what are the key concepts in research

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
• J Pharmacol Pharmacother
• v.4(2); Apr-Jun 2013

The critical steps for successful research: The research proposal and scientific writing: (A report on the pre-conference workshop held in conjunction with the 64 th annual conference of the Indian Pharmaceutical Congress-2012)

Pitchai balakumar.

Pharmacology Unit, Faculty of Pharmacy, AIMST University, Semeling, 08100 Bedong. Kedah Darul Aman, Malaysia

Mohammed Naseeruddin Inamdar

1 Department of Pharmacology, Al-Ameen College of Pharmacy, Bengaluru, Karnataka, India

Gowraganahalli Jagadeesh

2 Division of Cardiovascular and Renal Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, USA

An interactive workshop on ‘The Critical Steps for Successful Research: The Research Proposal and Scientific Writing’ was conducted in conjunction with the 64 th Annual Conference of the Indian Pharmaceutical Congress-2012 at Chennai, India. In essence, research is performed to enlighten our understanding of a contemporary issue relevant to the needs of society. To accomplish this, a researcher begins search for a novel topic based on purpose, creativity, critical thinking, and logic. This leads to the fundamental pieces of the research endeavor: Question, objective, hypothesis, experimental tools to test the hypothesis, methodology, and data analysis. When correctly performed, research should produce new knowledge. The four cornerstones of good research are the well-formulated protocol or proposal that is well executed, analyzed, discussed and concluded. This recent workshop educated researchers in the critical steps involved in the development of a scientific idea to its successful execution and eventual publication.

INTRODUCTION

Creativity and critical thinking are of particular importance in scientific research. Basically, research is original investigation undertaken to gain knowledge and understand concepts in major subject areas of specialization, and includes the generation of ideas and information leading to new or substantially improved scientific insights with relevance to the needs of society. Hence, the primary objective of research is to produce new knowledge. Research is both theoretical and empirical. It is theoretical because the starting point of scientific research is the conceptualization of a research topic and development of a research question and hypothesis. Research is empirical (practical) because all of the planned studies involve a series of observations, measurements, and analyses of data that are all based on proper experimental design.[ 1 – 9 ]

The subject of this report is to inform readers of the proceedings from a recent workshop organized by the 64 th Annual conference of the ‘ Indian Pharmaceutical Congress ’ at SRM University, Chennai, India, from 05 to 06 December 2012. The objectives of the workshop titled ‘The Critical Steps for Successful Research: The Research Proposal and Scientific Writing,’ were to assist participants in developing a strong fundamental understanding of how best to develop a research or study protocol, and communicate those research findings in a conference setting or scientific journal. Completing any research project requires meticulous planning, experimental design and execution, and compilation and publication of findings in the form of a research paper. All of these are often unfamiliar to naïve researchers; thus, the purpose of this workshop was to teach participants to master the critical steps involved in the development of an idea to its execution and eventual publication of the results (See the last section for a list of learning objectives).

THE STRUCTURE OF THE WORKSHOP

The two-day workshop was formatted to include key lectures and interactive breakout sessions that focused on protocol development in six subject areas of the pharmaceutical sciences. This was followed by sessions on scientific writing. DAY 1 taught the basic concepts of scientific research, including: (1) how to formulate a topic for research and to describe the what, why , and how of the protocol, (2) biomedical literature search and review, (3) study designs, statistical concepts, and result analyses, and (4) publication ethics. DAY 2 educated the attendees on the basic elements and logistics of writing a scientific paper and thesis, and preparation of poster as well as oral presentations.

The final phase of the workshop was the ‘Panel Discussion,’ including ‘Feedback/Comments’ by participants. There were thirteen distinguished speakers from India and abroad. Approximately 120 post-graduate and pre-doctoral students, young faculty members, and scientists representing industries attended the workshop from different parts of the country. All participants received a printed copy of the workshop manual and supporting materials on statistical analyses of data.

THE BASIC CONCEPTS OF RESEARCH: THE KEY TO GETTING STARTED IN RESEARCH

A research project generally comprises four key components: (1) writing a protocol, (2) performing experiments, (3) tabulating and analyzing data, and (4) writing a thesis or manuscript for publication.

Fundamentals in the research process

A protocol, whether experimental or clinical, serves as a navigator that evolves from a basic outline of the study plan to become a qualified research or grant proposal. It provides the structural support for the research. Dr. G. Jagadeesh (US FDA), the first speaker of the session, spoke on ‘ Fundamentals in research process and cornerstones of a research project .’ He discussed at length the developmental and structural processes in preparing a research protocol. A systematic and step-by-step approach is necessary in planning a study. Without a well-designed protocol, there would be a little chance for successful completion of a research project or an experiment.

Research topic

The first and the foremost difficult task in research is to identify a topic for investigation. The research topic is the keystone of the entire scientific enterprise. It begins the project, drives the entire study, and is crucial for moving the project forward. It dictates the remaining elements of the study [ Table 1 ] and thus, it should not be too narrow or too broad or unfocused. Because of these potential pitfalls, it is essential that a good or novel scientific idea be based on a sound concept. Creativity, critical thinking, and logic are required to generate new concepts and ideas in solving a research problem. Creativity involves critical thinking and is associated with generating many ideas. Critical thinking is analytical, judgmental, and involves evaluating choices before making a decision.[ 4 ] Thus, critical thinking is convergent type thinking that narrows and refines those divergent ideas and finally settles to one idea for an in-depth study. The idea on which a research project is built should be novel, appropriate to achieve within the existing conditions, and useful to the society at large. Therefore, creativity and critical thinking assist biomedical scientists in research that results in funding support, novel discovery, and publication.[ 1 , 4 ]

Elements of a study protocol

Research question

The next most crucial aspect of a study protocol is identifying a research question. It should be a thought-provoking question. The question sets the framework. It emerges from the title, findings/results, and problems observed in previous studies. Thus, mastering the literature, attendance at conferences, and discussion in journal clubs/seminars are sources for developing research questions. Consider the following example in developing related research questions from the research topic.

Hepatoprotective activity of Terminalia arjuna and Apium graveolens on paracetamol-induced liver damage in albino rats.

How is paracetamol metabolized in the body? Does it involve P450 enzymes? How does paracetamol cause liver injury? What are the mechanisms by which drugs can alleviate liver damage? What biochemical parameters are indicative of liver injury? What major endogenous inflammatory molecules are involved in paracetamol-induced liver damage?

A research question is broken down into more precise objectives. The objectives lead to more precise methods and definition of key terms. The objectives should be SMART-Specific, Measurable, Achievable, Realistic, Time-framed,[ 10 ] and should cover the entire breadth of the project. The objectives are sometimes organized into hierarchies: Primary, secondary, and exploratory; or simply general and specific. Study the following example:

To evaluate the safety and tolerability of single oral doses of compound X in normal volunteers.

To assess the pharmacokinetic profile of compound X following single oral doses.

To evaluate the incidence of peripheral edema reported as an adverse event.

The objectives and research questions are then formulated into a workable or testable hypothesis. The latter forces us to think carefully about what comparisons will be needed to answer the research question, and establishes the format for applying statistical tests to interpret the results. The hypothesis should link a process to an existing or postulated biologic pathway. A hypothesis is written in a form that can yield measurable results. Studies that utilize statistics to compare groups of data should have a hypothesis. Consider the following example:

• The hepatoprotective activity of Terminalia arjuna is superior to that of Apium graveolens against paracetamol-induced liver damage in albino rats.

All biological research, including discovery science, is hypothesis-driven. However, not all studies need be conducted with a hypothesis. For example, descriptive studies (e.g., describing characteristics of a plant, or a chemical compound) do not need a hypothesis.[ 1 ]

Relevance of the study

Another important section to be included in the protocol is ‘significance of the study.’ Its purpose is to justify the need for the research that is being proposed (e.g., development of a vaccine for a disease). In summary, the proposed study should demonstrate that it represents an advancement in understanding and that the eventual results will be meaningful, contribute to the field, and possibly even impact society.

Biomedical literature

A literature search may be defined as the process of examining published sources of information on a research or review topic, thesis, grant application, chemical, drug, disease, or clinical trial, etc. The quantity of information available in print or electronically (e.g., the internet) is immense and growing with time. A researcher should be familiar with the right kinds of databases and search engines to extract the needed information.[ 3 , 6 ]

Dr. P. Balakumar (Institute of Pharmacy, Rajendra Institute of Technology and Sciences, Sirsa, Haryana; currently, Faculty of Pharmacy, AIMST University, Malaysia) spoke on ‘ Biomedical literature: Searching, reviewing and referencing .’ He schematically explained the basis of scientific literature, designing a literature review, and searching literature. After an introduction to the genesis and diverse sources of scientific literature searches, the use of PubMed, one of the premier databases used for biomedical literature searches world-wide, was illustrated with examples and screenshots. Several companion databases and search engines are also used for finding information related to health sciences, and they include Embase, Web of Science, SciFinder, The Cochrane Library, International Pharmaceutical Abstracts, Scopus, and Google Scholar.[ 3 ] Literature searches using alternative interfaces for PubMed such as GoPubMed, Quertle, PubFocus, Pubget, and BibliMed were discussed. The participants were additionally informed of databases on chemistry, drugs and drug targets, clinical trials, toxicology, and laboratory animals (reviewed in ref[ 3 ]).

Referencing and bibliography are essential in scientific writing and publication.[ 7 ] Referencing systems are broadly classified into two major types, such as Parenthetical and Notation systems. Parenthetical referencing is also known as Harvard style of referencing, while Vancouver referencing style and ‘Footnote’ or ‘Endnote’ are placed under Notation referencing systems. The participants were educated on each referencing system with examples.

Bibliography management

Dr. Raj Rajasekaran (University of California at San Diego, CA, USA) enlightened the audience on ‘ bibliography management ’ using reference management software programs such as Reference Manager ® , Endnote ® , and Zotero ® for creating and formatting bibliographies while writing a manuscript for publication. The discussion focused on the use of bibliography management software in avoiding common mistakes such as incomplete references. Important steps in bibliography management, such as creating reference libraries/databases, searching for references using PubMed/Google scholar, selecting and transferring selected references into a library, inserting citations into a research article and formatting bibliographies, were presented. A demonstration of Zotero®, a freely available reference management program, included the salient features of the software, adding references from PubMed using PubMed ID, inserting citations and formatting using different styles.

Writing experimental protocols

The workshop systematically instructed the participants in writing ‘ experimental protocols ’ in six disciplines of Pharmaceutical Sciences.: (1) Pharmaceutical Chemistry (presented by Dr. P. V. Bharatam, NIPER, Mohali, Punjab); (2) Pharmacology (presented by Dr. G. Jagadeesh and Dr. P. Balakumar); (3) Pharmaceutics (presented by Dr. Jayant Khandare, Piramal Life Sciences, Mumbai); (4) Pharmacy Practice (presented by Dr. Shobha Hiremath, Al-Ameen College of Pharmacy, Bengaluru); (5) Pharmacognosy and Phytochemistry (presented by Dr. Salma Khanam, Al-Ameen College of Pharmacy, Bengaluru); and (6) Pharmaceutical Analysis (presented by Dr. Saranjit Singh, NIPER, Mohali, Punjab). The purpose of the research plan is to describe the what (Specific Aims/Objectives), why (Background and Significance), and how (Design and Methods) of the proposal.

The research plan should answer the following questions: (a) what do you intend to do; (b) what has already been done in general, and what have other researchers done in the field; (c) why is this worth doing; (d) how is it innovative; (e) what will this new work add to existing knowledge; and (f) how will the research be accomplished?

In general, the format used by the faculty in all subjects is shown in Table 2 .

Elements of a research protocol

Biostatistics

Biostatistics is a key component of biomedical research. Highly reputed journals like The Lancet, BMJ, Journal of the American Medical Association, and many other biomedical journals include biostatisticians on their editorial board or reviewers list. This indicates that a great importance is given for learning and correctly employing appropriate statistical methods in biomedical research. The post-lunch session on day 1 of the workshop was largely committed to discussion on ‘ Basic biostatistics .’ Dr. R. Raveendran (JIPMER, Puducherry) and Dr. Avijit Hazra (PGIMER, Kolkata) reviewed, in parallel sessions, descriptive statistics, probability concepts, sample size calculation, choosing a statistical test, confidence intervals, hypothesis testing and ‘ P ’ values, parametric and non-parametric statistical tests, including analysis of variance (ANOVA), t tests, Chi-square test, type I and type II errors, correlation and regression, and summary statistics. This was followed by a practice and demonstration session. Statistics CD, compiled by Dr. Raveendran, was distributed to the participants before the session began and was demonstrated live. Both speakers worked on a variety of problems that involved both clinical and experimental data. They discussed through examples the experimental designs encountered in a variety of studies and statistical analyses performed for different types of data. For the benefit of readers, we have summarized statistical tests applied frequently for different experimental designs and post-hoc tests [ Figure 1 ].

Conceptual framework for statistical analyses of data. Of the two kinds of variables, qualitative (categorical) and quantitative (numerical), qualitative variables (nominal or ordinal) are not normally distributed. Numerical data that come from normal distributions are analyzed using parametric tests, if not; the data are analyzed using non-parametric tests. The most popularly used Student's t -test compares the means of two populations, data for this test could be paired or unpaired. One-way analysis of variance (ANOVA) is used to compare the means of three or more independent populations that are normally distributed. Applying t test repeatedly in pair (multiple comparison), to compare the means of more than two populations, will increase the probability of type I error (false positive). In this case, for proper interpretation, we need to adjust the P values. Repeated measures ANOVA is used to compare the population means if more than two observations coming from same subject over time. The null hypothesis is rejected with a ‘ P ’ value of less than 0.05, and the difference in population means is considered to be statistically significant. Subsequently, appropriate post-hoc tests are used for pairwise comparisons of population means. Two-way or three-way ANOVA are considered if two (diet, dose) or three (diet, dose, strain) independent factors, respectively, are analyzed in an experiment (not described in the Figure). Categorical nominal unmatched variables (counts or frequencies) are analyzed by Chi-square test (not shown in the Figure)

Research and publication ethics

The legitimate pursuit of scientific creativity is unfortunately being marred by a simultaneous increase in scientific misconduct. A disproportionate share of allegations involves scientists of many countries, and even from respected laboratories. Misconduct destroys faith in science and scientists and creates a hierarchy of fraudsters. Investigating misconduct also steals valuable time and resources. In spite of these facts, most researchers are not aware of publication ethics.

Day 1 of the workshop ended with a presentation on ‘ research and publication ethics ’ by Dr. M. K. Unnikrishnan (College of Pharmaceutical Sciences, Manipal University, Manipal). He spoke on the essentials of publication ethics that included plagiarism (attempting to take credit of the work of others), self-plagiarism (multiple publications by an author on the same content of work with slightly different wordings), falsification (manipulation of research data and processes and omitting critical data or results), gift authorship (guest authorship), ghostwriting (someone other than the named author (s) makes a major contribution), salami publishing (publishing many papers, with minor differences, from the same study), and sabotage (distracting the research works of others to halt their research completion). Additionally, Dr. Unnikrishnan pointed out the ‘ Ingelfinger rule ’ of stipulating that a scientist must not submit the same original research in two different journals. He also advised the audience that authorship is not just credit for the work but also responsibility for scientific contents of a paper. Although some Indian Universities are instituting preventive measures (e.g., use of plagiarism detecting software, Shodhganga digital archiving of doctoral theses), Dr. Unnikrishnan argued for a great need to sensitize young researchers on the nature and implications of scientific misconduct. Finally, he discussed methods on how editors and peer reviewers should ethically conduct themselves while managing a manuscript for publication.

