: Qualitative data collection methods are often non-standardized, which means that the data is not collected in a standardized or uniform way.

Advantages of Qualitative Data

Some advantages of qualitative data are as follows:

Richness : Qualitative data provides a rich and detailed description of the social phenomena under investigation, allowing for a deeper understanding of the phenomena.
Flexibility : Qualitative data collection methods are flexible and can be adapted to the specific needs of the research question, allowing for a more nuanced exploration of social phenomena.
Contextualization : Qualitative data is collected in the context in which the social phenomena occur, which allows for a deeper understanding of the phenomena and their cultural and social context.
Subjectivity : Qualitative data reflects the subjective experiences, beliefs, attitudes, and behaviors of the individuals and communities under investigation, allowing for a more holistic understanding of the phenomena.
New insights : Qualitative data can generate new insights and hypotheses that can be further tested with quantitative data.
Participant voice : Qualitative data collection methods often involve direct participation by the individuals and communities under investigation, allowing for their voices to be heard.
Ethical considerations: Qualitative data collection methods often prioritize ethical considerations such as informed consent, confidentiality, and respect for the autonomy of the participants.

Limitations of Qualitative Data

Here are some limitations of qualitative data:

Subjectivity : Qualitative data is subjective, and the interpretation of the data depends on the researcher’s own biases, assumptions, and perspectives.
Small sample size: Qualitative data collection methods often involve a small sample size, which limits the generalizability of the findings.
Time-consuming: Qualitative data collection and analysis can be time-consuming, as it requires in-depth engagement with the data and often involves iterative processes.
Limited statistical analysis: Qualitative data is often not suitable for statistical analysis, which limits the ability to draw quantitative conclusions from the data.
Limited comparability: Qualitative data collection methods are often non-standardized, which makes it difficult to compare findings across different studies or contexts.
Social desirability bias : Qualitative data collection methods often rely on self-reporting by the participants, which can be influenced by social desirability bias.
Researcher bias: The researcher’s own biases, assumptions, and perspectives can influence the data collection and analysis, which can limit the objectivity of the findings.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

Secondary Data – Types, Methods and Examples

Research Data – Types Methods and Examples

Information in Research – Types and Examples

Quantitative Data – Types, Methods and Examples

Primary Data – Types, Methods and Examples

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
Neurol Res Pract

How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig. 1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig1_HTML.jpg

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig. 2 .

An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig2_HTML.jpg

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig. 3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig3_HTML.jpg

From data collection to data analysis

Attributions for icons: see Fig. Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig. 4 .

An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig4_HTML.jpg

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points


• Assessing complex multi-component interventions or systems (of change) • What works for whom when, how and why? • Focussing on intervention improvement	• Document study • Observations (participant or non-participant) • Interviews (especially semi-structured) • Focus groups	• Transcription of audio-recordings and field notes into transcripts and protocols • Coding of protocols • Using qualitative data management software

• Combinations of quantitative and/or qualitative methods, e.g.: • : quali and quanti in parallel • : quanti followed by quali • : quali followed by quanti	• Checklists • Reflexivity • Sampling strategies • Piloting • Co-coding • Member checking • Stakeholder involvement	• Protocol adherence • Sample size • Randomization • Interrater reliability, variability and other “objectivity checks” • Not being quantitative research

Acknowledgements

Abbreviations.

EVT	Endovascular treatment
RCT	Randomised Controlled Trial
SOP	Standard Operating Procedure
SRQR	Standards for Reporting Qualitative Research

Authors’ contributions

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

no external funding.

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Qualitative research examples

UserTesting

Qualitative research is a powerful tool that helps you unlock insights into the user experience—quintessential to building effective products and services. It provides a deeper understanding of complex behaviors, needs, and motivations. But what is qualitative research, and when is it ideal to use it? Let’s explore its methodologies and implementation with a few qualitative research examples.

What is qualitative research?

Qualitative research is a behavioral research method that seeks to understand the undertones, motivations, and subjective interpretations inherent in human behavior. It involves gathering nonnumerical data, such as text, audio, and video, allowing you to explore nuances and patterns that quantitative data can’t capture.

Instead of focusing on how many or how much, qualitative research questions delve into the why and how. This approach is instrumental in gaining a comprehensive understanding of a particular context, issue, or phenomenon from the perspective of those experiencing it. Examples of qualitative research questions include “How did you feel when you first used our product?” and “Could you describe your experience when you purchased a product from our website?”

Qualitative research methodology

Qualitative research design employs a variety of methodologies to collect and analyze data. The primary objective is to gather detailed and nuanced insights rather than generalizable findings. Steps include the following:

Formulating research questions: Qualitative research begins by identifying specific research questions to guide the study. These questions should align with the research objectives and provide a clear focus for data collection and analysis.
Selection of participants: Participant selection is a critical step in qualitative research. You must recruit participants who provide relevant and diverse perspectives on the research topic. It involves purposive sampling, where participants are chosen based on their knowledge or experiences related to the research questions.
Data collection: Qualitative research uses various methods to collect data, such as interviews, focus groups, observation, and document analysis. You often employ multiple methods to comprehensively understand the research topic.
Data analysis: Once the data is collected, it’s analyzed to identify recurring themes, patterns, and meanings. This analysis uses coding, thematic analysis, and constant comparison. The goal is to uncover the underlying perspectives of the participant.
Interpretation and reporting: This is the final step in which findings are synthesized and interpreted, revealing their significance to the research questions. You can present your findings through descriptive narratives, quotes, and illustrative examples to provide a rich understanding of the research topic.

Types of qualitative research methods

The best qualitative research method primarily depends on your research questions and objectives. Different methods uncover different discernments.

One-on-one interviews

You often use one-on-one interviews to delve deep into a topic or understand individual experiences or perspectives. An interviewer asks a participant open-ended questions to understand their perspective, thoughts, feelings, and experiences regarding a specific topic, product, or service. Read about open ended vs closed ended questions to learn which questions will be most effective in an interview.

Say you’re developing a new electric vehicle mode. You can conduct one-on-one interviews to understand user experiences, probing into aspects such as comfort, design, driving experience, and more.

Focus groups

In-person or remote focus groups involve a small group of people (usually 6–10) discussing a given topic or question under the guidance of a moderator. This method is beneficial when you want to understand group dynamics or collective views. The interaction among group members can disclose awarenesses that may not arise in one-on-one interviews.

In the gaming industry, for example, you can use focus groups to explore player reactions to a new game design. You can encourage group interaction to spark discussions about usability, game mechanics, graphics, storyline, and other aspects.

Case study research

Case study research provides an in-depth analysis of a particular case (an individual, group, organization, event, etc.) within its real-life context. It’s a valuable method for exploring something in-depth and in its natural setting.

For instance, a healthcare case study could explore implementing a new electronic health record system in a hospital, focusing on challenges, successes, and lessons learned.

Ethnographic research

Ethnographic research (or an ethnographic stud y) involves an immersive investigation into a group’s behaviors, culture, and practices. It requires you to engage directly with the participants over a prolonged period in their natural environment. It can help uncover how people interact with products or services in natural settings.

A gaming organization may choose to study players in their natural gaming environments (such as home, game cafes, or e-sport tournaments) to understand their gaming habits, social interactions, and responses to specific features. These insights can inform the development of more engaging and user-friendly games.

Process of observation

The process of observation typically doesn’t involve the same level of immersion as ethnographic research. You observe and record behavior related to a specific context or activity. It can be in natural settings (naturalistic observation) or a controlled environment. It’s more about observing and recording specific behaviors or situations rather than cultural norms or dynamics.

For example, a consumer technology organization could observe how users interact with a new software interface, noting challenges, efficiencies, and overall user experience.

Record keeping

Record keeping refers to collecting and analyzing documents, records, and artifacts that provide an understanding of the study area. Record keeping allows you to access historical and contextual data that can be examined and reexamined. It’s a nonobtrusive method, meaning it doesn’t involve direct contact with the participants, nor does it affect or alter the situation you’re studying.

An online retailer might examine shopping cart abandonment records to identify at what point in the buying process customers tend to drop off. This information can help streamline the checkout process and improve conversion rates.

Qualitative research: Data collection and analysis

Data collection and analysis in qualitative research are closely linked processes that help generate meaningful and useful results.

Data collection

Data collection involves gathering rich, detailed materials to explain and understand the subject. These include interview transcripts, meeting notes, personal diaries, and photographs.

There are various qualitative data collection methods to consider depending on your research questions and the context of your study. For example, you could use one-on-one interviews to understand personal user experiences with a financial services app. A moderated focus group may be more appropriate to discuss user preferences in a new media and entertainment platform.

Data analysis

Once data are collected, the analysis process begins. It’s where you extract patterns, themes, and insights from the collected data. It’s one of the most critical aspects of qualitative research, turning raw, unstructured data into valuable insights.

Qualitative data analysis usually takes place with several steps, such as:

Organizing and preparing the data for analysis
Reading through the data
Coding the data
Generating themes or categories
Interpreting the findings and
Representing the data

Your choice of qualitative data analysis method depends on your research questions and the data type you collected. Common analysis methods include thematic, content, discourse, and narrative analysis. Some research platforms provide AI features that can do much of this analysis for researchers to speed up insight gathering.

When to use qualitative research

Qualitative techniques are ideal for understanding human experiences and perspectives. Here are common situations where qualitative research is invaluable:

Exploring customer motivations, needs, behaviors, and pain points
Gathering in-depth user feedback on products and services
Understanding decision-making and buyer journeys
Discovering barriers to adoption and satisfaction
Developing hypotheses for future quantitative research
Testing concepts , interfaces, or designs
Identifying problems and improvement opportunities
Learning about group norms, cultures, and social interactions
Collecting evidence to develop theories and models
Capturing complex, nuanced insights beyond numbers

Qualitative research methods vs. quantitative research methods

Qualitative and quantitative research differ in their approach to data collection, analysis, and the nature of the findings. Here are some key differences:

Data collection: Qualitative research uses in-depth interviews , focus groups, observations, and analysis of documents to gather data. In contrast, quantitative research relies on structured surveys, experiments, and standard measurements.
Analysis: Qualitative research involves analyzing textual or visual data through coding, categorization, and theme identification techniques. Quantitative research uses statistical analysis to examine numerical data for patterns, correlations, and trends.
Sample size: Qualitative research typically involves smaller sample sizes, often selected through purposive sampling to ensure diversity and relevance. Quantitative research uses larger sample sizes to ensure statistical power and generalizability.
Generalizability: Qualitative research seeks in-depth insight into specific contexts or groups and does not prioritize generalizability. On the other hand, quantitative research seeks to draw conclusions that apply to a broader context.
Findings: Qualitative research generates descriptive and explanatory results that provide a deeper understanding of phenomena. Quantitative research produces numerical data that allows for statistical inferences and comparisons.
Theory development: Qualitative research often contributes to theory development by generating new concepts, theories, or frameworks based on the rich and context-specific data collected. However, quantitative research tests preexisting theories and hypotheses using statistical models.

Advantages and strengths of qualitative research

Qualitative research enriches your research process and outcomes, making it an invaluable tool in many fields, including UX research, marketing, and digital product development.

In-depth understanding

Qualitative research provides a rich, detailed, in-depth understanding of the research subject. Proactive qualitative research takes this further with ongoing data collection, allowing organizations to continuously capture insights and adapt strategies based on evolving user needs.

Contextual data

Qualitative research collects contextually relevant data. It captures nuances that might be missed in numerically-based quantitative data, allowing you to understand the contexts in which behaviors and interactions occur.

Flexibility

The methods used in qualitative research, like interviews and focus groups, enable you to explore different topics in depth and adapt your approach based on the participants’ responses.

Human perspective

Qualitative research lets you capture human experiences and thoughts. It’s advantageous in fields such as UX research, where the human perspective is critical.

Hypothesis generation

The exploratory nature of qualitative research helps you identify new areas for exploration or generate hypotheses you can test using quantitative methods.

Trendspotting

Qualitative research reveals trends in thought and opinions, diving deeper into the problem. This is helpful when trying to understand behaviors, culture, and user interactions.

Disadvantages and limitations of qualitative research

While qualitative research offers many advantages, it’s essential to acknowledge its limitations.

Time-consuming

Collecting and analyzing qualitative data, particularly from in-depth interviews or focus groups, requires significant time investment.

Qualitative research relies on the skills and judgment of the researcher, introducing potential bias into the research process. The researcher may actively shape the research by posing questions, interpreting data, and influencing the findings.

Requires skilled researchers

The quality of qualitative research heavily depends on the researcher’s skills, experience, and perspective. A less experienced researcher may overlook important nuances, potentially affecting the depth and accuracy of the findings.

Lacks generalizability

Qualitative research often involves a smaller, nonrepresentative sample size than quantitative research. Therefore, the findings may not be generalizable to a larger context.

Limited numeric representation

Qualitative research usually focuses on words, observations, or experiences, so it doesn’t provide the numeric estimates often desired in research studies.

Challenging to replicate and standardize

Qualitative research’s inherent flexibility and context dependence make it challenging to repeat the study under the same conditions. This flexibility can often make it hard to standardize. Researchers approach and conduct the study in various ways, leading to inconsistent results and interpretations.

Difficult to measure reliability and validity

Assessing reliability and validity is more difficult with qualitative research since it relies on subjective human interpretation and has few established metrics and statistical tools compared to quantitative research. Triangulation and member checking add credibility but lack the discreteness of quantitative measures. However, there have been advancement s in the measurement of qualitative research that help to quantify its impact.

Qualitative research gives you the opportunity to dive deep into human behavior, experiences, and perceptions. It offers a prolific, intricate perspective that quantifiable data alone can’t provide. Combine qualitative research methodologies with techniques like A/B testing to gain a more holistic understanding of user experiences and preferences.

Despite its limitations, the depth and richness of data procured through qualitative research are undeniable assets. By understanding and utilizing its diverse methods, you will uncover detailed insights from your target audience and enhance your products or services to meet their needs.

The UX research methodology guidebook

Learn how to gather the user feedback you need to build best-in-class products.

Why is qualitative research important?

Qualitative research delves into subjective experiences and social contexts, providing in-depth insights and understanding. It provides a deep understanding of individuals’ needs, motivations, and preferences, allowing organizations to develop products and services that meet customer expectations.

What’s the difference between quantitative and qualitative methods?

Quantitative methods focus on numerical data and statistical analysis, aiming for generalizability and objectivity. Qualitative methods explore meanings, experiences, and behaviors, seeking in-depth understanding and detailed descriptions.

What are the main qualitative research approaches?

The main qualitative research approaches include one-on-one interviews, focus groups, case study research, ethnographic research, observation, and record-keeping. Each approach offers unique benefits and applications.

What is data collection?

Data collection in qualitative research involves gathering information through various methods such as interviews, focus groups, observations, and document analysis. It’s a critical step in generating meaningful insights and understanding human experiences.

How do you analyze qualitative data?

What are the ethical considerations in qualitative research.

Ethical considerations refer to the protection of participants’ rights, privacy, and confidentiality. You must obtain informed consent, maintain anonymity, and handle sensitive information responsibly. Additionally, maintaining transparency, addressing power imbalances, and conducting research unbiased and respectfully are vital ethical considerations in qualitative research.

How can I incorporate qualitative research into my study or project?

To incorporate qualitative research into your study, you must first define your research objectives to guide the choice of methodology. Next, choose a suitable qualitative method, such as interviews or focus groups. Then, collect and analyze the data using appropriate techniques and, finally, interpret and present the findings clearly and meaningfully. Remember to be mindful of the ethical considerations throughout the process.

How do you effectively communicate and present qualitative research findings to stakeholders?

For a quality presentation, create engaging visual representations, such as infographics or data visualizations, and use storytelling techniques to highlight key insights. Also, prepare concise and informative reports and organize interactive presentations or workshops to facilitate discussion and understanding.

How do you translate qualitative research findings into actionable insights?

Identify key themes linked to research goals and propose strategic solutions to address core needs and barriers. These solutions should be tailored to specific needs.

How can I ensure the validity and reliability of qualitative research findings?

About the author(s).

With UserTesting’s on-demand platform, you uncover ‘the why’ behind customer interactions. In just a few hours, you can capture the critical human insights you need to confidently deliver what your customers want and expect.

Continuous discovery: all your questions answered

Photo of two women sitting at a desk looking at monitor showing a dashboard of ecommerce metrics

5 tips for retailers preparing for the 2024 holiday shopping season

How and why you should test your product description pages

Human understanding. Human experiences.

Get the latest news on events, research, and product launches

Oh no! We're unable to display this form.

Please check that you’re not running an adblocker and if you are please whitelist usertesting.com.

If you’re still having problems please drop us an email .

By submitting the form, I agree to the Privacy Policy and Terms of Use .

Find the right market research agencies, suppliers, platforms, and facilities by exploring the services and solutions that best match your needs

list of top MR Specialties

Browse all specialties

Browse Companies and Platforms

by Specialty

by Location

Browse Focus Group Facilities

Manage your listing

Follow a step-by-step guide with online chat support to create or manage your listing.

About Greenbook Directory

IIEX Conferences

Discover the future of insights at the Insight Innovation Exchange (IIEX) event closest to you

IIEX Virtual Events

Explore important trends, best practices, and innovative use cases without leaving your desk

Insights Tech Showcase

See the latest research tech in action during curated interactive demos from top vendors

Stay updated on what’s new in insights and learn about solutions to the challenges you face

Greenbook Future list

An esteemed awards program that supports and encourages the voices of emerging leaders in the insight community.

Insight Innovation Competition

Submit your innovation that could impact the insights and market research industry for the better.

Find your next position in the world's largest database of market research and data analytics jobs.

For Suppliers

Directory: Renew your listing

Directory: Create a listing

Event sponsorship

Get Recommended Program

Digital Ads

Content marketing

Ads in Reports

Podcasts sponsorship

Run your Webinar

Host a Tech Showcase

Future List Partnership

All services

Dana Stanley

Greenbook’s Chief Revenue Officer

Qualitative Research

June 28, 2024

8 Examples of Qualitative Research

Unveil the depth of human behavior with qualitative research. Dive into narratives and interpretations to find hidden meanings in market research and UX design.

by Ashley Shedlock

Content Coordinator at Greenbook

Qualitative research offers deep insights into human behavior by delving into individual perspectives, societal dynamics, and cultural influences. It emphasizes narratives and subjective interpretations to unveil hidden meanings. Real-world examples in fields like market research and UX design demonstrate how qualitative research uncovers consumer behaviors and user experiences, driving innovative solutions and informed decision-making through the richness of human interactions.

What is Qualitative Research?

Qualitative research is a methodology used to gain an in-depth understanding of human behavior and the reasons that govern such behavior. It focuses on exploring and interpreting phenomena in their natural settings, aiming to uncover the meaning individuals attribute to their experiences. Qualitative research encompasses a variety of methods such as interviews, observations, case studies, and focus groups, allowing researchers to delve deep into the complexities of human interactions and perceptions.

By emphasizing subjective experiences and perspectives, qualitative research adds richness and depth to our understanding of social phenomena. It is a valuable tool for uncovering nuances, exploring diverse viewpoints, and capturing the essence of complex human behavior that quantitative methods often overlook.

Qualitative Research Methods vs Quantitative Research Methods

When contrasting qualitative and quantitative research methods, it is crucial to recognize the unique approaches they employ in examining phenomena. Qualitative research methods involve delving into the depth and intricacies of human experiences, beliefs, and behaviors.

In contrast to quantitative research's focus on numerical data and statistical analysis, qualitative research delves into the intricacies of human narratives and perspectives. Qualitative research methods encompass various approaches such as interviews, focus groups, observations, and content analysis.

In qualitative research, researchers immerse themselves in the study's context to gain a comprehensive understanding of the subject matter. This approach allows for flexibility and adaptability, enabling researchers to uncover unexpected insights and meanings. For example, conducting in-depth interviews can unveil personal narratives and emotions that quantitative data may not capture alone.

Ethnographic research is another qualitative method where researchers observe and engage in the daily lives of the subjects. This approach provides insights into cultural practices, social interactions, and the contextual factors influencing behaviors. By immersing themselves in the research environment, researchers unveil valuable insights contributing to a broader understanding of the subject.

Thematic analysis, a qualitative research method, involves identifying patterns and themes within qualitative data. Researchers scrutinize textual or visual data to unveil recurring topics or ideas, facilitating the development of meaningful interpretations. This method aids in organizing and deriving sense from the vast qualitative data amassed during a study.

In contrast to quantitative research methods that quantify relationships and outcomes, qualitative methods emphasize exploring meanings, interpretations, and subjective experiences. By integrating various qualitative research methods, researchers can attain a holistic understanding of complex phenomena that transcends mere numerical representations.

While qualitative research methods may not yield universally applicable results like quantitative methods, they offer a profound exploration of the human experience. Embracing the complexities of qualitative research enables researchers to unearth valuable insights and deepen our understanding of the world.

Types of Qualitative Research

1. Interviews: One common type of qualitative research is conducting interviews. Researchers engage with participants in open-ended conversations to gather in-depth insights into their experiences, opinions, and perspectives. These interviews can be structured, semi-structured, or unstructured, allowing for a flexible approach to data collection.

2. Observations: Another key example of qualitative research is observations. Researchers directly observe subjects in their natural environment to understand behavior, interactions, and social dynamics. This method allows for the study of non-verbal cues, environmental influences, and group dynamics that may not be captured through other means.

3. Focus Groups: Qualitative research often utilizes focus groups to gather data from multiple participants simultaneously. In these group discussions, participants are encouraged to express their thoughts, feelings, and attitudes on a specific topic. The dynamic interaction among group members can yield rich insights and uncover collective beliefs or norms.

4. Case Studies: Case studies involve an in-depth analysis of a particular individual, group, or event. Researchers delve deeply into the case to explore nuances, contexts, and unique circumstances. By examining specific instances in detail, researchers can uncover rich, detailed insights that contribute to a broader understanding of the topic under study.

5. Content Analysis: Researchers may also employ content analysis as a qualitative research method. This involves systematically analyzing text, audio, video, or visual content to identify patterns, themes, and meanings. Through content analysis, a qualitative researcher can uncover underlying messages, cultural representations, and discourses present in the materials being studied.

6. Narrative Research: Narrative research focuses on the stories and personal accounts of individuals to understand their lived experiences. By analyzing narratives shared by participants, researchers can uncover themes, emotions, and perspectives that reveal deeper insights into human behavior and social phenomena.

7. Ethnographic Research: Ethnographic research involves immersing researchers in the culture or community being studied. Researchers spend extended periods observing and interacting with participants to gain a holistic understanding of their behaviors, practices, and beliefs. This immersive approach allows for a nuanced exploration of social contexts and cultural nuances.

8. Action Research: In action research, researchers actively engage with participants to bring about positive change or address real-world problems. This collaborative approach combines research and practical action, allowing for the co-creation of knowledge and the implementation of solutions based on research findings.

Each type of qualitative research offers a unique perspective and methodology for understanding complex human experiences and social phenomena. By employing a combination of these methods, researchers can gain comprehensive insight that enriches our understanding of the world around us.

Data Collection Techniques in Qualitative Research

Qualitative research utilizes interviews to gain detailed participant insight. Observations capture behaviors in natural settings, revealing hidden dynamics and influences. Focus groups facilitate group discussions to reveal shared beliefs and differences. Document analysis extracts insights from various materials, offering historical and cultural context.

Each method contributes uniquely to data collection: interviews provide personal accounts, observations offer direct insights, focus groups foster discussions, and document analysis adds historical perspective. Researchers should maintain clear communication, ethical standards, and rigorous data analysis. Examples include interviews uncovering patient experiences, observations revealing classroom dynamics, focus groups identifying consumer preferences, and document analysis unveiling social trends.

When to Use Qualitative Research Methods

Qualitative research methods are best utilized when you aim to delve deep into understanding complex phenomena that cannot be quantified easily. These methods are particularly valuable when exploring people's emotions, behaviors, motivations, and experiences, providing rich, nuanced insights that quantitative data alone cannot capture. By employing qualitative research, you can uncover underlying reasons behind certain trends or patterns, shedding light on the 'why' rather than just the 'what' of a particular situation or behavior.

One of the key advantages of qualitative research methods is their flexibility and adaptability to different research settings. Whether conducting in-depth interviews, focus groups, or observational studies, these methods allow researchers to immerse themselves in the context under study, gaining a holistic understanding of the subject matter. This hands-on approach enables the researcher to gather detailed, in-depth information that can offer unique perspectives and unveil unexpected insights.

Qualitative research methods excel in exploring sensitive topics or marginalized voices, giving a platform for individuals to share their experiences and perspectives in a supportive and non-threatening environment. This can be particularly valuable in areas such as social sciences, psychology, anthropology, and market research, where understanding human behavior and social dynamics is paramount.

Qualitative research provides a qualitative researcher with a powerful toolkit to explore the intricacies of human experiences, behaviors, and interactions. By embracing the richness of qualitative data, researchers can generate meaningful narratives, valuable insights, and actionable recommendations that contribute significantly to advancing knowledge and understanding in various fields of study.

Ashley Shedlock

11 articles

The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.

Comments are moderated to ensure respect towards the author and to prevent spam or self-promotion. Your comment may be edited, rejected, or approved based on these criteria. By commenting, you accept these terms and take responsibility for your contributions.

Evrim Tanis

July 4, 2024

This is a very detailed and beautiful article about qualitative research. Congratulations; you also combined research and technology.

Qualitative vs. Quantitative Market Research: Why Not Both?

Discover the benefits of qualitative and quantitative methods. Learn how to leverage both approaches for insights into consumer behavior and industry ...

August 14, 2024

Read article

Brand Strategy

Brand Tracking Tech 101

Gain valuable insights into consumer preferences and behaviors with brand tracking. Stay ahead of the competition by monitoring key brand metrics cons...

July 31, 2024

How to Use Automation in Research

Discover the power of automation in research. Streamline processes and enhance efficiency. Transform data collection and analysis for speed and scalab...

July 26, 2024

Customer Experience (CX)

How to Use Mystery Shopping Research to Improve the Customer Experience

Discover the power of mystery shopping research in improving customer experience. Uncover service strengths and exceed customer expectations to boost ...

July 25, 2024

Top in Quantitative Research

Moving Away from a Narcissistic Market Research Model

Why are we still measuring brand loyalty? It isn’t something that naturally comes up with consumers, who rarely think about brand first, if at all. Ma...

Devora Rogers

Chief Strategy Officer at Alter Agents

May 31, 2023

Get content that matters, written by top insights industry experts, delivered right to your inbox.

67k+ subscribers

Weekly Newsletter

Greenbook Podcast

Event Updates

I agree to receive emails with insights-related content from Greenbook. I understand that I can manage my email preferences or unsubscribe at any time and that Greenbook protects my privacy under the General Data Protection Regulation.*

Get the latest updates from top market research, insights, and analytics experts delivered weekly to your inbox

Your guide for all things market research and consumer insights

Create a New Listing

Manage My Listing

Find Companies

Find Focus Group Facilities

Tech Showcases

GRIT Report

Expert Channels

Get in touch

Marketing Services

Future List

Publish With Us

Cookie policy

Qualitative Research Definition

Qualitative research methods and examples, advantages and disadvantages of qualitative approaches, qualitative vs. quantitative research, showing qualitative research skills on resumes, what is qualitative research methods and examples.

Share on Twitter Share on Twitter
Share on Facebook Share on Facebook
Share on LinkedIn Share on LinkedIn

What Is Qualitative Research? Examples and methods

Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full editorial guidelines .

Qualitative research seeks to understand people’s experiences and perspectives by studying social organizations and human behavior. Data in qualitative studies focuses on people’s beliefs and emotional responses. Qualitative data is especially helpful when a company wants to know how customers feel about a product or service, such as in user experience (UX) design or marketing .

Researchers use qualitative approaches to “determine answers to research questions on human behavior and the cultural values that drive our thinking and behavior,” says Margaret J. King, director at The Center for Cultural Studies & Analysis in Philadelphia.

Data in qualitative research typically can’t be assessed mathematically — the data is not sets of numbers or quantifiable information. Rather, it’s collections of images, words, notes on behaviors, descriptions of emotions, and historical context. Data is collected through observations, interviews, surveys, focus groups, and secondary research.

However, a qualitative study needs a “clear research question at its base,” notes King, and the research needs to be “observed, categorized, compared, and evaluated (along a scale or by a typology chart) by reference to a baseline in order to determine an outcome with value as new and reliable information.”

What's the difference: Data science vs. software engineering?

Quantium Data Analytics

Explore the power of data and its ability to power breakthrough possibilities for individuals, organisations and societies with this free job simulation from Quantium.

Avg. Time: 4 to 5 hours

Skills you’ll build: Data validation, data visualisation, data wrangling, programming, data analysis, commercial thinking, statistical testing, presentation skills

Who Uses Qualitative Research?

Researchers in social sciences and humanities often use qualitative research methods, especially in specific areas of study like anthropology, history, education, and sociology.

Qualitative methods are also applicable in business, technology , and marketing spaces. For example, product managers use qualitative research to understand how target audiences respond to their products. They may use focus groups to gain insights from potential customers on product prototypes and improvements or surveys from existing customers to understand what changes users want to see.

Other careers that may involve qualitative research include:

Marketing analyst
UX and UI analyst
Market researcher
Statistician
Business analyst
Data analyst
Research assistant
Claims investigator

Electronic Arts Product Management

Learn how product managers leverage qualitative and other types of research to build and improve products in this free job simulation from EA.