SCIENTIFIC COMMUNICATION: THE KEY TO SUCCESSFUL SELLING OF FINDINGS

Research outcomes are measured through quality publications. Scientists must not only ‘do’ science but must ‘write’ science. The story of the project must be told in a clear, simple language weaving in previous work done in the field, answering the research question, and addressing the hypothesis set forth at the beginning of the study. Scientific publication is an organic process of planning, researching, drafting, revising, and updating the current knowledge for future perspectives. Writing a research paper is no easier than the research itself. The lectures of Day 2 of the workshop dealt with the basic elements and logistics of writing a scientific paper.

An overview of paper structure and thesis writing

Dr. Amitabh Prakash (Adis, Auckland, New Zealand) spoke on ‘ Learning how to write a good scientific paper .’ His presentation described the essential components of an original research paper and thesis (e.g., introduction, methods, results, and discussion [IMRaD]) and provided guidance on the correct order, in which data should appear within these sections. The characteristics of a good abstract and title and the creation of appropriate key words were discussed. Dr. Prakash suggested that the ‘title of a paper’ might perhaps have a chance to make a good impression, and the title might be either indicative (title that gives the purpose of the study) or declarative (title that gives the study conclusion). He also suggested that an abstract is a succinct summary of a research paper, and it should be specific, clear, and concise, and should have IMRaD structure in brief, followed by key words. Selection of appropriate papers to be cited in the reference list was also discussed. Various unethical authorships were enumerated, and ‘The International Committee of Medical Journal Editors (ICMJE) criteria for authorship’ was explained ( http://www.icmje.org/ethical_1author.html ; also see Table 1 in reference #9). The session highlighted the need for transparency in medical publication and provided a clear description of items that needed to be included in the ‘Disclosures’ section (e.g., sources of funding for the study and potential conflicts of interest of all authors, etc.) and ‘Acknowledgements’ section (e.g., writing assistance and input from all individuals who did not meet the authorship criteria). The final part of the presentation was devoted to thesis writing, and Dr. Prakash provided the audience with a list of common mistakes that are frequently encountered when writing a manuscript.

The backbone of a study is description of results through Text, Tables, and Figures. Dr. S. B. Deshpande (Institute of Medical Sciences, Banaras Hindu University, Varanasi, India) spoke on ‘ Effective Presentation of Results .’ The Results section deals with the observations made by the authors and thus, is not hypothetical. This section is subdivided into three segments, that is, descriptive form of the Text, providing numerical data in Tables, and visualizing the observations in Graphs or Figures. All these are arranged in a sequential order to address the question hypothesized in the Introduction. The description in Text provides clear content of the findings highlighting the observations. It should not be the repetition of facts in tables or graphs. Tables are used to summarize or emphasize descriptive content in the text or to present the numerical data that are unrelated. Illustrations should be used when the evidence bearing on the conclusions of a paper cannot be adequately presented in a written description or in a Table. Tables or Figures should relate to each other logically in sequence and should be clear by themselves. Furthermore, the discussion is based entirely on these observations. Additionally, how the results are applied to further research in the field to advance our understanding of research questions was discussed.

Dr. Peush Sahni (All-India Institute of Medical Sciences, New Delhi) spoke on effectively ‘ structuring the Discussion ’ for a research paper. The Discussion section deals with a systematic interpretation of study results within the available knowledge. He said the section should begin with the most important point relating to the subject studied, focusing on key issues, providing link sentences between paragraphs, and ensuring the flow of text. Points were made to avoid history, not repeat all the results, and provide limitations of the study. The strengths and novel findings of the study should be provided in the discussion, and it should open avenues for future research and new questions. The Discussion section should end with a conclusion stating the summary of key findings. Dr. Sahni gave an example from a published paper for writing a Discussion. In another presentation titled ‘ Writing an effective title and the abstract ,’ Dr. Sahni described the important components of a good title, such as, it should be simple, concise, informative, interesting and eye-catching, accurate and specific about the paper's content, and should state the subject in full indicating study design and animal species. Dr. Sahni explained structured (IMRaD) and unstructured abstracts and discussed a few selected examples with the audience.

Language and style in publication

The next lecture of Dr. Amitabh Prakash on ‘ Language and style in scientific writing: Importance of terseness, shortness and clarity in writing ’ focused on the actual sentence construction, language, grammar and punctuation in scientific manuscripts. His presentation emphasized the importance of brevity and clarity in the writing of manuscripts describing biomedical research. Starting with a guide to the appropriate construction of sentences and paragraphs, attendees were given a brief overview of the correct use of punctuation with interactive examples. Dr. Prakash discussed common errors in grammar and proactively sought audience participation in correcting some examples. Additional discussion was centered on discouraging the use of redundant and expendable words, jargon, and the use of adjectives with incomparable words. The session ended with a discussion of words and phrases that are commonly misused (e.g., data vs . datum, affect vs . effect, among vs . between, dose vs . dosage, and efficacy/efficacious vs . effective/effectiveness) in biomedical research manuscripts.

Working with journals

The appropriateness in selecting the journal for submission and acceptance of the manuscript should be determined by the experience of an author. The corresponding author must have a rationale in choosing the appropriate journal, and this depends upon the scope of the study and the quality of work performed. Dr. Amitabh Prakash spoke on ‘ Working with journals: Selecting a journal, cover letter, peer review process and impact factor ’ by instructing the audience in assessing the true value of a journal, understanding principles involved in the peer review processes, providing tips on making an initial approach to the editorial office, and drafting an appropriate cover letter to accompany the submission. His presentation defined the metrics that are most commonly used to measure journal quality (e.g., impact factor™, Eigenfactor™ score, Article Influence™ score, SCOPUS 2-year citation data, SCImago Journal Rank, h-Index, etc.) and guided attendees on the relative advantages and disadvantages of using each metric. Factors to consider when assessing journal quality were discussed, and the audience was educated on the ‘green’ and ‘gold’ open access publication models. Various peer review models (e.g., double-blind, single-blind, non-blind) were described together with the role of the journal editor in assessing manuscripts and selecting suitable reviewers. A typical checklist sent to referees was shared with the attendees, and clear guidance was provided on the best way to address referee feedback. The session concluded with a discussion of the potential drawbacks of the current peer review system.

Poster and oral presentations at conferences

Posters have become an increasingly popular mode of presentation at conferences, as it can accommodate more papers per meeting, has no time constraint, provides a better presenter-audience interaction, and allows one to select and attend papers of interest. In Figure 2 , we provide instructions, design, and layout in preparing a scientific poster. In the final presentation, Dr. Sahni provided the audience with step-by-step instructions on how to write and format posters for layout, content, font size, color, and graphics. Attendees were given specific guidance on the format of text on slides, the use of color, font type and size, and the use of illustrations and multimedia effects. Moreover, the importance of practical tips while delivering oral or poster presentation was provided to the audience, such as speak slowly and clearly, be informative, maintain eye contact, and listen to the questions from judges/audience carefully before coming up with an answer.

Guidelines and design to scientific poster presentation. The objective of scientific posters is to present laboratory work in scientific meetings. A poster is an excellent means of communicating scientific work, because it is a graphic representation of data. Posters should have focus points, and the intended message should be clearly conveyed through simple sections: Text, Tables, and Graphs. Posters should be clear, succinct, striking, and eye-catching. Colors should be used only where necessary. Use one font (Arial or Times New Roman) throughout. Fancy fonts should be avoided. All headings should have font size of 44, and be in bold capital letters. Size of Title may be a bit larger; subheading: Font size of 36, bold and caps. References and Acknowledgments, if any, should have font size of 24. Text should have font size between 24 and 30, in order to be legible from a distance of 3 to 6 feet. Do not use lengthy notes

PANEL DISCUSSION: FEEDBACK AND COMMENTS BY PARTICIPANTS

After all the presentations were made, Dr. Jagadeesh began a panel discussion that included all speakers. The discussion was aimed at what we do currently and could do in the future with respect to ‘developing a research question and then writing an effective thesis proposal/protocol followed by publication.’ Dr. Jagadeesh asked the following questions to the panelists, while receiving questions/suggestions from the participants and panelists.

• Does a Post-Graduate or Ph.D. student receive adequate training, either through an institutional course, a workshop of the present nature, or from the guide?
• Are these Post-Graduates self-taught (like most of us who learnt the hard way)?
• How are these guides trained? How do we train them to become more efficient mentors?
• Does a Post-Graduate or Ph.D. student struggle to find a method (s) to carry out studies? To what extent do seniors/guides help a post graduate overcome technical difficulties? How difficult is it for a student to find chemicals, reagents, instruments, and technical help in conducting studies?
• Analyses of data and interpretation: Most students struggle without adequate guidance.
• Thesis and publications frequently feature inadequate/incorrect statistical analyses and representation of data in tables/graphs. The student, their guide, and the reviewers all share equal responsibility.
• Who initiates and drafts the research paper? The Post-Graduate or their guide?
• What kind of assistance does a Post-Graduate get from the guide in finalizing a paper for publication?
• Does the guide insist that each Post-Graduate thesis yield at least one paper, and each Ph.D. thesis more than two papers, plus a review article?

The panelists and audience expressed a variety of views, but were unable to arrive at a decisive conclusion.

WHAT HAVE THE PARTICIPANTS LEARNED?

At the end of this fast-moving two-day workshop, the participants had opportunities in learning the following topics:

• Sequential steps in developing a study protocol, from choosing a research topic to developing research questions and a hypothesis.
• Study protocols on different topics in their subject of specialization
• Searching and reviewing the literature
• Appropriate statistical analyses in biomedical research
• Scientific ethics in publication
• Writing and understanding the components of a research paper (IMRaD)
• Recognizing the value of good title, running title, abstract, key words, etc
• Importance of Tables and Figures in the Results section, and their importance in describing findings
• Evidence-based Discussion in a research paper
• Language and style in writing a paper and expert tips on getting it published
• Presentation of research findings at a conference (oral and poster).

Overall, the workshop was deemed very helpful to participants. The participants rated the quality of workshop from “ satisfied ” to “ very satisfied .” A significant number of participants were of the opinion that the time allotted for each presentation was short and thus, be extended from the present two days to four days with adequate time to ask questions. In addition, a ‘hands-on’ session should be introduced for writing a proposal and manuscript. A large number of attendees expressed their desire to attend a similar workshop, if conducted, in the near future.

ACKNOWLEDGMENT

We gratefully express our gratitude to the Organizing Committee, especially Professors K. Chinnasamy, B. G. Shivananda, N. Udupa, Jerad Suresh, Padma Parekh, A. P. Basavarajappa, Mr. S. V. Veerramani, Mr. J. Jayaseelan, and all volunteers of the SRM University. We thank Dr. Thomas Papoian (US FDA) for helpful comments on the manuscript.

The opinions expressed herein are those of Gowraganahalli Jagadeesh and do not necessarily reflect those of the US Food and Drug Administration

Source of Support: Nil

Conflict of Interest: None declared.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Introduction to Research Methods

3 Understanding Key Research Concepts and Terms

Many terms and concepts are associated with research methods, particularly as it relates to the research planning decisions you must make along the way.  Throughout this textbook, you will be exposed to many of these terms and concepts.  Figure 1.1 is a general chart that will help you contextualize many of these terms and also understand the research process.  As you can see, Figure 1.1 begins with two key concepts: ontology and epistemology, advances through other concepts and concludes with three research methodological approaches: qualitative, quantitative and mixed methods.

However, it is important to note that research does not end with making decisions about the type of methods you will use. In fact, we could argue that the work is just beginning at this point. As such, Figure 1.1 does not represent an all-encompassing list of concepts and terms related to research methods. Keep in mind that each strategy has its own data collection and analysis approaches, which are associated with the various methodological approaches you choose.  Figure 1.1 is meant to provide a general overview of the lay of the research land. You may want to keep this figure handy as you read through the various chapters.

Ontology & epistemology

Thinking about what you know and how you know what you know involves questions of ontology and epistemology. Perhaps you have heard these concepts before in a philosophy class?  These concepts are relevant to the work of sociologists as well. As sociologists (those who undertake socially-focused research), we want to understand some aspect of our social world.  Usually, we are not starting with zero knowledge.  In fact, we usually start with some understanding of: 1) what is; 2) what can be known about what is; and, 3) what the best mechanism happens to be for learning about what is (Schmitz, 2012). In the following sections, we will define these terms and provide an example of ontology and epistemology

Ontology is a Greek word that means the study, theory, or science of being.  Ontology is concerned with the what is or the nature of reality (Saunders, Lewis, & Thornhill, 2009).  It can involve some very large and difficult to answer questions, such as: What is the purpose of life? What, if anything, exists beyond our universe?  Ontology also asks: What categories does it belong to? Is there such a thing as objective reality?  What does the verb “to be” mean?  

Ontology is comprised of two aspects: objectivism and subjectivism. Objectivism means that social entities exist externally to the social actors who are concerned with their existence. Subjectivism means that social phenomena are created from the perceptions and actions of the social actors who are concerned with their existence (Saunders, et al., 2009).  Figure 1.2 provides an example of a similar research project to be undertaken by two different students.  While the projects being proposed by the students are similar, they each have different research questions.  Read the scenario and then answer the questions that follow.

Subjectivist and objectivist approaches (adapted from Saunders et al., 2009)

Ana is an Emergency & Security Management Studies (ESMS) student at a local college. She is just beginning her capstone research project and she plans to do research at the City of Vancouver. Her research question is as follows: What is the role of City of Vancouver managers, working in the emergency management department, in enabling positive community relationships? She will be collecting data related to the roles and duties of managers in enabling positive community relationships.

Robert is also an ESMS student at the same college. He too will be undertaking his research at the City of Vancouver. His research question is as follows: What is the effect of the City of Vancouver’s corporate culture in enabling managers, working in the emergency management department, to develop a positive relationship with the local community? He will be collecting data related to perceptions of corporate culture and its effect on enabling positive community-emergency management department relationships.

Before the students begin collecting data, they learn that six months ago, the long-time emergency department manager and assistance manager both retired. They have been replaced by two senior staff managers who have Bachelor’s degrees in Emergency Services Management. These new managers are considered more up-to-date and knowledgeable on emergency services management, give their specialized academic training and practical on-the-job work experience in this department. The new managers have, essentially, the same job duties and operate under the same procedures as the managers they replaced. When Ana and Robert approach the managers to ask them to participate in their separate studies, the new managers state that they are just new on the job and probably cannot answer the research questions and they decline to participate. Ana and Robert are worried that they will need to start all over again with a new research project. They return to their supervisors to get their opinions on what they should do.

Before reading about their supervisors’ responses, answer the following questions:

• Is Ana’s research question indicative of an objectivist or a subjectivist approach?
• Is Robert’s research question indicative of an objectivist or a subjectivist approach?
• Given your answer in question 1, which managers could Ana interview (new, old, or both) for her research study? Why?
• Given your answer in question 2, which managers could Robert interview (new, old, or both) for his research study? Why?

Ana’s supervisor tells her that her research question set up for an objectivist approach. Her supervisor tells her that in her study the social entity (the City) exists in reality external to the social actors (the managers). In other words, there is a formal management structure at the City that has largely remained unchanged since the old managers left and the new ones started. The procedures remain the same regardless of whoever occupies those positions. As such, Ana using an objectivist approach, could state that the new managers have job descriptions which describe their duties and that they are a part of a formal structure with a hierarchy of people reporting to them and to whom they report to. She could further state that this hierarchy, which unique to this organization, also resembles hierarchies found in other similar organizations. As such, she can argue that the new managers will be able to speak about the role they play in enabling positive community relationships. Their answers are likely to be no different than the old managers, because the management structure and the procedures remain the same. Therefore, she can go back to the new managers and ask them to participate in her research study.

Robert’s supervisor tells him that his research sets up for a subjectivist approach because in his study the social phenomena (the effect of corporate culture on the relationship with the community) is created from the perceptions and consequent actions of the social actors (the managers). In other words, there is a continual process of social interaction, that is influenced by the corporate culture at the City, and it is these interactions that influence perceptions of the relationship with the community. The relationship is in a constant state of revision. As such, Robert, using a subjectivist approach, could state that the new managers may have had few interactions with the community members to date and therefore may not be fully cognizant of how the corporate culture affects the department’s relationship with the community. While it will be important to get the new mangers’ perceptions, he will also need to speak with the precious managers to get their perceptions from the time they were employed in their positions. This is because the community-department relationship is in a state of constant revision, which is influenced by the various managers perceptions of the corporate culture and its effect on their ability to form positive community relationships. Therefore, he can go back to the current managers and ask them to participate in his study and also ask that the department please contact the previous managers to see if they would be willing to participate in his study.

As you can see from the previous examples, it is the research question of each study that served to guide the decision as to whether the researcher should take a subjective or an objective ontological approach. This decision, in turn, guided their approach to the research study, including to whom they should interview in order to answer their respective interview questions.  We will be speaking a lot more about research questions in the upcoming chapters.

• Epistemology

Epistemology has to do with knowledge. Rather than dealing with questions about what is , epistemology deals with questions of how we know what is.  In sociology, there are many ways to uncover knowledge. We might interview people to understand public opinion about some topic, or perhaps we’ll observe them in their natural environment. We could avoid face-to-face interaction altogether by mailing people surveys for them to complete on their own or by reading what people have to say about their opinions in newspaper editorials. These methods are all ways that sociologists gain knowledge. Each method of data collection comes with its own set of epistemological assumptions about how to find things out (Schmitz, 2012). There are two main subsections of epistemology: positivist and interpretivist philosophies. We will examine these philosophies or paradigms in the following sections.

Long Descriptions

Figure 1.1 long description: The research process.

• Interpretivism
• Post-modernism
• Social constructivism
• Non-experiment
• Quasi-experiment
• Quantitative
• Qualitative
• Mixed methods
• Unobtrusive methods

[Return to Figure 1.1]

An Introduction to Research Methods in Sociology Copyright © 2019 by Valerie A. Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

Key Concepts in Qualitative Research

Qualitative studies, as we learned earlier in this course, use an inductive method. Meaning, they seek to understand a phenomenon, and then use an emergency design that evolves as the research takes place in order to finally produce a theory. Qualitative designs are also subjective  and use an analysis of words to understand the meaning of viewpoints and realities of the participants.

• Definition of Qualitative Methodology
• Assumptions of Qualitative Methods
• Types of Qualitative Studies
• Population and Samples
• Common Data Collection Methods
• Data Analyses
• Common Statistical Analyses

Objectives:

• Define qualitative research methodology.
• Describe the foundational assumptions of qualitative methods.
• Understand the types of qualitative studies.
• Describe sampling in qualitative research.
• Describe the common data collection methods and data analyses in qualitative research.
• Define mixed methods research.

Qualitative Research Methodology

A key concept is to remember that qualitative research is generally not generalizable, as we are not testing a hypothesis and not making inferences based on data. However, in qualitative research, it is often revolving around the concept of transferability. Transferability is established by providing evidence that the research study’s findings could be applicable to other contexts, situations, times, and populations.

Foundational Assumptions of Qualitative Methods.

The overarching assumptions in qualitative methodology include:

• Truth is fluid. Meaning, it is flexible and holistic.
• Some aspects of humanity and the human experience is best examined with qualitative methods so that we can have a deeper understanding of a person’s experience and viewpoints.

In general, qualitative design (methodology):

• Is flexible and capable to changing as the study progresses, depending on what is learned during the data collection.
• It often uses various data collection strategies in order to collect rich data.
• Is holistic in nature, with the goal of understanding of the whole.
• Researchers are involved, reflexive, and can interact with participants during data collection.

Types of qualitative studies

The common types of qualitative research include:

Phenomenology: the lived experiences; useful to learn about the human experience.

Grounded Theory: to discover the process; often a social process in nursing.

Ethnography: to describe a culture; used commonly in nursing to describe cultures (Brown, 2017).

Historical: a retrospective examination of events to explain and understand (Schmidt & Brown, 2019).

Case Study: a comprehensive investigation of individuals or groups of people to gain insight into a specific situation (Brown, 2017).

Sampling in Qualitative Research

Sample sizes in qualitative research are often much smaller than quantitative research. Remember, we are not generalizing findings to a larger population, so the sample size can be very small.

One of the reasons samples are smaller is because each participant contributes a large amount of data in the form of a narrative. The narrative (words) is then analyzed for themes (thematic analysis) and this takes a lot of time.

Data saturation involves sampling until no new information is obtained and redundancy is achieved. This can vary the sample size, depending on various factors. Data quality can absolutely affect the sample size. If participants are insightful and can share their narrative well, then saturation may be achieved with a relatively small sample.

Common Data Collection Methods and Data Analyses in Qualitative Research

Types of data collection methods in qualitative research include:

Self-Reports : These can include unstructured interviews that begin with a general question, and then subsequent questions are guided by the initial answers. Researchers utilize a general topic guide so that the interviews progress.

Focus Group Interviews : As above, but in a group setting when opinions and experiences are solicited simultaneously. The researcher/interviewer acts as moderator to keep conversation progressing.

Open-Ended Questions in a Survey : Participants can fill in a narrative as they wish. This sometimes elicits information that may not have been obtained in an in-person interview.

Personal Diaries : A standard data course in historical research.

Observations : The aim of observational is to understand the behaviors and experiences of people as they occur. The researcher participates in whatever group is being studies, which often elicits insights that would have eluded more passive or concealed observers.

Next are commonly used data analysis strategies used in qualitative methods. The intent is to introduce terms and how these relate to qualitative analysis.

Coding : line by line coding of the transcript is done to identify reappearing concepts in the data (Schmidt & Brown, 2019). Coding is the process of labeling and organizing your qualitative data to identify different themes and the relationships between them. When coding, you assign labels to words or phrases that represent important (and recurring) themes in each response.

Open coding : the grouping of data into main categories (Schmidt & Brown, 2019). With open coding, you break your data into discrete parts and create “codes” to label them. As its name would imply, open-coding is meant to open you up to new theoretical possibilities, as you first engage with your qualitative data.

Axial coding : after open coding is completed, the categories are analyzed (Schmidt & Brown, 2019).  Axial coding is when the researcher begins to draw connections between ideas in their research. 

There are some software programs that analyze qualitative data in transcripts to look for themes or commonly appearing concepts (Schmidt & Brown, 2019).

This can also be done manually by researchers. Some use index cards, tally marks, and other methods to note common themes/patterns (Leibold, 2020).

Mixed Methods Research

Finally, not all research is simply qualitative or quantitative. Research in which both types of methodology is utilized is called mixed-methods research . Mixed methods is a research approach whereby researchers collect and analyze both quantitative and qualitative data within the same study.

Growth of mixed methods research in nursing and healthcare has occurred at a time of internationally increasing complexity in healthcare delivery. Mixed methods research draws on potential strengths of both qualitative and quantitative methods, allowing researchers to explore diverse perspectives and uncover relationships that exist between the intricate layers of our multifaceted research questions. As providers and policy makers strive to ensure quality and safety for patients and families, researchers can use mixed methods to explore contemporary healthcare trends and practices across increasingly diverse practice settings (Shorten & Smith, 2017).

References & Attribution

“ Green check mark ” by rawpixel licensed CC0 .

Brown, S. J.   (2017). Evidence-based nursing: The research-practice connection (4th ed.). Jones & Bartlett Learning.

Leibold, N. (2020). Research variables. Measures and Concepts Commonly Encountered in EBP. CC BY-NC

Schmidt, N. A. & Brown, J. M. (2019). Evidence-based practice for nurses: Appraisal and application of research (4th ed.). Jones & Bartlett Learning.

Shorten, A., & Smith, J. (2017). Mixed methods research: Expanding the evidence base. Evidence-Based Nursing, 20 , 74-75.

Evidence-Based Practice & Research Methodologies Copyright © by Tracy Fawns is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

• Privacy Policy

Home » Conceptual Framework – Types, Methodology and Examples

Conceptual Framework – Types, Methodology and Examples

Table of Contents

Conceptual Framework

Definition:

A conceptual framework is a structured approach to organizing and understanding complex ideas, theories, or concepts. It provides a systematic and coherent way of thinking about a problem or topic, and helps to guide research or analysis in a particular field.

A conceptual framework typically includes a set of assumptions, concepts, and propositions that form a theoretical framework for understanding a particular phenomenon. It can be used to develop hypotheses, guide empirical research, or provide a framework for evaluating and interpreting data.

Conceptual Framework in Research

In research, a conceptual framework is a theoretical structure that provides a framework for understanding a particular phenomenon or problem. It is a key component of any research project and helps to guide the research process from start to finish.

A conceptual framework provides a clear understanding of the variables, relationships, and assumptions that underpin a research study. It outlines the key concepts that the study is investigating and how they are related to each other. It also defines the scope of the study and sets out the research questions or hypotheses.

Types of Conceptual Framework

Types of Conceptual Framework are as follows:

Theoretical Framework

A theoretical framework is an overarching set of concepts, ideas, and assumptions that help to explain and interpret a phenomenon. It provides a theoretical perspective on the phenomenon being studied and helps researchers to identify the relationships between different concepts. For example, a theoretical framework for a study on the impact of social media on mental health might draw on theories of communication, social influence, and psychological well-being.

Conceptual Model

A conceptual model is a visual or written representation of a complex system or phenomenon. It helps to identify the main components of the system and the relationships between them. For example, a conceptual model for a study on the factors that influence employee turnover might include factors such as job satisfaction, salary, work-life balance, and job security, and the relationships between them.

Empirical Framework

An empirical framework is based on empirical data and helps to explain a particular phenomenon. It involves collecting data, analyzing it, and developing a framework to explain the results. For example, an empirical framework for a study on the impact of a new health intervention might involve collecting data on the intervention’s effectiveness, cost, and acceptability to patients.

Descriptive Framework

A descriptive framework is used to describe a particular phenomenon. It helps to identify the main characteristics of the phenomenon and to develop a vocabulary to describe it. For example, a descriptive framework for a study on different types of musical genres might include descriptions of the instruments used, the rhythms and beats, the vocal styles, and the cultural contexts of each genre.

Analytical Framework

An analytical framework is used to analyze a particular phenomenon. It involves breaking down the phenomenon into its constituent parts and analyzing them separately. This type of framework is often used in social science research. For example, an analytical framework for a study on the impact of race on police brutality might involve analyzing the historical and cultural factors that contribute to racial bias, the organizational factors that influence police behavior, and the psychological factors that influence individual officers’ behavior.

Conceptual Framework for Policy Analysis

A conceptual framework for policy analysis is used to guide the development of policies or programs. It helps policymakers to identify the key issues and to develop strategies to address them. For example, a conceptual framework for a policy analysis on climate change might involve identifying the key stakeholders, assessing their interests and concerns, and developing policy options to mitigate the impacts of climate change.

Logical Frameworks

Logical frameworks are used to plan and evaluate projects and programs. They provide a structured approach to identifying project goals, objectives, and outcomes, and help to ensure that all stakeholders are aligned and working towards the same objectives.

Conceptual Frameworks for Program Evaluation

These frameworks are used to evaluate the effectiveness of programs or interventions. They provide a structure for identifying program goals, objectives, and outcomes, and help to measure the impact of the program on its intended beneficiaries.

Conceptual Frameworks for Organizational Analysis

These frameworks are used to analyze and evaluate organizational structures, processes, and performance. They provide a structured approach to understanding the relationships between different departments, functions, and stakeholders within an organization.

Conceptual Frameworks for Strategic Planning

These frameworks are used to develop and implement strategic plans for organizations or businesses. They help to identify the key factors and stakeholders that will impact the success of the plan, and provide a structure for setting goals, developing strategies, and monitoring progress.

Components of Conceptual Framework

The components of a conceptual framework typically include:

• Research question or problem statement : This component defines the problem or question that the conceptual framework seeks to address. It sets the stage for the development of the framework and guides the selection of the relevant concepts and constructs.
• Concepts : These are the general ideas, principles, or categories that are used to describe and explain the phenomenon or problem under investigation. Concepts provide the building blocks of the framework and help to establish a common language for discussing the issue.
• Constructs : Constructs are the specific variables or concepts that are used to operationalize the general concepts. They are measurable or observable and serve as indicators of the underlying concept.
• Propositions or hypotheses : These are statements that describe the relationships between the concepts or constructs in the framework. They provide a basis for testing the validity of the framework and for generating new insights or theories.
• Assumptions : These are the underlying beliefs or values that shape the framework. They may be explicit or implicit and may influence the selection and interpretation of the concepts and constructs.
• Boundaries : These are the limits or scope of the framework. They define the focus of the investigation and help to clarify what is included and excluded from the analysis.
• Context : This component refers to the broader social, cultural, and historical factors that shape the phenomenon or problem under investigation. It helps to situate the framework within a larger theoretical or empirical context and to identify the relevant variables and factors that may affect the phenomenon.
• Relationships and connections: These are the connections and interrelationships between the different components of the conceptual framework. They describe how the concepts and constructs are linked and how they contribute to the overall understanding of the phenomenon or problem.
• Variables : These are the factors that are being measured or observed in the study. They are often operationalized as constructs and are used to test the propositions or hypotheses.
• Methodology : This component describes the research methods and techniques that will be used to collect and analyze data. It includes the sampling strategy, data collection methods, data analysis techniques, and ethical considerations.
• Literature review : This component provides an overview of the existing research and theories related to the phenomenon or problem under investigation. It helps to identify the gaps in the literature and to situate the framework within the broader theoretical and empirical context.
• Outcomes and implications: These are the expected outcomes or implications of the study. They describe the potential contributions of the study to the theoretical and empirical knowledge in the field and the practical implications for policy and practice.

Conceptual Framework Methodology

Conceptual Framework Methodology is a research method that is commonly used in academic and scientific research to develop a theoretical framework for a study. It is a systematic approach that helps researchers to organize their thoughts and ideas, identify the variables that are relevant to their study, and establish the relationships between these variables.

Here are the steps involved in the conceptual framework methodology:

Identify the Research Problem

The first step is to identify the research problem or question that the study aims to answer. This involves identifying the gaps in the existing literature and determining what specific issue the study aims to address.

Conduct a Literature Review

The second step involves conducting a thorough literature review to identify the existing theories, models, and frameworks that are relevant to the research question. This will help the researcher to identify the key concepts and variables that need to be considered in the study.

Define key Concepts and Variables

The next step is to define the key concepts and variables that are relevant to the study. This involves clearly defining the terms used in the study, and identifying the factors that will be measured or observed in the study.

Develop a Theoretical Framework

Once the key concepts and variables have been identified, the researcher can develop a theoretical framework. This involves establishing the relationships between the key concepts and variables, and creating a visual representation of these relationships.

Test the Framework

The final step is to test the theoretical framework using empirical data. This involves collecting and analyzing data to determine whether the relationships between the key concepts and variables that were identified in the framework are accurate and valid.