Avg. Time: 1 to 2 hours

Skills you’ll build: Critical thinking, problem solving, performance metrics, written communication, project planning

Good research begins with a question, and this question informs the approach used by qualitative researchers.

Grounded Theory

Grounded theory is an inductive approach to theory development. In many forms of research, you begin with a hypothesis and then test it to see if you’re correct. In grounded theory, though, you go in without any assumptions and rely on the data you collect to form theories. You start with an open question about a phenomenon you are studying and collect and analyze data until you can form a fully-fledged theory from the information.

Example: A company wants to improve its brand and marketing strategies. The company performs a grounded theory approach to solving this problem by conducting interviews and surveys with past, current, and prospective customers. The information gathered from these methods helps the company understand what type of branding and marketing their customer-base likes and dislikes, allowing the team to inductively craft a new brand and marketing strategy from the data.

Action Research

Action research is one part study and one part problem-solving . Through action research, analysts investigate a problem or weakness and develop practical solutions. The process of action research is cyclical —- researchers assess solutions for efficiency and effectiveness, and create further solutions to correct any issues found.

Example: A manager notices her employees struggle to cooperate on group projects. She carefully reviews how team members interact with each other and asks them all to respond to a survey about communication. Through the survey and study, she finds that guidelines for group projects are unclear. After changing the guidelines, she reviews her team again to see if there are any changes to their behavior.

>>MORE: Explore how action research helps consultants serve clients with Accenture’s Client Research and Problem Identification job simulation .

Phenomenological Research

Phenomenological research investigates a phenomenon in depth, looking at people’s experiences and understanding of the situation. This sort of study is primarily descriptive and seeks to broaden understanding around a specific incident and the people involved. Researchers in phenomenological studies must be careful to set aside any biases or assumptions because the information used should be entirely from the subjects themselves.

Example : A researcher wants to better understand the lived experience of college students with jobs. The purpose of this research is to gain insights into the pressures of college students who balance studying and working at the same time. The researcher conducts a series of interviews with several college students, learning about their past and current situations. Through the first few interviews, the researcher builds a relationship with the students. Later discussions are more targeted, with questions prompting the students to discuss their emotions surrounding both work and school and the difficulties and benefits arising from their situation. The researcher then analyzes these interviews, and identifies shared themes to contextualize the experiences of the students.

GE Aerospace Human Resources

Learn the research and conflict resolution skills necessary for a career in human resources in this free job simulation from GE.

Avg. Time: 3 to 4 hours

Skills you’ll build: Feedback giving, communication skills, empowering with insights, basics of lean, process mapping, continuous improvement tools, dataset handling in Excel

Ethnography

Ethnography is an immersive study of a particular culture or community. Through ethnographic research, analysts aim to learn about a group’s conventions, social dynamics, and cultural norms. Some researchers use active observation methods, finding ways to integrate themselves into the culture as much as possible. Others use passive observation, watching closely from the outside but not fully immersing themselves.

Example: A company hires an external researcher to learn what their company’s culture is actually like. The researcher studies the social dynamics of the employees and may even look at how these employees interact with clients and with each other outside of the office. The goal is to deliver a comprehensive report of the company’s culture and the social dynamics of its employees.

Case Studies

A case study is a type of in-depth analysis of a situation. Case studies can focus on an organization, belief system, event, person, or action. The goal of a case study is to understand the phenomenon and put it in a real-world context. Case studies are also commonly used in marketing and sales to highlight the benefits of a company’s products or services.

Example: A business performs a case study of its competitors’ strategies. This case study aims to show why the company should adopt a specific business strategy. The study looks at each competitor’s business structure, marketing campaigns, product offerings, and historical growth trends. Then, using this data on other businesses, the researcher can theorize how that strategy would benefit their company.

>>MORE: Learn how companies use case study interviews to assess candidates’ research and problem-solving skills.

Qualitative research methods are great for generating new ideas. The exploratory nature of qualitative research means uncovering unexpected information, which often leads to new theories and further research topics. Additionally, qualitative findings feel meaningful. These studies focus on people, emotions, and societies and may feel closer to their communities than quantitative research that relies on more mathematical and logical data.

However, qualitative research can be unreliable at times. It’s difficult to replicate qualitative studies since people’s opinions and emotions can change quickly. For example, a focus group has a lot of variables that can affect the outcome, and that same group, asked the same questions a year later, may have entirely different responses. The data collection can also be difficult and time-consuming with qualitative research. Ultimately, interviewing people, reviewing surveys, and understanding and explaining human emotions can be incredibly complex.

Find your career fit

See what career path is right for you with our free career quiz!

While qualitative research deals with data that isn’t easily manipulated by mathematics, quantitative research almost exclusively involves numbers and numerical data. Quantitative studies aim to find concrete details, like units of time, percentages, or statistics.

Besides the types of data used, a core difference between quantitative and qualitative research is the idea of control and replication.

“Qualitative is less subject to control (as in lab studies) and, therefore, less statistically measurable than quantitative approaches,” says King.

One person’s interview about a specific topic can have completely different responses than every other person’s interview since there are so many variables in qualitative research. On the other hand, quantitative studies can often be replicated. For instance, when testing the effects of a new medication, quantifiable data, like blood test results, can be repeated. Qualitative data, though, like how people feel about the medication, may differ from person to person and from moment to moment.

J.P.Morgan bank corporation headquarters glass building concept. JP Morgan banking company symbol on front facade 3d illustration.

JPMorgan Quantitative Research

Discover how bankers use quantitative methods to analyze businesses and industry trends with this free job simulation.

Avg. Time: 6 to 7 hours

Skills you’ll build: Programming, data analysis, Python, critical thinking, statistics, dynamic programming

You can show your experience with qualitative research on your resume in your skills or work experience sections and your cover letter .

In your skills section , you can list types of qualitative research you are skilled at, like conducting interviews, performing grounded theory research, or crafting case studies.
In your work or internship experience descriptions , you can highlight specific examples, like talking about a time you used action research to solve a complex issue at your last job.
In your cover letter , you can discuss in-depth qualitative research projects you’ve completed. For instance, say you spent a summer conducting ethnographic research or a whole semester running focus groups to get feedback on a product. You can talk about these experiences in your cover letter and note how these skills make you a great fit for the job.

Grow your skills and explore your career options with Forage’s free job simulations .

Image credit: Canva

6 negotiation skills to level up your work life, how to build conflict resolution skills: case studies and examples, what is github uses and getting started, upskill with forage.

Top companies are hiring now!

MS in the Learning Sciences
Tuition & Financial Aid

SMU Simmons School of Education & Human Development

Qualitative vs. quantitative data analysis: How do they differ?

Learning analytics have become the cornerstone for personalizing student experiences and enhancing learning outcomes. In this data-informed approach to education there are two distinct methodologies: qualitative and quantitative analytics. These methods, which are typical to data analytics in general, are crucial to the interpretation of learning behaviors and outcomes. This blog will explore the nuances that distinguish qualitative and quantitative research, while uncovering their shared roles in learning analytics, program design and instruction.

What is qualitative data?

Qualitative data is descriptive and includes information that is non numerical. Qualitative research is used to gather in-depth insights that can't be easily measured on a scale like opinions, anecdotes and emotions. In learning analytics qualitative data could include in depth interviews, text responses to a prompt, or a video of a class period. 1

What is quantitative data?

Quantitative data is information that has a numerical value. Quantitative research is conducted to gather measurable data used in statistical analysis. Researchers can use quantitative studies to identify patterns and trends. In learning analytics quantitative data could include test scores, student demographics, or amount of time spent in a lesson. 2

Key difference between qualitative and quantitative data

It's important to understand the differences between qualitative and quantitative data to both determine the appropriate research methods for studies and to gain insights that you can be confident in sharing.

Data Types and Nature

Examples of qualitative data types in learning analytics:

Observational data of human behavior from classroom settings such as student engagement, teacher-student interactions, and classroom dynamics
Textual data from open-ended survey responses, reflective journals, and written assignments
Feedback and discussions from focus groups or interviews
Content analysis from various media

Examples of quantitative data types:

Standardized test, assessment, and quiz scores
Grades and grade point averages
Attendance records
Time spent on learning tasks
Data gathered from learning management systems (LMS), including login frequency, online participation, and completion rates of assignments

Methods of Collection

Qualitative and quantitative research methods for data collection can occasionally seem similar so it's important to note the differences to make sure you're creating a consistent data set and will be able to reliably draw conclusions from your data.

Qualitative research methods

Because of the nature of qualitative data (complex, detailed information), the research methods used to collect it are more involved. Qualitative researchers might do the following to collect data:

Conduct interviews to learn about subjective experiences
Host focus groups to gather feedback and personal accounts
Observe in-person or use audio or video recordings to record nuances of human behavior in a natural setting
Distribute surveys with open-ended questions

Quantitative research methods

Quantitative data collection methods are more diverse and more likely to be automated because of the objective nature of the data. A quantitative researcher could employ methods such as:

Surveys with close-ended questions that gather numerical data like birthdates or preferences
Observational research and record measurable information like the number of students in a classroom
Automated numerical data collection like information collected on the backend of a computer system like button clicks and page views

Analysis techniques

Qualitative and quantitative data can both be very informative. However, research studies require critical thinking for productive analysis.

Qualitative data analysis methods

Analyzing qualitative data takes a number of steps. When you first get all your data in one place you can do a review and take notes of trends you think you're seeing or your initial reactions. Next, you'll want to organize all the qualitative data you've collected by assigning it categories. Your central research question will guide your data categorization whether it's by date, location, type of collection method (interview vs focus group, etc), the specific question asked or something else. Next, you'll code your data. Whereas categorizing data is focused on the method of collection, coding is the process of identifying and labeling themes within the data collected to get closer to answering your research questions. Finally comes data interpretation. To interpret the data you'll take a look at the information gathered including your coding labels and see what results are occurring frequently or what other conclusions you can make. 3

Quantitative analysis techniques

The process to analyze quantitative data can be time-consuming due to the large volume of data possible to collect. When approaching a quantitative data set, start by focusing in on the purpose of your evaluation. Without making a conclusion, determine how you will use the information gained from analysis; for example: The answers of this survey about study habits will help determine what type of exam review session will be most useful to a class. 4

Next, you need to decide who is analyzing the data and set parameters for analysis. For example, if two different researchers are evaluating survey responses that rank preferences on a scale from 1 to 5, they need to be operating with the same understanding of the rankings. You wouldn't want one researcher to classify the value of 3 to be a positive preference while the other considers it a negative preference. It's also ideal to have some type of data management system to store and organize your data, such as a spreadsheet or database. Within the database, or via an export to data analysis software, the collected data needs to be cleaned of things like responses left blank, duplicate answers from respondents, and questions that are no longer considered relevant. Finally, you can use statistical software to analyze data (or complete a manual analysis) to find patterns and summarize your findings. 4

Qualitative and quantitative research tools

From the nuanced, thematic exploration enabled by tools like NVivo and ATLAS.ti, to the statistical precision of SPSS and R for quantitative analysis, each suite of data analysis tools offers tailored functionalities that cater to the distinct natures of different data types.

Qualitative research software:

NVivo: NVivo is qualitative data analysis software that can do everything from transcribe recordings to create word clouds and evaluate uploads for different sentiments and themes. NVivo is just one tool from the company Lumivero, which offers whole suites of data processing software. 5

ATLAS.ti: Similar to NVivo, ATLAS.ti allows researchers to upload and import data from a variety of sources to be tagged and refined using machine learning and presented with visualizations and ready for insert into reports. 6

SPSS: SPSS is a statistical analysis tool for quantitative research, appreciated for its user-friendly interface and comprehensive statistical tests, which makes it ideal for educators and researchers. With SPSS researchers can manage and analyze large quantitative data sets, use advanced statistical procedures and modeling techniques, predict customer behaviors, forecast market trends and more. 7

R: R is a versatile and dynamic open-source tool for quantitative analysis. With a vast repository of packages tailored to specific statistical methods, researchers can perform anything from basic descriptive statistics to complex predictive modeling. R is especially useful for its ability to handle large datasets, making it ideal for educational institutions that generate substantial amounts of data. The programming language offers flexibility in customizing analysis and creating publication-quality visualizations to effectively communicate results. 8

Applications in Educational Research

Both quantitative and qualitative data can be employed in learning analytics to drive informed decision-making and pedagogical enhancements. In the classroom, quantitative data like standardized test scores and online course analytics create a foundation for assessing and benchmarking student performance and engagement. Qualitative insights gathered from surveys, focus group discussions, and reflective student journals offer a more nuanced understanding of learners' experiences and contextual factors influencing their education. Additionally feedback and practical engagement metrics blend these data types, providing a holistic view that informs curriculum development, instructional strategies, and personalized learning pathways. Through these varied data sets and uses, educators can piece together a more complete narrative of student success and the impacts of educational interventions.

Master Data Analysis with an M.S. in Learning Sciences From SMU

Whether it is the detailed narratives unearthed through qualitative data or the informative patterns derived from quantitative analysis, both qualitative and quantitative data can provide crucial information for educators and researchers to better understand and improve learning. Dive deeper into the art and science of learning analytics with SMU's online Master of Science in the Learning Sciences program . At SMU, innovation and inquiry converge to empower the next generation of educators and researchers. Choose the Learning Analytics Specialization to learn how to harness the power of data science to illuminate learning trends, devise impactful strategies, and drive educational innovation. You could also find out how advanced technologies like augmented reality (AR), virtual reality (VR), and artificial intelligence (AI) can revolutionize education, and develop the insight to apply embodied cognition principles to enhance learning experiences in the Learning and Technology Design Specialization , or choose your own electives to build a specialization unique to your interests and career goals.

For more information on our curriculum and to become part of a community where data drives discovery, visit SMU's MSLS program website or schedule a call with our admissions outreach advisors for any queries or further discussion. Take the first step towards transforming education with data today.

Retrieved on August 8, 2024, from nnlm.gov/guides/data-glossary/qualitative-data
Retrieved on August 8, 2024, from nnlm.gov/guides/data-glossary/quantitative-data
Retrieved on August 8, 2024, from cdc.gov/healthyyouth/evaluation/pdf/brief19.pdf
Retrieved on August 8, 2024, from cdc.gov/healthyyouth/evaluation/pdf/brief20.pdf
Retrieved on August 8, 2024, from lumivero.com/solutions/
Retrieved on August 8, 2024, from atlasti.com/
Retrieved on August 8, 2024, from ibm.com/products/spss-statistics
Retrieved on August 8, 2024, from cran.r-project.org/doc/manuals/r-release/R-intro.html#Introduction-and-preliminaries

Return to SMU Online Learning Sciences Blog

Southern Methodist University has engaged Everspring , a leading provider of education and technology services, to support select aspects of program delivery.

This will only take a moment

surveys | August 27, 2020

The Guide to Qualitative Research: Methods, Types, and Examples

Daniel Ndukwu

Qualitative research is an important part of any project. It gives you insights that quantitative research can’t hope to match.

To receive the benefits that qualitative research can bring to the table, it’s essential to do it properly. That’s easier said than done.

This in-depth guide will give you a better understanding of qualitative research, how it can be used, the methods for carrying it out, and its limitations.

Table of Contents

What is qualitative research?

Qualitative research is the process of gathering non-numerical data that helps you understand the deeper meaning behind a topic. It can help you decipher the motivations, thought processes, and opinions of people who are experiencing the problem or situation.

For example, an entrepreneur wants to start a shoe brand targeted at a younger demographic. They know younger people spend more money on name-brand basketball shoes. Qualitative research will help them understand the motivations and thought processes behind why those shoes are appealing.

With the help of capable marketing teams and mentors , they can use this data to craft communication plans that will resonate with their audience.

The data gained helps develop better hypotheses, confirm or disprove theories, and informs quantitative research studies. There are multiple quantitative research methods that are ideal for certain situations and this guide delves deeper into those data collection processes .

Keep in mind that qualitative research gives you descriptive data that must then be analyzed and interpreted. This process is much more difficult than a quantitative analysis which is why many organizations opt to skip it entirely.

What’s the purpose of qualitative research?

Qualitative research was popularized by psychologists and sociologists who were unhappy with the scientific method in use.

In the legal industry, understanding qualitative insights can significantly enhance strategies for law firm SEO , helping firms to better align their services with client needs.

Traditional scientific methods were only able to tell what was happening but failed to understand why.

Qualitative research, on the other hand, seeks to find the deeper meaning behind actions and situations. For example, you may realize a relationship between two things exist like poverty and lower literacy rates. It’s qualitative data that can help you understand why this relationship exists.

In the diverse landscape of qualitative research its application extends beyond conventional fields offering valuable insights in specialized areas take for instance the legal sector where understanding nuanced human experiences is crucial a cerebral palsy lawyer leveraging qualitative research delves deeper into the multifaceted experiences of individuals and families impacted by cerebral palsy this methodical approach aids in comprehending the broader social emotional and economic ramifications thereby guiding more compassionate and effective legal representation.

When should qualitative research be used

There’s a simple stress test to understand whether qualitative research or quantitative research should be used. Ask yourself the following questions:

Do you have a clear understanding of the problem? If not, use it;
Do you understand the reasons that contribute to the problem or situation? If not, use it;
Are the attitudes of the people who experience or display the behavior clear to you? If not, use it;
Have you already analyzed first-person accounts or research related to the topic? If not, use it.

Qualitative research vs quantitative research

There’s a big difference between the two types of research. For the most part, qualitative research is exploratory. You’re trying to figure out the reasons behind situations and form a clearer hypothesis. Those hypotheses are then tested with further qualitative or quantitative research.

Quantitative research focuses on collecting numerical data that can be used to quantify the magnitude of a situation. The data gained can be organized and statistical analysis carried out.

For example, qualitative research may tell you that people in lower-income areas drop out of school and have lower literacy rates. Quantitative research can tell you the percentage of people that end up dropping out of school within a given population.

As you can see, they work together to give you a holistic understanding of a market or problem.

Qualitative research data collection Methods

We’ve written an in-depth guide about the data collection methods you can use for both quantitative and qualitative research. This section will give you a quick overview of the data collection methods available.

The first data collection method and the most common are surveys. More specifically, surveys with open-ended questions . These give your respondents the opportunity to explain things with their own words.

Another benefit of surveys, especially with online survey tools like KyLeads is that you can quickly distribute your survey to a huge audience. This can cut down on your costs while still giving you the insights you need.

There are two problems with surveys. The first one is that you’re unable to ask relevant clarifying questions. Some of the data you collect may be unclear and lead you to the wrong conclusions.

The second problem is that respondents, unless adequately incentivized, may abandon the survey or give inadequate answers. This is known as survey fatigue and is a challenge when you have longer surveys. You can mitigate the effects by placing the most important questions first.

Focus groups

A focus group involves 3 – 10 people and a specialized moderator. Groups larger than ten should be broken up and those fewer than three won’t be able to deliver the insights you need.

The benefits of a focus group come from the ability to recreate specific situations or test scenarios before they happen. To get the most out of the focus group, it’s important to carefully select the participants based on their demographic and psychographic profiles .

The advantage of a focus group is that the information is insightful and comes from multiple people within your target market. The disadvantage is that groupthink can be a real problem.

You can prevent groupthink by having people write their opinions down before voicing them and even assigning one person to play devil’s advocate. Don’t discourage divergent opinions or perspectives.

Another challenge is that focus groups are expensive compared to other methods listed here. The participants are usually paid for their time and it requires things like meeting space and specialized staff.

Interviews are an old staple of qualitative research and are almost as common as surveys. Interviews can be conducted over the phone, in person, or even through a video conference. The important part is that they’re real-time and you can ask clarifying questions so you don’t draw the wrong conclusions.

There are multiple types of interviews. You can use structured interviews, unstructured interviews, or semi-structured interviews. Keep in mind that the structured interview may not be the best option if you’re doing exploratory =research.

Observation/immersion

This is the process of observing the ongoing behavior of an individual or group. It’s most prevalent in social sciences and marketing applications. This data collection method is the most passive and may not be ideal when doing initial exploratory research. You may be drawing conclusions on incomplete information.

There is an option of participating actively in what you’re observing. Keep in mind that this is frowned upon because the researcher may accidentally introduce biases. The biggest disadvantage is that some things simply can’t be observed by a researcher without interaction.

Try to use team collaboration to cut down on the biases that will be introduced. Compare notes and, as much as possible, look at things objectively. A teammate is invaluable for this kind of exercise.

Pros and cons of qualitative research

Qualitative research is powerful and has many benefits but it also has multiple disadvantages you should be aware of before jumping in.

Get a deep understanding of the behaviors and attitudes of your target group
You can get those insights from smaller samples sizes
As long as you choose the right aspects to focus on and groups to work with, the insights can have much wider applications.
Helps reduce biases because you’re doing exploratory research to get a baseline of information
Most qualitative research is fluid meaning it adapts to the inputs to get a better understanding of the overall situation
The data itself is subjective because it’s based on the experiences and biases of the respondents
It’s more expensive than quantitative research
It can take much longer to go through the more involved data collection methods like focus groups and interviews
It’s more difficult to analyze and often requires people with specialized skills
It’s nonnumerical in nature so statistical analysis cannot be applied to the data
Results can’t be easily replicated following the scientific method

Qualitative research can be a powerful tool in your arsenal but there are many things to take into consideration. It tends to take longer to collect the data and analyze it. It’s also more expensive than most quantitative research methods.

Before diving into a qualitative research strategy, define clear goals, a timeframe for completion, and the kind of information you need to solve your problem.

Let me know what you think in the comments and don’t forget to share.

what types of questionnaire appropriate to be use in qualitative research ?

This guide will give you a detailed answer https://www.kyleads.com/blog/questionnaire/

The Guide To Good Employee Engagement Survey Questions (+25 Examples)

Employee satisfaction surveys are inconclusive. No matter how many polls you conduct, the results aren’t revealing anything substantial about the […]

December 6, 2021 | surveys

How to Analyze Survey Results and Display Them Visually

How to present your survey data in a way that’s visually appealing, engaging, and informative? Through the magic of visualization. […]

Mariya Koracheva

May 19, 2021 | surveys

4 Best Practices of Asking for Customer Feedback with Emails

Satisfied customers are the lifeblood of any business. Happy customers spend more on brands they support which means increased sales […]

Hugh Beaulac

May 14, 2021 | Email Marketing

How it works

Qualitative Research Questionnaire – Types & Examples

Published by Alvin Nicolas at August 19th, 2024 , Revised On August 20, 2024

Before you start your research, the first thing you need to identify is the research method . Depending on different factors, you will either choose a quantitative or qualitative study.

Qualitative research is a great tool that helps understand the depth and richness of human opinions and experiences. Unlike quantitative research, which focuses on numerical data , qualitative research allows exploring and interpreting the experiences of the subject. Questionnaires, although mostly associated with quantitative research, can also be a valuable instrument in qualitative studies. Let’s explore what qualitative research questionnaires are and how you can create one.

What Is A Qualitative Research Questionnaire

Qualitative research questionnaires are a structured or semi-structured set of questions designed to gather detailed, open-ended participant responses. It allows you to uncover underlying reasons and opinions and provides insights into a particular phenomenon.

While quantitative questionnaires often have closed-ended questions and numerical responses, a qualitative questionnaire encourages participants to express themselves freely. Before you design your questionnaire, you should know exactly what you need so you can keep your questions specific enough for the participants to understand.

For example:

Describe your experience using our product.
How has technology impacted your work-life balance?

Types of Qualitative Research Questions With Examples

Now that you are familiar with what qualitative research questions are, let’s look at the different types of questions you can use in your survey .

Descriptive Questions

These are used to explore and describe a phenomenon in detail. It helps answer the “what” part of the research, and the questions are mostly foundational.

Example: How do students experience online learning?

Comparative Questions

This type allows you to compare and contrast different groups or situations. You can explore the differences and similarities to highlight the impact of specific variables.

Example: How do the study habits of first-year and fourth-year university students differ?

Interpretive Questions

These questions help you understand the meanings people attach to experiences or phenomena by answering the “how” and “why”.

Example: What does “success” mean to entrepreneurs?

Evaluative Questions

You can use these to assess the quality or value of something. These allow you to understand the outcomes of various situations.

Example: How effective is the new customer service training program?

Process-Oriented Questions

To understand how something happens or develops over time, researchers often use process-oriented questions.

Example: How do individuals develop their career goals?

Exploratory Questions

These allow you to discover new perspectives on a topic. However, you have to be careful that there must be no preconceived notions or research biases to it.

Example: What are the emerging trends in the mobile gaming industry?

How To Write Qualitative Research Questions?

For your study to be successful, it is important to consider designing a questionnaire for qualitative research critically, as it will shape your research and data collection. Here is an easy guide to writing your qualitative research questions perfectly.

Tip 1: Understand Your Research Goals

Many students start their research without clear goals, and they have to make substantial changes to their study in the middle of the research. This wastes time and resources.

Before you start crafting your questions, it is important to know your research objectives. You should know what you aim to discover through your research, or what specific knowledge gaps you are going to fill. With the help of a well-defined research focus, you can develop relevant and meaningful information.

Tip 2: Choose The Structure For Research Questions

There are mostly open-ended questionnaires in qualitative research. They begin with words like “how,” “what,” and “why.” However, the structure of your research questions depends on your research design . You have to consider using broad, overarching questions to explore the main research focus, and then add some specific probes to further research the particular aspects of the topic.

Tip 3: Use Clear Language

The more clear and concise your research questions are, the more effective and free from ambiguity they will be. Do not use complex terminology that might confuse participants. Try using simple and direct language that accurately conveys your intended meaning.

Here is a table to explain the wrong and right ways of writing your qualitative research questions.


How would you characterise your attitude towards e-commerce transactions?	How do you feel about online shopping?
Could you elucidate on the obstacles encountered in your professional role?	What challenges do you face in your job?
What is your evaluation of the innovative product aesthetic?	What do you think about the new product design?
Can you elaborate on the influence of social networking platforms on your interpersonal connections?	How has social media impacted your relationships?

Tip 4: Check Relevance With Research Goals

Once you have developed some questions, check if they align with your research objectives. You must ensure that each question contributes to your overall research questions. After this, you can eliminate any questions that do not serve a clear purpose in your study.

Tip 5: Concentrate On A Single Theme

While it is tempting to cover multiple aspects of a topic in one question, it is best to focus on a single theme per question. This helps to elicit focused responses from participants. Moreover, you have to avoid combining unrelated concepts into a single question.

If your main research question is complicated, you can create sub-questions with a “ladder structure”. These allow you to understand the attributes, consequences, and core values of your research. For example, let’s say your main broad research question is:

How do you feel about your overall experience with our company?

The intermediate questions may be:

What aspects of your experience were positive?
What aspects of your experience were negative?
How likely are you to recommend our company to a friend or colleague?

Types Of Survey Questionnaires In Qualitative Research

It is important to consider your research objectives, target population, resources and needed depth of research when selecting a survey method. The main types of qualitative surveys are discussed below.

Face To Face Surveys

Face-to-face surveys involve direct interaction between the researcher and the participant. This method allows observers to capture non-verbal cues, body language, and facial expressions, and helps adapt questions based on participant responses. They also let you clarify any misunderstandings. Moreover, there is a higher response rate because of personal interaction.

Example: A researcher conducting a study on consumer experiences with a new product might visit participants’ homes to conduct a detailed interview.

Telephone Surveys

These type of qualitative research survey questionnaires provide a less intrusive method for collecting qualitative data. The benefits of telephone surveys include, that it allows you to collect data from a wider population. Moreover, it is generally less expensive than face-to-face interviews and interviews can be conducted efficiently.

Example: A market research firm might conduct telephone surveys to understand customer satisfaction with a telecommunication service.

Online Surveys

Online survey questionnaires are a convenient and cost-effective way to gather qualitative data. You can reach a wide audience quickly, and participants may feel more comfortable sharing sensitive information because of anonymity. Additionally, there are no travel or printing expenses.

Example: A university might use online surveys to explore students’ perceptions of online learning experiences.

Strengths & Limitations Of Questionnaires In Qualitative Research

Questionnaires are undoubtedly a great data collection tool. However, it comes with its fair share of advantages and disadvantages. Let’s discuss the benefits of questionnaires in qualitative research and their cons as well.


Can be inexpensive to distribute and collect	Can suffer from low response rates
Allow researchers to reach a wide audience	There is a lack of control over the environment
Consistent across participants	Once the questionnaire is distributed, it cannot be modified
Anonymity helps make participants feel more comfortable	Participants may not fully understand questions
Open-ended questions provide rich, detailed responses	Open-ended questions may not capture the right answers

Qualitative Research Questionnaire Example

Here is a concise qualitative research questionnaire sample for research papers to give you a better idea of its format and how it is presented.

Thank you for participating in our survey. We value your feedback on our new mobile app. Your responses will help us improve the applications and better meet your needs.

Demographic Information

Occupation:
How long have you been using smartphones:
How would you describe your overall experience with the new mobile app?
What do you like most about the app?
What do you dislike most about the app?
Are there any specific features you find particularly useful or helpful? Please explain.
Are there any features you think are missing or could be improved? Please elaborate.
How easy is the app to navigate? Please explain any difficulties you encountered.
How does this app compare to other similar apps you have used?
What are your expectations for future updates or improvements to the app?
Is there anything else you would like to share about your experience with the app?

Are questionnaires quantitative or qualitative research?

A survey research questionnaire can have both qualitative and quantitative questions. The qualitative questions are mostly open-ended, and quantitative questions take the form of yes/no, or Likert scale rating.

Can we use questionnaires in qualitative research?