Examples of Conceptual Framework

Some realtime Examples of Conceptual Framework are as follows:

• In economics , the concept of supply and demand is a well-known conceptual framework. It provides a structure for understanding how prices are set in a market, based on the interplay of the quantity of goods supplied by producers and the quantity of goods demanded by consumers.
• In psychology , the cognitive-behavioral framework is a widely used conceptual framework for understanding mental health and illness. It emphasizes the role of thoughts and behaviors in shaping emotions and the importance of cognitive restructuring and behavior change in treatment.
• In sociology , the social determinants of health framework provides a way of understanding how social and economic factors such as income, education, and race influence health outcomes. This framework is widely used in public health research and policy.
• In environmental science , the ecosystem services framework is a way of understanding the benefits that humans derive from natural ecosystems, such as clean air and water, pollination, and carbon storage. This framework is used to guide conservation and land-use decisions.
• In education, the constructivist framework is a way of understanding how learners construct knowledge through active engagement with their environment. This framework is used to guide instructional design and teaching strategies.

Applications of Conceptual Framework

Some of the applications of Conceptual Frameworks are as follows:

• Research : Conceptual frameworks are used in research to guide the design, implementation, and interpretation of studies. Researchers use conceptual frameworks to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data.
• Policy: Conceptual frameworks are used in policy-making to guide the development of policies and programs. Policymakers use conceptual frameworks to identify key factors that influence a particular problem or issue, and to develop strategies for addressing them.
• Education : Conceptual frameworks are used in education to guide the design and implementation of instructional strategies and curriculum. Educators use conceptual frameworks to identify learning objectives, select appropriate teaching methods, and assess student learning.
• Management : Conceptual frameworks are used in management to guide decision-making and strategy development. Managers use conceptual frameworks to understand the internal and external factors that influence their organizations, and to develop strategies for achieving their goals.
• Evaluation : Conceptual frameworks are used in evaluation to guide the development of evaluation plans and to interpret evaluation results. Evaluators use conceptual frameworks to identify key outcomes, indicators, and measures, and to develop a logic model for their evaluation.

Purpose of Conceptual Framework

The purpose of a conceptual framework is to provide a theoretical foundation for understanding and analyzing complex phenomena. Conceptual frameworks help to:

• Guide research : Conceptual frameworks provide a framework for researchers to develop hypotheses, identify research questions, and select appropriate methods for collecting and analyzing data. By providing a theoretical foundation for research, conceptual frameworks help to ensure that research is rigorous, systematic, and valid.
• Provide clarity: Conceptual frameworks help to provide clarity and structure to complex phenomena by identifying key concepts, relationships, and processes. By providing a clear and systematic understanding of a phenomenon, conceptual frameworks help to ensure that researchers, policymakers, and practitioners are all on the same page when it comes to understanding the issue at hand.
• Inform decision-making : Conceptual frameworks can be used to inform decision-making and strategy development by identifying key factors that influence a particular problem or issue. By understanding the complex interplay of factors that contribute to a particular issue, decision-makers can develop more effective strategies for addressing the problem.
• Facilitate communication : Conceptual frameworks provide a common language and conceptual framework for researchers, policymakers, and practitioners to communicate and collaborate on complex issues. By providing a shared understanding of a phenomenon, conceptual frameworks help to ensure that everyone is working towards the same goal.

When to use Conceptual Framework

There are several situations when it is appropriate to use a conceptual framework:

• To guide the research : A conceptual framework can be used to guide the research process by providing a clear roadmap for the research project. It can help researchers identify key variables and relationships, and develop hypotheses or research questions.
• To clarify concepts : A conceptual framework can be used to clarify and define key concepts and terms used in a research project. It can help ensure that all researchers are using the same language and have a shared understanding of the concepts being studied.
• To provide a theoretical basis: A conceptual framework can provide a theoretical basis for a research project by linking it to existing theories or conceptual models. This can help researchers build on previous research and contribute to the development of a field.
• To identify gaps in knowledge : A conceptual framework can help identify gaps in existing knowledge by highlighting areas that require further research or investigation.
• To communicate findings : A conceptual framework can be used to communicate research findings by providing a clear and concise summary of the key variables, relationships, and assumptions that underpin the research project.

Characteristics of Conceptual Framework

key characteristics of a conceptual framework are:

• Clear definition of key concepts : A conceptual framework should clearly define the key concepts and terms being used in a research project. This ensures that all researchers have a shared understanding of the concepts being studied.
• Identification of key variables: A conceptual framework should identify the key variables that are being studied and how they are related to each other. This helps to organize the research project and provides a clear focus for the study.
• Logical structure: A conceptual framework should have a logical structure that connects the key concepts and variables being studied. This helps to ensure that the research project is coherent and consistent.
• Based on existing theory : A conceptual framework should be based on existing theory or conceptual models. This helps to ensure that the research project is grounded in existing knowledge and builds on previous research.
• Testable hypotheses or research questions: A conceptual framework should include testable hypotheses or research questions that can be answered through empirical research. This helps to ensure that the research project is rigorous and scientifically valid.
• Flexibility : A conceptual framework should be flexible enough to allow for modifications as new information is gathered during the research process. This helps to ensure that the research project is responsive to new findings and is able to adapt to changing circumstances.

Advantages of Conceptual Framework

Advantages of the Conceptual Framework are as follows:

• Clarity : A conceptual framework provides clarity to researchers by outlining the key concepts and variables that are relevant to the research project. This clarity helps researchers to focus on the most important aspects of the research problem and develop a clear plan for investigating it.
• Direction : A conceptual framework provides direction to researchers by helping them to develop hypotheses or research questions that are grounded in existing theory or conceptual models. This direction ensures that the research project is relevant and contributes to the development of the field.
• Efficiency : A conceptual framework can increase efficiency in the research process by providing a structure for organizing ideas and data. This structure can help researchers to avoid redundancies and inconsistencies in their work, saving time and effort.
• Rigor : A conceptual framework can help to ensure the rigor of a research project by providing a theoretical basis for the investigation. This rigor is essential for ensuring that the research project is scientifically valid and produces meaningful results.
• Communication : A conceptual framework can facilitate communication between researchers by providing a shared language and understanding of the key concepts and variables being studied. This communication is essential for collaboration and the advancement of knowledge in the field.
• Generalization : A conceptual framework can help to generalize research findings beyond the specific study by providing a theoretical basis for the investigation. This generalization is essential for the development of knowledge in the field and for informing future research.

Limitations of Conceptual Framework

Limitations of Conceptual Framework are as follows:

• Limited applicability: Conceptual frameworks are often based on existing theory or conceptual models, which may not be applicable to all research problems or contexts. This can limit the usefulness of a conceptual framework in certain situations.
• Lack of empirical support : While a conceptual framework can provide a theoretical basis for a research project, it may not be supported by empirical evidence. This can limit the usefulness of a conceptual framework in guiding empirical research.
• Narrow focus: A conceptual framework can provide a clear focus for a research project, but it may also limit the scope of the investigation. This can make it difficult to address broader research questions or to consider alternative perspectives.
• Over-simplification: A conceptual framework can help to organize and structure research ideas, but it may also over-simplify complex phenomena. This can limit the depth of the investigation and the richness of the data collected.
• Inflexibility : A conceptual framework can provide a structure for organizing research ideas, but it may also be inflexible in the face of new data or unexpected findings. This can limit the ability of researchers to adapt their research project to new information or changing circumstances.
• Difficulty in development : Developing a conceptual framework can be a challenging and time-consuming process. It requires a thorough understanding of existing theory or conceptual models, and may require collaboration with other researchers.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

What is a Hypothesis – Types, Examples and...

Dissertation vs Thesis – Key Differences

Assignment – Types, Examples and Writing Guide

Data Collection – Methods Types and Examples

Context of the Study – Writing Guide and Examples

Limitations in Research – Types, Examples and...

Into the Field: Effective Library Research: Identify Key Research Concepts

• Planning your Research Strategy
• Identify Key Research Concepts
• Identify Information Types
• Find: Where to Search
• Find: How to search
• Using Library Search
• Using Research databases
• Evaluate your search results
• Referencing
• Getting Help

Getting Started: understanding your research topic

• Mapping out Research Concepts - Worksheet

Background reading can also help you to identify key authors and texts (whose bibliographies you can use to generate further ideas). If you find a really useful article, you could mine that for all sorts of other useful related material. 

For example:

Has the author written additional material on the topic?

Does the article have useful keywords or subject terms you can use for further research?

Does the article have references or a bibliography you can use to explore related material?

Does the article link you through to other related material? 

Useful starting points for exploring your research topic in textbooks and reference works are:

Library Search

Sage Knowledge

An important part of the planning process is scoping out the topic areas that you are researching.  It can help to do some brain storming to map out the main topics/concepts you will be looking at.

Mind mapping can be a useful way of capturing these concepts, themes and sub themes - but use whatever technique works best for you.

Ask yourself questions to help you start thinking around your topic, such as;

• Are there particular themes I want to concentrate on? 
• Are there particular works or writers I want to critique? 
• Are there key works that I wish to analyse in detail?

Break your research topic down in to a number of smaller sub topics and address those in turn, before bringing everything together to answer your overarching research query.

This process will help you develop your understanding of exactly what it is you are going to be looking at as you will need to think around your broad topic and start exploring the connections between various sub topics and themes.

As you move through your research you may wish to refresh your scoping exercise in order to encompass new areas you discover as you begin to explore the literature or to close off particular avenues of research that you considered at the outset.

• << Previous: Planning your Research Strategy
• Next: Identify Information Types >>
• Last Updated: Sep 4, 2024 4:20 PM
• URL: https://libguides.exeter.ac.uk/IntoTheField

Key concepts in research

Key concepts, action research.

In education, action research typically refers to a cycle of reflective inquiry to understand and improve practice. The cycle typically involves the steps of identifying the problem, developing a research plan, collecting and analysing data, incorporating findings into planning, implementing actions, and monitoring and evaluation.

An  approach  is the term AERO uses to refer to a practice, program or policy.

association (or correlation)

An  association  is when there is a relationship between two elements, factors or events, but the association cannot be proved or explained. Associations can be positive (for example, higher socioeconomic status is associated with higher student achievement) or negative (for example, higher student absenteeism is associated with lower student achievement).

A baseline is information from an initial point in time, often used for comparison to see how things change over time.

causation (or cause(s)/causal/causal evidence)

Causation  is when one element, factor or event is known to cause another (for example, a particular teaching practice is known to lead to improvements in student test scores). To prove causation between two things (let’s call them  A  and  B ), researchers need to show: 1. that there is an association between  A  and  B ; 2. that  A  happens before  B ; and 3. that  B  is not caused by a third thing (that is,  C  or  D ). In education settings, proving causation is often challenging because of the many influences on teacher and student outcomes.

comparison groups (or control groups)

A comparison group is a group of people in a research study whose responses or outcomes function as a comparison against which the effect of the approach being tested can be measured. Comparison groups receive a different treatment to the group receiving the treatment or approach being tested. There can be any number of comparison groups in a study. A comparison group is called a ‘control group’ when it receives no treatment at all.

context (or contextual factors)

Context is the social, cultural and environmental factors found in research settings. Taking context into account in research studies is important because context can affect the outcomes of research (i.e. evidence generated in one context may not necessarily apply to a different context). Evidence is most relevant when it has been generated in a context similar to the context in which it will be applied. Examples of ‘context’ may include location, demographics of research participants, or the level of organisational support for the particular approach being researched.

Data  is information that is collected and analysed in order to produce findings and/or to inform decision-making. Data can be qualitative (for example, teacher observations or quotes from students) or quantitative (for example, student test scores or attendance data).

effective/ness

An educational approach is effective if it causes (see causation above) a desired change in a particular outcome. This desired change can be an increase in an outcome (for example, increases in student achievement) or it can be a decrease in an outcome (for example, reduction in student absenteeism).

empirical research

Empirical research  presents observable data to substantiate its claims. This data may be primary data (observation and measurement of phenomena or events directly experienced by the researcher) or secondary data (data that has already been collected by other researchers).

Evaluation  is the systematic and objective assessment of an approach. Evaluation provides evidence of what has been done well, what could be done better, the extent to which objectives have been achieved and/or the impact of the approach. This evidence can then be used to inform ongoing decision-making regarding the approach.

evidence (or education evidence)

Evidence  is any type of information that supports an assertion, hypothesis or claim. There are many types of evidence in education, including insights drawn from child or student assessments, classroom observations, recommendations from popular education books and findings from research studies and syntheses. AERO refers to two types of evidence in its work:

• research evidence: This is academic research, such as causal research or synthesis research, which uses rigorous methods to provide insights into educational practice.
• practitioner-generated evidence: This is evidence generated through practitioners in their daily practice (for example, teacher observations, information gained from formative assessments or insights from student feedback on teacher practice).

evidence-based practice

Evidence-based practices  are educational approaches that are backed up by research evidence. This means there is broad consensus from rigorously conducted evaluations that they work. 

evidence-informed practice

Evidence-informed practice  is an educational approach that is applied using evidence from research together with a practitioner’s professional expertise and judgement. The expertise and judgement used by practitioners can be based on knowledge or understanding of their children and students, or the environment in which they work.

experimental design

Experimental design  is the process of planning an experiment that can establish a ‘cause and effect’ relationship (that is, an experiment to determine the specific factors that influence an outcome). Experimental designs account for all other factors that could influence an outcome, so the cause of an effect can be isolated.

generalisable

Findings from a piece of research are generalisable if they are:

• a fair representation of trends in the wider population from which the study participants were sampled and/or
• applicable to settings or contexts other than those in which the study was conducted.

hierarchy of evidence

Hierarchies of evidence are sometimes used to rank evidence according to rigour, helping people to compare and evaluate the quality of different types of research evidence. The higher up on the hierarchy, the more rigorous the methodology. Instead of a hierarchy, AERO uses Standards of evidence – a continuum of four levels of confidence along which rigour and relevance increase.

history effect

A  history effect  is the descriptive term for influences that occur at the same time as an approach is being evaluated and/or influences that occur between the approach being implemented and the outcomes being measured. For example, researchers may want to know the effect of a particular teacher’s writing program on student writing test scores. However, to do this they need to separate the effects of any influences that occur simultaneously (for example, other teachers using different writing strategies with these students) and/or those that occur in the two weeks between the implementation of the writing program and the writing test (for example, a whole-school writing celebration).

hypothesise

To  hypothesise  is to put forward an assumption or idea so that it can be tested to see whether it might be true.

intervention (or treatment)

An approach that is applied to address a problem is sometimes referred to as an  intervention ; for example, a teacher may implement a certain early literacy intervention to support struggling readers. In a research study, an intervention is the approach that is being investigated, tested or evaluated. An intervention is sometimes called a ‘treatment’ in a research study.

literature review

A  literature review  identifies, evaluates and synthesises the relevant literature within a particular field of research. It usually discusses common and emerging approaches, notable patterns and trends, areas of conflict and controversies, and gaps within the relevant literature. Literature reviews do not usually explicitly state the methods used to identify, evaluate or synthesise the relevant literature.

maturation effect

Maturation effects  are the effects in a setting where an approach is applied that occur naturally (that would have occurred anyway), as opposed to the effects that occur as a  result  of the approach. For example, researchers may want to know the effect of a particular educational program on student social and emotional skills. However, social and emotional skills develop over time as children mature, and so researchers need to distinguish between the effect of the educational program and the effects of natural development as a result of students getting older.

meta-analysis

A  meta-analysis  uses statistical methods to summarise the results of individual studies. It is designed to assess the behaviours that lead to a particular approach working and/or to provide an estimate of how much more likely one approach is to work over another. It is the quantitative version of a literature review or systematic review.

mixed-methods research

Mixed-methods research  is research that uses both qualitative (non-numerical data) and quantitative (numerical data) research methods.

A  monograph  is an academic piece of writing on a single subject or aspect of a subject that presents the findings of primary research and/or original scholarship. It is usually written by one person.

outcome measure

An  outcome measure  is an observation that can be used to measure the effect of a particular approach. Outcome measures can be qualitative (such as quotes or observations) or quantitative (such as test scores). For example, when examining whether a particular approach helps students understand a concept, a teacher could set an assessment. The student assessment score could then be used as an outcome measure of student understanding.

peer review

Peer review  is the assessment of research by others working in the same or a related field. The assessment is based on the expertise and experience of the researcher undertaking the review and should be impartial and independent.

A  pilot  study, pilot project or pilot experiment is a small-scale trial that is conducted in order to test the effects of an approach before implementing it on a larger scale. A pilot project can also help to determine feasibility, cost, adverse events and necessary improvements to the approach.

positive effect

If a study shows that an approach leads to the desired outcome, it is said to have a  positive effect . Conversely, if a study shows that an approach has the opposite of the desired outcome, it is said to have a negative effect.

primary study

A primary study is an individual study which reports on data collected and analysed by the researchers themselves. Primary studies are designed according to the type of research question being answered - for example, they may use qualitative methods, quantitative methods, or be mixed-methods research. The findings from a number of primary studies may be synthesised in meta-analyses, systematic reviews, rapid reviews or literature reviews.

qualitative methods

Qualitative methods  involve collecting and analysing non-numerical data, and may include observations, interviews, questionnaires, focus groups, and documents and artifact analysis. Qualitative methods can be used to understand concepts, opinions or experiences as well as to gather in-depth insights into a problem or generate new ideas.

quantitative methods

Quantitative methods  involve collecting and analysing numerical data. Quantitative methods are generally used to find patterns and averages, make predictions, test causal relationships and generalise results to wider populations.

quasi-experimental design

A  quasi-experimental design  is a research methodology that aims to establish a ‘cause and effect’ relationship (that is, to determine the specific factors that influence an outcome), but it cannot completely eliminate all factors that could influence an outcome (that is, there may still be an element of subjectiveness in the findings).

randomised controlled trial

A  randomised controlled trial  is a trial of a particular approach that is set up in such as a way that allows researchers to test its effects. In a randomised controlled trial, subjects are randomly assigned to one of two groups: one receiving the approach) that is being tested (the experimental group), and the other receiving an alternative approach or no approach (the comparison group or control). After the trial period, differences between the groups can be attributed to the approach being tested. Researchers and teachers who use randomisation must take into account ethical concerns, such as whether it is ethical to withhold treatment from subjects in the comparison group.

rapid review

A rapid review is an evidence-based (or ‘objective’) approach to searching and synthesising research evidence. It uses similar steps to a systematic review, but simplifies or skips some steps so that findings can be reached more quickly (making them more current). Rapid reviews answer a precise, clearly defined question and explicitly outline: the methods for data collection, the methods for data extraction, the number of papers included in the review and the methods for data analysis.

relevant evidence

Relevant evidence  is evidence produced in contexts that are similar to one’s own context. Evidence can also be considered relevant when it is derived from a large number of studies conducted over a wide range of contexts.

research (types)

Research  is ‘the creation of new knowledge and/or the use of existing knowledge in a new and creative way so as to generate new concepts, methodologies, inventions and understandings’ (Australian Research Council, 2015). There are many types of research. For example:

• exploratory research  involves investigating an issue or problem. It aims to better understand this problem and sometimes leads to the formation of hypotheses or theories about the problem.
• descriptive research  describes a population, situation or event that is being studied. It focuses on developing knowledge about what exists and what is happening.
• causal research (also known as ‘ evaluative research’ )  uses experimentation to determine whether a cause-and-effect relationship exists between two or more elements, features or factors.
• synthesis research  combines, compares and links existing information to provide a summary and/or new insights or information about a given topic.

research methods

Research methods  are the methods used to conduct research. Research methods are generally classified as ‘qualitative’ or ‘quantitative’. When both methods are used, it is referred to as ‘mixed methods’ research. Qualitative methods involve collecting and analysing non-numerical data (such as  observations, interviews, questionnaires, focus groups, documents and artifacts). Qualitative methods can be used to understand concepts, opinions or experiences as well as to gather in-depth insights into a problem or generate new ideas. Quantitative methods involve collecting and analysing numerical data. Quantitative methods are generally used to find patterns and averages, make predictions, test causal relationships and generalise results to wider populations.

rigour (rigorous evidence)

Evidence is considered  rigorous  when it proves that a particular approach causes a particular outcome. Rigorous evidence is produced by using specialised research methods that can identify the impact of one particular influence. The most common research method used to produce rigorous evidence is the randomised controlled trial. However, there are many other methods that can produce rigorous evidence, whether qualitative, quantitative or mixed methods. What is important in producing rigorous evidence is that the research method can rule out the effects of as many other influences as possible.

A  rubric  is a set of criteria that can be used to make consistent judgements. In education settings, a rubric is usually used to help assess learning or development in a particular area. 

sample size

When studying a large population, it is not possible to include every individual. Research studies usually include a certain number of individuals to represent the population. Those that are included in the study are referred to as a sample of the population.  Sample size  refers to the number of people in a sample. Generally, the larger the sample size, the more accurate the research findings. If a sample is too small, it will not provide a fair picture of the whole population.

selection bias

Selection bias  is when the sample in a study does not represent the general population. Selection bias can occur in two ways: 1. when individuals selected in a research study have characteristics that make them different to the general population; or 2. when individuals opt into a research study and have characteristics different to the general population. Selection bias can affect the outcome of a study, as it is possible that any effect detected by the research is due to the specific characteristics of the sample, rather than the approach itself.

seminal research

Seminal  research is a term used to describe studies that are recognised within a particular discipline as presenting an idea of significant and enduring importance or influence.

statistical significance

A data analysis result is statistically significant when it is likely to be true, rather than by chance. Researchers often use statistical significance to describe the confidence in their results. 

systematic review

A  systematic review  is an evidence-based (or ‘objective’) approach to a literature review. Systematic reviews answer a precise, clearly defined question to produce evidence to underpin a piece of research. A systematic review must explicitly outline: the methods for data collection, the methods for data extraction, the number of papers included in the review, and the methods for data analysis.

Validation  is the process of determining whether the way you are measuring something is appropriate given the research aims and conclusions of the study. There are many considerations when determining whether the way you measure is ‘appropriate’. These include but are not limited to:

• whether the way you measure is reliable (for example, will different researchers score a teacher in the same way when using this observation framework?)
• whether it provides data that accurately represents the outcome (for example, is a student’s score on this twenty-question reading comprehension test an accurate reflection of their reading ability?)
• whether the way you measure should be used given the consequences (for example, should we rely on this data when deciding whether to ask a student to repeat a year?).
• Evidence - use & generation
• The impact of context on evidence-based practices: A rapid literature scan on formative assessment, explicit instruction and mastery learning
• Linking quality and child development in early childhood education and care: Technical report
• Linking quality and child development in early childhood education and care: Research summary
• Actionable insights into Australian education
• Assessing research evidence

Australia's national education evidence body

Fastest Nurse Insight Engine

• MEDICAL ASSISSTANT
• Abdominal Key
• Anesthesia Key
• Basicmedical Key
• Otolaryngology & Ophthalmology
• Musculoskeletal Key
• Obstetric, Gynecology and Pediatric
• Oncology & Hematology
• Plastic Surgery & Dermatology
• Clinical Dentistry
• Radiology Key
• Thoracic Key
• Veterinary Medicine
• Gold Membership

Key concepts in research

2. Key concepts in research Key points • Research is a lot easier to appreciate through an understanding of some of the concepts covered in this chapter. • Quantitative and qualitative approaches to research relate to the different research designs, and are based on philosophical beliefs about the nature of empirical evidence, that is, evidence collected in the real world through the senses. Quantitative research is based on the belief that the truth of a situation exists in an objective state outside the personal views or perceptions of the individual. It emphasises accuracy, and produces numerical data. Qualitative researchers believe that the truth of a situation is produced by our subjective experience, and that we need to look at things from an individual’s point of view. Midwifery is concerned with issues that draw on both beliefs. • Research questions can relate to three levels of exploration. Level-one questions relate to describing one variable, usually about which little is known, or that has rarely been the subject of research. Level-two questions look for relationships between variables but where little theory exists. Level-three questions relate to questions where theory exists and the aim is to test hypotheses based on the theory. • Variables are the elements in which the researcher is interested. In level-three questions, there will be a dependent variable that is the outcome or effect, and one or more independent variables that are presumed to influence or cause the dependent variable. • Concept definitions relate to how the researcher defines the topic in which they are interested. This can be thought of as a dictionary definition or alternative word for the topic of interest. • Operational definitions refer to the way in which a concept is measured. It reduces the vagueness of such words as comfort, pain, and benefit by producing a clear specification of how the researcher will make them visible in a specific study. • Theoretical and conceptual frameworks provide the context and meaning for the ideas and concepts contained in a study. • Reliability, validity, bias and rigour relate first to the extent to which the tool of data collection is accurate and consistent between different measurements, or different researchers. Validity relates to whether the method does measure what the researcher intends it to measure. Bias is the extent to which the findings are distorted either by the choice of subjects or the method of measurement. Rigour is the extent to which the researcher has attempted to conduct the study to ensure accuracy and high-quality research. This chapter will examine some of the important concepts used by researchers and simplify the language by helping you to understand its meaning. The language of research can appear to be composed of ‘jargon’, that is, unhelpful and meaningless words. This can form a barrier to understanding research, as people resent the use of words they do not understand, particularly if they feel they are just being used for effect. However, in reality, the words are a shorthand for complex ideas, and once the most commonly used words are understood, research can take on a completely different level of understanding. The chapter will also cover some of the important issues that researchers face when demonstrating that their research is accurate and carried out to a high standard. These are called ‘methodological issues’. An important starting point is to recognise that research takes many different forms; in this book we will focus specifically on research examining midwifery issues, carried out on the whole by midwives. In Chapter 1 research was defined as the systematic collection of information using carefully designed and controlled methods that answer a specific question objectively and as accurately as possible. This definition can look similar to audit and so lead to some confusion between these two sources of information. The basic difference between the two, however, is that the key role of research is to extend knowledge and understanding of a particular topic or issue through the systematic collection of information that leads to generalisations about the topic examined. Research conclusions are usually placed within a context of existing knowledge. That is, they are usually compared to previous research that has examined the same topic in order to confirm existing knowledge or help to clarify or extend it. The purpose is always to enrich our understanding of the topic so that we can better use, or control its features. Audit, on the other hand, is usually interested in the performance level of a part of a service, and a comparison of results against an agreed standard (or previous audit results) that may allow action to be taken. Watson and Keady (2008) suggest that we can think of audit as management activity concerned with measuring the extent to which agreed standards for clinical practice or procedures are being met or are reaching a sufficient level. Gerrish and Lacey (2010) agree, saying it is a process of measuring care against predetermined standards. This is very different from the way research is designed to increasing our overall understanding of a topic and which can be applied generally, rather than the very specific location to which audit data can apply. One problem in trying to define research is that it is similar to words such as ‘care’, ‘birth’, or ‘midwifery’; it is used as though it consisted of a single entity when, in fact, in can take many different alternative forms. This means that once we decide to study it, we have to learn something about the many forms it can take. At this stage it is useful to think of research as a process that will follow a number of principles or guidelines that will change depending on the type or category of research considered. In this book we will focus on midwifery research, that is, research that explores the problems and issues of direct concern to the midwife and that has implications for the work of the midwife more than any other discipline. Quantitative and qualitative research These two concepts are an ideal starting point for learning about research as they categorise very different approaches to thinking about the role of research and the beliefs or philosophies underpinning its production. This is important as it explains why some studies look very different from others. If we know why they differ we can make the best use of both types. Although Chapter 4 on quantitative and qualitative research explores the differences in more detail in, here we need outline ideas associated with them, and the implications these have for midwifery research and knowledge. Historically, research has been synonymous with the word ‘scientific’, often associated with words like ‘objective’ or ‘accurate’, as these are two key characteristics that ‘good’ research is presumed to posses. Gerrish and Lacey (2010: 8) see a scientific approach to research as indicating ‘a rigorous approach to a systematic form of enquiry’. The philosophy or belief on which this approach is based is that the natural or ‘real’ world does not depend on an individual’s experience of it to exist and that it is open to study and quantification. In other words, it can be measured in some way independent of the person doing the measuring. This type of research can be characterised as ‘ quantitative’ research as it attempts to quantify concepts, such as blood pressure, family size and even pain, in the form of a numeric value. These numbers can be summarised and allow the use of a range of statistical techniques to give the results greater usefulness and meaning ( Chapter 13 ). The purpose of quantitative research is seen as the search for relationships between things in the world so that we can understand the way they act and relate together. The ultimate aim of this understanding is to be able to control the elements in our world that impact on human existence. Our understanding of gravity and how we are influenced by its ‘laws’ is a good example of this measurement and developing of relationships leading to theories about ‘how things are’. In midwifery, an example may be the search for a relationship between physical skin-to-skin contact with the baby at birth and parental feelings of emotional attachment so this pattern can be measured and demonstrated to be advantageous. This scientific view is one ‘ paradigm’ or total way of looking at things (world view) in research. It is the one embraced by medical research as the ‘right’ and ‘proper’ approach for a profession that is concerned with clinical outcomes. These words have been put in inverted commas to show that there may not be total agreement on this statement, and it is open to debate whether the belief applies in all circumstances. We must remember that this is only one approach to research and, without suggesting that it is not an indispensable approach in midwifery, that there are other, just as legitimate ways of conducting a study in addition to counting or measuring something that can also extend midwifery knowledge and practice. Qualitative research (sometimes referred to as representing a naturalistic paradigm as it avoids controlling situations) is the second in the pair of concepts that go to make up the two largest research approaches in midwifery. This has a different view of the characteristics of knowledge and the best way of conducting research to discover, extend or confirm that knowledge. It is believed that the real world can only be understood through our personal experience of it, and everything depends on how we experience and interpret that experience. This explains why some people are afraid of spiders or going to the dentist. It is a product of how people experience them, or the associations they hold for the individual. It does not mean that spiders or dentists themselves are frightening. Naturalistic or qualitative researchers believe that if we are to understand a topic we need to look at it through the eyes of those who experience it and try to understand it from their point of view. This way of thinking creates a different understanding of reality and the type of research we need to capture it accurately. This kind of research produces qualitative data in the form of verbal or written statements and dialogue, or extensive descriptions of observed human activity and behaviour. It uses methods such as interviews or observations, and information taken from documents such as diaries or health records that capture perceptions, interpretations, experiences or understanding. One of the guiding principles of qualitative research is that it tries to capture people’s thoughts and feelings in their own words. So, questionnaires with fixed-choice options would not be classed as qualitative research even though they may have tried to see things from the individual’s point of view, as the list of alternative answers has been developed by the researcher. This format does not allow individuals to express ideas and answers in their own words, only in those of the researchers who have designed the alternatives and selected what they think are relevant alternatives. An important visual distinction between quantitative and qualitative research is the presentation of data. Quantitative research will use numerical or visual forms of data presentation such as tables, bar charts and histograms (more of these in Chapter 13 on statistics). This form of data presentation is not a main feature of qualitative research, although some studies may present a table showing details of the sample, such as age, number of children, etc. It is more usual for qualitative results to avoid numbers and simply present broad theme headings and discuss the type of comments made, often with examples of direct quotations or dialogue. As will be seen in Chapter 4 , these two forms of research are so different they are almost two different entities. The importance of this is that we must avoid criticising qualitative research using the criteria of a quantitative approach. Which of these two approaches is best suited to midwifery research? The answer is, the one that is most appropriate to the question posed. If the midwifery question is one of quantity, or frequency, particularly in regard to clinical outcomes, then a quantitative approach will be appropriate; if the question is one of perceptions, understanding and interpretations, then the best approach will be qualitative. Levels of questions in research There is no shortage of questions that need to be answered through midwifery research. From the research point of view, it is the question posed by the researcher that results in the aim of the research. The aim usually begins with the word ‘to’ as in: … this study aims to examine how a certain group of midwives (the participants) conceptualise the phenomenon of the ‘good’ midwife and the ‘good’ leader. Byrom and Downe (2010: 127) Research questions will differ in their complexity and this will have implications for the way a study is designed. Wood and Ross-Kerr (2006) make a useful distinction between what they call the three levels of research question. These levels are influenced by how much is known about a particular subject, or how much theory exists in relation to it ( Table 2.1 ). The advantage of this system is that it allows you to predict the way a study should be structured to answer a question at each of the levels. Table 2.1 Levels of research questions Level of question Description Type of research Level 1 Examines one variable (or a series of variables) but without looking for patterns between variables. Exploratory situation where little is known about the topic. Quantitative descriptive, e.g. survey Qualitative study: all types are level 1. Level 2

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related posts:

• The basic framework of research
• The research question
• The challenge of the future
• Sampling methods

Stay updated, free articles. Join our Telegram channel

Comments are closed for this page.