Yes, survey questionnaires can be used in qualitative research for data collection. However, instead of a Likert scale or rating, you can post open-ended questions to your respondents. The participants can provide detailed responses to the questions asked.

Why are questionnaires good for qualitative research?

In qualitative research, questionnaires allow you to collect qualitative data. The open-ended and unstructured questions help respondents present their ideas freely and provide insights.

Extract insights from Customer & Employee Interviews. At Scale.

Kinds of data in qualitative research examples.

Home » Kinds of data in qualitative research examples

Qualitative data types play a crucial role in understanding the complexities of human behavior and perspectives. Through methods such as interviews, focus groups, and content analysis, researchers gather rich descriptive data that often reveals in-depth insights hidden from quantitative approaches. This qualitative data provides a context that facilitates a deeper understanding of social phenomena, cultural narratives, and individual experiences.

The diversity of qualitative data types encompasses various forms such as text, audio, and video. Each format has unique advantages, allowing researchers to capture nuances that often escape traditional numeric data. By engaging thoroughly with qualitative data types, researchers can illuminate patterns and themes that foster a comprehensive understanding of their subject matter, ultimately driving more informed decision-making and innovation in their respective fields.

Qualitative Data Types: Unstructured Data

Unstructured data is a core element of qualitative research, consisting of information that lacks a predefined format or structure. This type of data often arises from sources like interviews, open-ended survey responses, and social media posts. Unlike structured data, which is easily organized and analyzed, unstructured data requires more nuanced methods to derive meaningful insights.

To effectively utilize unstructured data, researchers often engage in several key processes. First, they must collect data through methods such as in-depth interviews or focus groups, where participants share thoughts and feelings freely. Second, data analysis involves thematic coding to identify patterns and trends. Finally, interpreting the findings provides a deeper understanding of participant experiences and attitudes. Understanding how to navigate unstructured data is essential, as it offers rich, contextual insights into human behavior, which are invaluable for qualitative research.

Interviews and Focus Groups: Exploring Human Experiences

Interviews and focus groups provide a rich tapestry of qualitative data types, delving into the complexities of human experiences. Through one-on-one interviews, researchers can deeply engage with individuals, unearthing their personal narratives, emotions, and perceptions. This method allows for an intimate understanding of how personal backgrounds and circumstances shape viewpoints, making it invaluable for discussing topics like leadership and organizational culture.

Focus groups, on the other hand, offer a dynamic setting where participants engage in collective discussions. This format encourages interaction and the sharing of diverse perspectives, revealing how group dynamics influence ideas and attitudes. By capturing the nuances of participant interactions, researchers can gather insights that are often overlooked in isolated interviews. Both methods enrich the data collected and highlight the intricate human experiences that underpin qualitative research.

Open-Ended Surveys: Capturing Nuanced Responses

Open-ended surveys are a valuable tool for qualitative research, providing in-depth insights and capturing nuanced responses from participants. Unlike closed-ended questions that require fixed answers, open-ended queries allow respondents to express their feelings and thoughts freely. This flexibility often leads to richer data, revealing complexities that pre-defined options may overlook.

In administering open-ended surveys, researchers can adopt several strategies. First, crafting thoughtful questions encourages detailed responses, making it essential to consider wording carefully. Secondly, offering anonymity may increase honesty, as participants feel safer sharing candid opinions. Lastly, thorough analysis of the collected data can uncover trends and themes, contributing significantly to qualitative data types. This process informs decision-making and enhances understanding of the subject matter, making open-ended surveys an indispensable method in qualitative research.

Qualitative Data Types: Structured Data

In qualitative research, structured data is a crucial element that contributes to a comprehensive understanding of various phenomena. This type of data often consists of predetermined response categories and fixed formats, making it easier to analyze and interpret. For instance, surveys with multiple-choice questions or rating scales collect structured data, allowing researchers to quantify responses and identify trends. The clarity of structured data enables researchers to draw conclusions effectively and create visually appealing reports.

Structured data types can be categorized into several forms, including quantitative surveys, checklists, and guided interviews. Each form serves a specific purpose in research. Quantitative surveys help in gathering numerical data quickly, while checklists ensure that key areas are covered during observations. Guided interviews provide a framework for discussions, promoting consistency in responses. Collectively, these structured data types enhance the richness of qualitative research, making it a valuable tool for uncovering insights in various fields.

Observational Data: Recording In-Field Behaviors

Observational data plays a crucial role in understanding in-field behaviors, serving as a direct reflection of interactions and responses in real-world settings. This method involves systematically recording behaviors as they occur, allowing researchers to capture authentic reactions and dynamics that might otherwise go unnoticed. By focusing on qualitative data types, researchers gain deep insights into participants' actions, expressions, and contextual factors influencing their behavior.

To effectively utilize observational data, researchers should consider several key aspects. First, defining the specific behaviors of interest ensures that observations remain focused and relevant. Next, utilizing a structured observation checklist can help maintain consistency and detail in the data collected. Finally, documenting the context of behaviors, such as environmental factors and participant interactions, enriches the data's qualitative depth, ultimately leading to more accurate interpretations and conclusions. Through these practices, observational data becomes a powerful tool in qualitative research, offering valuable insights into human behavior.

Document Analysis: Deriving Insights from Existing Texts

Document analysis plays a crucial role in qualitative research by extracting meaningful insights from existing texts. This method involves examining various forms of qualitative data types, such as interview transcripts, documents, and historical records. By identifying themes and patterns within these texts, researchers can derive valuable insights that contribute to understanding broader contexts or specific phenomena.

One effective approach in document analysis is to focus on keywords, recurring topics, and underlying sentiments. Through systematic coding and categorization, researchers can pinpoint significant trends and expert opinions that inform their inquiries. This analytical process not only unveils insights about risks and challenges but also highlights gaps in current knowledge. Ultimately, a rigorous document analysis provides a solid foundation for qualitative research, paving the way for more in-depth exploration and understanding of complex issues.

Conclusion: Understanding Qualitative Data Types in Research

Understanding qualitative data types is crucial for any research endeavor. These data types, including text, audio, and video, provide rich insights that quantitative data cannot. By recognizing the different forms of qualitative data, researchers can choose the best methods for analysis and draw meaningful conclusions. Each type of data serves unique purposes, allowing for a comprehensive understanding of participants and their experiences.

In conclusion, mastery of qualitative data types enhances the overall quality and impact of research. An effective approach ensures that biases are minimized and insights are maximized. Qualitative research thrives on the depth of understanding it provides, making it essential for formulating strategies that resonate with audiences. Embracing these concepts can significantly improve the effectiveness of research initiatives.

Turn interviews into actionable insights

On this Page

Coding for qualitative research: AI-powered tools

You may also like, top qualitative resources for academic and market research.

Top Qualitative Techniques in Research for 2024

Research article using qualitative approach: how-to guide.

Unlock Insights from Interviews 10x faster

Request demo
Get started for free

Stakeholders Perspective of Integrating Female Genital Schistosomiasis into HIV Care: A Qualitative Study in Ghana

Find this author on Google Scholar
Find this author on PubMed
Search for this author on this site
ORCID record for Philip Teg-Nefaah Tabong
For correspondence: [email protected]
Info/History
Preview PDF

Background In Sub-Saharan Africa (SSA), HIV infection is the main factor contributing to adult premature death. The prevalence of HIV in the region could also be associated with recent increases in Female Genital Schistosomiasis (FGS) globally. The fast-rising prevalence of FGS in SSA nations including Ghana, which has led to the emergence of dual HIV-FGS conditions, provides evidence of the trend. As such the WHO is advocating for integrated services of HIV and FGS care. This study explored stakeholders’ perspectives of the integration of prevention and control measures for Female Genital Schistosomiasis and HIV care in FGS endemic settings in Ghana. Methods The study was conducted in the Ga South Municipality in the Greater Accra region of Ghana. Using qualitative research methods, Focus Group Discussion was conducted with Community Health Officers (n=9) and Key Informant Interviews with stakeholders including health care professionals and providers at the Regional, District and community levels (n=13) to explore the feasibility, challenges, and opportunities of integrating FGS prevention and control package with HIV continuum of care in communities. In-depth interviews were also conducted among Persons with FGS and HIV (n=13), Female Households (n=10), Community Health Management Committee members and Community leader (n=7) to explore their views on the facilitators and barriers of the integration of FGS into HIV care into the Primary Health Care (PHC) in Ghana. All study participants were purposively sampled to achieve the study objective. All audio-recorded data were transcribed verbatim, a codebook developed, and the data was thematically analysed with the aid of NVivo software version 13. Results The study identified a knowledge gap regarding Female Genital Schistosomiasis (FGS) compared to HIV. The majority of Community Health Officers (CHOs) exhibited limited knowledge about FGS. Additionally, health workers misconstrued FGS as sexually transmitted infections. Community members who expressed knowledge of FGS were about gynecological symptoms of FGS. Three main health outlets; health facilities, herbal centers, and spiritual centers are utilized either concurrently or in sequence. This health seeking behaviour negatively affected the early detection and management of FGS among HIV clients. Integration of HIV and FGS may be affected by the limited awareness and knowledge, resource constraints, stigma and discrimination, healthcare providers’ attitudes and practices, and cultural beliefs. Conclusions The study finds that knowledge of FGS was usually low among both community members and Community Health Officers. This was having a detrimental effect on regular screening of females for genital schistosomiasis. Integration of FGS and HIV has the potential to help Ghana achieve HIV eradication; however, before such a program is launched, implementation barriers such as stigma, knowledge gap, unavailability of needed logistics at health facilities, shortage of FGS and HIV drugs and issues of accessibility of drugs must be addressed. The results also imply that forming alliances and working together with various community health care professionals may help with early HIV and FGS diagnosis and treatment. Finally, there is the pressing need to develop a clinical protocol for FGS and HIV integration.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

Author declarations.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The protocol for the study was reviewed and approved by the Ghana Health Service Ethics Review Committee (GHS -ERC: 001/01/24).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Data Availability

The data is available on request sent to the Administrator of Ghana Health Service Ethics Review Committee at [email protected]

View the discussion thread.

Thank you for your interest in spreading the word about medRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Citation Manager Formats

EndNote (tagged)
EndNote 8 (xml)
RefWorks Tagged
Ref Manager
Tweet Widget
Facebook Like
Google Plus One

Subject Area

Public and Global Health
Addiction Medicine (341)
Allergy and Immunology (665)
Anesthesia (180)
Cardiovascular Medicine (2624)
Dentistry and Oral Medicine (314)
Dermatology (221)
Emergency Medicine (397)
Endocrinology (including Diabetes Mellitus and Metabolic Disease) (929)
Epidemiology (12169)
Forensic Medicine (10)
Gastroenterology (756)
Genetic and Genomic Medicine (4061)
Geriatric Medicine (384)
Health Economics (675)
Health Informatics (2620)
Health Policy (997)
Health Systems and Quality Improvement (976)
Hematology (359)
HIV/AIDS (843)
Infectious Diseases (except HIV/AIDS) (13657)
Intensive Care and Critical Care Medicine (789)
Medical Education (398)
Medical Ethics (109)
Nephrology (429)
Neurology (3829)
Nursing (209)
Nutrition (569)
Obstetrics and Gynecology (734)
Occupational and Environmental Health (690)
Oncology (2005)
Ophthalmology (581)
Orthopedics (238)
Otolaryngology (304)
Pain Medicine (250)
Palliative Medicine (73)
Pathology (471)
Pediatrics (1107)
Pharmacology and Therapeutics (459)
Primary Care Research (447)
Psychiatry and Clinical Psychology (3397)
Public and Global Health (6497)
Radiology and Imaging (1388)
Rehabilitation Medicine and Physical Therapy (806)
Respiratory Medicine (869)
Rheumatology (400)
Sexual and Reproductive Health (406)
Sports Medicine (338)
Surgery (441)
Toxicology (52)
Transplantation (185)
Urology (165)

Log in using your username and password

Search More Search for this keyword Advanced search
Latest content
Current issue
BMJ Journals

Rebecca Payne 1 ,
Aileen Clarke 1 ,
Nadia Swann 1 ,
Jackie van Dael 1 ,
Natassia Brenman 1 ,
Rebecca Rosen 2 ,
Adam Mackridge 3 ,
Lucy Moore 1 ,
Asli Kalin 1 ,
Emma Ladds 1 ,
Nina Hemmings 2 ,
Sarah Rybczynska-Bunt 4 ,
Stuart Faulkner 1 ,
Isabel Hanson 1 ,
Sophie Spitters 5 ,
http://orcid.org/0000-0002-7758-8493 Sietse Wieringa 1 , 6 ,
Francesca H Dakin 1 ,
Sara E Shaw 1 ,
Joseph Wherton 1 ,
Richard Byng 4 ,
Laiba Husain 1 ,
http://orcid.org/0000-0003-2369-8088 Trisha Greenhalgh 1
1 Nuffield Department of Primary Care Health Sciences , University of Oxford , Oxford , UK
2 Nuffield Trust , London , UK
3 Betsi Cadwaladr University Health Board , Bangor , UK
4 Peninsula Schools of Medicine and Dentistry , University of Plymouth , Plymouth , UK
5 Wolfson Institute of Population Health , Queen Mary University of London , London , UK
6 Sustainable Health Unit , University of Oslo , Oslo , Norway
Correspondence to Professor Trisha Greenhalgh; trish.greenhalgh{at}phc.ox.ac.uk

Background Triage and clinical consultations increasingly occur remotely. We aimed to learn why safety incidents occur in remote encounters and how to prevent them.

Setting and sample UK primary care. 95 safety incidents (complaints, settled indemnity claims and reports) involving remote interactions. Separately, 12 general practices followed 2021–2023.

Methods Multimethod qualitative study. We explored causes of real safety incidents retrospectively (‘Safety I’ analysis). In a prospective longitudinal study, we used interviews and ethnographic observation to produce individual, organisational and system-level explanations for why safety and near-miss incidents (rarely) occurred and why they did not occur more often (‘Safety II’ analysis). Data were analysed thematically. An interpretive synthesis of why safety incidents occur, and why they do not occur more often, was refined following member checking with safety experts and lived experience experts.

Results Safety incidents were characterised by inappropriate modality, poor rapport building, inadequate information gathering, limited clinical assessment, inappropriate pathway (eg, wrong algorithm) and inadequate attention to social circumstances. These resulted in missed, inaccurate or delayed diagnoses, underestimation of severity or urgency, delayed referral, incorrect or delayed treatment, poor safety netting and inadequate follow-up. Patients with complex pre-existing conditions, cardiac or abdominal emergencies, vague or generalised symptoms, safeguarding issues, failure to respond to previous treatment or difficulty communicating seemed especially vulnerable. General practices were facing resource constraints, understaffing and high demand. Triage and care pathways were complex, hard to navigate and involved multiple staff. In this context, patient safety often depended on individual staff taking initiative, speaking up or personalising solutions.

Conclusion While safety incidents are extremely rare in remote primary care, deaths and serious harms have resulted. We offer suggestions for patient, staff and system-level mitigations.

Primary care
Diagnostic errors
Safety culture
Qualitative research
Prehospital care

Data availability statement

Data are available upon reasonable request. Details of real safety incidents are not available for patient confidentiality reasons. Requests for data on other aspects of the study from other researchers will be considered.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjqs-2023-016674

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

WHAT IS ALREADY KNOWN ON THIS TOPIC

Safety incidents are extremely rare in primary care but they do happen. Concerns have been raised about the safety of remote triage and remote consultations.

WHAT THIS STUDY ADDS

Rare safety incidents (involving death or serious harm) in remote encounters can be traced back to various clinical, communicative, technical and logistical causes. Telephone and video encounters in general practice are occurring in a high-risk (extremely busy and sometimes understaffed) context in which remote workflows may not be optimised. Front-line staff use creativity and judgement to help make care safer.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

As remote modalities become mainstreamed in primary care, staff should be trained in the upstream causes of safety incidents and how they can be mitigated. The subtle and creative ways in which front-line staff already contribute to safety culture should be recognised and supported.

Introduction

In early 2020, remote triage and remote consultations (together, ‘remote encounters’), in which the patient is in a different physical location from the clinician or support staff member, were rapidly expanded as a safety measure in many countries because they eliminated the risk of transmitting COVID-19. 1–4 But by mid-2021, remote encounters had begun to be depicted as potentially unsafe because they had come to be associated with stories of patient harm, including avoidable deaths and missed cancers. 5–8

Providing triage and clinical care remotely is sometimes depicted as a partial solution to the system pressures facing primary healthcare in many countries, 9–11 including rising levels of need or demand, the ongoing impact of the COVID-19 pandemic and workforce challenges (especially short-term or longer-term understaffing). In this context, remote encounters may be an important component of a mixed-modality health service when used appropriately alongside in-person contacts. 12 13 But this begs the question of what ‘appropriate’ and ‘safe’ use of remote modalities in a primary care context is. Safety incidents (defined as ‘any unintended or unexpected incident which could have, or did, lead to harm for one or more patients receiving healthcare 14 ’) are extremely rare in primary healthcare consultations generally, 15 16 in-hours general practice telephone triage 17 and out-of-hours primary care. 18 But the recent widespread expansion of remote triage and remote consulting in primary care means that a wider range of patients and conditions are managed remotely, making it imperative to re-examine where the risks lie.

Theoretical approaches to safety in healthcare fall broadly into two traditions. 19 ‘Safety I’ studies focus on what went wrong. Incident reports are analysed to identify ‘root causes’ and ‘safety gaps’, and recommendations are made to reduce the chance that further similar incidents will happen in the future. 20 Such studies, undertaken in isolation, tend to lead to a tightening of rules, procedures and protocols. ‘Safety II’ studies focus on why, most of the time, things do not go wrong. Ethnography and other qualitative methods are employed to study how humans respond creatively to unique and unforeseen situations, thereby preventing safety incidents most of the time. 19 Such studies tend to show that actions which achieve safety are highly context specific, may entail judiciously breaking the rules and require human qualities such as courage, initiative and adaptability. 21 Few previous studies have combined both approaches.

In this study, we aimed to use Safety I methods to learn why safety incidents occur (although rarely) in remote primary care encounters and also apply Safety II methods to examine the kinds of creative actions taken by front-line staff that contribute to a safety culture and thereby prevent such incidents.

Study design and origins

Multimethod qualitative study across UK, including incident analysis, longitudinal ethnography and national stakeholder interviews.

The idea for this safety study began during a longitudinal ethnographic study of 12 general practices across England, Scotland and Wales as they introduced (and, in some cases, subsequently withdrew) various remote and digital modalities. Practices were selected for maximum diversity in geographical location, population served and digital maturity and followed from mid-2021 to end 2023 using staff and patient interviews and in-person ethnographic visits. The study protocol, 22 baseline findings 23 and a training needs analysis 24 have been published. To provide context for our ethnography, we interviewed a sample of national stakeholders in remote and digital primary care, including out-of-hours providers running telephone-led services, and held four online multistakeholder workshops, one of which was on the theme of safety, for policymakers, clinicians, patients and other parties. Early data from this detailed qualitative work revealed staff and patient concerns about the safety of remote encounters but no actual examples of harm.

To explore the safety theme further, we decided to take a dual approach. First, following Safety I methodology for the study of rare harms, 20 we set out to identify and analyse a sample of safety incidents involving remote encounters. These were sourced from arm’s-length bodies (NHS England, NHS Resolution, Healthcare Safety Investigation Branch) and providers of healthcare at scale (health boards, integrated care systems and telephone advice services), since our own small sample had not identified any of these rare occurrences. Second, we extended our longitudinal ethnographic design to more explicitly incorporate Safety II methodology, 19 allowing us to examine safety culture and safety practices in our 12 participating general practices, especially the adaptive work done by staff to avert potential safety incidents.

Data sources and management

Table 1 summarises the data sources.

View inline

Summary of data sources

The Safety I dataset (rows 2-5) consisted of 95 specific incident reports, including complaints submitted to the main arm’s-length NHS body in England, NHS England, between 2020 and 2023 (n=69), closed indemnity claims that had been submitted to a national indemnity body, NHS Resolution, between 2015 and 2023 (n=16), reports from an urgent care telephone service in Wales (NHS 111 Wales) between 2020 and 2023 (n=6) and a report on an investigation of telephone advice during the COVID-19 crisis between 2020 and 2022 7 (n=4). These 95 incidents were organised using Microsoft Excel spreadsheets.

The Safety II dataset (rows 6-10) consisted of extracts from fieldnotes, workshop transcripts and interviews collected over 2 years, stored and coded on NVivo qualitative software. These were identified by searching for text words and codes (e.g. ‘risk’, ‘safety’, ‘incident’) and by asking researchers-in-residence, who were closely familiar with practices, to highlight safety incidents involving harm and examples of safety-conscious work practices. This dataset included over 100 formal interviews and numerous on-the-job interviews with practice staff, plus interviews with a sample of 10 GP (general practitioner) trainers and 10 GP trainees (penultimate row of table 1 ) and with six clinical safety experts identified through purposive sampling from government, arm’s-length bodies and health boards (bottom row of table 1 ).

Data analysis

We analysed incident reports, interview data and ethnographic fieldnotes using thematic analysis as described by Braun and Clarke. 25 These authors define a theme as an important, broad pattern in a set of qualitative data, which can (where necessary) be further refined using coding.

Themes in the incident dataset were identified by five steps. First, two researchers (both medically qualified) read each source repeatedly to gain familiarity. Second, those researchers worked independently using Braun and Clarke’s criterion (‘whether it captures something important in relation to the overall research question’—p 82 25 ) to identify themes. Third, they discussed their initial interpretations with each other and resolved differences through discussion. Fourth, they extracted evidence from the data sources to illustrate and refine each theme. Finally, they presented their list of themes along with illustrative examples to the wider team. Cases used to illustrate themes were systematically fictionalised by changing age, randomly allocating gender and altering clinical details. 26 For example, an acute appendicitis could be changed to acute diverticulitis if the issue was a missed acute abdomen.

These safety themes were then used to sensitise us to seek relevant (confirming and disconfirming) material from our ethnographic and interview datasets. For example, the theme ‘poor communication’ (and subthemes such as ‘failure to seek further clarification’ within this) promoted us to look for examples in our stakeholder interviews of poor communication offered as a cause of safety incidents and examples in our ethnographic notes of good communication (including someone seeking clarification). We used these wider data to add nuance to the initial list of themes.

As a final sense-checking step, the draft findings from this study were shown to each of the six safety experts in our sample and refined in the light of their comments (in some cases, for example, they considered the case to have been overfictionalised, thereby losing key clinical messages; they also gave additional examples to illustrate some of the themes we had identified, which underlined the importance of those themes).

Overview of dataset

The dataset ( table 1 ) consisted of 95 incident reports (see fictionalised examples in box 1 ), plus approximately 400 pages of extracts from interviews, ethnographic fieldnotes and workshop discussions, including situated safety practices (see examples in box 2 ), plus strategic insights relating to policy, organisation and planning of services. Notably, almost all incidents related to telephone calls.

Examples of safety incidents involving death or serious harm in remote encounters

All these cases have been systematically fictionalised as explained in the text.

Case 1 (death)

A woman in her 70s experiencing sudden breathlessness called her GP (general practitioner) surgery. The receptionist answered the phone and informed her that she would place her on the doctor’s list for an emergency call-back. The receptionist was distracted by a patient in the waiting room and did not do so. The patient deteriorated and died at home that afternoon.—NHS Resolution case, pre-2020

Case 2 (death)

An elderly woman contacted her GP after a telephone contact with the out-of-hours service, where constipation had been diagnosed. The GP prescribed laxatives without seeing the patient. The patient self-presented to the emergency department (ED) the following day in obstruction secondary to an incarcerated hernia and died in the operating theatre.—NHS Resolution case, pre-2020

Case 3 (risk to vulnerable patients)

A daughter complained that her elderly father was unable to access his GP surgery as he could not navigate the online triage system. When he phoned the surgery directly, he was directed back to the online system and told to get a relative to complete the form for him.—Complaint to NHS England, 2021

Case 4 (harm)

A woman in her first pregnancy at 28 weeks’ gestation experiencing urinary incontinence called NHS 111. She was taken down by a ‘urinary problems’ algorithm. Both the call handler and the subsequent clinician failed to recognise that she had experienced premature rupture of membranes. She later presented to the maternity department in active labour, and the opportunity to give early steroids to the premature infant was missed.—NHS Resolution case, pre-2020

Case 5 (death)

A doctor called about a 16-year-old girl with lethargy, shaking, fever and poor oral intake who had been unwell for 5 days. The doctor spoke to her older sister and advised that the child had likely glandular fever and should rest. When the parents arrived home, they called an ambulance but the child died of sepsis in the ED.—NHS Resolution case, pre-2020

Case 6 (death)

A 40-year-old woman, 6 weeks after caesarean section, contacted her GP due to shortness of breath, increased heart rate and dry cough. She was advised to get a COVID test and to dial 111 if she developed a productive cough, fever or pain. The following day she collapsed and died at home. The postmortem revealed a large pulmonary embolus. On reviewing the case, her GP surgery felt that had she been seen face to face, her oxygen saturations would have been measured and may have led to suspicion of the diagnosis.—NHS Resolution case, 2020

Case 7 (death)

A son complained that his father with diabetes and chronic kidney disease did not receive any in-person appointments over a period of 1 year. His father went on to die following a leg amputation arising from a complication of his diabetes.—Complaint to NHS England, 2021

Case 8 (death)

A 73-year-old diabetic woman with throat pain and fatigue called the surgery. She was diagnosed with a viral illness and given self-care advice. Over the next few days, she developed worsening breathlessness and was advised to do a COVID test and was given a pulse oximeter. She was found dead at home 4 days later. Postmortem found a blocked coronary artery and a large amount of pulmonary oedema. The cause of death was myocardial infarction and heart failure.—NHS Resolution case, pre-2020

Case 9 (harm)

A patient with a history of successfully treated cervical cancer developed vaginal bleeding. A diagnosis of fibroids was made and the patient received routine care by telephone over the next few months until a scan revealed a local recurrence of the original cancer.—Complaint to NHS England, 2020

Case 10 (death)

A 65-year-old female smoker with chronic cough and breathlessness presented to her GP. She was diagnosed with chronic obstructive pulmonary disease (COPD) and monitored via telephone. She did not respond to inhalers or antibiotics but continued to receive telephone monitoring without further investigation. Her symptoms continued to worsen and she called an ambulance. In the ED, she was diagnosed with heart failure and died soon after.—Complaint to NHS England, 2021

Case 11 (harm)

A 30-year-old woman presented with intermittent episodes of severe dysuria over a period of 2 years. She was given repeated courses of antibiotics but no urine was sent for culture and she was not examined. After 4 months of symptoms, she saw a private GP and was diagnosed with genital herpes.—Complaint to NHS England, 2021

Case 12 (harm)

There were repeated telephone consultations about a baby whose parents were concerned that the child was having a funny colour when feeding or crying. The 6-week check was done by telephone and at no stage was the child seen in person. Photos were sent in, but the child’s dark skin colour meant that cyanosis was not easily apparent to the reviewing clinician. The child was subsequently admitted by emergency ambulance where a significant congenital cardiac abnormality was found.—Complaint to NHS England, 2020 1

Case 13 (harm)

A 35-year-old woman in her third trimester of pregnancy had a telephone appointment with her GP about a breast lump. She was informed that this was likely due to antenatal breast changes and was not offered an in-person appointment. She attended after delivery and was referred to a breast clinic where a cancer was diagnosed.—Complaint to NHS England, 2020

Case 14 (harm)

A 63-year-old woman with a variety of physical symptoms including diarrhoea, hip girdle pain, palpitations, light-headedness and insomnia called her surgery on multiple occasions. She was told her symptoms were likely due to anxiety, but was diagnosed with stage 4 ovarian cancer and died soon after.—Complaint to NHS England, 2021

Case 15 (death)

A man with COPD with worsening shortness of breath called his GP surgery. The staff asked him if it was an emergency, and when the patient said no, scheduled him for 2 weeks later. The patient died before the appointment.—Complaint to NHS England, 2021

Examples of safety practices

Case 16 (safety incident averted by switching to video call for a sick child)

‘I’ve remembered one father that called up. Really didn’t seem to be too concerned. And was very much under-playing it and then when I did a video call, you know this child… had intercostal recession… looked really, really poorly. And it was quite scary actually that, you know, you’d had the conversation and if you’d just listened to what Dad was saying, actually, you probably wouldn’t be concerned.’—GP (general practitioner) interview 2022

Case 17 (‘red flag’ spotted by support staff member)

A receptionist was processing routine ‘administrative’ encounters sent in by patients using AccuRx (text messaging software). She became concerned about a sick note renewal request from a patient with a mental health condition. The free text included a reference to feeling suicidal, so the receptionist moved the request to the ‘red’ (urgent call-back) list. In interviews with staff, it became apparent that there had recently been heated discussion in the practice about whether support staff were adding ‘too many’ patients to the red list. After discussing cases, the doctors concluded that it should be them, not the support staff, who should absorb the risk in uncertain cases. The receptionist said that they had been told: ‘if in doubt, put it down as urgent and then the duty doctor can make a decision.’—Ethnographic fieldnotes from general practice 2023

Case 18 (‘check-in’ phone call added on busy day)

A duty doctor was working through a very busy Monday morning ‘urgent’ list. One patient had acute abdominal pain, which would normally have triggered an in-person appointment, but there were no slots and hard decisions were being made. This patient had had the pain already for a week, so the doctor judged that the general rule of in-person examination could probably be over-ridden. But instead of simply allocating to a call-back, the doctor asked a support staff member to phone the patient, ask ‘are you OK to wait until tomorrow?’ and offer basic safety-netting advice.—Ethnographic fieldnotes from general practice 2023

Case 19 (receptionist advocating on behalf of ‘angry’ walk-in patient)

A young Afghan man with limited English walked into a GP surgery on a very busy day, ignoring the prevailing policy of ‘total triage’ (make contact by phone or online in the first instance). He indicated that he wanted a same-day in-person appointment for a problem he perceived as urgent. A heated exchange occurred with the first receptionist, and the patient accused her of ‘racism’. A second receptionist of non-white ethnicity herself noted the man’s distress and suspected that there may indeed be an urgent problem. She asked the first receptionist to leave the scene, saying she wanted to ‘have a chat’ with the patient (‘the colour of my skin probably calmed him down more than anything’). Through talking to the patient and looking through his record, she ascertained that he had an acute infection that likely needed prompt attention. She tried to ‘bend the rules’ and persuade the duty doctor to see the patient, conveying the clinical information but deliberately omitting the altercation. But the first receptionist complained to the doctor (‘he called us racists’) and the doctor decided that the patient would not therefore be offered a same-day appointment. The second receptionist challenged the doctor (‘that’s not a reason to block him from getting care’). At this point, the patient cried and the second receptionist also became upset (‘this must be serious, you know’). On this occasion, despite her advocacy the patient was not given an immediate appointment.—Ethnographic fieldnotes from general practice 2022

Case 20 (long-term condition nurse visits ‘unengaged’ patients at home)

An advanced nurse practitioner talks of two older patients, each with a long-term condition, who are ‘unengaged’ and lacking a telephone. In this practice, all long-term condition reviews are routinely done by phone. She reflects that some people ‘choose not to have avenues of communication’ (ie, are deliberately not contactable), and that there may be reasons for this (‘maybe health anxiety or just old’). She has, on occasion, ‘turned up’ unannounced at the patient’s home and asked to come in and do the review, including bloods and other tests. She reflects that while most patients engage well with the service, ‘half my job is these patients who don’t engage very well.’—Ethnographic fieldnotes from digitally advanced general practice 2022

Case 21 (doctor over-riding patient’s request for telephone prescribing)

A GP trainee described a case of a 53-year-old first-generation immigrant from Pakistan, a known smoker with hypertension and diabetes. He had booked a telephone call for vomiting and sinus pain. There was no interpreter available but the man spoke some English. He said he had awoken in the night with pain in his sinuses and vomiting. All he wanted was painkillers for his sinuses. The story did not quite make sense, and the man ‘sounded unwell’. The GP told him he needed to come in and be examined. The patient initially resisted but was persuaded to come in. When the GP went to call him in, the man was visibly unwell and lying down in the waiting room. When seen in person, he admitted to shoulder pain. The GP sent him to accident and emergency (A&E) where a myocardial infarction was diagnosed.—Trainee interview 2023

Below, we describe the main themes that were evident in the safety incidents: a challenging organisational and system context, poor communication compounded by remote modalities, limited clinical information, patient and carer burden and inadequate training. Many safety incidents illustrated multiple themes—for example, poor communication and failures of clinical assessment or judgement and patient complexity and system pressures. In the detailed findings below, we illustrate why safety incidents occasionally occur and why they are usually avoided.

The context for remote consultations: system and operational challenges

Introduction of remote triage and expansion of remote consultations in UK primary care occurred at a time of unprecedented system stress (an understaffed and chronically under-resourced primary care sector, attempting to cope with a pandemic). 23 Many organisations had insufficient telephone lines or call handlers, so patients struggled to access services (eg, half of all calls to the emergency COVID-19 telephone service in March 2020 were never answered 7 ). Most remote consultations were by telephone. 27

Our safety incident dataset included examples of technically complex access routes which patients found difficult or impossible to navigate (case 3 in box 1 ) and which required non-clinical staff to make clinical or clinically related judgements (cases 4 and 15). Our ethnographic dataset contained examples of inflexible application of triage rules (eg, no face-to-face consultation unless the patient had already had a telephone call), though in other practices these rules could be over-ridden by staff using their judgement or asking colleagues. Some practices had a high rate of failed telephone call-backs (patient unobtainable).

High demand, staff shortages and high turnover of clinical and support staff made the context for remote encounters inherently risky. Several incidents were linked to a busy staff member becoming distracted (case 1). Telephone consultations, which tend to be shorter, were sometimes used in the hope of improving efficiency. Some safety incidents suggested perfunctory and transactional telephone consultations, with flawed decisions made on the basis of incomplete information (eg, case 2).

Many practices had shifted—at least to some extent—from a demand-driven system (in which every request for an appointment was met) to a capacity-driven one (in which, if a set capacity was exceeded, patients were advised to seek care elsewhere), though the latter was often used flexibly rather than rigidly with an expectation that some patients would be ‘squeezed in’. In some practices, capacity limits had been introduced to respond to escalation of demand linked to overuse of triage templates (eg, to inquire about minor symptoms).

As a result of task redistribution and new staff roles, a single episode of care for one problem often involved multiple encounters or tasks distributed among clinical and non-clinical staff (often in different locations and sometimes also across in-hours and out-of-hours providers). Capacity constraints in onward services placed pressure on primary care to manage risk in the community, leading in some cases to failure to escalate care appropriately (case 6).

Some safety incidents were linked to organisational routines that had not adapted sufficiently to remote—for example, a prescription might be issued but (for various reasons) it could not be transmitted electronically to the pharmacy. Certain urgent referrals were delayed if the consultation occurred remotely (a referral for suspected colon cancer, for example, would not be accepted without a faecal immunochemical test).

Training, supervising and inducting staff was more difficult when many were working remotely. If teams saw each other less frequently, relationship-building encounters and ‘corridor’ conversations were reduced, with knock-on impacts for individual and team learning and patient care. Those supervising trainees or allied professionals reported loss of non-verbal cues (eg, more difficult to assess how confident or distressed the trainee was).

Clinical and support staff regularly used initiative and situated judgement to compensate for an overall lack of system resilience ( box 1 ). Many practices had introduced additional safety measures such as lists of patients who, while not obviously urgent, needed timely review by a clinician. Case 17 illustrates how a rule of thumb ‘if in doubt, put it down as urgent’ was introduced and then applied to avert a potentially serious mental health outcome. Case 18 illustrates how, in the context of insufficient in-person slots to accommodate all high-risk cases, a unique safety-netting measure was customised for a patient.

Poor communication is compounded by remote modalities

Because sense data (eg, sight, touch, smell) are missing, 28 remote consultations rely heavily on the history. Many safety incidents were characterised by insufficient or inaccurate information for various reasons. Sometimes (cases 2, 5, 6, 8, 9, 10 and 11), the telephone consultation was too short to do justice to the problem; the clinician asked few or no questions to build rapport, obtain a full history, probe the patient’s answers for additional detail, confirm or exclude associated symptoms and inquire about comorbidities and medication. Video provided some visual cues but these were often limited to head and shoulders, and photographs were sometimes of poor quality.

Cases 2, 4, 5 and 9 illustrate the dangers of relying on information provided by a third party (another staff member or a relative). A key omission (eg, in case 5) was failing to ask why the patient was unable to come to the phone or answer questions directly.

Some remote triage conversations were conducted using an inappropriate algorithm. In case 4, for example, the call handler accepted a pregnant patient’s assumption that leaking fluid was urine when the problem was actually ruptured membranes. The wrong pathway was selected; vital questions remained unasked; and a skewed history was passed to (and accepted by) the clinician. In case 8, the patient’s complaint of ‘throat’ pain was taken literally and led to ‘viral illness’ advice, overlooking a myocardial infarction.

The cases in box 2 illustrate how staff compensated for communication challenges. In case 16, a GP plays a hunch that a father’s account of his child’s asthma may be inaccurate and converts a phone encounter to video, revealing the child’s respiratory distress. In case 19 (an in-person encounter but relevant because the altercation occurs partly because remote triage is the default modality), one receptionist correctly surmises that the patient’s angry demeanour may indicate urgency and uses her initiative and interpersonal skills to obtain additional clinical information. In case 20, a long-term condition nurse develops a labour-intensive workaround to overcome her elderly patients’ ‘lack of engagement’. More generally, we observed numerous examples of staff using both formal tools (eg, see ‘red list’ in case 17) and informal measures (eg, corridor chats) to pass on what they believed to be crucial information.

Remote consulting can provide limited clinical information

Cases 2 and 4–14 all describe serious conditions including congenital cyanotic heart disease, pulmonary oedema, sepsis, cancer and diabetic foot which would likely have been readily diagnosed with an in-person examination. While patients often uploaded still images of skin lesions, these were not always of sufficient quality to make a confident diagnosis.

Several safety incidents involved clinicians assuming that a diagnosis made on a remote consultation was definitive rather than provisional. Especially when subsequent consultations were remote, such errors could become ingrained, leading to diagnostic overshadowing and missed or delayed diagnosis (cases 2, 8, 9, 10, 11 and 13). Patients with pre-existing conditions (especially if multiple or progressive), the very young and the elderly were particularly difficult to assess by telephone (cases 1, 2, 8, 10, 12 and 16). Clinical conditions difficult to assess remotely included possible cardiac pain (case 8), acute abdomen (case 2), breathing difficulties (cases 1, 6 and 10), vague and generalised symptoms (cases 5 and 14) and symptoms which progressed despite treatment (cases 9, 10 and 11). All these categories came up repeatedly in interviews and workshops as clinically risky.

Subtle aspects of the consultation which may have contributed to safety incidents in a telephone consultation included the inability to fully appraise the patient’s overall health and well-being (including indicators relevant to mental health such as affect, eye contact, personal hygiene and evidence of self-harm), general demeanour, level of agitation and concern, and clues such as walking speed and gait (cases 2, 5, 6, 7, 8, 10, 12 and 14). Our interviews included stories of missed cases of new-onset frailty and dementia in elderly patients assessed by telephone.

In most practices we studied, most long-term condition management was undertaken by telephone. This may be appropriate (and indeed welcome) when the patient is well and confident and a physical examination is not needed. But diabetes reviews, for example, require foot examination. Case 7 describes the deterioration and death of a patient with diabetes whose routine check-ups had been entirely by telephone. We also heard stories of delayed diagnosis of new diabetes in children when an initial telephone assessment failed to pick up lethargy, weight loss and smell of ketones, and point-of-care tests of blood or urine were not possible.

Nurses observed that remote consultations limit opportunities for demonstrating or checking the patient’s technique in using a device for monitoring or treating their condition such as an inhaler, oximeter or blood pressure machine.

Safety netting was inadequate in many remote safety incidents, even when provided by a clinician (cases 2, 5, 6, 8, 10, 12 and 13) but especially when conveyed by a non-clinician (case 15). Expert interviewees identified that making life-changing diagnoses remotely and starting patients on long-term medication without an in-person appointment was also risky.

Our ethnographic data showed that various measures were used to compensate for limited clinical information, including converting a phone consultation to video (case 16), asking the patient if they felt they could wait until an in-person slot was available (case 18), visiting the patient at home (case 20) and enacting a ‘if the history doesn’t make sense, bring the patient in for an in-person assessment’ rule of thumb (case 21). Out-of-hours providers added examples of rules of thumb that their services had developed over years of providing remote services, including ‘see a child face-to-face if the parent rings back’, ‘be cautious about third-party histories’, ‘visit a palliative care patient before starting a syringe driver’ and ‘do not assess abdominal pain remotely’.

Remote modalities place additional burdens on patients and carers

Given the greater importance of the history in remote consultations, patients who lacked the ability to communicate and respond in line with clinicians’ expectations were at a significant disadvantage. Several safety incidents were linked to patients’ limited fluency in the language and culture of the clinician or to specific vulnerabilities such as learning disability, cognitive impairment, hearing impairment or neurodiversity. Those with complex medical histories and comorbidities, and those with inadequate technical set-up and skills (case 3), faced additional challenges.

In many practices, in-person appointments were strictly limited according to more or less rigid triage criteria. Some patients were unable to answer the question ‘is this an emergency?’ correctly, leading to their condition being deprioritised (case 15). Some had learnt to ‘game’ the triage system (eg, online templates 29 ) by adapting their story to obtain the in-person appointment they felt they needed. This could create distrust and lead to inaccurate information on the patient record.

Our ethnographic dataset contained many examples of clinical and support staff using initiative to compensate for vulnerable patients’ inability or unwillingness to take on the additional burden of remote modalities (cases 19 and 20 in Box 2 30 31 ).

Training for remote encounters is often inadequate

Safety incidents highlighted various training needs for support staff members (eg, customer care skills, risks of making clinical judgements) and clinicians (eg, limitations of different modalities, risks of diagnostic overshadowing). Whereas out-of-hours providers gave thorough training to novice GPs (covering such things as attentiveness, rapport building, history taking, probing, attending to contextual cues and safety netting) in telephone consultations, 32–34 many in-hours clinicians had never been formally taught to consult by telephone. Case 17 illustrates how on-the-job training based on acknowledgement of contextual pressures and judicious use of rules of thumb may be very effective in averting safety incidents.

Statement of principal findings

An important overall finding from this study is that examples of deaths or serious harms associated with remote encounters in primary care were extremely rare, amounting to fewer than 100 despite an extensive search going back several years.

Analysis of these 95 safety incidents, drawn from multiple complementary sources, along with rich qualitative data from ethnography, interviews and workshops has clarified where the key risks lie in remote primary care. Remote triage and consultations expanded rapidly in the context of the COVID-19 crisis; they were occurring in the context of resource constraints, understaffing and high demand. Triage and care pathways were complex, multilayered and hard to navigate; some involved distributed work among multiple clinical and non-clinical staff. In some cases, multiple remote encounters preceded (and delayed) a needed in-person assessment.

In this high-risk context, safety incidents involving death or serious harm were rare, but those that occurred were characterised by a combination of inappropriate choice of modality, poor rapport building, inadequate information gathering, limited clinical assessment, inappropriate clinical pathway (eg, wrong algorithm) and failure to take account of social circumstances. These led to missed, inaccurate or delayed diagnoses, underestimation of severity or urgency, delayed referral, incorrect or delayed treatment, poor safety netting and inadequate follow-up. Patients with complex or multiple pre-existing conditions, cardiac or abdominal emergencies, vague or generalised symptoms, safeguarding issues and failure to respond to previous treatment, and those who (for any reason) had difficulty communicating, seemed particularly at risk.

Strengths and limitations of the study

The main strength of this study was that it combined the largest Safety I study undertaken to date of safety incidents in remote primary care (using datasets which have not previously been tapped for research), with a large, UK-wide ethnographic Safety II analysis of general practice as well as stakeholder interviews and workshops. Limitations of the safety incident sample (see final column in table 1 ) include that it was skewed towards very rare cases of death and serious harm, with relatively few opportunities for learning that did not result in serious harm. Most sources were retrospective and may have suffered from biases in documentation and recall. We also failed to obtain examples of safeguarding incidents (which would likely turn up in social care audits). While all cases involved a remote modality (or a patient who would not or could not use one), it is impossible to definitively attribute the harm to that modality.

Comparison with existing literature

This study has affirmed previous findings that processes, workflows and training in in-hours general practice have not adapted adequately to the booking, delivery and follow-up of remote consultations. 24 35 36 Safety issues can arise, for example, from how the remote consultation interfaces with other key practice routines (eg, for making urgent referrals for possible cancer). The sheer complexity and fragmentation of much remote and digital work underscores the findings from a systematic review of the importance of relational coordination (defined as ‘a mutually reinforcing process of communicating and relating for the purpose of task integration ’ (p 3) 37 ) and psychological safety (defined as ‘people’s perceptions of the consequences of taking interpersonal risks in a particular context such as a workplace ’ (p 23) 38 ) in building organisational resilience and assuring safety.

The additional workload and complexity associated with running remote appointments alongside in-person ones is cognitively demanding for staff and requires additional skills for which not all are adequately trained. 24 39 40 We have written separately about the loss of traditional continuity of care as primary care services become digitised, 41–43 and about the unmet training needs of both clinical and support staff for managing remote and digital encounters. 24

Our findings also resonate with research showing that remote modalities can interfere with communicative tasks such as rapport building, establishing a therapeutic relationship and identifying non-verbal cues such as tearfulness 35 36 44 ; that remote consultations tend to be shorter and feature less discussion, information gathering and safety netting 45–48 ; and that clinical assessment in remote encounters may be challenging, 27 49 50 especially when physical examination is needed. 35 36 51 These factors may rarely contribute to incorrect or delayed diagnoses, underestimation of the seriousness or urgency of a case, and failure to identify a deteriorating trajectory. 35 36 52–54

Even when systems seem adequate, patients may struggle to navigate them. 23 30 31 This finding aligns with an important recent review of cognitive load theory in the context of remote and digital health services: because such services are more cognitively demanding for patients, they may widen inequities of access. 55 Some patients lack navigating and negotiating skills, access to key technologies 13 36 or confidence in using them. 30 35 The remote encounter may require the patient to have a sophisticated understanding of access and cross-referral pathways, interpret their own symptoms (including making judgements about severity and urgency), obtain and use self-monitoring technologies (such as a blood pressure machine or oximeter) and convey these data in medically meaningful ways (eg, by completing algorithmic triage forms or via a telephone conversation). 30 56 Furthermore, the remote environment may afford fewer opportunities for holistically evaluating, supporting or safeguarding the vulnerable patient, leading to widening inequities. 13 35 57 Previous work has also shown that patients with pre-existing illness, complex comorbidities or high-risk states, 58 59 language non-concordance, 13 35 inability to describe their symptoms (eg, due to autism 60 ), extremes of age 61 and those with low health or system literacy 30 are more difficult to assess remotely.

Lessons for safer care

Many of the contributory factors to safety incidents in remote encounters have been suggested previously, 35 36 and align broadly with factors that explain safety incidents more generally. 53 62 63 This new study has systematically traced how upstream factors may, very rarely, combine to contribute to avoidable human tragedies—and also how primary care teams develop local safety practices and cultures to help avoid them. Our study provides some important messages for practices and policymakers.

First, remote encounters in general practice are mostly occurring in a system designed for in-person encounters, so processes and workflows may work less well.

Second, because the remote encounter depends more on history taking and dialogue, verbal communication is even more mission critical. Working remotely under system pressures and optimising verbal communication should both be priorities for staff training.

Third, the remote environment may increase existing inequities as patients’ various vulnerabilities (eg, extremes of age, poverty, language and literacy barriers, comorbidities) make remote communication and assessment more difficult. Our study has revealed impressive efforts from staff to overcome these inequities on an individual basis; some of these workarounds may become normalised and increase efficiency, but others are labour intensive and not scalable.

A final message from this study is that clinical assessment provides less information when a physical examination (and even a basic visual overview) is not possible. Hence, the remote consultation has a higher degree of inherent uncertainty. Even when processes have been optimised (eg, using high-quality triage to allocate modality), but especially when they have not, diagnoses and assessments of severity or urgency should be treated as more provisional and revisited accordingly. We have given examples in the Results section of how local adaptation and rule breaking bring flexibility into the system and may become normalised over time, leading to the creation of locally understood ‘rules of thumb’ which increase safety.

Overall, these findings underscore the need to share learning and develop guidance about the drivers of risk, how these play out in different kinds of remote encounters and how to develop and strengthen Safety II approaches to mitigate those risks. Table 2 shows proposed mitigations at staff, process and system levels, as well as a preliminary list of suggestions for patients, which could be refined with patient input using codesign methods. 64

Reducing safety incidents in remote primary care

Unanswered questions and future research

This study has helped explain where the key risks lie in remote primary care encounters, which in our dataset were almost all by telephone. It has revealed examples of how front-line staff create and maintain a safety culture, thereby helping to prevent such incidents. We suggest four key avenues for further research. First, additional ethnographic studies in general practice might extend these findings and focus on specific subquestions (eg, how practices identify, capture and learn from near-miss incidents). Second, ethnographic studies of out-of-hours services, which are mostly telephone by default, may reveal additional elements of safety culture from which in-hours general practice could learn. Third, the rise in asynchronous e-consultations (in which patients complete an online template and receive a response by email) raises questions about the safety of this new modality which could be explored in mixed-methods studies including quantitative analysis of what kinds of conditions these consultations cover and qualitative analysis of the content and dynamics of the interaction. Finally, our findings suggest that the safety of new clinically related ‘assistant’ roles in general practice should be urgently evaluated, especially when such staff are undertaking remote assessment or remote triage.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Ethical approval was granted by the East Midlands—Leicester South Research Ethics Committee and UK Health Research Authority (September 2021, 21/EM/0170 and subsequent amendments). Access to the NHS Resolution dataset was obtained by secondment of the RP via honorary employment contract, where she worked with staff to de-identify and fictionalise relevant cases. The Remote by Default 2 study (referenced in main text) was co-designed by patients and lay people; it includes a diverse patient panel. Oversight was provided by an independent external advisory group with a lay chair and patient representation. A person with lived experience of a healthcare safety incident (NS) is a co-author on this paper and provided input to data analysis and writing up, especially the recommendations for patients in table 2 .

Acknowledgments

We thank the participating organisations for cooperating with this study and giving permission to use fictionalised safety incidents. We thank the participants in the ethnographic study (patients, practice staff, policymakers, other informants) who gave generously of their time and members of the study advisory group.

Sarbadhikari SN ,
Jacob AG , et al
Hall Dykgraaf S ,
Desborough J ,
de Toca L , et al
Koonin LM ,
Tsang CA , et al
England NHS
Papoutsi C ,
Greenhalgh T
↵ Healthcare safety investigation branch: NHS 111’s response to callers with COVID-19-related symptoms during the pandemic . 2022 . Available : https://www.hsib.org.uk/investigations-and-reports/response-of-nhs-111-to-the-covid-19-pandemic/nhs-111s-response-to-callers-with-covid-19-related-symptoms-during-the-pandemic [Accessed 25 Jun 2023 ].
Royal College of General Practitioners
NHS Confederation
Gupta PP , et al
Panagioti M ,
Keers RN , et al
Panesar SS ,
deSilva D ,
Carson-Stevens A , et al
Campbell JL ,
Britten N ,
Green C , et al
Huibers L , et al
Hollnagel E ,
Braithwaite J
Institute of Medicine (US)
Jerak-Zuiderent S
Greenhalgh T ,
Alvarez Nishio A , et al
Hemmings N , et al
Hughes G , et al
Salisbury C , et al
Berens E-M ,
Nowak P , et al
Macdonald S ,
Browne S , et al
Edwards PJ ,
Bennett-Britton I ,
Ridd MJ , et al
Warren C , et al
Challiner J , et al
Wieringa S ,
Greenhalgh T , et al
Rushforth A , et al
Edmondson AC ,
Eddison N ,
Healy A , et al
Paparini S , et al
Byng R , et al
Moore L , et al
McKinstry B ,
Hammersley V ,
Burton C , et al
Gafaranga J ,
McKinstry B
Seuren LM ,
Wherton J , et al
Donaghy E ,
Parker R , et al
Sharma SC ,
Thakker A , et al
Johnsen TM ,
Norberg BL ,
Kristiansen E , et al
Wherton J ,
Ferwerda R ,
Tijssen R , et al
NHS Resolution
Marincowitz C ,
Bath P , et al
Antonio MG ,
Williamson A ,
Kameswaran V , et al
Oudshoorn N
Winters D ,
Newman T , et al
Huibers L ,
Renaud V , et al
↵ Remote consultations . n.d. Available : https://www.gmc-uk.org/ethical-guidance/ethical-hub/remote-consultations
Doherty M ,
Neilson S ,
O’Sullivan J , et al
Carson-Stevens A ,
Hibbert P ,
Williams H , et al
Edwards A ,
Powell C , et al
Morris RL ,
Fraser SW ,

X @dakinfrancesca, @trishgreenhalgh

Contributors RP led the Safety I analysis with support from AC. The Safety II analysis was part of a wider ethnographic study led by TG and SS, on which all other authors undertook fieldwork and contributed data. TG and RP wrote the paper, with all other authors contributing refinements. All authors checked and approved the final manuscript. RP is guarantor.

Funding Funding was from NIHR HS&DR (grant number 132807) (Remote by Default 2 study) and NIHR School for Primary Care Research (grant number 594) (ModCons study), plus an NIHR In-Practice Fellowship for RP.

Competing interests RP was National Professional Advisor, Care Quality Commission 2017–2022, where her role included investigation of safety issues.

Provenance and peer review Not commissioned; externally peer reviewed.

Linked Articles

Editorial Examining telehealth through the Institute of Medicine quality domains: unanswered questions and research agenda Timothy C Guetterman Lorraine R Buis BMJ Quality & Safety 2024; 33 552-555 Published Online First: 09 May 2024. doi: 10.1136/bmjqs-2023-016872

Read the full text or download the PDF:

Open access
Published: 16 August 2024

Examining the perception of undergraduate health professional students of their learning environment, learning experience and professional identity development: a mixed-methods study

Banan Mukhalalati 1 ,
Aaliah Aly 1 ,
Ola Yakti 1 ,
Sara Elshami 1 ,
Alaa Daud 2 ,
Ahmed Awaisu 1 ,
Ahsan Sethi 3 ,
Alla El-Awaisi 1 ,
Derek Stewart 1 ,
Marwan Farouk Abu-Hijleh 4 &
Zubin Austin 5

BMC Medical Education volume 24 , Article number: 886 ( 2024 ) Cite this article

354 Accesses

Metrics details

The quality of the learning environment significantly impacts student engagement and professional identity formation in health professions education. Despite global recognition of its importance, research on student perceptions of learning environments across different health education programs is scarce. This study aimed to explore how health professional students perceive their learning environment and its influence on their professional identity development.

An explanatory mixed-methods approach was employed. In the quantitative phase, the Dundee Ready Education Environment Measure [Minimum–Maximum possible scores = 0–200] and Macleod Clark Professional Identity Scale [Minimum–Maximum possible scores = 1–45] were administered to Qatar University-Health students ( N = 908), with a minimum required sample size of 271 students. Data were analyzed using SPSS, including descriptive statistics and inferential analysis. In the qualitative phase, seven focus groups (FGs) were conducted online via Microsoft Teams. FGs were guided by a topic guide developed from the quantitative results and the framework proposed by Gruppen et al. (Acad Med 94:969-74, 2019), transcribed verbatim, and thematically analyzed using NVIVO®.

The questionnaire response rate was 57.8% (525 responses out of 908), with a usability rate of 74.3% (390 responses out of 525) after excluding students who only completed the demographic section. The study indicated a “more positive than negative” perception of the learning environment (Median [IQR] = 132 [116–174], Minimum–Maximum obtained scores = 43–185), and a “good” perception of their professional identity (Median [IQR] = 24 [22–27], Minimum–Maximum obtained scores = 3–36). Qualitative data confirmed that the learning environment was supportive in developing competence, interpersonal skills, and professional identity, though opinions on emotional support adequacy were mixed. Key attributes of an ideal learning environment included mentorship programs, a reward system, and measures to address fatigue and boredom.

Conclusions

The learning environment at QU-Health was effective in developing competence and interpersonal skills. Students' perceptions of their learning environment positively correlated with their professional identity. Ideal environments should include mentorship programs, a reward system, and strategies to address fatigue and boredom, emphasizing the need for ongoing improvements in learning environments to enhance student satisfaction, professional identity development, and high-quality patient care.

Peer Review reports

The learning environment is fundamental to higher education and has a profound impact on student outcomes. As conceptualized by Gruppen et al. [ 1 ], it comprises a complex interplay of physical, social, and virtual factors that shape student engagement, perception, and overall development. Over the last decade, there has been a growing global emphasis on the quality of the learning environment in higher education [ 2 , 3 , 4 ]. This focus stems from the recognition that a well-designed learning environment that includes good facilities, effective teaching methods, strong social interactions, and adherence to cultural and administrative standards can greatly improve student development [ 2 , 5 , 6 , 7 ]. Learning environments impact not only knowledge acquisition and skill development but also value formation and the cultivation of professional attitudes [ 5 ].

Professional identity is defined as the “attitudes, values, knowledge, beliefs, and skills shared with others within a professional group” [ 8 ]. The existing research identified a significant positive association between the development of professional identity and the quality of the learning environment, and this association is characterized by being multifaceted and dynamic [ 9 ]. According to Hendelman and Byszewski [ 10 ] a supportive learning environment, characterized by positive role models, effective feedback mechanisms, and opportunities for reflective practice, fosters the development of a strong professional identity among medical students. Similarly, Jarvis-Selinger et al. [ 11 ] argue that a nurturing learning environment facilitates the socialization process which enables students to adopt and integrate the professional behaviors and attitudes expected in their field. Furthermore, Sarraf-Yazdi et al. [ 12 ] highlighted that professional identity formation is a continuous and multifactorial process involving the interplay of individual values, beliefs, and environmental factors. This dynamic process is shaped by both clinical and non-clinical experiences within the learning environment [ 12 ].

Various learning theories, such as the Communities of Practice (CoP) theory [ 13 ], emphasize the link between learning environments and learning outcomes, including professional identity development. The CoP theory describes communities of professionals with a shared knowledge interest who learn through regular interaction [ 13 , 14 ]. Within the CoP, students transition from being peripheral observers to central members [ 15 ]. Therefore, the CoP theory suggests that a positive learning environment is crucial for fostering learning, professional identity formation, and a sense of community [ 16 ].