Full access? Get Clinical Tree

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

2 Chapter 2: Principles of Research

Principles of research, 2.1  basic concepts.

Before we address where research questions in psychology come from—and what makes them more or less interesting—it is important to understand the kinds of questions that researchers in psychology typically ask. This requires a quick introduction to several basic concepts, many of which we will return to in more detail later in the book.

Research questions in psychology are about variables. A variable is a quantity or quality that varies across people or situations. For example, the height of the students in a psychology class is a variable because it varies from student to student. The sex of the students is also a variable as long as there are both male and female students in the class. A quantitative variable is a quantity, such as height, that is typically measured by assigning a number to each individual. Other examples of quantitative variables include people’s level of talkativeness, how depressed they are, and the number of siblings they have. A categorical variable is a quality, such as sex, and is typically measured by assigning a category label to each individual. Other examples include people’s nationality, their occupation, and whether they are receiving psychotherapy.

“Lots of Candy Could Lead to Violence”

Although researchers in psychology know that  correlation does not imply causation , many journalists do not. Many headlines suggest that a causal relationship has been demonstrated, when a careful reading of the articles shows that it has not because of the directionality and third-variable problems.

One article is about a study showing that children who ate candy every day were more likely than other children to be arrested for a violent offense later in life. But could candy really “lead to” violence, as the headline suggests? What alternative explanations can you think of for this statistical relationship? How could the headline be rewritten so that it is not misleading?

As we will see later in the book, there are various ways that researchers address the directionality and third-variable problems. The most effective, however, is to conduct an experiment. An experiment is a study in which the researcher manipulates the independent variable. For example, instead of simply measuring how much people exercise, a researcher could bring people into a laboratory and randomly assign half of them to run on a treadmill for 15 minutes and the rest to sit on a couch for 15 minutes. Although this seems like a minor addition to the research design, it is extremely important. Now if the exercisers end up in more positive moods than those who did not exercise, it cannot be because their moods affected how much they exercised (because it was the researcher who determined how much they exercised). Likewise, it cannot be because some third variable (e.g., physical health) affected both how much they exercised and what mood they were in (because, again, it was the researcher who determined how much they exercised). Thus experiments eliminate the directionality and third-variable problems and allow researchers to draw firm conclusions about causal relationships.

2.2  Generating Good Research Questions

Good research must begin with a good research question. Yet coming up with good research questions is something that novice researchers often find difficult and stressful. One reason is that this is a creative process that can appear mysterious—even magical—with experienced researchers seeming to pull interesting research questions out of thin air. However, psychological research on creativity has shown that it is neither as mysterious nor as magical as it appears. It is largely the product of ordinary thinking strategies and persistence (Weisberg, 1993). This section covers some fairly simple strategies for finding general research ideas, turning those ideas into empirically testable research questions, and finally evaluating those questions in terms of how interesting they are and how feasible they would be to answer.

Finding Inspiration

Research questions often begin as more general research ideas—usually focusing on some behaviour or psychological characteristic: talkativeness, memory for touches, depression, bungee jumping, and so on. Before looking at how to turn such ideas into empirically testable research questions, it is worth looking at where such ideas come from in the first place. Three of the most common sources of inspiration are informal observations, practical problems, and previous research.

Informal observations include direct observations of our own and others’ behaviour as well as secondhand observations from nonscientific sources such as newspapers, books, and so on. For example, you might notice that you always seem to be in the slowest moving line at the grocery store. Could it be that most people think the same thing? Or you might read in the local newspaper about people donating money and food to a local family whose house has burned down and begin to wonder about who makes such donations and why. Some of the most famous research in psychology has been inspired by informal observations. Stanley Milgram’s famous research on obedience, for example, was inspired in part by journalistic reports of the trials of accused Nazi war criminals—many of whom claimed that they were only obeying orders. This led him to wonder about the extent to which ordinary people will commit immoral acts simply because they are ordered to do so by an authority figure (Milgram, 1963).

Practical problems can also inspire research ideas, leading directly to applied research in such domains as law, health, education, and sports. Can human figure drawings help children remember details about being physically or sexually abused? How effective is psychotherapy for depression compared to drug therapy? To what extent do cell phones impair people’s driving ability? How can we teach children to read more efficiently? What is the best mental preparation for running a marathon?

Probably the most common inspiration for new research ideas, however, is previous research. Recall that science is a kind of large-scale collaboration in which many different researchers read and evaluate each other’s work and conduct new studies to build on it. Of course, experienced researchers are familiar with previous research in their area of expertise and probably have a long list of ideas. This suggests that novice researchers can find inspiration by consulting with a more experienced researcher (e.g., students can consult a faculty member). But they can also find inspiration by picking up a copy of almost any professional journal and reading the titles and abstracts. In one typical issue of Psychological Science, for example, you can find articles on the perception of shapes, anti-Semitism, police lineups, the meaning of death, second-language learning, people who seek negative emotional experiences, and many other topics. If you can narrow your interests down to a particular topic (e.g., memory) or domain (e.g., health care), you can also look through more specific journals, such as Memory Cognition or Health Psychology.

Generating Empirically Testable Research Questions

Once you have a research idea, you need to use it to generate one or more empirically testable research questions, that is, questions expressed in terms of a single variable or relationship between variables. One way to do this is to look closely at the discussion section in a recent research article on the topic. This is the last major section of the article, in which the researchers summarize their results, interpret them in the context of past research, and suggest directions for future research. These suggestions often take the form of specific research questions, which you can then try to answer with additional research. This can be a good strategy because it is likely that the suggested questions have already been identified as interesting and important by experienced researchers.

But you may also want to generate your own research questions. How can you do this? First, if you have a particular behaviour or psychological characteristic in mind, you can simply conceptualize it as a variable and ask how frequent or intense it is. How many words on average do people speak per day? How accurate are children’s memories of being touched? What percentage of people have sought professional help for depression? If the question has never been studied scientifically—which is something that you will learn in your literature review—then it might be interesting and worth pursuing.

If scientific research has already answered the question of how frequent or intense the behaviour or characteristic is, then you should consider turning it into a question about a statistical relationship between that behaviour or characteristic and some other variable. One way to do this is to ask yourself the following series of more general questions and write down all the answers you can think of.

·         What are some possible causes of the behaviour or characteristic?

·         What are some possible effects of the behaviour or characteristic?

·         What types of people might exhibit more or less of the behaviour or characteristic?

·         What types of situations might elicit more or less of the behaviour or characteristic?

In general, each answer you write down can be conceptualized as a second variable, suggesting a question about a statistical relationship. If you were interested in talkativeness, for example, it might occur to you that a possible cause of this psychological characteristic is family size. Is there a statistical relationship between family size and talkativeness? Or it might occur to you that people seem to be more talkative in same-sex groups than mixed-sex groups. Is there a difference in the average level of talkativeness of people in same-sex groups and people in mixed-sex groups? This approach should allow you to generate many different empirically testable questions about almost any behaviour or psychological characteristic.

If through this process you generate a question that has never been studied scientifically—which again is something that you will learn in your literature review—then it might be interesting and worth pursuing. But what if you find that it has been studied scientifically? Although novice researchers often want to give up and move on to a new question at this point, this is not necessarily a good strategy. For one thing, the fact that the question has been studied scientifically and the research published suggests that it is of interest to the scientific community. For another, the question can almost certainly be refined so that its answer will still contribute something new to the research literature. Again, asking yourself a series of more general questions about the statistical relationship is a good strategy.

·         Are there other ways to operationally define the variables?

·         Are there types of people for whom the statistical relationship might be stronger or weaker?

·         Are there situations in which the statistical relationship might be stronger or weaker—including situations with practical importance?

For example, research has shown that women and men speak about the same number of words per day—but this was when talkativeness was measured in terms of the number of words spoken per day among college students in the United States and Mexico. We can still ask whether other ways of measuring talkativeness—perhaps the number of different people spoken to each day—produce the same result. Or we can ask whether studying elderly people or people from other cultures produces the same result. Again, this approach should help you generate many different research questions about almost any statistical relationship.

2.3  Evaluating Research Questions

Researchers usually generate many more research questions than they ever attempt to answer. This means they must have some way of evaluating the research questions they generate so that they can choose which ones to pursue. In this section, we consider two criteria for evaluating research questions: the interestingness of the question and the feasibility of answering it.

Interestingness

How often do people tie their shoes? Do people feel pain when you punch them in the jaw? Are women more likely to wear makeup than men? Do people prefer vanilla or chocolate ice cream? Although it would be a fairly simple matter to design a study and collect data to answer these questions, you probably would not want to because they are not interesting. We are not talking here about whether a research question is interesting to us personally but whether it is interesting to people more generally and, especially, to the scientific community. But what makes a research question interesting in this sense? Here we look at three factors that affect the interestingness of a research question: the answer is in doubt, the answer fills a gap in the research literature, and the answer has important practical implications.

First, a research question is interesting to the extent that its answer is in doubt. Obviously, questions that have been answered by scientific research are no longer interesting as the subject of new empirical research. But the fact that a question has not been answered by scientific research does not necessarily make it interesting. There has to be some reasonable chance that the answer to the question will be something that we did not already know. But how can you assess this before actually collecting data? One approach is to try to think of reasons to expect different answers to the question—especially ones that seem to conflict with common sense. If you can think of reasons to expect at least two different answers, then the question might be interesting. If you can think of reasons to expect only one answer, then it probably is not. The question of whether women are more talkative than men is interesting because there are reasons to expect both answers. The existence of the stereotype itself suggests the answer could be yes, but the fact that women’s and men’s verbal abilities are fairly similar suggests the answer could be no. The question of whether people feel pain when you punch them in the jaw is not interesting because there is absolutely no reason to think that the answer could be anything other than a resounding yes.

A second important factor to consider when deciding if a research question is interesting is whether answering it will fill a gap in the research literature. Again, this means in part that the question has not already been answered by scientific research. But it also means that the question is in some sense a natural one for people who are familiar with the research literature. For example, the question of whether human figure drawings can help children recall touch information would be likely to occur to anyone who was familiar with research on the unreliability of eyewitness memory (especially in children) and the ineffectiveness of some alternative interviewing techniques.

A final factor to consider when deciding whether a research question is interesting is whether its answer has important practical implications. Again, the question of whether human figure drawings help children recall information about being touched has important implications for how children are interviewed in physical and sexual abuse cases. The question of whether cell phone use impairs driving is interesting because it is relevant to the personal safety of everyone who travels by car and to the debate over whether cell phone use should be restricted by law.

Feasibility

A second important criterion for evaluating research questions is the feasibility of successfully answering them. There are many factors that affect feasibility, including time, money, equipment and materials, technical knowledge and skill, and access to research participants. Clearly, researchers need to take these factors into account so that they do not waste time and effort pursuing research that they cannot complete successfully.

Looking through a sample of professional journals in psychology will reveal many studies that are complicated and difficult to carry out. These include longitudinal designs in which participants are tracked over many years, neuroimaging studies in which participants’ brain activity is measured while they carry out various mental tasks, and complex non-experimental studies involving several variables and complicated statistical analyses. Keep in mind, though, that such research tends to be carried out by teams of highly trained researchers whose work is often supported in part by government and private grants. Keep in mind also that research does not have to be complicated or difficult to produce interesting and important results. Looking through a sample of professional journals will also reveal studies that are relatively simple and easy to carry out—perhaps involving a convenience sample of college students and a paper-and-pencil task.

A final point here is that it is generally good practice to use methods that have already been used successfully by other researchers. For example, if you want to manipulate people’s moods to make some of them happy, it would be a good idea to use one of the many approaches that have been used successfully by other researchers (e.g., paying them a compliment). This is good not only for the sake of feasibility—the approach is “tried and true”—but also because it provides greater continuity with previous research. This makes it easier to compare your results with those of other researchers and to understand the implications of their research for yours, and vice versa.

Key Takeaways

·         Research ideas can come from a variety of sources, including informal observations, practical problems, and previous research.

·         Research questions expressed in terms of variables and relationships between variables can be suggested by other researchers or generated by asking a series of more general questions about the behaviour or psychological characteristic of interest.

·         It is important to evaluate how interesting a research question is before designing a study and collecting data to answer it. Factors that affect interestingness are the extent to which the answer is in doubt, whether it fills a gap in the research literature, and whether it has important practical implications.

·         It is also important to evaluate how feasible a research question will be to answer. Factors that affect feasibility include time, money, technical knowledge and skill, and access to special equipment and research participants.

References from Chapter 2

Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67, 371–378.

Stanovich, K. E. (2010). How to think straight about psychology (9th ed.). Boston, MA: Allyn Bacon.

Weisberg, R. W. (1993). Creativity: Beyond the myth of genius. New York, NY: Freeman.

Research Methods in Psychology & Neuroscience Copyright © by Dalhousie University Introduction to Psychology and Neuroscience Team. All Rights Reserved.

Ontology & Epistemology

Thinking about what you know and how you know what you know involves questions of ontology and epistemology. Perhaps you have heard these concepts before in a philosophy class? These concepts are relevant to the work of sociologists as well. As sociologists (those who undertake socially-focused research), we want to understand some aspect of our social world. Usually, we are not starting with zero knowledge. In fact, we usually start with some understanding of three concepts: 1) what is; 2) what can be known about what is; and, 3) what the best mechanism happens to be for learning about what is (Saylor Academy, 2012). In the following sections, we will define these concepts and provide an example of the terms, ontology and epistemology.

Ontology is a Greek word that means the study, theory, or science of being. Ontology is concerned with the what is or the nature of reality (Saunders, Lewis, & Thornhill, 2009). It can involve some very large and difficult to answer questions, such as:

• What is the purpose of life?
• What, if anything, exists beyond our universe?
• What categories does it belong to?
• Is there such a thing as objective reality?
• What does the verb “to be” mean?

Ontology is comprised of two aspects: objectivism and subjectivism. Objectivism means that social entities exist externally to the social actors who are concerned with their existence. Subjectivism means that social phenomena are created from the perceptions and actions of the social actors who are concerned with their existence (Saunders, et al., 2009). Figure 1.2 provides an example of a similar research project to be undertaken by two different students. While the projects being proposed by the students are similar, they each have different research questions. Read the scenario and then answer the questions that follow.

Subjectivist and objectivist approaches (adapted from Saunders et al., 2009)

Ana is an Emergency & Security Management Studies (ESMS) student at a local college. She is just beginning her capstone research project and she plans to do research at the City of Vancouver. Her research question is: What is the role of City of Vancouver managers in the Emergency Management Department (EMD) in enabling positive community relationships? She will be collecting data related to the roles and duties of managers in enabling positive community relationships.

Robert is also an ESMS student at the same college. He, too, will be undertaking his research at the City of Vancouver. His research question is: What is the effect of the City of Vancouver’s corporate culture in enabling EMD managers to develop a positive relationship with the local community? He will be collecting data related to perceptions of corporate culture and its effect on enabling positive community-emergency management department relationships.

Before the students begin collecting data, they learn that six months ago, the long-time emergency department manager and assistance manager both retired. They have been replaced by two senior staff managers who have Bachelor’s degrees in Emergency Services Management. These new managers are considered more up-to-date and knowledgeable on emergency services management, given their specialized academic training and practical on-the-job work experience in this department. The new managers have essentially the same job duties and operate under the same procedures as the managers they replaced. When Ana and Robert approach the managers to ask them to participate in their separate studies, the new managers state that they are just new on the job and probably cannot answer the research questions; they decline to participate. Ana and Robert are worried that they will need to start all over again with a new research project. They return to their supervisors to get their opinions on what they should do.

Before reading about their supervisors’ responses, answer the following questions:

• Is Ana’s research question indicative of an objectivist or a subjectivist approach?
• Is Robert’s research question indicative of an objectivist or a subjectivist approach?
• Given your answer in question 1, which managers could Ana interview (new, old, or both) for her research study? Why?
• Given your answer in question 2, which managers could Robert interview (new, old, or both) for his research study? Why?

Ana’s supervisor tells her that her research question is set up for an objectivist approach. Her supervisor tells her that in her study the social entity (the City) exists in reality external to the social actors (the managers), i.e., there is a formal management structure at the City that has largely remained unchanged since the old managers left and the new ones started. The procedures remain the same regardless of whoever occupies those positions. As such, Ana, using an objectivist approach, could state that the new managers have job descriptions which describe their duties and that they are a part of a formal structure with a hierarchy of people reporting to them and to whom they report. She could further state that this hierarchy, which is unique to this organization, also resembles hierarchies found in other similar organizations. As such, she can argue that the new managers will be able to speak about the role they play in enabling positive community relationships. Their answers would likely be no different than those of the old managers, because the management structure and the procedures remain the same. Therefore, she could go back to the new managers and ask them to participate in her research study.

Robert’s supervisor tells him that his research is set up for a subjectivist approach. In his study, the social phenomena (the effect of corporate culture on the relationship with the community) is created from the perceptions and consequent actions of the social actors (the managers); i.e., the corporate culture at the City continually influences the process of social interaction, and these interactions influence perceptions of the relationship with the community. The relationship is in a constant state of revision. As such, Robert, using a subjectivist approach, could state that the new managers may have had few interactions with the community members to date and therefore may not be fully cognizant of how the corporate culture affects the department’s relationship with the community. While it would be important to get the new managers’ perceptions, he would also need to speak with the previous managers to get their perceptions from the time they were employed in their positions. This is because the community-department relationship is in a state of constant revision, which is influenced by the various managers’ perceptions of the corporate culture and its effect on their ability to form positive community relationships. Therefore, he could go back to the current managers and ask them to participate in his study, and also ask that the department please contact the previous managers to see if they would be willing to participate in his study.

As you can see the research question of each study guides the decision as to whether the researcher should take a subjective or an objective ontological approach. This decision, in turn, guides their approach to the research study, including whom they should interview.

Epistemology

Epistemology has to do with knowledge. Rather than dealing with questions about what is, epistemology deals with questions of how we know what is.  In sociology, there are many ways to uncover knowledge. We might interview people to understand public opinion about a topic, or perhaps observe them in their natural environment. We could avoid face-to-face interaction altogether by mailing people surveys to complete on their own or by reading people’s opinions in newspaper editorials. Each method of data collection comes with its own set of epistemological assumptions about how to find things out (Saylor Academy, 2012). There are two main subsections of epistemology: positivist and interpretivist philosophies. We will examine these philosophies or paradigms in the following sections.

Research Methods, Data Collection and Ethics Copyright © 2020 by Valerie Sheppard is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Share This Book

2nd Edition

Research Methods The Key Concepts

• Taylor & Francis eBooks (Institutional Purchase) Opens in new tab or window

Description

This book provides an overview of ninety key concepts which often trouble those who are new to researching within the social sciences. It covers theories of knowledge, methodologies and methods. Each entry offers a definition of a concept, shows how researchers have used that concept in their research and discusses difficulties that the concept presents. The book supports those undertaking their own social research projects by providing detailed critical commentary on key concepts in a particularly accessible way. In exploring these concepts, a wide range of research reports across many different fields are described. These include not only classic accounts, but also a broad selection of recent studies, some written by new researchers. The book will be useful for higher-education students carrying out projects within social science faculties at the end of their first degree or during a master's programme, though it will also be helpful for those undertaking doctoral research, and some entries have been written with the production of a thesis in mind. This second edition of Research Methods: The Key Concepts provides a more comprehensive and up-to-date coverage, as old entries have been updated and 19 new entries added. It helps new researchers to navigate the changing landscape of social research by recognising a) the changes in the ways researchers are thinking about knowledge and acquiring knowledge, b) the increasing use of digital tools to collect data, and c) the desire many contemporary researchers feel to promote social justice through their research.

Table of Contents

Michael Hammond leads an MA in social science research and is Reader in Education at the University of Warwick, UK. Jerry Wellington was a Professor and Head of Research Degrees in the School of Education University of Sheffield, UK, and is now an educational consultant.

About VitalSource eBooks

VitalSource is a leading provider of eBooks.

• Access your materials anywhere, at anytime.
• Customer preferences like text size, font type, page color and more.
• Take annotations in line as you read.

Multiple eBook Copies

This eBook is already in your shopping cart. If you would like to replace it with a different purchasing option please remove the current eBook option from your cart.

Book Preview

The country you have selected will result in the following:

• Product pricing will be adjusted to match the corresponding currency.
• The title Perception will be removed from your cart because it is not available in this region.

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

4-Precision Searching

2. Main Concepts

Identify the main concepts in your research question by selecting nouns important to the meaning of your question. Leave out words that don’t help the search, such as adjectives, adverbs, prepositions and, usually, verbs. Nouns that you would use to tag your research question so you could find it later are likely to be its main concepts.

Finding the main concepts in a research question is a lot like finding the main idea in an essay or story. Often the main idea is in the first paragraph, but not always. Sometimes it’s in a later paragraph or even in the conclusion. The same is true with research questions—the main concepts can be at the beginning, middle, or end. Stick to the nouns and only what’s necessary, not already implied. Don’t read in concepts that are not really there. Be alert to words that may have connotations other than the concept you are interested in. For instance, if you identify depression as a main idea, be aware that the search engine won’t automatically know whether you mean depression as a psychological state or as a condition of the economy or as a weather characteristic.

Example: How are birds affected by wind turbines?

The main concepts are birds and wind turbines. Avoid terms like affect (except the noun) and effect as search terms, even when you’re looking for studies that report effects or effectiveness.

Example: What lesson plans are available for teaching fractions?

The main concepts are lesson plans and fractions. Stick to what’s necessary. For instance, don’t include: children—nothing in the research question suggests the lesson plans are for children; teaching—teaching isn’t necessary because lesson plans imply teaching; available—available is not necessary.

Sometimes your research question itself can seem complicated. Make sure you’ve stated the question as precisely as possible (as you learned in Research Questions ). Then apply our advice for identifying main concepts as usual.

Activity: Main Concepts

Open activity in a web browser.

Activity: More Main Concepts

Example: does the use of mobile technologies by teachers and students in the classroom distract or enhance the educational experience.

Acceptable main concepts are teaching methods and mobile technology. Another possibility is mobile technologies and education. Watch out for overly broad terms. For example, don’t include:

• Educational experience (it misses mobile technology).
• Classroom distractions (too broad because there are distractions that have nothing to do with technology).
• Technology (too broad because the question is focused on mobile technology).

Choosing & Using Sources: A Guide to Academic Research Copyright © 2015 by Teaching & Learning, Ohio State University Libraries is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

Share This Book

Systematic searching: 2. Identifying key concepts

• Grey literature
• Handsearching
• 1. From a topic to a research question
• 2. Identifying key concepts
• 3. Coming up with keywords
• 4. Finding database-specific subject headings
• 5. Focusing the search
• 6. Building search strings
• 7. Running the search in databases
• 8. Limiting the search
• 9. Evaluating the search result
• Finding full texts
• Documenting the search
• Managing references
• Quality assessment
• Handbooks and methods guides
• Finnish This link opens in a new window

Identifying key concepts

The research question or questions you formulate are not directly suitable to use as search terms. Key concepts should be identified for the search.  Concepts should be considered as separate topics or groups of concepts.

Your research question will determine how many concept groups you need. Sometimes you can get good results with just one concept (a rare term), typically a search includes two or three concepts. 

Nursing students' hand hygiene skills 

Research question: Which factors contribute to nursing students' hand hygiene skills during their studies?

• << Previous: 1. From a topic to a research question
• Next: 3. Coming up with keywords >>
• Last Updated: Mar 25, 2024 7:41 AM
• URL: https://libguides.tuni.fi/systematic-searching

Email: [email protected] P. 0294 520 900

Saavutettavuusseloste Accessibility statement Palaute | Feedback

the phd writer

Developing key concepts.

Which concepts will you need to explore and develop most carefully? The answer will only become apparent as your research progresses, but you will certainly need to consider in relation to your research:

• Concepts that feature prominently in research questions or claims
• Concepts that are relatively new or unfamiliar to readers in your field
• Concepts that appear to be unstable or fluid
• Concepts that appear to be contested by certain writers

A useful starting-point might be to look at the efforts of other writers. There are some notable examples to follow:

Raymond Williams’ “Keywords” and the “Keywords Project”

Although the “Keywords” book was published in 1983, it is still a source of inspiration to many writers in Social Science or Arts and Humanities disciplines. It demonstrates how difficult concepts can be fully explored and different interpretations carefully considered. The starting-point for Williams was a consideration of how the meaning of ‘culture’ appeared to be changing in the immediate post-war period.

For further details see: http://keywords.pitt.edu/williams_keywords.html

“New Keywords” and Discipline-Specific Guides

There are many other books that can serve as a useful point of reference when you are struggling to unpack certain concepts. The best-known generic example is “New Keywords” published by Wiley. Another publisher, Palgrave Macmillan, has produced a series of excellent guides in specific subject areas. See:

https://books.google.co.uk/books/about/New_Keywords.html?id=14nbHemut9MC

https://books.google.co.uk/books/about/Key_Concepts_in_Politics.html?id=XrLDQgAACAAJ

Share this:

• Already have a WordPress.com account? Log in now.
• Subscribe Subscribed
• Copy shortlink
• Report this content
• View post in Reader
• Manage subscriptions
• Collapse this bar

Theoretical Definition in Psychology: Key Concepts and Applications

Theoretical definitions, the unsung heroes of psychological research, serve as the backbone of our understanding of the human mind and behavior, shaping the way we conceptualize, investigate, and apply knowledge in this ever-evolving field. These intellectual constructs are the silent architects of our psychological understanding, quietly guiding researchers and practitioners through the labyrinth of human cognition and behavior.

Imagine, if you will, a world without theoretical definitions in psychology. It would be akin to navigating a vast, uncharted ocean without a compass or map. We’d be adrift, unable to make sense of the complex phenomena we observe in human behavior and mental processes. Thankfully, we’re not left to flounder in such a sea of uncertainty. Theoretical definitions provide us with the conceptual tools we need to chart our course through the murky waters of the human psyche.

But what exactly are these theoretical definitions, and why are they so crucial to psychological research? At their core, theoretical definitions are carefully crafted explanations of psychological constructs that go beyond simple dictionary definitions. They’re the result of years of research, debate, and refinement, distilling complex ideas into manageable concepts that can be studied and applied in real-world settings.

It’s important to note that theoretical definitions are distinct from their operational counterparts. While operational definitions in psychology focus on how a concept is measured or observed in a specific study, theoretical definitions delve into the underlying nature of the concept itself. They’re the “why” behind the “how,” providing a deeper understanding of psychological phenomena.

The history of theoretical definitions in psychology is as rich and varied as the field itself. From the early days of introspection and psychoanalysis to the cognitive revolution and beyond, psychologists have been grappling with how to define and understand the intricacies of human thought and behavior. Each era has brought new insights and perspectives, shaping and reshaping our theoretical understanding of the mind.

The Building Blocks of Theoretical Definitions

Now, let’s roll up our sleeves and dive into the nitty-gritty of what makes a good theoretical definition in psychology. It’s not just about stringing together a bunch of fancy words – there’s a real art and science to it.

First up, we’ve got the conceptual framework. Think of this as the skeleton of your definition. It’s the basic structure that outlines what your concept is and how it relates to other psychological ideas. For example, if you’re defining “intelligence,” your conceptual framework might touch on cognitive processes, problem-solving abilities, and adaptability.

Next, we’ve got underlying assumptions. These are the unspoken beliefs or premises that your definition rests upon. In psychology, these assumptions often relate to human nature, the role of the environment, or the nature of consciousness. They’re like the foundation of a house – you might not see them, but they’re crucial for supporting everything else.

Then there’s explanatory power. A good theoretical definition doesn’t just describe a concept; it helps explain how it works and why it’s important. It should give us those “aha!” moments where suddenly, human behavior makes a little more sense.

Last but not least, we’ve got testability and falsifiability. This is where the rubber meets the road in scientific psychology. A theoretical definition needs to be specific enough that we can design experiments to test it. And – here’s the kicker – it needs to be possible to prove it wrong. That might sound counterintuitive, but it’s a crucial part of the scientific process. After all, if a theory can’t be disproven, how can we ever be sure it’s truly accurate?

A Smorgasbord of Theoretical Definitions

Now that we’ve got the ingredients, let’s look at the different flavors of theoretical definitions you might encounter in psychology. It’s like a buffet of brain-bending concepts!

First on the menu, we’ve got construct definitions. These are the bread and butter of psychological theory. They define abstract concepts that we can’t directly observe but believe exist based on other observable behaviors. Think of things like “intelligence,” “personality,” or “motivation.” We can’t see these directly, but we infer their existence from how people act and think.

Next up, we’ve got hypothetical constructs. These are similar to construct definitions, but they’re a bit more speculative. They’re educated guesses about what might be going on “under the hood” of human behavior. For example, the concept of the “unconscious mind” in psychoanalytic theory is a hypothetical construct. We can’t directly observe it, but it helps explain certain patterns of behavior.

Then we’ve got intervening variables. These are like the middlemen of psychological theory. They’re hypothetical processes that help explain the relationship between what we can observe (like behavior) and what we’re trying to understand (like mental states). For instance, in learning theory, “attention” might be considered an intervening variable between a stimulus and a learned response.

Last but not least, we’ve got functional definitions. These focus on what a psychological concept does rather than what it is. It’s like defining a chair not by its physical characteristics, but by the fact that it’s something you sit on. In psychology, we might functionally define “memory” as the process that allows us to store and retrieve information, rather than trying to pinpoint its exact neurological basis.

Crafting Theoretical Definitions: A Labor of Love

Creating a theoretical definition isn’t something you do on a whim over your morning coffee. It’s a meticulous process that requires a deep dive into existing knowledge and a keen eye for gaps in our understanding.

The journey often begins with a thorough literature review. Researchers pore over existing theories and studies, trying to get a handle on what we already know about a concept. It’s like being a detective, sifting through clues to piece together a coherent picture. This process helps identify gaps in our current knowledge – the missing pieces of the puzzle that our new definition might help fill.