Undoubtedly, health professional education programs (e.g., Medicine, Dental Medicine, Pharmacy, and Health Sciences) play a vital role not only in shaping the knowledge, expertise, and abilities of health professional students but also in equipping them with the necessary competencies for implementing healthcare initiatives and strategies and responding to evolving healthcare demands [ 17 ]. Within the field of health professions education, international organizations like the United Nations Educational, Scientific, and Cultural Organization (UNESCO), European Union (EU), American Council on Education (ACE), and World Federation for Medical Education (WFME) have emphasized the importance of high-quality learning environments in fostering the development of future healthcare professionals and called for considerations of the enhancement of the quality of the learning environment of health profession education programs [ 18 , 19 ]. These environments are pivotal for nurturing both the academic and professional growth necessary to navigate an increasingly globalized healthcare landscape [ 18 , 19 ].

Professional identity development is integral to health professions education which evolves continuously from early university years until later stages of the professional life as a healthcare practitioner [ 20 , 21 ]. This ongoing development helps students establish clear professional roles and boundaries, thereby reducing role ambiguity within multidisciplinary teams [ 9 ]. It is expected that as students advance in their professional education, their perception of the quality of the learning environment changes, which influences their learning experiences, the development of their professional identity, and their sense of community [ 22 ]. Cruess et al. [ 23 ] asserted that medical schools foster professional identity through impactful learning experiences, effective role models, clear curricula, and assessments. A well-designed learning environment that incorporates these elements supports medical students' socialization and professional identity formation through structured learning, reflective practices, and constructive feedback in both preclinical and clinical stages [ 23 ].

Despite the recognized importance of the quality of learning environments and their influence on student-related outcomes, this topic has been overlooked regionally and globally [ 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. There is a significant knowledge gap in understanding how different components of the learning environment specifically contribute to professional identity formation. Most existing studies focus on general educational outcomes without exploring the detailed ways in which the learning environment shapes professional attitudes, values, and identity. Moreover, there is a global scarcity of research exploring how students’ perceptions of the quality of the learning environment and professional identity vary across various health profession education programs at different stages of their undergraduate education. This lack of comparative studies makes it challenging to identify best practices that can be adapted across different educational contexts. Furthermore, most research tends to focus on single-discipline studies, neglecting the interdisciplinary nature of modern healthcare education, which is essential for preparing students for collaborative practice in real-world healthcare settings. Considering the complex and demanding nature of health profession education programs and the increased emphasis on the quality of learning environments by accreditation bodies, examining the perceived quality of the educational learning environment by students is crucial [ 19 ]. Understanding students’ perspectives can provide valuable insights into areas needing improvement and highlight successful strategies that enhance both learning environment and experiences and professional identity development.

This research addresses this gap by focusing on the interdisciplinary health profession education programs to understand the impact of the learning environment on the development of the professional identity of students and its overall influence on their learning experiences. The objectives of this study are to 1) examine the perception of health professional students of the quality of their learning environment and their professional identity, 2) identify the association between health professional students’ perception of the quality of their learning environment and the development of their professional identity, and 3) explore the expectations of health professional students of the ideal educational learning environment. This research is essential in providing insights to inform educational practices globally to develop strategies to enhance the quality of health profession education.

Study setting and design

This study was conducted at Qatar University Health (QU Health) Cluster which is an interdisciplinary health profession education program that was introduced as the national provider of higher education in health and medicine in the state of Qatar. QU Health incorporates five colleges: Health Sciences (CHS), Pharmacy (CPH), Medicine (CMED), Dental Medicine (CDEM) and Nursing (CNUR) [ 31 ]. QU Health is dedicated to advancing inter-professional education (IPE) through its comprehensive interdisciplinary programs. By integrating IPE principles into the curriculum and fostering collaboration across various healthcare disciplines, the cluster prepares students to become skilled and collaborative professionals. Its holistic approach to teaching, research, and community engagement not only enhances the educational experience but also addresses local and regional healthcare challenges, thereby making a significant contribution to the advancement of population health in Qatar [ 32 ]. This study was conducted from November 2022 to July 2023. An explanatory sequential mixed methods triangulation approach was used for an in-depth exploration and validation of the quantitative results qualitatively [ 33 , 34 ]. Ethical approval for the study was obtained from the Qatar University Institutional Review Board (approval number: QU-IRB 1734-EA/22).

For the quantitative phase, a questionnaire was administered via SurveyMonkey® incorporating two previously validated questionnaires: the Dundee Ready Educational Environment Measure (DREEM), developed by Roff et al. in 1997 [ 35 ], and the Macleod Clark Professional Identity Scale-9 (MCPIS-9), developed by Adam et al. in 2006 [ 8 ]. Integrating DREEM and MCPIS-9 into a single questionnaire was undertaken to facilitate a comprehensive evaluation of two distinct yet complementary dimensions—namely, the educational environment and professional identity—that collectively influence the learning experience and outcomes of students, as no single instrument effectively assesses both aspects simultaneously [ 36 ]. The survey comprised three sections—Section A: sociodemographic characteristics, Section B: the DREEM scoring scale for assessing the quality of the learning environment, and Section C: the MCPIS-9 scoring scale for assessing professional identity. For the qualitative phase, seven focus groups (FGs) were arranged with a sample of QU-Health students. The qualitative and quantitative data obtained were integrated at the interpretation and reporting level using a narrative, contiguous approach [ 37 , 38 ].

Quantitative phase

Population and sampling.

The total population sampling approach in which all undergraduate QU-Health students who had declared their majors (i.e., the primary field of study that an undergraduate student has chosen during their academic program) at the time of conducting the study in any of the four health colleges under QU-Health ( N = 908), namely, CPH, CMED, CDEM, and CHS, such as Human Nutrition (Nut), Biomedical Science (Biomed), Public Health (PH), and Physiotherapy (PS), were invited to participate in the study. Nursing students were excluded from this study because the college was just established in 2022; therefore, students were in their general year and had yet to declare their majors at the time of the study. The minimum sample size required for the study was determined to be 271 students based on a margin error of 5%, a confidence level of 95%, and a response distribution of 50%.

Data collection

Data was collected in a cross-sectional design. After obtaining the approval of the head of each department, contact information for eligible students was extracted from the QU-Health student databases for each college, and invitations were sent via email. The distribution of these invitations was done by the administrators of the respective colleges. The invitation included a link to a self-administered questionnaire on SurveyMonkey® (Survey Monkey Inc., San Mateo, California, USA), along with informed consent information. All 908 students were informed about the study’s purpose, data collection process, anonymity and confidentiality assurance, and the voluntary nature of participation. The participants were sent regular reminders to complete the survey to increase the response rate.

A focused literature review identified the DREEM as the most suitable validated tool for this study. The DREEM is considered the gold standard for assessing undergraduate students' perceptions of their learning environment [ 35 ]. Its validity and reliability have been consistently demonstrated across various settings (i.e., clinical and non-clinical) and health professions (e.g., nursing, medicine, dentistry, and pharmacy), in multiple countries worldwide, including the Gulf Cooperation Council countries [ 24 , 35 , 39 , 40 , 41 , 42 ]. The DREEM is a 50-item inventory divided into 5 subscales and developed to measure the academic climate of educational institutions using a five-point Likert scale from 0 “strongly disagree” to 4 “strongly agree”. The total score ranges from 0 to 200, with higher scores reflecting better perceptions of the learning environment [ 35 , 39 , 43 ]. The interpretation includes very poor (0–50), plenty of problems (51–100), more positive than negative (101–151), and excellent (151–200).

The first subscale, Perception to Learning (SpoL), with 12 items scoring 0–48. Interpretation includes very poor (0–12), teaching is viewed negatively (13–24), a more positive approach (25–36), and teaching is highly thought of (37–48). The second domain, Perception to Teachers (SpoT), with 11 items scoring 0–44. Interpretation includes abysmal (0–11), in need of some retraining (12–22), moving in the right direction (23–33), and model teachers (34–44). The third domain, academic self-perception (SASP), with 8 items scoring 0–32. Interpretation includes a feeling of total failure (0–8), many negative aspects (9–16), feeling more on the positive side (17–24), and confident (25–32). The fourth domain, Perception of the atmosphere (SPoA), with 12 items scoring 0–48. Interpretation includes a terrible environment (0–12); many issues need to be changed (13–24), a more positive atmosphere (25–36), and a good feeling overall (37–48). Lastly, the fifth domain, social self-perception (SSSP), with 7 items scoring 0–28. Interpretation includes Miserable (0–7), Not a nice place (8–14), Not very bad (15–21), and very good socially (22–28).

Several tools have been developed to explore professional identity in health professions [ 44 ], but there is limited research on their psychometric qualities [ 45 ]. The MCPIS-9 is notable for its robust psychometric validation and was chosen for this study due to its effectiveness in a multidisciplinary context as opposed to other questionnaires that were initially developed for the nursing profession [ 8 , 46 , 47 ]. MCPIS-9 is a validated 9-item instrument, which uses a 5-point Likert response scale, with scores ranging from 1 “strongly disagree” to 5 “strongly agree”. Previous studies that utilized the MCPIS-9 had no universal guidance for interpreting the MCPIS-9 score; however, the higher the score, the stronger the sense of professional identity [ 46 , 48 ].

Data analysis

The quantitative data were analyzed using SPSS software (IBM SPSS Statistics for Windows, version 27.0; IBM Corp., Armonk, NY, USA). The original developers of the DREEM inventory identified nine negative items: items 11, 12, 19, 20, 21, 23, 42, 43, and 46 – these items were reverse-coded. Additionally, in the MCPIS-9 tool, the original developers identified three negative items: items 3, 4, and 5. Descriptive and inferential analyses were also conducted. Descriptive statistics including number (frequencies [%]), mean ± SD, and median (IQR), were used to summarize the demographics and responses to the DREEM and MCPIS-9 scoring scales. In the inferential analysis, to test for significant differences between demographic subgroups in the DREEM and MCPIS-9 scores, Kruskal–Wallis tests were used for variables with more than two categories, and Mann–Whitney U-tests were used for variables with two categories. Spearman's rank correlation analysis was used to investigate the association between perceived learning environment and professional identity development. The level of statistical significance was set a priori at p < 0.05. The internal consistency of the DREEM and MCPIS-9 tools was tested against the acceptable Cronbach's alpha value of 0.7.

Qualitative phase

A purposive sampling approach was employed to select students who were most likely to provide valuable insights to gain a deeper understanding of the topic. The inclusion criteria required that participants should have declared their major in one of the following programs: CPH, CMED, CDEM, CHS: Nut, Biomed, PS, and PH. This selection criterion aimed to ensure that participants had sufficient knowledge and experience related to their chosen fields of study within QU-Health. Students were included if they were available and willing to share their experiences and thoughts. Students who did not meet these criteria were excluded from participation. To ensure a representative sample, seven FGs were conducted, one with each health professional education program. After obtaining the approval of the head of each department, participants were recruited by contacting the class representative of each professional year to ask for volunteers to join and provide their insights. Each FG involved students from different professional years to ensure a diverse representation of experiences and perspectives.

The topic guide (Supplementary Material 1) was developed and conceptualized based on the research objectives, selected results from the quantitative phase, and the Gruppen et. al. framework [ 1 ]. FGs were conducted online using Microsoft Teams® through synchronous meetings. Before initiating the FGs, participants were informed of their rights and returned signed consent forms to the researchers. FGs were facilitated by two research assistants (AA and OY), each facilitating separate sessions. The facilitators, who had prior experience with conducting FGs and who were former pharmacy students from the CPH, were familiar with some of the participants, and hence were able to encourage open discussion, making it easier for students to share their perceptions of the learning environment within the QU Health Cluster. Participants engaged in concurrent discussions were encouraged to use the "raise hand" feature on Microsoft Teams to mimic face-to-face interactions. Each FG lasted 45–60 min, was conducted in English, and was recorded and transcribed verbatim and double-checked for accuracy. After the seventh FG, the researchers were confident that a saturation point had been reached where no new ideas emerged, and any further data collection through FGs was unnecessary. Peer and supervisory audits were conducted throughout the research process.

The NVIVO ® software (version 12) was utilized to perform a thematic analysis incorporating both deductive and inductive approaches. The deductive approach involved organizing the data into pre-determined categories based on the Gruppen et al. framework, which outlines key components of the learning environment. This framework enabled a systematic analysis of how each component of the learning environment contributes to students' professional development and highlighted areas for potential improvement. Concurrently, the inductive approach was applied to explore students' perceptions of an ideal learning environment, facilitating the emergence of new themes and insights directly from the data, independent of pre-existing categories. This dual approach provided a comprehensive understanding of the data by validating the existing theory while also exploring new findings [ 49 ]. Two coders were involved in coding the transcripts (AA and BM) and in cases of disagreements between researchers, consensus was achieved through discussion.

The response rate was 57.8% (525 responses out of 908), while the usability rate was 74.3% (390 responses out of 525) after excluding students who only completed the demographic section. The demographic and professional characteristics of the participants are presented in Table 1 . The majority were Qataris (37.0% [ n = 142]), females (85.1% [ n = 332]), and of the age group of 21–23 years (51.7% [ n = 201]). The students were predominantly studying at the CHS (36.9%[ n = 144]), in their second professional year (37.4% [ n = 146]), and had yet to be exposed to experiential learning, that is, clinical rotations (70.2% [ n = 273]).

Perceptions of students of their learning environment

The overall median DREEM score for study participants indicated that QU Health students perceive their learning environment to be "more positive than negative" (132 [IQR = 116–174]). The reliability analysis for this sample of participants indicated a Cronbach's alpha for the total DREEM score of 0.94, and Cronbach's alpha scores for each domain of the DREEM tool, SPoL, SPoT, SASP, SPoA, and SSSP of 0.85, 0.74, 0.81, 0.85, and 0.65, respectively.

Individual item responses representing each domain of the DREEM tool are presented in Table 2 . For Domain I, QU Health students perceived the teaching approach in QU Health to be "more positive" (32 [IQR = 27–36]). Numerous participants agreed that the teaching was well-focused (70.7% [ n = 274]), student-focused (66.1% [ n = 254]) and aimed to develop the competencies of students (72.0% [ n = 278]). The analysis of students’ perceptions related to Domain II revealed that faculty members were perceived to be “moving in the right direction” (30 [IQR = 26–34]). Most students agreed that faculty members were knowledgeable (90.7%[ n = 345]) and provided students with clear examples and constructive feedback (77.6% [ n = 294] and 63.8% [ n = 224], respectively. Furthermore, the analysis of Domain III demonstrated that QU Health students were shown to have a "positive academic self-perception" (22 [IQR = 19–25]). In this regard, most students believed that they were developing their problem-solving skills (78% [ n = 292]) and that what they learned was relevant to their professional careers (76% [ n = 288]). Furthermore, approximately 80% ( n = 306) of students agreed that they had learned empathy in their profession. For Domain IV, students perceived the atmosphere of their learning environment to be "more positive" (32 [IQR = 14–19]). A substantial number of students asserted that there were opportunities for them to develop interpersonal skills (77.7% [ n = 293]), and that the atmosphere motivated them as learners (63.0% [ n = 235]). Approximately one-third of students believed that the enjoyment did not outweigh the stress of studying (32.3% [ n = 174]). Finally, analysis of Domain V indicates that students’ social self-perception was “not very bad” (17 [IQR = 27–36]). Most students agreed that they had good friends at their colleges (83% [ n = 314]) and that their social lives were good (68% [ n = 254]).

Table 3 illustrates the differences in the perception of students of their overall learning environment according to their demographic and professional characteristics. No significant differences were noted in the perception of the learning environment among the subgroups with selected demographic and professional characteristics, except for the health profession program in which they were enrolled ( p -value < 0.001), whether they had relatives who studied or had studied the same profession ( p -value < 0.002), and whether they started their experiential learning ( p -value = 0.043). Further analyses comparing the DREEM subscale scores according to their demographic and professional characteristics are presented in Supplementary Material 1.

Students’ perceptions of their professional identities

The students provided positive responses relating to their perceptions of their professional identity (24.00 IQR = [22–27]). The reliability analysis of this sample indicated a Cronbach's alpha of 0.605. The individual item responses representing the MCPIS-9 tool are presented in Table 2 . Most students (85% [ n = 297]) expressed pleasant feelings about belonging to their own profession, and 81% ( n = 280) identified positively with members of their profession. No significant differences were noted in the perception of students of their professional identity when analyzed against selected demographic subgroups, except for whether they had relatives who had studied or were studying the same profession ( p -value = 0.027). Students who had relatives studying or had studied the same profession tended to perceive their professional identity better (25 IQR = [22–27] and 24 IQR = [21–26], respectively) (Table 3 ).

Association between MCPIS-9 and DREEM

Spearman's rank correlation between the DREEM and MCPIS-9 total scores indicated an intermediate positive correlation between perceptions of students toward their learning environment and their professional identity development (r = 0.442, p -value < 0.001). The DREEM questionnaire, with its 50 items divided into five subscales, comprehensively assessed various dimensions of the learning environment. Each subscale evaluated a distinct aspect of the educational experience, such as the effectiveness of teaching, teacher behavior and attitudes, academic confidence, the overall learning atmosphere, and social integration. The MCPIS-9 questionnaire specifically assessed professional identity through nine items that measure attitudes, values, and self-perceived competence in the professional domain. The positive correlation demonstrated between the DREEM and MCPIS-9 scores indicated that as students perceive their learning environment more positively, their professional identity is also enhanced.

Thirty-seven students from the QU Health colleges were interviewed: eleven from CPH, eight from CMED, four from CDEM, and fourteen from CHS (six from Nut, three from PS, three from Biomed, and three from PH). Four conventional themes were generated deductively using Gruppen et al.’s conceptual framework, while one theme was derived through inductive analysis. The themes and sub-themes generated are demonstrated in Table 4 .

Theme 1. The personal component of the learning environment

This theme focused on student interactions and experiences within their learning environment and their impact on perceptions of learning, processes, growth, and professional development.

Sub-theme 1.1. Experiences influencing professional identity formation

Students classified their experiences into positive and negative. Positive experiences included hands-on activities such as on-campus practical courses and pre-clinical activities, which built their confidence and professional identity. In this regard, one student mentioned:

“Practical courses are one of the most important courses to help us develop into pharmacists. They make you feel confident in your knowledge and more willing to share what you know.” [CPH-5]

Many students claimed that interprofessional education (IPE) activities enhanced their self-perception, clarified their roles, and boosted their professional identity and confidence. An interviewee stated:

"I believe that the IPE activity,…., is an opportunity for us to explore our role. It has made me know where my profession stands in the health sector and how we all depend on each other through interprofessional thinking and discussions." [CHS-Nut-32]

However, several participants reported that an extensive workload hindered their professional identity development. A participant stated:

“The excessive workload prevents us from joining activities that would contribute to our professional identity development. Also, it restricts our networking opportunities and makes us always feel burnt out.” [CHS-Nut-31]

Sub-theme 1.2. Strategies used by students to pursue their goals

QU Health students employed various academic and non-academic strategies to achieve their objectives, with many emphasizing list-making and identifying effective study methods as key approaches:

“Documentation. I like to see tasks that I need to do on paper. Also, I like to classify my tasks based on their urgency. I mean, deadlines.” [CHS-Nut-31]

“I always try to be as efficient as possible when studying and this can be by knowing what studying method best suits me.” [CHS-Biomed-35]

Nearly all students agreed that seeking feedback from faculty was crucial for improving their work and performance. In this context, a student said:

“We must take advantage of the provided opportunity to discuss our assignments, projects, and exams, like what we did correctly, and what we did wrongly. They always discuss with us how to improve our work on these things.” [CHS-Nut-32]

Moreover, many students also believed that developing communication skills was vital for achieving their goals, given their future roles in interprofessional teams. A student mentioned:

“Improving your communication skills is a must because inshallah (with God’s will) in the future we will not only work with biomedical scientists, but also with nurses, pharmacists, and doctors. So, you must have good communication abilities.” [CHS-Biomed-34]

Finally, students believe that networking is crucial for achieving their goals because it opens new opportunities for them as stated by a student:

“Networking with different physicians or professors can help you to know about research or training opportunities that you could potentially join.” [CMED-15]

Subtheme 1.3. Students’ mental and physical well-being

Students agreed that while emotional well-being is crucial for good learning experiences and professional identity development, colleges offered insufficient support. An interviewee stated:

“We simply don't have the optimal support we need to take care of our emotional well-being as of now, despite how important it is and how it truly reflects on our learning and professional development” [CDEM-20]

Another student added:

“…being in an optimal mental state provides us with the opportunity to acquire all required skills that would aid in our professional identity development. I mean, interpersonal skills, adaptability, self-reflection” [CPH-9]

Students mentioned some emotional support provided by colleges, such as progress tracking and stress-relief activities. Students said:

“During P2 [professional year 2], I missed a quiz, and I was late for several lectures. Our learning support specialist contacted me … She was like, are you doing fine? I explained everything to her, and she contacted the professors for their consideration and support.” [CPH-7]

“There are important events that are done to make students take a break and recharge, but they are not consistent” [CHS-PS-27]

On the physical well-being front, students felt that their colleges ensured safety, especially in lab settings, with proper protocols to avoid harm. A student mentioned:

“The professors and staff duly ensure our safety, especially during lab work. They make sure that we don't go near any harmful substances and that we abide by the lab safety rules” [CHS-Biomed -35]

Theme 2. Social component of the learning environment

This theme focused on how social interactions shape students’ perceptions of learning environments and learning experiences.

Sub-theme 2.1. Opportunities for community engagement

Participants identified various opportunities for social interactions through curricular and extracurricular activities. Project-based learning (PBL) helped them build connections, improve teamwork and enhance critical thinking and responsibility as stated by one student:

“I believe that having PBL as a big part of our learning process improves our teamwork and interpersonal skills and makes us take responsibility in learning, thinking critically, and going beyond what we would have received in class to prepare very well and deep into the topic.” [CMED-12]

Extracurricular activities, including campaigns and events, helped students expand their social relationships and manage emotional stress. A student stated:

“I think that the extracurricular activities that we do, like the campaigns or other things that we hold in the college with other students from other colleges, have been helpful for me in developing my personality and widening my social circle. Also, it dilutes the emotional stress we are experiencing in class” [CDEM-22]

Sub-theme 2.2. Opportunities for learner-to-patient interactions

Students noted several approaches their colleges used to enhance patient-centered education and prepare them for real-world patient interactions. These approaches include communication skills classes, simulated patient scenarios, and field trips. Students mentioned:

“We took a class called Foundation of Health, which mainly focused on how to communicate our message to patients to ensure that they were getting optimal care. This course made us appreciate the term ‘patient care’ more.” [CHS-PH-38]

“We began to appreciate patient care when we started to take a professional skills course that entailed the implementation of a simulated patient scenario. We started to realize that communication with patients didn’t go as smoothly as when we did it with a colleague in the classroom.” [CPH-1]

“We went on a field trip to ‘Shafallah Center for Persons with Disability’ and that helped us to realize that there were a variety of patients that we had to care for, and we should be physically and mentally prepared to meet their needs.” [CDEM-21]

Theme 3. Organizational component of the learning environment

This theme explored students' perceptions of how the college administration, policies, culture, coordination, and curriculum design impact their learning experiences.

Sub-theme 3.1. Curriculum and study plan

Students valued clinical placements for their role in preparing them for the workplace and developing professional identity. A student stated:

“Clinical placements are very crucial for our professional identity development; we get the opportunity to be familiarized with and prepared for the work environment.” [CHS-PS-27]

However, students criticized their curriculum for not equipping them with adequate knowledge and skills. For example, a student said:

“… Not having a well-designed curriculum is of concern. We started very late in studying dentistry stuff and that led to us cramming all the necessary information that we should have learned.” [CDEM-20]

Furthermore, students reported that demanding schedules and limited course availability hindered learning and delayed progress:

“Last semester, I had classes from Sunday to Thursday from 8:00 AM till 3:00 PM in the same classroom, back-to-back, without any break. I was unable to focus in the second half of the day.” [CHS-Nut-38]

“Some courses are only offered once a year, and they are sometimes prerequisites for other courses. This can delay our clinical internship or graduation by one year.” [CHS-Biomed-36]

Additionally, the outdated curriculum was seen as misaligned with advancements in artificial intelligence (AI). One student stated:

“… What we learn in our labs is old-fashioned techniques, while Hamad Medical Corporation (HMC) is following a new protocol that uses automation and AI. So, I believe that we need to get on track with HMC as most of us will be working there after graduation.” [CHS-Biomed-35]

Sub-theme 3.2. Organizational climate and policies

Students generally appreciated the positive university climate and effective communication with the college administration which improves course quality:

“Faculty members and the college administration usually listen to our comments about courses or anything that we want to improve, and by providing a course evaluation at the end of the semester, things get better eventually.” [CPH-2]

Students also valued faculty flexibility with scheduling exams and assignments, and praised the new makeup exam policy which enhances focus on learning:

“Faculty members are very lenient with us. If we want to change the date of the exam or the deadline for any assignment, they agree if everyone in the class agrees. They prioritize the quality of our work over just getting an assignment done.” [CHS-PS-37]

“I am happy with the introduction of makeup exams. Now, we are not afraid of failing and losing a whole year because of a course. I believe that this will help us to focus on topics, not just cramming the knowledge to pass.” [CPH-9]

However, students expressed concerns about the lack of communication between colleges and clinical placements and criticized the lengthy approval process for extracurricular activities:

“There is a contract between QU and HMC, but the lack of communication between them puts students in a grey area. I wish there would be better communication between them.” [CMED-15]

“To get a club approved by QU, you must go through various barriers, and it doesn't work every time. A lot of times you won't get approved.” [CMED-14]

Theme 4. Materialistic component of the learning environment

This theme discussed how physical and virtual learning spaces affect students' learning experiences and professional identity.

Sub-theme 4.1. The physical space for learning

Students explained that the interior design of buildings and the fully equipped laboratory facilities in their programs enhanced focus and learning:

“The design has a calming effect, all walls are simple and isolate the noise, the classrooms are big with big windows, so that the sunlight enters easily, and we can see the green grass. This is very important for focusing and optimal learning outcomes.” [CPH-5]

“In our labs, we have beds and all the required machines for physiotherapy exercises and practical training, and we can practice with each other freely.” [CHS-PS-27]

Students from different emphasized the need for dedicated lecture rooms for each batch and highlighted the importance of having on-site cafeterias to avoid disruptions during the day:

“We don't have lecture rooms devoted to each batch. Sometimes we don't even find a room to attend lectures and we end up taking the lectures in the lab, which makes it hard for us to focus and study later.” [CDEM-23]

“Not having a cafeteria in this building is a negative point. Sometimes we miss the next lecture or part of it if we go to another building to buy breakfast.” [CHS-Nut-29]

Sub-theme 4.2. The virtual space for online learning

Students appreciated the university library's extensive online resources and free access to platforms like Microsoft Teams and Webex for efficient learning and meetings. They valued recorded lectures for flexible study and appreciated virtual webinars and workshops for global connectivity.

“QU Library provides us with a great diversity and a good number of resources, like journals or books, as well as access medicine, massive open online courses, and other platforms that are very useful for studying.” [CMED-16].

“Having your lectures recorded through virtual platforms made it easier to take notes efficiently and to study at my own pace.” [CHS-PS-38]

"I hold a genuine appreciation for the provided opportunities to register in online conferences. I remember during the COVID-19 pandemic, I got the chance to attend an online workshop. This experience allowed me to connect with so many people from around the world." [CMED-15]

Theme 5. Characteristics of an ideal learning environment

This theme explored students’ perceptions of an ideal learning environment and its impact on their professional development and identity.

Sub-theme 5.1. Active learning and professional development supporting environment

Students highlighted that an ideal learning environment should incorporate active learning methods and a supportive atmosphere. They suggested using simulated patients in case-based learning and the use of game-based learning platforms:

“I think if we have, like in ITQAN [a Clinical Simulation and Innovation Center located on the Hamad Bin Khalifa Medical City (HBKMC) campus of Hamad Medical Corporation (HMC)], simulated patients, I think that will be perfect like in an “Integrated Case-Based Learning” case or professional skills or patient assessment labs where we can go and intervene with simulated patients and see what happens as a consequence. This will facilitate our learning.” [CPH-4]

“I feel that ‘Kahoot’ activities add a lot to the session. We get motivated and excited to solve questions and win. We keep laughing, and I honestly feel that the answers to these questions get stuck in my head.” [CHS-PH-38].

Students emphasized the need for more opportunities for research, career planning, and equity in terms of providing resources and opportunities for students:

“Students should be provided with more opportunities to do research, publish, and practice.” [CMED-16]

“We need better career planning and workshops or advice regarding what we do after graduation or what opportunities we have.” [CHS-PS-25]

“I think that opportunities are disproportionate, and this is not ideal. I believe all students should have the same access to opportunities like having the chance to participate in conferences and receiving research opportunities, especially if one fulfills the requirements.” [CHS-Biomed-35]

Furthermore, the students proposed the implementation of mentorship programs and a reward system to enable a better learning experience:

“Something that could enable our personal development is a mentorship program, which our college started to implement this year, and I hope they continue to because it’s an attribute of an ideal learning environment.” [CPH-11]

“There has to be some form of reward or acknowledgments to students, especially those who, for example, have papers published or belong to leading clubs, not just those who are, for example, on a dean’s list because education is much more than just academics.” [CHS-PS-26]

Subtheme 5.2. Supportive physical environment

Participants emphasized that the physical environment of the college significantly influences their learning attitudes. A student said:

“The first thing that we encounter when we arrive at the university is the campus. I mean, our early thoughts toward our learning environment are formed before we even know anything about our faculty members or the provided facilities. So, ideally, it starts here.” [CPH-10]

Therefore, students identified key characteristics of an optimal physical environment which included: having a walkable campus, designated study and social areas, and accessible food and coffee.