Once we’ve got a good grasp of the existing landscape, it’s time to start formulating hypotheses. This is where creativity meets scientific rigor. Researchers ask themselves, “What if…?” and “How might…?” questions, trying to come up with new ways of understanding psychological phenomena.

The next step is refining and operationalizing these concepts. This is where theoretical definitions start to bridge the gap with their operational counterparts. Researchers need to figure out how their shiny new concept can be measured or observed in the real world. It’s like translating a beautiful piece of poetry into a different language – you want to keep the essence and meaning, but make it accessible in a new context.

Theoretical Definitions in Action

So, we’ve got our theoretical definitions all polished and ready to go. But what do we actually do with them? Well, buckle up, because this is where things get exciting!

First and foremost, theoretical definitions are the building blocks of psychological theories. They’re the raw materials that researchers use to construct models of how the mind works. It’s like playing with really sophisticated Lego – each definition is a piece that can be combined with others to create a bigger picture of human psychology.

These definitions also serve as guiding lights for empirical studies. They help researchers decide what questions to ask, what variables to measure, and how to interpret their results. Without solid theoretical definitions, we’d be stumbling around in the dark, not knowing what to look for or how to make sense of what we find.

When it comes to interpreting research findings, theoretical definitions are like the Rosetta Stone of psychology. They help us translate raw data into meaningful insights about human behavior and mental processes. For example, when we see certain patterns of brain activity, our theoretical definitions of cognitive processes help us understand what those patterns might mean.

Ultimately, the goal of all this theorizing and defining is to advance our scientific understanding of psychological phenomena. Each well-crafted theoretical definition is a step forward in our quest to unravel the mysteries of the human mind. It’s like we’re all working together on a massive jigsaw puzzle, with each definition helping to fill in another piece of the big picture.

The Thorny Side of Theoretical Definitions

Now, before we get too carried away singing the praises of theoretical definitions, let’s take a moment to acknowledge that they’re not without their challenges. Like any tool in science, they have their limitations and pitfalls.

One of the biggest hurdles is the inherent ambiguity and subjectivity in psychological concepts. Unlike in physics, where we can precisely define things like mass or velocity, psychological constructs are often fuzzy and open to interpretation. What exactly do we mean by “intelligence” or “personality”? Ask ten psychologists and you might get eleven different answers!

Cultural and contextual influences also throw a wrench in the works. Many psychological concepts that we once thought were universal turn out to be heavily influenced by culture. What’s considered “normal” behavior in one society might be seen as odd or even pathological in another. This makes it tricky to create theoretical definitions that hold up across different cultural contexts.

Another challenge is the evolving nature of psychological concepts. As our understanding of the mind and behavior grows, our definitions need to keep pace. It’s like trying to hit a moving target – just when we think we’ve nailed down a definition, new research comes along that forces us to rethink our assumptions.

Finally, there’s the tricky balance between specificity and generalizability. We want our theoretical definitions to be specific enough to be useful, but not so narrow that they only apply in very limited circumstances. It’s a bit like walking a tightrope – lean too far in either direction and you risk falling off.

The Road Ahead for Theoretical Definitions

As we wrap up our journey through the world of theoretical definitions in psychology, it’s worth taking a moment to reflect on their importance and consider what the future might hold.

Theoretical definitions are more than just academic exercises. They’re the conceptual tools that allow us to make sense of the complex tapestry of human behavior and mental processes. Without them, we’d be lost in a sea of observations with no way to organize or understand what we’re seeing.

Looking to the future, there are exciting possibilities for improving how we create and use theoretical definitions in psychology. Advances in neuroscience and technology are giving us new ways to observe and measure psychological phenomena. This could lead to more precise and nuanced definitions of long-standing concepts.

There’s also a growing recognition of the need for more diverse perspectives in psychology. As the field becomes more global and inclusive, we’re likely to see theoretical definitions that better reflect the rich variety of human experiences across different cultures and contexts.

The implications of these developments for psychological research and practice are profound. Better theoretical definitions could lead to more targeted interventions in clinical psychology, more effective educational strategies, and deeper insights into human behavior in fields like organizational psychology.

In conclusion, theoretical definitions might not be the flashiest part of psychology, but they’re absolutely crucial to the field’s progress. They’re the silent workhorses that keep psychological research moving forward, constantly pushing the boundaries of our understanding of the human mind and behavior. So the next time you come across a theoretical definition in psychology, take a moment to appreciate the thought, debate, and refinement that went into crafting it. It’s not just a string of words – it’s a key that helps unlock the mysteries of the human psyche.

References:

1. Bunge, M. (1999). The sociology-philosophy connection. Transaction Publishers.

2. Cacioppo, J. T., & Berntson, G. G. (1992). Social psychological contributions to the decade of the brain: Doctrine of multilevel analysis. American Psychologist, 47(8), 1019-1028.

3. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), 281-302.

4. Danziger, K. (1997). Naming the mind: How psychology found its language. Sage Publications.

5. Gergen, K. J. (1985). The social constructionist movement in modern psychology. American Psychologist, 40(3), 266-275.

6. Henriques, G. (2003). The tree of knowledge system and the theoretical unification of psychology. Review of General Psychology, 7(2), 150-182.

7. Machado, A., & Silva, F. J. (2007). Toward a richer view of the scientific method: The role of conceptual analysis. American Psychologist, 62(7), 671-681.

8. Slaney, K. L., & Racine, T. P. (2013). What’s in a name? Psychology’s ever evasive construct. New Ideas in Psychology, 31(1), 4-12.

9. Sternberg, R. J. (1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.

10. Teo, T. (2009). Philosophical concerns in critical psychology. In D. Fox, I. Prilleltensky, & S. Austin (Eds.), Critical psychology: An introduction (2nd ed., pp. 36-53). Sage Publications.

Similar Posts

Sense of Self in Psychology: Exploring Identity and Self-Awareness

A sense of self, the elusive yet essential fabric of our psychological tapestry, weaves together the threads of identity, self-awareness, and personal growth, shaping the very essence of who we are and how we navigate life’s complexities. It’s a concept that has fascinated philosophers, psychologists, and thinkers for centuries, yet it remains as mysterious as…

Complex Definition Psychology: Understanding Psychological Complexes and Their Impact

From Freud’s Oedipus complex to lesser-known phenomena like the Messiah complex, psychological complexes shape our thoughts, emotions, and behaviors in ways that often elude our conscious understanding. These intricate mental constructs, woven from the threads of our experiences, beliefs, and unconscious desires, can profoundly influence our lives without us even realizing it. It’s like having…

Love Language Psychology: Decoding the Science of Affection

Unraveling the intricate tapestry of affection, love language psychology delves into the subtle nuances of how we express and experience love, offering profound insights that can transform our relationships and deepen our connections with others. This fascinating field of study has captivated the hearts and minds of researchers, therapists, and couples alike, shedding light on…

Autonomous State Psychology: Exploring Self-Determination and Mental Well-being

As humans, we innately yearn for the freedom to shape our lives according to our own desires, a concept deeply rooted in the core of autonomous state psychology. This fascinating field of study explores the intricate relationship between our innate need for self-determination and our overall mental well-being. It’s a subject that resonates with many…

Uplift Psychology: Harnessing Positive Emotions for Personal Growth and Well-being

What if harnessing the power of positive emotions could transform your life, fostering personal growth and lasting well-being? This tantalizing question lies at the heart of uplift psychology, a burgeoning field that’s revolutionizing our approach to mental health and personal development. It’s not just about putting on a happy face or ignoring life’s challenges. No,…

Creative Intelligence in Psychology: Definition, Importance, and Applications

Revolutionizing our understanding of the human mind, creative intelligence has emerged as a captivating and multifaceted concept in the field of psychology, shedding light on the intricate processes that fuel innovation and problem-solving. It’s a concept that has captured the imagination of researchers and laypeople alike, sparking countless debates and inspiring a wealth of groundbreaking…

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

Have a language expert improve your writing

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

• Knowledge Base

Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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 test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information 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.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

Is this article helpful?

Other students also liked, writing strong research questions | criteria & examples.

• What Is a Research Design | Types, Guide & Examples
• Data Collection | Definition, Methods & Examples

More interesting articles

• Between-Subjects Design | Examples, Pros, & Cons
• Cluster Sampling | A Simple Step-by-Step Guide with Examples
• Confounding Variables | Definition, Examples & Controls
• Construct Validity | Definition, Types, & Examples
• Content Analysis | Guide, Methods & Examples
• Control Groups and Treatment Groups | Uses & Examples
• Control Variables | What Are They & Why Do They Matter?
• Correlation vs. Causation | Difference, Designs & Examples
• Correlational Research | When & How to Use
• Critical Discourse Analysis | Definition, Guide & Examples
• Cross-Sectional Study | Definition, Uses & Examples
• Descriptive Research | Definition, Types, Methods & Examples
• Ethical Considerations in Research | Types & Examples
• Explanatory and Response Variables | Definitions & Examples
• Explanatory Research | Definition, Guide, & Examples
• Exploratory Research | Definition, Guide, & Examples
• External Validity | Definition, Types, Threats & Examples
• Extraneous Variables | Examples, Types & Controls
• Guide to Experimental Design | Overview, Steps, & Examples
• How Do You Incorporate an Interview into a Dissertation? | Tips
• How to Do Thematic Analysis | Step-by-Step Guide & Examples
• How to Write a Literature Review | Guide, Examples, & Templates
• How to Write a Strong Hypothesis | Steps & Examples
• Inclusion and Exclusion Criteria | Examples & Definition
• Independent vs. Dependent Variables | Definition & Examples
• Inductive Reasoning | Types, Examples, Explanation
• Inductive vs. Deductive Research Approach | Steps & Examples
• Internal Validity in Research | Definition, Threats, & Examples
• Internal vs. External Validity | Understanding Differences & Threats
• Longitudinal Study | Definition, Approaches & Examples
• Mediator vs. Moderator Variables | Differences & Examples
• Mixed Methods Research | Definition, Guide & Examples
• Multistage Sampling | Introductory Guide & Examples
• Naturalistic Observation | Definition, Guide & Examples
• Operationalization | A Guide with Examples, Pros & Cons
• Population vs. Sample | Definitions, Differences & Examples
• Primary Research | Definition, Types, & Examples
• Qualitative vs. Quantitative Research | Differences, Examples & Methods
• Quasi-Experimental Design | Definition, Types & Examples
• Questionnaire Design | Methods, Question Types & Examples
• Random Assignment in Experiments | Introduction & Examples
• Random vs. Systematic Error | Definition & Examples
• Reliability vs. Validity in Research | Difference, Types and Examples
• Reproducibility vs Replicability | Difference & Examples
• Reproducibility vs. Replicability | Difference & Examples
• Sampling Methods | Types, Techniques & Examples
• Semi-Structured Interview | Definition, Guide & Examples
• Simple Random Sampling | Definition, Steps & Examples
• Single, Double, & Triple Blind Study | Definition & Examples
• Stratified Sampling | Definition, Guide & Examples
• Structured Interview | Definition, Guide & Examples
• Survey Research | Definition, Examples & Methods
• Systematic Review | Definition, Example, & Guide
• Systematic Sampling | A Step-by-Step Guide with Examples
• Textual Analysis | Guide, 3 Approaches & Examples
• The 4 Types of Reliability in Research | Definitions & Examples
• The 4 Types of Validity in Research | Definitions & Examples
• Transcribing an Interview | 5 Steps & Transcription Software
• Triangulation in Research | Guide, Types, Examples
• Types of Interviews in Research | Guide & Examples
• Types of Research Designs Compared | Guide & Examples
• Types of Variables in Research & Statistics | Examples
• Unstructured Interview | Definition, Guide & Examples
• What Is a Case Study? | Definition, Examples & Methods
• What Is a Case-Control Study? | Definition & Examples
• What Is a Cohort Study? | Definition & Examples
• What Is a Conceptual Framework? | Tips & Examples
• What Is a Controlled Experiment? | Definitions & Examples
• What Is a Double-Barreled Question?
• What Is a Focus Group? | Step-by-Step Guide & Examples
• What Is a Likert Scale? | Guide & Examples
• What Is a Prospective Cohort Study? | Definition & Examples
• What Is a Retrospective Cohort Study? | Definition & Examples
• What Is Action Research? | Definition & Examples
• What Is an Observational Study? | Guide & Examples
• What Is Concurrent Validity? | Definition & Examples
• What Is Content Validity? | Definition & Examples
• What Is Convenience Sampling? | Definition & Examples
• What Is Convergent Validity? | Definition & Examples
• What Is Criterion Validity? | Definition & Examples
• What Is Data Cleansing? | Definition, Guide & Examples
• What Is Deductive Reasoning? | Explanation & Examples
• What Is Discriminant Validity? | Definition & Example
• What Is Ecological Validity? | Definition & Examples
• What Is Ethnography? | Definition, Guide & Examples
• What Is Face Validity? | Guide, Definition & Examples
• What Is Non-Probability Sampling? | Types & Examples
• What Is Participant Observation? | Definition & Examples
• What Is Peer Review? | Types & Examples
• What Is Predictive Validity? | Examples & Definition
• What Is Probability Sampling? | Types & Examples
• What Is Purposive Sampling? | Definition & Examples
• What Is Qualitative Observation? | Definition & Examples
• What Is Qualitative Research? | Methods & Examples
• What Is Quantitative Observation? | Definition & Examples
• What Is Quantitative Research? | Definition, Uses & Methods

"I thought AI Proofreading was useless but.."

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

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
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

Key concepts in rapid reviews: an overview

Affiliations.

• 1 Evidence Synthesis Ireland & Cochrane Ireland, University of Galway, Galway, Ireland; School of Nursing and Midwifery, University of Galway, Galway, Ireland; HRB-Trials Methodology Research Network, University of Galway, Galway, Ireland.
• 2 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada.
• 3 Department for Evidence-based Medicine and Evaluation & Cochrane Austria, University for Continuing Education Krems, Krems, Austria; Center for Public Health Methods, RTI International, Research Triangle Park, USA.
• 4 Department for Evidence-based Medicine and Evaluation & Cochrane Austria, University for Continuing Education Krems, Krems, Austria.
• 5 Evidence Synthesis Ireland & Cochrane Ireland, School of Nursing and Midwifery, University of Galway, Galway, Ireland.
• 6 School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Canada; Global Health & Guidelines Division, Public Health Agency of Canada, Ottawa, Ontario, Canada.
• PMID: 39245414
• DOI: 10.1016/j.jclinepi.2024.111518

Rapid reviews have gained popularity as a pragmatic approach to synthesise evidence in a timely manner to inform decision-making in healthcare. This article provides an overview of the key concepts and methodological considerations in conducting rapid reviews, drawing from a series of recently published guidance papers by the Cochrane Rapid Reviews Methods Group. We discuss the definition, characteristics, and potential applications of rapid reviews and the trade-offs between speed and rigour. We present a practical example of a rapid review and highlight the methodological considerations outlined in the updated Cochrane guidance, including recommendations for literature searching, study selection, data extraction, risk of bias assessment, synthesis, and assessing the certainty of evidence. Rapid reviews can be a valuable tool for evidence-based decision-making, but it is essential to understand their limitations and adhere to methodological standards to ensure their validity and reliability. As the demand for rapid evidence synthesis continues to grow, further research is needed to refine and standardise the methods and reporting of rapid reviews.

Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

PubMed Disclaimer

Related information

Linkout - more resources, full text sources.

• ClinicalKey
• Elsevier Science

Research Materials

• NCI CPTC Antibody Characterization Program

• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.