“I think that learning in what they refer to as a walkable campus, which entails having the colleges and facilities within walking distance from each other, without restrictions of high temperature and slow transportation, is ideal.” [CPH-8]

“The classrooms and library should be conducive to studying and focusing, and there should also be other places where one can actually socialize and sit with one’s friends.” [CDEM-22]

“It is really important to have a food court or café in each building, as our schedules are already packed, and we have no time to go get anything for nearby buildings.” [CHS-Biomed-34]

Data integration

Table 5 represents the integration of data from the quantitative and qualitative phases. It demonstrates how the quantitative findings informed and complemented the qualitative analysis and explains how quantitative data guided the selection of themes in the qualitative phase. The integration of quantitative and qualitative data revealed both convergences and divergences in students' views of their learning environment. Both data sources consistently indicated that the learning environment supported the development of interpersonal skills, fostered strong relationships with faculty, and promoted an active, student-centered learning approach. This environment was credited with enhancing critical thinking, independence, and responsibility, as well as boosting students' confidence and competence through clear role definitions and constructive faculty feedback.

However, discrepancies emerged between the two phases. Quantitative data suggested general satisfaction with timetables and support systems, while qualitative data uncovered significant dissatisfaction. Although quantitative results indicated that students felt well-prepared and able to memorize necessary material, qualitative findings revealed challenges with concentration and focus. Furthermore, while quantitative data showed contentment with institutional support, qualitative responses pointed to shortcomings in emotional and physical support.

This study examined the perceptions of QU Health students regarding the quality of their learning environment and the characteristics of an ideal learning environment. Moreover, this study offered insights into the development of professional identity, emphasizing the multifaceted nature of learning environments and their substantial impact on professional identity formation.

Perceptions of the learning environment

The findings revealed predominantly positive perceptions among students regarding the quality of the overall learning environment at QU Health and generally favorable perception of all five DREEM subscales, which is consistent with the international studies using the DREEM tool [ 43 , 50 , 51 , 52 , 53 , 54 ]. Specifically, participants engaged in experiential learning expressed heightened satisfaction, which aligns with existing research indicating that practical educational approaches enhance student engagement and satisfaction [ 55 , 56 ]. Additionally, despite limited literature, students without relatives in the same profession demonstrated higher perceptions of their learning environment, possibly due to fewer preconceived expectations. A 2023 systematic review highlighted how students’ expectations influence their satisfaction and academic achievement [ 57 ]. However, specific concerns arose regarding the learning environment, including overemphasis on factual learning in teaching, student fatigue, and occasional boredom. These issues were closely linked to the overwhelming workload and conventional teaching methods, as identified in the qualitative phase.

Association between learning environment and professional identity

This study uniquely integrated the perceptions of the learning environment with insights into professional identity formation in the context of healthcare education which is a relatively underexplored area in quantitative studies [ 44 , 58 , 59 , 60 ]. This study demonstrated a positive correlation between students' perceptions of the learning environment (DREEM) and their professional identity development (MCPIS-9) which suggested that a more positive learning environment is associated with enhanced professional identity formation. For example, a supportive and comfortable learning atmosphere (i.e., high SPoA scores) can enhance students' confidence and professional self-perception (i.e., high MCPIS-9 scores). The relationship between these questionnaires is fundamental to this study. The DREEM subscales, particularly Perception of Learning (SpoL) and Academic Self-Perception (SASP), relate to how the learning environment supports or hinders the development of a professional identity, as measured by MCPIS-9. Furthermore, the Perception of Teachers (SpoT) subscale examines how teacher behaviors and attitudes impact students, which can influence their professional identity development. The Perception of Atmosphere (SPoA) and Social Self-Perception (SSSP) subscales evaluate the broader environment and social interactions, which are crucial for professional identity formation as they foster a sense of community and belonging.

Employing a mixed methods approach and analyzing both questionnaires and FGs through the framework outlined by Gruppen et al. highlighted key aspects across four dimensions of the learning environment: personal development, social dimension, organizational setting, and materialistic dimension [ 1 ]. First, the study underscored the significance of both personal development and constructive feedback. IPE activities emerged as a key factor that promotes professional identity by cultivating collaboration and role identification which is consistent with Bendowska and Baum's findings [ 61 ]. Similarly, the positive impact of constructive faculty feedback on student learning outcomes aligned with the work of Gan et al. which revealed that feedback from faculty members positively influences course satisfaction and knowledge retention, which are usually reflected in course results [ 62 ]. Importantly, the research also emphasized the need for workload management strategies to mitigate negative impacts on student well-being, a crucial factor for academic performance and professional identity development [ 63 , 64 ]. The inclusion of community events and support services could play a significant role in fostering student well-being and reducing stress, as suggested by Hoferichter et al. [ 65 ]. Second, the importance of the social dimension of the learning environment was further highlighted by the study. Extracurricular activities were identified as opportunities to develop essential interpersonal skills needed for professional identity, mirroring the conclusions drawn by Achar Fujii et al. who argued that extracurricular activities lead to the development of fundamental skills and attitudes to build and refine their professional identity and facilitate the learning process, such as leadership, commitment, and responsibility [ 66 ]. Furthermore, Magpantay-Monroe et al. concluded that community and social engagement led to professional identity development in nursing students through the expansion of their knowledge and communication with other nursing professionals [ 67 ]. PBL activities were another key element that promoted critical thinking, learning, and ultimately, professional identity development in this study similar to what was reported by Zhou et al. and Du et al. [ 68 , 69 ]. Third, the organizational setting, particularly the curriculum and clinical experiences, emerged as crucial factors. Clinical placements and field trips were found to be instrumental in cultivating empathy and professional identity [ 70 , 71 ]. However, maintaining an up-to-date curriculum that reflects advancements in AI healthcare education is equally important, as highlighted by Randhawa and Jackson in 2019 [ 72 ]. Finally, the study underlined the role of the materialistic dimension of the learning environment. Physical learning environments with natural light and managed noise levels were found to contribute to improved academic performance [ 73 , 74 ]. Additionally, the value of online educational resources, such as online library resources and massive open online course, as tools facilitating learning by providing easy access to materials, was emphasized, which is consistent with the observations of Haleem et al. [ 75 ].

The above collectively contribute to shaping students' professional identities through appreciating their roles, developing confidence, and understanding the interdependence of different health professions. These indicate that a supportive and engaging learning environment is crucial for fostering a strong sense of professional identity. Incorporating these student-informed strategies can assist educational institutions in cultivating well-rounded healthcare professionals equipped with the knowledge, skills, and emotional resilience needed to thrive in the dynamic healthcare landscape. Compared to existing quantitative data, this study reported a lower median MCPIS-9 score of 24.0, in contrast to previously reported scores of 39.0, 38.0, 38.0, respectively. [ 76 , 77 , 78 ]. This discrepancy may be influenced by the fact that the participants were in their second professional year, known for weaker identity development [ 79 ]. Students with relatives in the same profession perceived their identity more positively, which is likely due to role model influences [ 22 ].

Expectations of the ideal educational learning environment

This study also sought to identify the key attributes of an ideal learning environment from the perspective of students at QU-Health. The findings revealed a strong emphasis on active learning strategies, aligning with Kolb's experiential learning theory [ 80 ]. This preference suggests a desire to move beyond traditional lecture formats and engage in activities that promote experimentation and reflection, potentially mitigating issues of student boredom. Furthermore, students valued the implementation of simple reward systems such as public recognition, mirroring the positive impact such practices have on academic achievement reported by Dannan in 2020 [ 81 ]. The perceived importance of mentorship programs resonates with the work of Guhan et al. who demonstrated improved academic performance, particularly for struggling students [ 82 ]. Finally, the study highlighted the significance of a walkable campus with accessible facilities. This aligns with Rohana et al. who argued that readily available and useable facilities contribute to effective teaching and learning processes, ultimately resulting in improved student outcomes [ 83 ]. Understanding these student perceptions, health professions education programs can inform strategic planning for curricular and extracurricular modifications alongside infrastructural development.

The complementary nature of qualitative and quantitative methods in understanding student experiences

This study underscored the benefits of employing mixed methods to comprehensively explore the interplay between the learning environment and professional identity formation as complex phenomena. The qualitative component provided nuanced insights that complemented the baseline data provided by DREEM and MCPIS-9 questionnaires. While DREEM scores generally indicated positive perceptions, qualitative findings highlighted the significant impact of experiential learning on students' perceptions of the learning environment and professional identity development. Conversely, discrepancies emerged between questionnaire responses and FG interviews, revealing deeper issues such as fatigue and boredom associated with traditional teaching methods and heavy workloads, potentially influenced by cultural factors. In FGs, students revealed cultural pressures to conform and stigma against expressing dissatisfaction, which questionnaire responses may not capture. Qualitative data allowed students to openly discuss culturally sensitive issues, indicating that interviews complement surveys by revealing insights overlooked in quantitative assessments alone. These insights can inform the design of learning environments that support holistic student development. The study also suggested that cultural factors can influence student perceptions and should be considered in educational research and practice.

Application of findings

The findings from this study can be directly applied to inform and enhance educational practices, as well as to influence policy and practice sectors. Educational institutions should prioritize integrating active learning strategies and mentorship programs to combat issues such as student fatigue and boredom. Furthermore, practical opportunities, including experiential learning and IPE activities, should be emphasized to strengthen professional identity and engagement. To address these challenges comprehensively, policymakers should consider developing policies that support effective workload management and community support services, which are essential for improving student well-being and academic performance. Collaboration between educational institutions and practice sectors can greatly improve students' satisfaction with their learning environment and experience. This partnership enhances the relevance and engagement of their education, leading to a stronger professional identity and better preparation for successful careers.

Limitations

As with all research, this study has several limitations. For instance, there was a higher percentage of female participants compared to males; however, it is noteworthy to highlight the demographic composition of QU Health population, where students are majority female. Furthermore, the CHS, which is one of the participating colleges in this study, enrolls only female students. Another limitation is the potentially underpowered statistical comparisons among the sociodemographic characteristics in relation to the total DREEM and MCPIS-9 scores. Thus, the findings of this study should be interpreted with caution.

The findings of this study reveal that QU Health students generally hold a positive view of their learning environment and professional identity, with a significant positive correlation exists between students’ perceptions of their learning environment and their professional identity. Specifically, students who engaged in experiential learning or enrolled in practical programs rated their learning environment more favorably, and those with relatives in the same profession had a more positive view of their professional identity. The participants of this study also identified several key attributes that contribute to a positive learning environment, including active learning approaches and mentorship programs. Furthermore, addressing issues like fatigue and boredom is crucial for enhancing student satisfaction and professional development.

To build on these findings, future research should focus on longitudinal studies that monitor changes in the perceptions of students over time and identify the long-term impact of implementing the proposed attributes of an ideal learning environment on the learning process and professional identity development of students. Additionally, exploring the intricate dynamics of learning environments and their impact on professional identity can allow educators to better support students in their professional journey. Future research should also continue to explore these relationships, particularly on diverse cultural settings, in order to develop more inclusive and effective educational strategies. This approach will ensure that health professional students are well-prepared to meet the demands of their profession and provide high-quality care to their patients.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

United Nations Educational, Scientific, and Cultural Organization

European Union

American Council on Education

World Federation for Medical Education

Communities of Practice

Qatar University Health

College of Health Sciences

College of Pharmacy

College of Medicine

Dental Medicine

College of Nursing

Human Nutrition

Biomedical Science

Public Health

Physiotherapy

Dundee Ready Education Environment Measure

Perception to Learning

Perception to Teachers

Academic Self-Perception

Perception of the Atmosphere

Social Self-Perception

Macleod Clark Professional Identity Scale

Focus Group

InterProfessional Education

Project-Based Learning

Hamad Medical Corporation

Hamad Bin Khalifa Medical City

Artificial Intelligence

Gruppen LD, Irby DM, Durning SJ, Maggio LA. Conceptualizing Learning Environments in the Health Professions. Acad Med. 2019;94(7):969–74.

Article Google Scholar

OECD. Trends Shaping Education 2019. 2019.

Rawas H, Yasmeen N. Perception of nursing students about their educational environment in College of Nursing at King Saud Bin Abdulaziz University for Health Sciences. Saudi Arabia Med Teach. 2019;41(11):1307–14.

Google Scholar

Rusticus SA, Wilson D, Casiro O, Lovato C. Evaluating the Quality of Health Professions Learning Environments: Development and Validation of the Health Education Learning Environment Survey (HELES). Eval Health Prof. 2020;43(3):162–8.

Closs L, Mahat M, Imms W. Learning environments’ influence on students’ learning experience in an Australian Faculty of Business and Economics. Learning Environ Res. 2022;25(1):271–85.

Bakhshialiabad H, Bakhshi G, Hashemi Z, Bakhshi A, Abazari F. Improving students’ learning environment by DREEM: an educational experiment in an Iranian medical sciences university (2011–2016). BMC Med Educ. 2019;19(1):397.

Karani R. Enhancing the Medical School Learning Environment: A Complex Challenge. J Gen Intern Med. 2015;30(9):1235–6.

Adams K, Hean S, Sturgis P, Clark JM. Investigating the factors influencing professional identity of first-year health and social care students. Learn Health Soc Care. 2006;5(2):55–68.

Brown B, Crawford P, Darongkamas J. Blurred roles and permeable boundaries: the experience of multidisciplinary working in community mental health. Health Soc Care Community. 2000;8(6):425–35.

Hendelman W, Byszewski A. Formation of medical student professional identity: categorizing lapses of professionalism, and the learning environment. BMC Med Educ. 2014;14(1):139.

Jarvis-Selinger S, MacNeil KA, Costello GRL, Lee K, Holmes CL. Understanding Professional Identity Formation in Early Clerkship: A Novel Framework. Acad Med. 2019;94(10):1574–80.

Sarraf-Yazdi S, Teo YN, How AEH, Teo YH, Goh S, Kow CS, et al. A Scoping Review of Professional Identity Formation in Undergraduate Medical Education. J Gen Intern Med. 2021;36(11):3511–21.

Lave J, Wenger E. Learning in Doing: Social, cognitive and computational perspectives. Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press; 1991. https://www.cambridge.org/highereducation/books/situatedlearning/6915ABD21C8E4619F750A4D4ACA616CD#overview .

Wenger, E. Communities of practice: Learning, meaning and identity. Cambridge: Cambridge University; 1998.

Eberle J, Stegmann K, Fischer F. Legitimate Peripheral Participation in Communities of Practice: Participation Support Structures for Newcomers in Faculty Student Councils. J Learn Sci. 2014;23(2):216–44.

Graven M, Lerman S, Wenger E. Communities of practice: Learning, meaning and identity. J Math Teacher Educ. 1998;2003(6):185–94.

Brown T, Williams B, Lynch M. The Australian DREEM: evaluating student perceptions of academic learning environments within eight health science courses. Int J Med Educ. 2011;2:94.

International standards in medical education: assessment and accreditation of medical schools'--educational programmes. A WFME position paper. The Executive Council, The World Federation for Medical Education. Med Educ. 1998;32(5):549–58.

Frank JR, Taber S, van Zanten M, Scheele F, Blouin D, on behalf of the International Health Professions Accreditation Outcomes C. The role of accreditation in 21st century health professions education: report of an International Consensus Group. BMC Medical Education. 2020;20(1):305.

Trede F, Macklin R, Bridges D. Professional identity development: A review of the higher education literature. Stud High Educ. 2012;37:365–84.

de Lasson L, Just E, Stegeager N, Malling B. Professional identity formation in the transition from medical school to working life: a qualitative study of group-coaching courses for junior doctors. BMC Med Educ. 2016;16(1):165.

Findyartini A, Greviana N, Felaza E, Faruqi M, Zahratul Afifah T, Auliya FM. Professional identity formation of medical students: A mixed-methods study in a hierarchical and collectivist culture. BMC Med Educ. 2022;22(1):443.

Cruess RL, Cruess SR, Boudreau JD, Snell L, Steinert Y. A schematic representation of the professional identity formation and socialization of medical students and residents: a guide for medical educators. Acad Med. 2015;90(6):718–25.

Prashanth GP, Ismail SK. The Dundee Ready Education Environment Measure: A prospective comparative study of undergraduate medical students’ and interns’ perceptions in Oman. Sultan Qaboos Univ Med J. 2018;18(2):e173–81.

Helou MA, Keiser V, Feldman M, Santen S, Cyrus JW, Ryan MS. Student well-being and the learning environment. Clin Teach. 2019;16(4):362–6.

Brown T, Williams B, McKenna L, Palermo C, McCall L, Roller L, et al. Practice education learning environments: the mismatch between perceived and preferred expectations of undergraduate health science students. Nurse Educ Today. 2011;31(8):e22–8.

Wasson LT, Cusmano A, Meli L, Louh I, Falzon L, Hampsey M, et al. Association Between Learning Environment Interventions and Medical Student Well-being: A Systematic Review. JAMA. 2016;316(21):2237–52.

Aktaş YY, Karabulut N. A Survey on Turkish nursing students’ perception of clinical learning environment and its association with academic motivation and clinical decision making. Nurse Educ Today. 2016;36:124–8.

Enns SC, Perotta B, Paro HB, Gannam S, Peleias M, Mayer FB, et al. Medical Students’ Perception of Their Educational Environment and Quality of Life: Is There a Positive Association? Acad Med. 2016;91(3):409–17.

Rodríguez-García MC, Gutiérrez-Puertas L, Granados-Gámez G, Aguilera-Manrique G, Márquez-Hernández VV. The connection of the clinical learning environment and supervision of nursing students with student satisfaction and future intention to work in clinical placement hospitals. J Clin Nurs. 2021;30(7–8):986–94.

QU Health QU. QU Health Members https://www.qu.edu.qa/sites/en_US/health/members2020 . Accessed 11 May 2024.

QU Health QU. Vision and Mission https://www.qu.edu.qa/sites/en_US/health/2018 . Accessed 11 May 2024.

Schoonenboom J, Johnson RB. How to Construct a Mixed Methods Research Design. Kolner Z Soz Sozpsychol. 2017;69(Suppl 2):107–31.

Almeida F. Strategies to perform a mixed methods study. Eur J Educ Stud. 2018;5(1):137–51. https://doi.org/10.5281/zenodo.1406214 .

Roff S, McAleer S, Harden RM, Al-Qahtani M, Ahmed AU, Deza H, et al. Development and validation of the Dundee ready education environment measure (DREEM). Med Teach. 1997;19(4):295–9.

Woodside AG. Book Review: Handbook of Research Design and Social Measurement. J Mark Res. 1993;30(2):259–63.

Creswell JW, Poth CN. Qualitative Inquiry and Research Design Choosing among Five Approaches. 4th Edition, Thousand Oaks: SAGE Publications, Inc., 2018.

Fetters MD, Curry LA, Creswell JW. Achieving integration in mixed methods designs-principles and practices. Health Serv Res. 2013;48(6 Pt 2):2134–56.

Dunne F, McAleer S, Roff S. Assessment of the undergraduate medical education environment in a large UK medical school. Health Educ J. 2006;65(2):149–58.

Koohpayehzadeh J, Hashemi A, Arabshahi KS, Bigdeli S, Moosavi M, Hatami K, et al. Assessing validity and reliability of Dundee ready educational environment measure (DREEM) in Iran. Med J Islam Repub Iran. 2014;28:60.

Shehnaz SI, Sreedharan J. Students’ perceptions of educational environment in a medical school experiencing curricular transition in United Arab Emirates. Med Teach. 2011;33(1):e37–42.

Zawawi A, Owaiwid L, Alanazi F, Alsogami L, Alageel N, Alassafi M, et al. Using Dundee Ready Educational Environment Measure (DREEM) to evaluate educational environments in Saudi Arabia. Int J Med Develop Countr. 2022;1:1526–33.

McAleer S, Roff S. A practical guide to using the Dundee Ready Education Environment Measure (DREEM). AMEE medical education guide. 2001;23(5):29–33.

Soemantri D, Herrera C, Riquelme A. Measuring the educational environment in health professions studies: a systematic review. Med Teach. 2010;32(12):947–52.

Matthews J, Bialocerkowski A, Molineux M. Professional identity measures for student health professionals–a systematic review of psychometric properties. BMC Med Educ. 2019;19(1):1–10.

Worthington M, Salamonson Y, Weaver R, Cleary M. Predictive validity of the Macleod Clark Professional Identity Scale for undergraduate nursing students. Nurse Educ Today. 2013;33(3):187–91.

Cowin LS, Johnson M, Wilson I, Borgese K. The psychometric properties of five Professional Identity measures in a sample of nursing students. Nurse Educ Today. 2013;33(6):608–13.

Brown R, Condor S, Mathews A, Wade G, Williams J. Explaining intergroup differentiation in an industrial organization. J Occup Psychol. 1986;59(4):273–86.

Proudfoot K. Inductive/Deductive Hybrid Thematic Analysis in Mixed Methods Research. J Mixed Methods Res. 2022;17(3):308–26.

Kossioni A, Varela R, Ekonomu I, Lyrakos G, Dimoliatis I. Students’ perceptions of the educational environment in a Greek Dental School, as measured by DREEM. Eur J Dent Educ. 2012;16(1):e73–8.

Leman M. Conctruct Validity Assessment of Dundee Ready Educational Environment Measurement (Dreem) in a School of Dentistry. Jurnal Pendidikan Kedokteran Indonesia: The Indonesian Journal of Medical Education. 2017;6:11.

Mohd Said N, Rogayah J, Hafizah A. A study of learning environments in the kulliyyah (faculty) of nursing, international islamic university malaysia. Malays J Med Sci. 2009;16(4):15–24.

Ugusman A, Othman NA, Razak ZNA, Soh MM, Faizul PNK, Ibrahim SF. Assessment of learning environment among the first year Malaysian medical students. Journal of Taibah Univ Med Sci. 2015;10(4):454–60.

Zamzuri A, Ali A, Roff S, McAleer S. Students perceptions of the educational environment at dental training college. Malaysian Dent J. 2004;25:15–26.

Ye J-H, Lee Y-S, He Z. The relationship among expectancy belief, course satisfaction, learning effectiveness, and continuance intention in online courses of vocational-technical teachers college students. Front Psychol. 2022;13: 904319.

Ashby SE, Adler J, Herbert L. An exploratory international study into occupational therapy students’ perceptions of professional identity. Aust Occup Ther J. 2016;63(4):233–43.

Al-Tameemi RAN, Johnson C, Gitay R, Abdel-Salam A-SG, Al Hazaa K, BenSaid A, et al. Determinants of poor academic performance among undergraduate students—A systematic literature review. Int J Educ Res Open. 2023;4:100232.

Adeel M, Chaudhry A, Huh S. Physical therapy students’ perceptions of the educational environment at physical therapy institutes in Pakistan. jeehp. 2020;17(0):7–0.

Clarke C, Martin M, Sadlo G, de-Visser R. The development of an authentic professional identity on role-emerging placements. Bri J Occupation Ther. 2014;77(5):222–9.

Hunter AB, Laursen SL, Seymour E. Becoming a scientist: The role of undergraduate research in students’ cognitive, personal, and professional development. Sci Educ. 2007;91(1):36–74.

Bendowska A, Baum E. The significance of cooperation in interdisciplinary health care teams as perceived by polish medical students. Int J Environ Res Public Health. 2023;20(2):954.

Gan Z, An Z, Liu F. Teacher feedback practices, student feedback motivation, and feedback behavior: how are they associated with learning outcomes? Front Psychol. 2021;12: 697045.

Sattar K, Yusoff MSB, Arifin WN, Mohd Yasin MA, Mat Nor MZ. A scoping review on the relationship between mental wellbeing and medical professionalism. Med Educ Online. 2023;28(1):2165892.

Yangdon K, Sherab K, Choezom P, Passang S, Deki S. Well-Being and Academic Workload: Perceptions of Science and Technology Students. Educ Res Reviews. 2021;16(11):418–27.

Hoferichter F, Kulakow S, Raufelder D. How teacher and classmate support relate to students’ stress and academic achievement. Front Psychol. 2022;13: 992497.

Achar Fujii RN, Kobayasi R, Claassen Enns S, Zen Tempski P. Medical Students’ Participation in Extracurricular Activities: Motivations, Contributions, and Barriers. A Qualitative Study. Advances in Medical Education and Practice. 2022;13:1133–41. https://doi.org/10.2147/amep.s359047 .

Magpantay-Monroe ER, Koka O-H, Aipa K. Community Engagement Leads to Professional Identity Formation of Nursing Students. Asian/Pacific Island Nurs J. 2020;5(3):181.

Zhou F, Sang A, Zhou Q, Wang QQ, Fan Y, Ma S. The impact of an integrated PBL curriculum on clinical thinking in undergraduate medical students prior to clinical practice. BMC Med Educ. 2023;23(1):460.

Du X, Al Khabuli JOS, Ba Hattab RAS, Daud A, Philip NI, Anweigi L, et al. Development of professional identity among dental students - A qualitative study. J Dent Educ. 2023;87(1):93–100.

Zulu BM, du Plessis E, Koen MP. Experiences of nursing students regarding clinical placement and support in primary healthcare clinics: Strengthening resilience. Health SA Gesondheid. 2021;26:1–11. https://doi.org/10.4102/hsag.v26i0.1615 .

McNally G, Haque E, Sharp S, Thampy H. Teaching empathy to medical students. Clin Teach. 2023;20(1): e13557.

Randhawa GK, Jackson M. The role of artificial intelligence in learning and professional development for healthcare professionals. Healthc Manage Forum. 2019;33(1):19–24.

Cooper AZ, Simpson D, Nordquist J. Optimizing the Physical Clinical Learning Environment for Teaching. J Grad Med Educ. 2020;12(2):221–2.

Gad SE-S, Noor W, Kamar M. How Does The Interior Design of Learning Spaces Impact The Students` Health, Behavior, and Performance? J Eng Res. 2022;6(4):74–87.

Haleem A, Javaid M, Qadri MA, Suman R. Understanding the role of digital technologies in education: A review. Sustain Operation Comput. 2022;3:275–85.

Faihs V, Heininger S, McLennan, S. et al. Professional Identity and Motivation for Medical School in First-Year Medical Students: A Cross-sectional Study. Med Sci Educ. 2023;33:431–41. https://doi.org/10.1007/s40670-023-01754-7 .

Johnston T, Bilton N. Investigating paramedic student professional identity. Australasian J Paramed. 2020;17:1–8.

Mumena WA, Alsharif BA, Bakhsh AM, Mahallawi WH. Exploring professional identity and its predictors in health profession students and healthcare practitioners in Saudi Arabia. PLoS ONE. 2024;19(5): e0299356.

Kis V. Quality assurance in tertiary education: Current practices in OECD countries and a literature review on potential effects. Tertiary Review: A contribution to the OECD thematic review of tertiary education. 2005;14(9):1–47.

Kolb D. Experiential learning as the science of learning and development. Englewood Cliffs, NJ: Prentice Hall; 1984.

Dannan A. The Effect of a Simple Reward Model on the Academic Achievement of Syrian Dental Students. International Journal of Educational Research Review. 2020;5(4):308–14.

Guhan N, Krishnan P, Dharshini P, Abraham P, Thomas S. The effect of mentorship program in enhancing the academic performance of first MBBS students. J Adv Med Educ Prof. 2020;8(4):196–9.

Rohana K, Zainal N, Mohd Aminuddin Z, Jusoff K. The Quality of Learning Environment and Academic Performance from a Student’s Perception. Int J Business Manag. 2009;4:171–5.

Download references

Acknowledgements

The authors would like to thank all students who participated in this study.

This work was supported by the Qatar University Internal Collaborative Grant: QUCG-CPH-22/23–565.

Author information

Authors and affiliations.

Department of Clinical Pharmacy and Practice, College of Pharmacy, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar

Banan Mukhalalati, Aaliah Aly, Ola Yakti, Sara Elshami, Ahmed Awaisu, Alla El-Awaisi & Derek Stewart

College of Dental Medicine, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar

College of Health Sciences, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar

Ahsan Sethi

College of Medicine, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar

Marwan Farouk Abu-Hijleh

Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada

Zubin Austin

You can also search for this author in PubMed Google Scholar

Contributions

Study conception and design: BM, and SE; data collection: BM, OY, AA, and AD; analysis and interpretation of results: all authors; draft manuscript preparation: all authors. All authors reviewed the results and approved the final version of the manuscript.

Corresponding author

Correspondence to Banan Mukhalalati .

Ethics declarations

Ethics approval and consent to participate.

The data of human participants in this study were conducted in accordance with the Helsinki Declaration. Ethical approval for the study was obtained from the Qatar University Institutional Review Board (approval number: QU-IRB 1734-EA/22). All participants provided informed consent prior to participation.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary material 1, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Mukhalalati, B., Aly, A., Yakti, O. et al. Examining the perception of undergraduate health professional students of their learning environment, learning experience and professional identity development: a mixed-methods study. BMC Med Educ 24 , 886 (2024). https://doi.org/10.1186/s12909-024-05875-4

Download citation

Received : 03 July 2024

Accepted : 08 August 2024

Published : 16 August 2024

DOI : https://doi.org/10.1186/s12909-024-05875-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Learning Environment
Professional Identity
Healthcare Professions Education
Gruppen et al. Framework

BMC Medical Education

ISSN: 1472-6920

General enquiries: [email protected]

Open access
Published: 20 August 2024

An evaluation of a multi-partner approach to increase routine immunization coverage in six northern Nigerian States

Leanne Dougherty ORCID: orcid.org/0000-0002-5702-9328 1 , 2 ,
Mayokun Adediran 1 ,
Akinwumi Akinola 1 ,
Matthew Alabi 1 ,
Eno-Obong Etim 1 ,
Jane Ohioghame 1 &
Adebola Adedimeji 1

BMC Health Services Research volume 24 , Article number: 951 ( 2024 ) Cite this article

46 Accesses

Metrics details

Global health partnerships are increasingly being used to improve coordination, strengthen health systems, and incentivize government commitment for public health programs. From 2012 to 2022, the Bill & Melinda Gates Foundation (BMGF) and Aliko Dangote Foundation (ADF) forged Memorandum of Understanding (MoU) partnership agreements with six northern state governments to strengthen routine immunization (RI) systems and sustainably increase immunization coverage. This mixed methods evaluation describes the RI MoUs contribution to improving program performance, strengthening capacity and government financial commitment as well as towards increasing immunization coverage.

Drawing from stakeholder interviews and a desk review, we describe the MoU inputs and processes and adherence to design. We assess the extent to which the program achieved its objectives as well as the benefits and challenges by drawing from a health facility assessment, client exit interview and qualitative interviews with service providers, community leaders and program participants. Finally, we assess the overall impact of the MoU by evaluating trends in immunization coverage rates.

We found the RI MoUs across the six states to be mostly successful in strengthening health systems, improving accountability and coordination, and increasing the utilization of services and financing for RI. Across all six states, pentavalent 3 vaccine coverage increased from 2011 to 2021 and in some states, the gains were substantial. For example, in Yobe, vaccination coverage increased from 10% in 2011 to nearly 60% in 2021. However, in Sokoto, the change was minimal increasing from only 4% in 2011 to nearly 8% in 2021. However, evaluation findings indicate that issues pertaining to human resources for health, insecurity that inhibits supportive supervision and vaccine logistics as well as harmful socio-cultural norms remain a persistent challenge in the states. There is also a need for a rigorous monitoring and evaluation plan with well-defined measures collected prior to and throughout implementation.

Introducing a multi-partner approach grounded in a MoU agreement provides a promising approach to addressing health system challenges that confront RI programs.

Peer Review reports

Introduction

Routine Immunization (RI) is the backbone of all national immunization programs and disease control efforts. The Government of Nigeria has faced persistent challenges in addressing low immunization coverage rates in the northern region. According to the 2015 National Nutrition and Health Surveys, children receiving the pentavalent vaccine in six northern states ranged from 4% in Sokoto to 33% in Kaduna [ 1 ]. Between 2008 and 2018, Demographic and Health Surveys (DHS) reported that the country’s RI coverage had stagnated nationally and deteriorated in the northern regions. The 2018 DHS estimated full immunization coverage to be only 31% nationally, and 20–23% in the northwestern and northeastern regions respectively [ 2 ]. These low coverage rates have been driven by several challenges such as, shortage of vaccines and supplies, poor community engagement, weak human resource system and harmonization of stakeholder efforts, inadequate ownership; systemic bottlenecks including sub-optimal funding by many state governments; weak cold-chain and vaccine logistics systems; and ineffective supportive supervision [ 3 , 4 , 5 , 6 ]. In the northern states specifically, the RI program and polio eradication campaign have faced historical boycotts at the local level driven by rumors (e.g., vaccinations causes HIV or sterility in young Muslim girls) and amplified by the political context [ 7 ]. One significant determinant of the poor performance and underlying restraints included a need for political commitment and accountability that contributed to weak financial support [ 8 ]. While the government and several development partners have deployed significant resources to improve RI coverage in Nigeria, the results often fell short of expectations due to weak harmonization of stakeholder efforts [ 9 ].

Over the last twenty years, global health partnerships have emerged as an important resource for health system strengthening and addressing public health challenges [ 10 , 11 , 12 ]. These partnerships bring together two or more organizations toward a common goal and often engage in advocacy, provide financing, and support technical or capacity strengthening efforts [ 13 ]. Previous studies have identified a number of benefits from these partnerships including increased coordination, reduced duplication of investments and activities, knowledge sharing and increased funding due to the establishment of a common platform that gains legitimacy and support [ 14 , 15 ]. Despite these benefits, a number of criticisms have also been made about global health partnerships, including that they impose external priorities through the introduction of vertical disease programs that distract countries from focusing on health system strengthening, limit stakeholders’ voices in decision making, provide insufficient resources, and promote poor governance practices [ 16 , 17 , 18 ].

Intervention description

In response to the challenges with the routine immunization program in northern Nigeria, the Bill & Melinda Gates Foundation (BMGF) and Aliko Dangote Foundation (ADF) forged a partnership with six northern state governments (Bauchi, Borno, Kaduna, Kano, Sokoto and Yobe) in a multi-year Memorandum of Understanding (MoU) partnership that aimed to strengthen RI systems and sustainably increase its immunization coverage. Unlike previous global health partnerships that operated in multiple countries or at a national level, these RI MoUs created six state-level public-private platforms on which to establish sustainable financing for RI, improve partner coordination and accountability, strengthen RI systems and, ultimately, increase vaccination coverage. Ultimately, the MoU aimed to increase vaccination coverage for DPT3 to 80% by the end of the agreement which, is the immunization coverage rate needed to achieve herd immunity to prevent the spread of the poliovirus. The first partnership in collaboration with the Kano state government was introduced in 2012 and later expanded between 2014 and 2016, as the governments of Bauchi, Borno, Yobe, Kaduna, and Sokoto states negotiated and signed RI MoUs with the foundations. The United States Agency for International Development (USAID) joined as a technical partner in Bauchi and Sokoto states. An important component of the RI MoU was the establishment of state managed RI program bank accounts (referred to as basket funds) whereby partners could contribute to the program. BMGF also provided technical assistance through its local partners, Solina Health, Chigari Foundation, and others. Key resources and sample documents for the MoU approach including a sample MoU, workplan and costing model are publicly available [ 19 ].

RI MoU logic model

The MoU approach was developed with the primary outcome of increasing immunization coverage in six northern states of Nigeria by improving program performance and increasing capacity of the State Primary Health Care Development Agency (SPHCDA) and its staff to manage the program. To achieve these outcomes, inputs, as shown in Fig. 1 , were focused on (a) the creation of a basket fund where resources from donors and government could be pooled together in a regressive funding model (i.e. BMGF and ADF contributed approximately 70% of RI program funds in the first year and then the proportion of funding declined each year as the state increased their contribution to fully fund the program by the end of the agreement), (b) establishment of meetings with key stakeholders and government officials to ensure high level government engagement, and (c) provision of technical assistance to support implementation of the program. The inputs aimed to facilitate processes related to governance, financial management, vaccine supply chain, service delivery, and monitoring and evaluation and community engagement that would ultimately improve (1) coordination and management, (2) financial accountability and transparency, (3) vaccine availability, (4) equitable access to quality services, (5) availability of quality administrative data for action, and (6) demand for RI services.

The RI MoU logic model

While there is some evidence on the benefits and challenges in implementing institutional health partnerships, there is limited evidence on their effectiveness [ 20 ]. In this paper, we contribute to the existing evidence base to evaluate the RI MoU partnership. We describe the extent to which the MoU was successful in achieving the desired objectives outlined in the RI MoU logic model and describe governments, donors and other stakeholders adherence to their financial commitments.

Materials and methods

Study setting.

The MoU approach was implemented at the state, local government area (LGA) (i.e. an administrative subdivision of the state government) and health facility levels in six northern states. Population size across the six states ranges from approximately 13 million in Kano to three million in Yobe [ 21 ]. Several states (i.e., Borno, Kaduna and Sokoto) experienced insecurity during implementation.

Study design

We conducted a mixed methods study to evaluate the effectiveness of the RI MoU approach in the six northern states. The rationale for the study approach was to (1) strengthen the level of inference for key findings by triangulating multiple data sources given the lack of baseline and comparison data values and; (2) provide a holistic understanding by capturing perspectives from multiple levels (e.g. participants, service providers, community structures, partners, donors and government). The evaluation was commissioned by the BMGF and conducted by the Population Council; an organization external to the MoU approach. First, to describe the MoU inputs and processes and adherence to design, the study team reviewed existing program documents through a desk review and conducted Key Informant (KI) interviews with stakeholders and state program implementers. Second, the study team conducted a quantitative health facility assessment and client exit interview and qualitative interviews with service providers, community leaders and program participants to assess the extent to which the approach achieved the objectives outlined in the RI MoU logic model and to understand the benefits and challenges of the approach. Finally, to assess the overall impact of the MoU in achieving program outcomes, we assessed data from household surveys and the District Health Information System 2 (DHIS2). The household survey data provided an objective assessment of RI program performance while the DHIS2 figures informed how well the system monitored and evaluated program performance. A summary of measures based on programmatic outputs and outcomes is described in Table 1 .

Desk review

Documents included in the desk review addressed all stages of the MoU design, start-up, and implementation. To inform analysis on the design of the MoU, the team reviewed the diagnostic reports, MoU agreements and case studies. To assess fidelity to implementation design, the team reviewed MoU related meeting summaries and presentations, workplans and strategies such as the community engagement strategy. To assess the extent to which the MoU achieved its objectives, the team reviewed findings from the national Primary Healthcare Under One Roof (PHCUOR) Implementation Scorecard, state financial management trackers, vaccine dashboards, routine immunization supportive supervision (RISS) monitoring, DHIS2 data to review fixed and outreach session completion, and AFeNET variance assessments between survey and administrative data. And, to assess impact of the MoU approach, the team reviewed National Indicator Cluster Survey/ Multiple indicator cluster survey (NICS/MICS) data from 2011, 2016, and 2021 to assess the proportion of children 12–23 months who received the pentavalent 3 vaccine.

Quantitative data

A health facility assessment of Primary Health Centers (PHC) was conducted in March-April 2022 in selected local LGAs of the six implementation states (Supplementary file 1). We used a two-stage stratified sampling procedure in selecting health facilities. We generated a list of all the LGAs in each of the three senatorial districts and selected 50% of the total number of LGAs in each state with the exception of Borno and Kaduna due to security concerns as described in Table 2 and shown in Fig. 2 . In Borno, the study team selected five LGA’s and oversampled health facilities within a secured area around the capital of Borno instead of the 14 LGAs as planned. In Kaduna, four LGAs near the capital of Kaduna were over sampled to replace LGAs in the western part of the state which could not be accessed due to security concerns. In each of the LGAs, approximately two PHCs were randomly selected. The targeted number of health facilities across all the LGAs was 156, at two health facilities per LGA. A total of 163 Health Facility Assessments (HFA) were conducted across all six MoU states. The additional seven health facilities were because of oversampling in Borno state due to the inability to access some LGAs because of security reasons. Client Exit Interviews (CEI) ( N = 1,093) were conducted in the sampled health facilities to assess client satisfaction with RI services provided (Supplementary file 2). The study team interviewed on average 3–7 clients per facility except for in Yobe where immunization days were taking place resulting in a higher volume of clients referred for interviews. Clients were selected to participate in exit interviews if they were a primary caregiver (at least 18 years or older) of a child under the age of two years, accessing vaccination service.

Map of Nigeria and study sites

Qualitative data

The qualitative data was collected in three separate data gathering activities between March and June, 2022. We conducted KI interviews with BMGF staff, government stakeholders, and implementers on the program model, execution, impact, and opportunities to be leveraged for future programs (Supplementary file 6). Second, In-depth Interviews (IDIs) with health workers were conducted to assess the extent to which the MoU achieved its objectives including benefits and challenges and lessons learned from the health worker perspective (Supplementary file 5). Lastly, Focus Group Discussions (FGDs) were conducted with community leaders (e.g. traditional, religious leaders) and program participants to assess benefits and challenges of the MoU and lessons learned from the community and program participants’ perspective (Supplementary files 3 and 4). KIs lasted approximately two hours while IDIs lasted approximately one hour in duration, both were conducted in English. FGDs lasted approximately 1–1.5 h in duration and were conducted in Hausa. Table 3 provides a summary of the interviews conducted by qualitative method and study respondent.

For the quantitative data sources, we computed counts with percentages for categorical variables and medians with standard deviations for continuous variables. Data cleaning and analysis were performed using Stata version 14 software. For all of the qualitative data sources, the study team determined deductive codes prior to analysis based on the RI MoU logic model which draws from the World Health Organization health systems building blocks framework [ 22 ] and then generated subcodes inductively by reviewing transcripts line by line. Inconsistencies and questions that arose during coding were discussed through reoccurring meetings and resolved by consensus as a team to ensure inter-rater reliability. Sub-codes were further grouped during analysis to address research questions which included lessons learned, areas of improvement, recommendations, what worked well and what did not work well and sustainability. Additional codes were generated for the KIs conducted with national and international respondents and covered areas related to design, implementation, and transition. Codes for all of the qualitative data were analyzed thematically by state.

Study team members were responsible for managing specific data sources from data collection through analysis and used a convergence model of triangulation to bring together the complementary data sources during an analysis workshop conducted in June 2022. Study authors attended the analysis workshop. The objective of the workshop was to provide team members leading specific aspects of the study (e.g., qualitative interviews, desk reviews and quantitative surveys) an opportunity to present their respective findings by evaluation question and to discuss how each data source responded to the study questions and contributed to the overall evaluation findings.

The workshop was followed by regularly scheduled meetings where the team came together to discuss how each source responded to the study questions. We compared findings on similar topics and identified where different data sources worked to explain pathways outlined in the RI MoU logic model [ 23 ].

Ethical approval

The study received approval from the Population Council Institutional Review Board (Protocol number 992). In Nigeria, ethical approval to conduct the study was obtained at national and state levels. At the national level, approval was granted by the National Health Research Ethics Committee with approval number NHREC/01/01/2007-17/01/2022. At the state level, ethics applications were submitted, and approval obtained from individual State Health and Research Ethics Committee before the commencement of field activity. Bauchi (NREC/03/11/19B/2021/10); Borno (073/2021); Kaduna (MOH/ADM/744/VOL.1/1171); Kano (SHREC/2022/3078); Sokoto (SKHREC/016/2022) and Yobe (MOH/GEN/747). The relevant ethical approval and consent details were received and are available on request by the editor or editorial office. Study participants provided informed consent by using their signature. In addition, all methods were carried out in accordance with relevant guidelines and regulations and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

We present findings for each output considered in the RI MoU logic model specifically related to governance, financial management, vaccine supply chain, service delivery, and monitoring and evaluation and community engagement. Next, we consider outcome measures including the extent to which each partner met their financial contribution to the RI MoU and an assessment of immunization coverage rates over the period of implementation. A summary of the RI MoU performance measures by state is presented in Table 4 .

Governance: improved program coordination and management

The PHCUOR policy, enacted in June 2014 and considered a precondition for the MoU, called for states to consolidate planning and management around all PHC services and resources “under one roof,” the SPHCDA. The RI MoU aimed to support improved program coordination and management by encouraging adoption and implementation of the PHCUOR and its principles including the establishment of one annual workplan supported by the basket fund and one coordinating mechanism. The PHCUOR scorecard provides evidence of the state’s average performance across the nine PHCUOR pillars as shown in Table 4 under Governance. The nine pillars assessed governance and ownership, legislation, adoption of a minimum service package, repositioning, system development, operational guidelines, human resources, funding sources and structure and office setup. All six state governments improved their overall performance from 2015 to 2019 with a percentage point increase ranging from 19 to 51%.

The RI MoU also supported the establishment of functional thematic area working groups led by government employees with defined membership and clear terms of reference. The working groups addressed specific areas that needed strengthening, including finance, community engagement/social mobilization, monitoring and evaluation/supportive supervision, logistics, and training. This structure strengthened government ownership of the program contributing to strong political will for RI funding and creating partnerships to support program delivery.

“Although it took time for everyone to come together and put it into one single workplan , but it has helped us to be operating as a single team. The spirit of teamwork was strengthened and visibility. So , even a new partner that comes , will have to now look at it and see where does your work key into this… So , [there is] integration in Yobe and [a] single work plan.” Government stakeholder , KI , Yobe .

However, several challenges contributed to some delays in implementation including competing priorities between the national and state government as well as state government and partners.

“The challenge sometimes is the approach from the partners. Sometimes what we want to do or intend to do is different from what the partners want us to do. although it is our own decision. We talked about this ownership , but sometimes this doesn’t exist when you look at it deeply. This is a challenge , really.” Government stakeholder , KI , Borno .

In addition, political differences and interference in program implementation remains a challenge.

“A politician … will just come and tell you , ‘Sir , appoint so person.’… If you didn’t appoint him then he will go back to the community and sabotage all your effort. And if you appoint him he may not be able to do the work you assign him to.” Government stakeholder , KI Sokoto .

Financial Management: improved financial accountability and transparency across all levels

The RI MoU instituted several processes to improve financial accountability and transparency across all levels of the health system. These processes included (1) instituting the no-objection process for program spending which stipulates that the state must seek approval from the MoU signatories to spend funds above a specified threshold; (2) instituting direct disbursements of program funds to end users through dedicated RI accounts and development of predefined disbursement schedules; (3) ensuring prompt retirement and submission, analysis and validation of funds; (4) instituting a system for recouping unspent/unretired MoU funds; and (5) conducting internal and external audits.

With the introduction of the MoU, bank accounts were opened at the state, LGA, and health facility level and the quarterly release and direct disbursement of funds was initiated. After the introduction of the MoU, the percentage of health facilities assessed which reported that funds were disbursed from state to health facility bank accounts at least quarterly ranged from 67% in Kaduna to 92% in Sokoto as shown in Table 4 under Financial management. Diagnostic reports conducted to inform the MoU design found that prior to the RI MoU funds disbursed were not regularly accounted for, and financial audits were not conducted on a regular basis. The MoU introduced financial management procedures including internal and external audits and aimed for all facilities to participate in a financial audit each year. As a result, the percentage of facilities assessed reported completing an audit in the 12 months preceding the assessment ranged from 50% in Sokoto to 94% in Yobe.

MoU partners considered the establishment of the basket fund to pool resources an effective mechanism that supported program coordination by eliminating multiple implementation silos and reducing duplication.

“Having the funds in one basket has made it very nice… You have one channel of getting the resources , one channel again to implement all the programs…. unlike other ones when everybody is running his own parallel programs.” Government stakeholder , KI Kaduna .

Through the introduction of the new MoU financial systems and processes, stakeholders also reflected on improved financial accountability and transparency.

“We have introduced electronic digital financial tracking tool to ensure financial accountability , because you give people money to conduct an activity , if they don’t conduct the activity , they need to refund it. So , the executive secretary has made that every activity that has not been reported or that has been confirmed not to be conducted , the money must be refunded , and we have a lot of cases where people are refunding the money.” –Government stakeholder , KI , Yobe .

However, some challenges still exist in the release of partners funds to support activities in the workplan due to conflicting fiscal years which has resulted in delays including quarterly disbursement from state to health facility bank accounts.

“Although there are clear guidelines on how this funding should come but sometimes there is delay in the release of the funds. You have a beautiful plan , and it is time bound. You need to do this in January , you need to do 1 , 2 , 3 , activities in the first week of February and the activities are costed and time bound. If the funds are not available as at when due , the activities may not take place.” Government stakeholder , KI Kano .

Vaccine supply Chain: availability of sufficient, potent vaccines at all service delivery points

The RI MoU implemented several measures aimed to redesign and institutionalize a Direct Vaccine Delivery system to ensure last mile delivery of vaccines. This included setting up stock data management systems to ensure visibility into stock data and procuring, installing, and routinely maintaining solar cold chain equipment (CCE) across all wards.

Prior to the MoU, there were routine stock outs and the diagnostic reports found that the method used to forecast vaccines which was based on target population and coverage was underestimating potential demand because LGAs were running out of stock by the end of the month. Following introduction of the MoU, the proportion of all antigens below the minimum level of adequate stock or stocked out at the apex health facilities ranged from 32% in Sokoto to 41% in Kano and Yobe in 2021 as shown in Table 4 under Vaccine supply chain. Several service providers noted that improved stock management further strengthened the state’s ability to make available sufficient, potent vaccines at all service delivery points.

“I told you that we used to plan for how many vaccines we want , right? So , if … I didn’t plan for it , I didn’t know how many vaccines , how many doses of vaccines do I need… people will come waiting for me and at the end of the day I will say I didn’t have the vaccine or the vaccine has finished…There is one key form that we use to fill; that one you’ll fill it based on your vaccine consumption… They will not … just give me [vaccines] off head [without vaccine use data].” - Service provider , IDI , Kano .

Adequate CCE was also procured through the MoU to ensure a more consistent supply of appropriately stored vaccines and fewer stockouts. The percentage of wards with functional cold chain equipment according to government managed vaccine dashboards increased across all six states. For example, in Bauchi, the percentage of wards with functional cold chain equipment was 96% in Bauchi in 2021 up from 28% in 2014–2015 at the time of MoU diagnostic assessments. Similarly, the percentage of wards with functional cold chain equipment was 93% in Sokoto in 2021 up from 29% in 2014–2015.

The increased availability of functional solar drives and other CCE strengthened the states’ ability to make available sufficient, potent vaccines at all service delivery points, as well as the use of third-party vendors for vaccine delivery in some states.

“In every ward , we also have cold chain equipment. It’s also maintained by solar so there will be no wahala (problem) … We can keep [vaccines] at the local government level or at the facility level… if you go to anyone , they all have solar for maintenance of all our vaccines.” Government stakeholder , KI Bauchi .

Initially, a push system for direct delivery of vaccines was introduced to apex health facilities through a private distributor to improve the reliability of vaccine delivery. With this approach, vaccines were distributed to bigger PHCs with Solar direct drive (apex facilities) in the community, from which smaller facilities or those without CCE – which rely on apex facilities for weekly vaccine supplies - may “pull” their supply. This eliminated high costs and long travel for personnel, as well as concerns about dangers associated with travel to collect vaccines. In Borno and Kaduna states, direct vaccine delivery through a third-party vendor alleviated pre-MoU challenges. However, in other states such as Bauchi, the government realized they had the capacity and means to effectively deliver vaccines and did not need to rely on a third-party distributor which was more expensive. In the end, facility readiness for CCE due to inadequate refurbishment by government, or theft, vandalism, or destruction of installed CCE, led most states to pursue a hybrid push-pull system for vaccine delivery despite initial focus on push system to apex facilities.

“Previously , there were transportation issues around how we went to get the vaccines from the state’s cold chain officer… But presently it is easier because it is directly delivered by the vendors… making the routine immunization easier for us.” Service provider , IDI , Borno .

However, insecurity, poor terrain, delays from the national level in vaccine delivery, and insufficient resources continued to pose problems in the timely delivery of vaccines to service delivery points.

“During the rainy season , there are some areas you cannot go. We have hard to reach areas , no matter whatever the strategy you apply , you cannot get to that place. So , it’s a serious challenge.” Government stakeholder , KI Bauchi .

Service delivery: improved equitable access to quality immunization services for all eligible children

The RI MoU aimed to improve the equitable access to quality immunization services for all eligible children by fully scaling up service availability across all health facilities in the state; developing and updating comprehensive health facility reaching every ward (REW) microplans and session plans and funding and monitoring implementation of fixed and outreach sessions and supportive supervisory visits to health facilities. The investments contributed to high levels of planned fixed and outreach sessions conducted between 2017 and 2020 (data not shown). For example, planned supportive supervision visits that were conducted also increased in Kaduna from 55% in 2018 to 82% in 2020 as observed in the RI supportive supervision dashboard. Increases in planned supportive supervision visits conducted in Yobe also increased from 70% in 2018 to 84% in 2020.

The RI MOU also aimed to improve the quality of immunization services provided. Client exit interviews assessed the quality of provider-client interactions by asking if providers provided information on four important RI counseling points. In three states (Bauchi, Kaduna, and Sokoto), the percentage of clients who said providers shared information on the four RI counseling was over 85% as shown in Table 4 under service delivery. However, more variation was observed in Borno where the percentage of clients who said providers shared information on the four RI counseling was less than 70% for three of the four components.

Monitoring and Evaluation: Improved availability and use of complete and quality administrative data for action

The RI MoU worked to institutionalize the use of DHIS2 as the primary source of administrative data by providing tools to ensure timeliness and completeness of reporting. Additional efforts included instituting data quality interventions to improve the integrity of the data and establishing platforms for data review, feedback, and continuous monitoring.

Evidence of improvements in data quality was identified in Bauchi where the variance between survey and administrative immunization coverage rates declined from 67% in 2017 for pentavalent 3 to 59% in 2020 as shown in Table 4 under Monitoring and evaluation. Similar trends were observed in other states such as Kaduna where the variance declined from 72% in 2017 for pentavalent 3 to 38% in 2020. The establishment of frequent data review meetings has contributed to the improvements in data quality as well as digitized supportive supervision improved monitoring efforts.

“What worked well is that we’ve already digitalized our supervision because they are in the same group. Now we are using digital devices to do supervision , it’s faster , easier and it has the coordinates , unlike before where somebody will sit down on his bed and fill a form that he has gone to supervision. Now when you send our report it will show the coordinates where you sent [it from]. – Government stakeholder , KI Kano.

Despite these improvements, challenges remain with data reporting including falsification of monitoring data as described by one government stakeholder, an overburdened workforce, and issues with security.

“The challenges we are facing is that health workers are … overstretched with a lot of activities. And they tend to see the data reporting as not important as the rendering of the services. So…in reporting , they tend to be negligent in some of the activities.” Government stakeholder , KI Yobe.

Community Engagement: improved community demand for routine immunization services

The RI MoU aimed to improve community demand for RI services by implementing a name-based community engagement strategy including identification and tracking of all eligible children led by a traditional system. All states adopted the use of line listing for newborn, as well as defaulter tracking to improve community use of vaccination services. States worked with community actors (Mai Unguwas) and created defined roles and plans to support the work. This engagement with community actors was seen as an important contribution to the RI program.

“We used to call the community stakeholders , telling them the importance of immunization , and we use to tell them the importance of their participation for these services. So that helps us a lot. They used to go for community mobilization. They are having meeting within themselves to mobilize their people that they should come and take this vaccine because the vaccine is very important.” Service provider , IDI Bauchi.

Based on client exit interviews, mothers are not the primary decision maker regarding the child’s vaccination status in a number of states. For example, in Kano, 62% of fathers are the primary decision makers regarding whether the child goes for vaccinations as shown in Table 4 under community engagement. This challenge was reflected in the qualitative interviews, where a program participant noted that women cannot access services without the husband’s approval.

“The woman cannot do anything about [service uptake] if her husband is against it.” Program participant , FGD Bauchi .

However, there is some evidence that religious leaders are engaging with both men and women to encourage the use of vaccination services.

“We both know we’re in the North. I mean not just even in the North , Nigeria as a whole , we tend to really listen to our religious and traditional leaders… Carrying along those institutions that we knew that could have some influence on the people was also something that went well.” Partner , KI Kaduna .

While community leaders played an important role, the lack of incentives for community volunteers and influencers resulted in poor motivation to conduct activities.

“They [volunteers] are not on a pay roll. And you know the economic situation in…not only the state , in the country… Some are still volunteering to do the job , but some are saying since there is no pay , we are not continuing.” Government stakeholder , KI Kaduna .

This is further supported with qualitative evidence where spousal refusal from poor sensitization on adverse events following immunization, contributed to vaccine hesitancy and refusal.

“The children get fever when we return. When he [husband] asked why and I told him that I collected an injection for them , he asked why? I should not go again; that on the quest of getting drugs for catarrh , I have brought something new [and more serious] upon him.” Non-beneficiary , FGD Borno .

Improved Financing for RI

The MoU approach was developed with the goal of creating sustained financing for the RI program. We assessed MoU funds contributed between 2013 and 2022 by contributor. Overall, BMGF and ADF paid the full amount of their committed funds over the course of the MoU period for all six states. However, each state made varied progress towards their commitment of assuming the full program costs as shown in Table 5 . Bauchi state paid $3.8 million of the $6.5 million U.S. Dollar (USD) committed from 2015 to 2018 while Kaduna state paid $3.5 million of the $4.6 million USD committed from 2016 to 2021. Kano paid $7.8 million of the $12.5 million USD committed from 2013 to 2021 while Yobe paid $2.8 million of the $4 million USD committed from 2016 to 2021. Borno paid $1.8 million of the $2.6 million USD committed while Sokoto paid $2.6 million of the $3.8 million USD committed both from 2016 to 2021.

Improved capacity of the SPHCDA and its staff to manage the RI program efficiently and independently and with clear accountability

The MoU aimed to improve the capacity of the SPHCDA and its staff to manage the RI program. Management capacity to implement the MoU was built through trainings and learning visits to Kano. Cascade trainings were implemented and built capacity to deliver RI services, manage cold chain, improve monitoring and evaluation, etc. and, the Basic Guide for RI Service Providers was introduced and used to train staff and serve as a reference document.

The HFA found that in most states, the National Primary Health Care Development Agency (NPHCDA) minimum standard number of at least two community health officers (CHO) and five community health extension workers (CHEWs) were not available. For example, in Bauchi, there was a median of two CHOs at the facility and there were no full-time nurses or midwife assigned to the facility as shown in Table 4 under Staff capacity. Community health worker motivation was another challenge reflected through the qualitative interviews.

“The challenge is that they need some incentives , then some support either financially or what have you , most especially those volunteers. They are not having salaries; their work is voluntary. So sometimes , they may demand some assistance , and we use to take it into consideration , but the authority concerned cannot do it.” Service provider , IDI Bauchi .

However, efforts to improve health worker performance through appraisals, rewards, and annual recognitions was seen as a promising approach.

Outside urban areas, insufficient numbers of skilled health workers to meet rising demand for services, and dwindling state resources to hire health workers and pay their salaries was mentioned as a challenge.

“There [are] dwindling resources to employ. Even when you want to employ the satisfactory number of health workers into the facilities…sometimes their salaries and wages is something …we’ve been having these challenges of resources.” Government stakeholder , KI Kaduna .

Sustained increase in immunization coverage

The MoU approach was developed with the primary outcome of increasing immunization coverage. Figure 3 presents the proportion of children 12–23 months who were fully vaccinated. Across all six states, vaccination coverage increased from 2011 to 2021. In some states, the gains were substantial. For example, in Yobe, vaccination coverage increased from 10% in 2011 to nearly 60% in 2021. However, in Sokoto, the change was minimal increasing from only 4% in 2011 to nearly 8% in 2021.

Proportion of children 12–23 months who fully vaccinated by MoU State, 2011, 2016, 2021

This evaluation explains the extent to which the RI MoU contributed to improved program performance including increased immunization coverage through strengthened health system capacity and increased government financial commitment across six states in northern Nigeria. Our findings, organized by RI MoU logic model, contribute to the growing body of literature exploring how global health partnerships can be used to strengthen public health programs. Drawing from multiple data sources over the course of implementation, we assessed measures of program performance and identified benefits and challenges associated with implementation.

Several notable achievements associated with RI MoU investments were observed. First, we found the RI MoU was successful in instituting mechanisms that improved coordination across partners and increased government ownership of decisions which was consistent with previous research [ 24 ]. There was also evidence from the PHCUOR scorecard assessment of progress in addressing the PHCUOR pillars. However, state governments addressed specific pillars to varying degrees which may be consistent with previous findings that state governments are more interested in executing aspects of the PHCUOR that are easy to achieve rather than address the more challenging human resource management and funding requirements [ 25 , 26 ]. The RI MoU was also successful in improving financial accountability and transparency. Previous research has found a lack of accountability and widespread corruption to be a barrier to high RI program performance in Nigeria [ 27 , 28 ]. However, evaluation findings found evidence that investments led to improvements in accountability and transparency because of the introduction of electronic mechanisms for validating expenditures as well as establishing routine audits. The significant investment in upgrading the vaccine supply chain including the procurement of solar refrigerators and direct to facility deliveries of vaccine supplies has also contributed to a reduction in stock out rates [ 29 ]. However, insecurity remains a challenge in some areas resulting in the destruction of installed CCE in some wards and more effort is required to work directly with community leaders to protect installed CCE.

RI MoU states showed improvement in vaccination coverage rates from 2011. However, there was variation between states suggesting that challenges remain. First, the RI MoU community engagement efforts focused largely on line listing approaches to encourage uptake of vaccination which may not have been adequate to address the numerous challenges at the community level. The approach required strong support from community leaders and the use of community volunteers who were not compensated for their services. Introducing non-monetary incentives may be an effective option to increase community based participation and motivation for the RI program [ 30 ]. While the use of community leaders is important in addressing community level barriers [ 31 ], the approach did not focus on the individual behavioral barriers that may require efforts to address knowledge, attitudes, beliefs, social norms, and self-efficacy. Efforts such as SMS reminders may be one way to raise awareness about vaccination services [ 32 ]. In addition, efforts to engage directly with fathers who were often the primary decision maker of whether a child was vaccinated through traditional channels such as Wanzams may also address barriers to vaccination coverage [ 33 , 34 ].

In addition to challenges at the community level, a number of challenges were noted relating to service delivery and staff capacity. Data from the HFA found that the median number of health workers was below the recommended number at PHCs in all states. Given the limitations of the public sector to provide services due to insufficient staff as well as challenges in reaching insecure areas, it may be beneficial to consider a public-private partnership model to expand service delivery [ 35 ] to hard-to-reach areas or consider redistributing and/or incentivizing staff to work in hard to reach areas. In addition, given the frequent migration and political insecurity, it may be necessary to adopt new methods such as applying satellite derived maps to identify vulnerable populations that are not being reached through traditional RI microplan approaches [ 36 , 37 , 38 ]. Finally, training health providers on how to address vaccine hesitancy and concerns related to adverse events following immunization may also be required [ 39 ].

Several efforts were made to improve routine monitoring of the RI program including the incorporation of RI module in DHIS2 which provided information to inform planning [ 40 , 41 , 42 ]. However, insecurity remained a challenge in some areas compromising monitoring and supportive supervision visits in some local governments, which has led to poor data reporting. Consequently, the state must explore innovative approaches to retrieve program data from high-risk security areas [ 43 ]. Finally, the RI MoU logic model provided a structure for assessing the RI MoU performance, however a theory driven model including a clear monitoring and evaluation plan with indicators and targets established prior to implementation of the MoU is required in order to provide a more rigorous assessment of the RI MoU approach [ 44 , 45 ]. This approach would also help to provide a better understanding of why some states such as Yobe have been effective in increasing immunization coverages while others such as Borno and Sokoto continue to struggle.

Limitations

There are several limitations associated with this study. First, each state included in the evaluation initiated implementation at different time points and progressed to more comprehensive PHC MoU models at staggered times. In addition, while the states completed a comprehensive diagnostic assessment prior to implementation, comparable baseline measures were not collected. Next, due to the complexity of the approach, no single data source could be used to measure the full influence of the approach. This coupled with the lack of a comparison area made it impossible to control for the effect of individual inputs or how the MoU states performed relative to other states in the region who did not benefit from the MoU investment [ 20 ]. Third, a comprehensive monitoring and evaluation plan was not established prior to implementation with clearly defined indicators and data sources. As such, limited data were available following several years of implementation and at irregular intervals. Finally, details on programs not operating under the purview of the RI MoU approach as well as contextual factors likely influenced the variable outcomes observed across the six states [ 46 ]. Specifically, Gavi’s national level investments to strengthen the health system including cold chain equipment investment despite focusing on non-MoU states may have reached to a limited extent MoU states. And, the Covid-19 pandemic while not assessed in this evaluation contributed to a lack of transport and limited outreach visits [ 47 ]. Despite these challenges, the evaluation did endeavor to achieve a holistic understanding of the RI MoU approach by gathering perspectives from multiple levels (e.g. participants, service providers, community structures, partners, donors and government stakeholders).

Consistent with previous research on the advantages of partnership models, we found the RI MoUs across the six states to be mostly successful in strengthening health systems, improving accountability and coordination, and increasing the utilization of services and financing for RI which serves as an important foundation as the country transitions to sector wide approaches [ 14 , 15 ]. However, evaluation findings indicate that issues pertaining to human resources for health, insecurity that inhibits supportive supervision and vaccine logistics as well as harmful socio-cultural norms remain a persistent challenge in the states suggest that the RI MoU approach would benefit from increased technical assistance and capacity building to address these limitations [ 13 ]. Attention to numbers, capacity, and distribution of frontline health providers will be an important component for health system strengthening moving forward. Furthermore, addressing cultural norms received minimal consideration throughout the MoU design. If interventions to address socio-cultural norms are not incorporated into the program, service uptake may remain low.

Data availability

The datasets generated and/or analysed during the current study are not publicly available to protect the confidentiality of study participants but are available from the corresponding author on reasonable request.

Abbreviations

Aliko Dangote Foundation

Bill and Melinda Gates Foundation

Cold Chain Equipment

Community Health Extension Worker

Community Health Officer

Client Exit Interview

District Health Information System 2

Demographic and Health Survey

Focus Group Discussion

Health Facility Assessment

In depth Interview

Key Informant

Local Government Area

Memorandum of Understanding

National Primary Health Care Development Agency

Primary Health Care

Primary Health Care Under One Roof

Reaching every ward

Routine immunization

Routine Immunization Supportive Supervision

Solar Direct Drive

State Primary Health Care Development Agency

U.S Agency for International Development

United States Dollar

National Bureau of Statistics (NBS) and United Nations Children’s Fund (UNICEF). Nigeria National Nutrition and Health Survey. 2018. 2018.

NPC and ICF, Nigeria Demographic. and Health Survey 2018. Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF. Abuja, Nigeria, and Rockville, Maryland, USA; 2019.

Fatiregun AA, Etukiren EE. Determinants of uptake of third doses of oral polio and DTP vaccines in the Ibadan North Local Government Area of Nigeria. Int Health. 2014;6:213–24.

Article PubMed Google Scholar

Adeloye D, Jacobs W, Amuta AO, Ogundipe O, Mosaku O, Gadanya MA, et al. Coverage and determinants of childhood immunization in Nigeria: a systematic review and meta-analysis. Vaccine. 2017;35:2871–81.

Bala U, Ajumobi O, Umar A, Adewole A, Waziri N, Gidado S, et al. Assessment of health service delivery parameters in Kano and Zamfara States, Nigeria. BMC Health Serv Res. 2020;20:874.

Article PubMed PubMed Central Google Scholar

Abad N, Uba BV, Patel P, Barau DN, Ugochukwu O, Aliyu N et al. A rapid qualitative assessment of barriers associated with demand and uptake of health facility-based childhood immunizations and recommendations to improve immunization service delivery in Sokoto State, Northwest Nigeria, 2017.

Ghinai I, Willott C, Dadari I, Larson HJ. Listening to the rumours: what the northern Nigeria Polio vaccine boycott can tell us ten years on. Glob Public Health. 2013;8:1138–50.

Stokes-Prindle C, Chizoba Wonodi M, Aina G, Oni T, Olukowi, Pate MA et al. Landscape Analysis of Routine Immunization in Nigeria: Identifying Barriers and Prioritizing Interventions. 2012. https://doi.org/10.13140/rg.2.2.19444.60800

National Primary Health Care Development Agency. IMPLEMENTATION STATUS OF PRIMARY HEALTH CARE UNDER ONE ROOF (PHCUOR) - SCORECARD 4. 2018.

Cohen J. The New World of Global Health. Science. 2006;311:162–7.

Article CAS PubMed Google Scholar

Brugha R, Global Health Initiatives and Public Health Policy. International Encyclopedia of Public Health. Elsevier; 2008. pp. 72–81.

Storeng KT. The GAVI Alliance and the ‘Gates approach’ to health system strengthening. Glob Public Health. 2014;9:865–79.

Plamondon KM, Brisbois B, Dubent L, Larson CP. Assessing how global health partnerships function: an equity-informed critical interpretive synthesis. Global Health. 2021;17:73.

Cahill K, Flemming D, Conway M, Gupta S. Global Health Partnerships: assessing Country consequences. Seattle, WA, USA: Bill and Melinda Gates Foundation; 2003.

Google Scholar

Caines K, Buse K, Carlson C. Assessing the Impact of Global Health Partnerships.:52.

Buse K, Harmer AM. Seven habits of highly effective global public–private health partnerships: practice and potential. Soc Sci Med. 2007;64:259–71.

Biesma RG, Brugha R, Harmer A, Walsh A, Spicer N, Walt G. The effects of global health initiatives on country health systems: a review of the evidence from HIV/AIDS control. Health Policy Plann. 2009;24:239–52.

Article Google Scholar

Mwisongo A, Nabyonga-Orem J. Global health initiatives in Africa – governance, priorities, harmonisation and alignment. BMC Health Serv Res. 2016;16.

John Snow Inc. RI MoU: Links to key resources and sample documents. https://www.jsi.com/implementing-a-memorandum-of-understanding/

Kelly E, Doyle V, Weakliam D, Schönemann Y. A rapid evidence review on the effectiveness of institutional health partnerships. Globalization Health. 2015;11.

National Bureau of Statistics. Demographic Statistics Bulletin. Nigeria; 2017.

World Health Organization. Monitoring the building blocks of health systems: a handbook of indicators and their measurement strategies. Geneva: World Health Organization; 2010.

Creswell J, Plano VL, Clark. Designing and conducting mixed methods research. 3rd Ed. Thousand Oaks, CA: SAGE Publications, Inc.

Beran D, Aebischer Perone S, Alcoba G, Bischoff A, Bussien C-L, Eperon G, et al. Partnerships in global health and collaborative governance: lessons learnt from the Division of Tropical and Humanitarian Medicine at the Geneva University Hospitals. Global Health. 2016;12:14.

Adeloye D, David RA, Olaogun AA, Auta A, Adesokan A, Gadanya M, et al. Health workforce and governance: the crisis in Nigeria. Hum Resour Health. 2017;15:32.

Eboreime EA, Abimbola S, Obi FA, Ebirim O, Olubajo O, Eyles J et al. Evaluating the sub-national fidelity of national initiatives in decentralized health systems: Integrated Primary Health Care Governance in Nigeria. BMC Health Serv Res. 2017;17.

Erchick DJ, George AS, Umeh C, Wonodi C. Understanding internal accountability in Nigeria’s routine immunization system: perspectives from government officials at the National, State, and local levels. Int J Health Policy Manag. 2016;6:403–12.

Article PubMed Central Google Scholar

Onwujekwe O, Orjiakor CT, Hutchinson E, McKee M, Agwu P, Mbachu C et al. Where do we start? Building Consensus on drivers of Health Sector Corruption in Nigeria and ways to address it. Int J Health Policy Manag. 2019;:1.

Aina M, Igbokwe U, Jegede L, Fagge R, Thompson A, Mahmoud N. Preliminary results from direct-to-facility vaccine deliveries in Kano, Nigeria. Vaccine. 2017;35:2175–82.

Dougherty L, Stammer E, Derbile E, Dery M, Yahaya W, Gle DB et al. A mixed-methods evaluation of a community-based Behavior Change Program to improve maternal Health outcomes in the Upper West Region of Ghana. J Health Communication. 2017;:1–11.

Iwu CA, Uwakwe K, Oluoha U, Duru C, Nwaigbo E. Empowering traditional birth attendants as agents of maternal and neonatal immunization uptake in Nigeria: a repeated measures design. BMC Public Health. 2021;21:287.

Obi-Jeff C, Garcia C, Adewumi F, Bamiduro T, David W, Labrique A, et al. Implementing SMS reminders for routine immunization in Northern Nigeria: a qualitative evaluation using the RE-AIM framework. BMC Public Health. 2022;22:2370.

Raji MO, Sani AA, Luqman SI, Hafsah M, Oladigbolu RA, Kaoje AU. Assessment of the knowledge of fathers, Uptake of Routine Immunization, and its Associated factors in a Rural Community of North West Nigeria. Annals Afr Med. 2019;18:97–102.

Dougherty L, Abdulkarim M, Ahmed A, Cherima Y, Ladan A, Abdu S, et al. Engaging traditional barbers to identify and refer newborns for routine immunization services in Sokoto, Nigeria: a mixed methods evaluation. Int J Public Health. 2020. https://doi.org/10.1007/s00038-020-01518-9 .

Oluoha C, Umeh C, Ahaneku H. Assessing the contributions of private health facilities in a pioneer private-public partnership in childhood immunization in Nigeria. J Public Health Afr. 2014;5.

Umeh GC, Madubu DM, Korir C, Loveday N, Ishaku S, Iyal H, et al. Micro-planning for immunization in Kaduna State, Nigeria: lessons learnt, 2017. Vaccine. 2018;36:7361–8.

Dougherty L, Abdulkarim M, Mikailu F, Tijani U, Owolabi K, Gilroy K, et al. From paper maps to digital maps: enhancing routine immunisation microplanning in Northern Nigeria. BMJ Glob Health. 2019;4(Suppl 5):e001606.

Higgins J, Adamu U, Adewara K, Aladeshawe A, Aregay A, Barau I, et al. Finding inhabited settlements and tracking vaccination progress: the application of satellite imagery analysis to guide the immunization response to confirmation of previously-undetected, ongoing endemic wild poliovirus transmission in Borno State, Nigeria. Int J Health Geogr. 2019;18:11.

Omoleke SA, Getachew B, Isyaku A, Aliyu AB, Mustapha AM, Dansanda SM, et al. Understanding and experience of adverse event following immunization (AEFI) and its consequences among healthcare providers in Kebbi State, Nigeria: a qualitative study. BMC Health Serv Res. 2022;22:741.

Shuaib F, Garba AB, Meribole E, Obasi S, Sule A, Nnadi C, et al. Implementing the routine immunisation data module and dashboard of DHIS2 in Nigeria, 2014–2019. BMJ Glob Health. 2020;5:e002203.

Adeoye OB, Adegoke OJ, Nnadi C, Elmousaad H, Nguku P, Makinde I et al. Data management needs assessment for the scale-up of district health information system and introduction of routine (essential) immunization module in Bauchi State, Nigeria, 2015.

Tchoualeu DD, Elmousaad HE, Osadebe LU, Adegoke OJ, Haladu SA, Jacenko SM et al. Use of a district health information system 2 routine immunization dashboard for immunization program monitoring and decision making, Kano State, Nigeria.

Tegegne SG, Shuaib F, Braka F, Mkanda P, Erbeto TB, Aregay A et al. The role of supportive supervision using mobile technology in monitoring and guiding program performance: a case study in Nigeria, 2015–2016. BMC Public Health. 2018;18.

Paina L, Wilkinson A, Tetui M, Ekirapa-Kiracho E, Barman D, Ahmed T et al. Using theories of change to inform implementation of health systems research and innovation: experiences of Future Health Systems consortium partners in Bangladesh, India and Uganda. Health Res Policy Syst. 2017;15.

Adamu AA, Uthman OA, Gadanya MA, Wiysonge CS. Using the consolidated framework for implementation research (CFIR) to assess the implementation context of a quality improvement program to reduce missed opportunities for vaccination in Kano, Nigeria: a mixed methods study. Hum Vaccines Immunotherapeutics. 2020;16:465–75.

Shaw RP, Wang H, Kress D, Hovig D. Donor and Domestic Financing of Primary Health Care in Low Income Countries. Health Syst Reform. 2015;1:72–88.

Dadari I, Sharkey A, Hoare I, Izurieta R. Analysis of the impact of COVID-19 pandemic and response on routine childhood vaccination coverage and equity in Northern Nigeria: a mixed methods study. BMJ Open. 2023;13:e076154.

Download references

Acknowledgements

The authors would like to thank the Bill and Melinda Gates Foundation in commissioning and funding this study. We would also like to thank the field staff who supported the data collection efforts.

The Bill and Melinda Gates Foundation provided funding and reviewed the draft manuscript. The contents are the responsibility of the authors and do not necessarily reflect the views of the foundation.

Author information

Authors and affiliations.

Population Council, Abuja, Nigeria

Leanne Dougherty, Mayokun Adediran, Akinwumi Akinola, Matthew Alabi, Eno-Obong Etim, Jane Ohioghame & Adebola Adedimeji

4301 Connecticut Avenue, NW, Suite 280, Washington, DC, 20008, USA

Leanne Dougherty

You can also search for this author in PubMed Google Scholar

Contributions

LD conceptualized the study. LD, MA, AA, MA, EE, JO, AA contributed to data collection, analysis and reporting. LD drafted the manuscript. All authors reviewed and provided critical revision into the final version of the manuscript as well as final approval of the version to be submitted. The manuscript is not under consideration for publication elsewhere and if accepted will not be published elsewhere.

Corresponding author

Correspondence to Leanne Dougherty .

Ethics declarations

Ethical approval and consent to participate, consent for publication.

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Dougherty, L., Adediran, M., Akinola, A. et al. An evaluation of a multi-partner approach to increase routine immunization coverage in six northern Nigerian States. BMC Health Serv Res 24 , 951 (2024). https://doi.org/10.1186/s12913-024-11403-3

Download citation

Received : 09 October 2023

Accepted : 05 August 2024

Published : 20 August 2024

DOI : https://doi.org/10.1186/s12913-024-11403-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Partnership
Immunization
Health system strengthening
Accountability

BMC Health Services Research

ISSN: 1472-6963

General enquiries: [email protected]

IMAGES

5 Qualitative Research Methods Every UX Researcher Should Know [+ Examples]
Understanding Qualitative Research: An In-Depth Study Guide
6 Types of Qualitative Research Methods
Types Of Qualitative Research Design With Examples
18 Qualitative Research Examples (2024)
Qualitative Research: Definition, Types, Methods and Examples (2023)

COMMENTS

What Is Qualitative Research?
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data. Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research.
Qualitative Research
Here are some examples of how qualitative research is used: ... Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide ...
8 Types of Qualitative Research Methods With Examples
Types of Data Analysis in Qualitative Research. Qualitative research employs different data analysis methods, each suited to specific research goals: Thematic Analysis: Identifies recurring themes or concepts within data. Content Analysis: Systematically categorizes and quantifies text or media content.
Planning Qualitative Research: Design and Decision Making for New
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
16 Qualitative Methods Examples (2024)
See More Discourse Analysis Examples Here. 15. Life History Research. Life history research is a qualitative methodology that focuses on understanding people's lives and experiences through their personal narratives over a prolonged period, usually their entire life (Goodson & Sykes, 2016[ 20]).
Chapter 1. Introduction
Examples of Qualitative Research. You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research "in the field." A good qualitative researcher will present the ...
What Is Qualitative Research?
Qualitative research methods. Each of the research approaches involve using one or more data collection methods.These are some of the most common qualitative methods: Observations: recording what you have seen, heard, or encountered in detailed field notes. Interviews: personally asking people questions in one-on-one conversations. Focus groups: asking questions and generating discussion among ...
What is Qualitative Research? Methods, Types, Approaches, And Examples
Qualitative research methods 2. Researchers can choose from several qualitative research methods depending on the study type, research question, the researcher's role, data to be collected, etc. The following table lists the common qualitative research approaches with their purpose and examples, although there may be an overlap between some.
Qualitative Research: 7 Methods and Examples
You can use mixed methods in your research design, which combines qualitative and quantitative approaches to gain both descriptive and statistical insights. For example, user surveys can have both close-ended and open-ended questions, providing comprehensive data like percentages of user views and descriptive reasoning behind their answers.
Qualitative Research: Definition, Types, Methods and Examples
Also, read about qualitative research examples: 1. One-on-one interview. Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time.
The SAGE Encyclopedia of Qualitative Research Methods
Qualitative research projects are informed by a wide range of methodologies and theoretical frameworks. The SAGE Encyclopedia of Qualitative Research Methods presents current and complete information as well as ready-to-use techniques, facts, and examples from the field of qualitative research in a very accessible style. In taking an ...
18 Qualitative Research Examples (2024)
Qualitative Research Examples. 1. Ethnography. Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology, this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.
The Oxford Handbook of Qualitative Research
Abstract. The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research ...
Qualitative Research: Methods and Examples
Qualitative research: methods and examples. Qualitative research is an excellent way to gain insight into real-world problems. This research type can explain various aspects of individuals in a target group, such as their traits, behaviors, and motivations. Qualitative research involves gathering and evaluating non-numerical information to ...
Characteristics of Qualitative Research
Qualitative research is a method of inquiry used in various disciplines, including social sciences, education, and health, to explore and understand human behavior, experiences, and social phenomena. It focuses on collecting non-numerical data, such as words, images, or objects, to gain in-depth insights into people's thoughts, feelings, motivations, and perspectives.
Qualitative vs Quantitative Research: What's the Difference?
Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people. ... There are different types of qualitative research methods, including diary accounts, in-depth interviews, documents, focus groups, case ...
Qualitative Data
Marketing: In marketing, qualitative data is used to understand consumer behavior and preferences. For example, a researcher might conduct in-depth interviews with customers to understand their purchasing decisions. Anthropology: In anthropology, qualitative data is used to study human cultures and societies.
What is Qualitative Research? Definition, Types, Examples, Methods, and
Qualitative research is defined as an exploratory method that aims to understand complex phenomena, often within their natural settings, by examining subjective experiences, beliefs, attitudes, and behaviors. Learn more about qualitative research methods, types, examples and best practices.
How to use and assess qualitative research methods
Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...
Qualitative Research Examples
Qualitative research is a behavioral research method that seeks to understand the undertones, motivations, and subjective interpretations inherent in human behavior. It involves gathering nonnumerical data, such as text, audio, and video, allowing you to explore nuances and patterns that quantitative data can't capture.
8 Examples of Qualitative Research
1. Qualitative research offers deep insights into human behavior by delving into individual perspectives, societal dynamics, and cultural influences. It emphasizes narratives and subjective interpretations to unveil hidden meanings. Real-world examples in fields like market research and UX design demonstrate how qualitative research uncovers ...
What is Qualitative Research? Methods and Examples
Researchers in social sciences and humanities often use qualitative research methods, especially in specific areas of study like anthropology, history, education, and sociology. Qualitative methods are also applicable in business, technology, and marketing spaces. For example, product managers use qualitative research to understand how target ...
Qualitative vs. Quantitative Data Analysis in Education
Qualitative research methods. Because of the nature of qualitative data (complex, detailed information), the research methods used to collect it are more involved. Qualitative researchers might do the following to collect data: Conduct interviews to learn about subjective experiences; Host focus groups to gather feedback and personal accounts
The Guide to Qualitative Research: Methods, Types, and Examples
Quantitative research focuses on collecting numerical data that can be used to quantify the magnitude of a situation. The data gained can be organized and statistical analysis carried out. For example, qualitative research may tell you that people in lower-income areas drop out of school and have lower literacy rates.
Qualitative Research Questionnaire
Types of Qualitative Research Questions With Examples. Now that you are familiar with what qualitative research questions are, let's look at the different types of questions you can use in your survey. Descriptive Questions; These are used to explore and describe a phenomenon in detail.
Kinds of data in qualitative research examples
Both methods enrich the data collected and highlight the intricate human experiences that underpin qualitative research. Open-Ended Surveys: Capturing Nuanced Responses. Open-ended surveys are a valuable tool for qualitative research, providing in-depth insights and capturing nuanced responses from participants.
Stakeholders Perspective of Integrating Female Genital Schistosomiasis
Using qualitative research methods, Focus Group Discussion was conducted with Community Health Officers (n=9) and Key Informant Interviews with stakeholders including health care professionals and providers at the Regional, District and community levels (n=13) to explore the feasibility, challenges, and opportunities of integrating FGS ...
Patient safety in remote primary care encounters: multimethod
Background Triage and clinical consultations increasingly occur remotely. We aimed to learn why safety incidents occur in remote encounters and how to prevent them. Setting and sample UK primary care. 95 safety incidents (complaints, settled indemnity claims and reports) involving remote interactions. Separately, 12 general practices followed 2021-2023. Methods Multimethod qualitative study ...
Examining the perception of undergraduate health professional students
The quality of the learning environment significantly impacts student engagement and professional identity formation in health professions education. Despite global recognition of its importance, research on student perceptions of learning environments across different health education programs is scarce. This study aimed to explore how health professional students perceive their learning ...
An evaluation of a multi-partner approach to increase routine
Second, the study team conducted a quantitative health facility assessment and client exit interview and qualitative interviews with service providers, community leaders and program participants to assess the extent to which the approach achieved the objectives outlined in the RI MoU logic model and to understand the benefits and challenges of ...

Have a language expert improve your writing

What Is Qualitative Research? | Methods & Examples

Table of contents

Receive feedback on language, structure, and formatting

Prevent plagiarism. Run a free check.

Cite this Scribbr article

Is this article helpful?

Pritha Bhandari

8 Types of Qualitative Research - Overview & Examples

What is Qualitative Research?

Characteristics of Qualitative Research

Types of Qualitative Research Methods

Ethnographic Research Method

Narrative Method

Phenomenological Method

Grounded Theory Method

Case Study Research

Historical Method

Action Research

Focus Groups

Types of Data Analysis in Qualitative Research

Benefits of Qualitative Research

Keep reading

Chapter 1. Introduction

Why an Open Access Textbook on Qualitative Research Methods?

What is Research?

What is Qualitative Research?

Examples of Qualitative Research

Example 1 : The End Game (ethnography + interviews)

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

How Is This Book Organized?

Chapter Descriptions

Recommended Reading: Other Qualitative Research Textbooks

Patton’s Ten Suggestions for Doing Qualitative Research

Have a language expert improve your writing

What Is Qualitative Research? | Methods & Examples

Table of contents

Prevent plagiarism, run a free check.

Cite this Scribbr article

Is this article helpful?

Pritha Bhandari

What is Qualitative Research? Methods, Types, Approaches and Examples

What is qualitative research? 1

Qualitative research methods 2

Types of qualitative research 3,4

Qualitative research : Data collection and analysis

Characteristics of qualitative research methods 4

When to use qualitative research 4

A qualitative research method case study to understand when to use qualitative research 7

Advantages of qualitative research 1

Disadvantages of qualitative research 1

Differences between qualitative research and quantitative research 1

Frequently asked questions on qualitative research

Q: How do I ensure the reliability and validity of my qualitative research findings?

Q: Are there any sampling strategies or techniques for qualitative research ?

Q: What ethical standards need to be followed with qualitative research ?

Q: How do I address bias in my qualitative research ?

Related Posts

What are the Best Research Funding Sources

Inductive vs. Deductive Research Approach

Qualitative research examples: How to unlock, rich, descriptive insights

Qualitative UX research made easy

7 Qualitative research methods: An overview

1. User interviews

When to use user interviews

How to conduct user interviews: The basics

User interviews: A qualitative research example

2. Focus groups

When to use focus groups

How to conduct focus group studies: The basics

Focus groups: A qualitative research example

3. Ethnographic research

When to use ethnographic research

How to conduct ethnographic research:

Ethnographic research: A qualitative research example

4. Qualitative observation

When to qualitative observation

How to conduct qualitative observation:

Qualitative observation: An qualitative research example