are case studies considered as scientific research

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• R. M. Channaveer 4 &
• Rajendra Baikady 5  

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This chapter reviews the strengths and limitations of case study as a research method in social sciences. It provides an account of an evidence base to justify why a case study is best suitable for some research questions and why not for some other research questions. Case study designing around the research context, defining the structure and modality, conducting the study, collecting the data through triangulation mode, analysing the data, and interpreting the data and theory building at the end give a holistic view of it. In addition, the chapter also focuses on the types of case study and when and where to use case study as a research method in social science research.

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Channaveer, R.M., Baikady, R. (2022). Case Study. In: Islam, M.R., Khan, N.A., Baikady, R. (eds) Principles of Social Research Methodology. Springer, Singapore. https://doi.org/10.1007/978-981-19-5441-2_21

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The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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11 Case research

Case research—also called case study—is a method of intensively studying a phenomenon over time within its natural setting in one or a few sites. Multiple methods of data collection, such as interviews, observations, pre-recorded documents, and secondary data, may be employed and inferences about the phenomenon of interest tend to be rich, detailed, and contextualised. Case research can be employed in a positivist manner for the purpose of theory testing or in an interpretive manner for theory building. This method is more popular in business research than in other social science disciplines.

Case research has several unique strengths over competing research methods such as experiments and survey research. First, case research can be used for either theory building or theory testing, while positivist methods can be used for theory testing only. In interpretive case research, the constructs of interest need not be known in advance, but may emerge from the data as the research progresses. Second, the research questions can be modified during the research process if the original questions are found to be less relevant or salient. This is not possible in any positivist method after the data is collected. Third, case research can help derive richer, more contextualised, and more authentic interpretation of the phenomenon of interest than most other research methods by virtue of its ability to capture a rich array of contextual data. Fourth, the phenomenon of interest can be studied from the perspectives of multiple participants and using multiple levels of analysis (e.g., individual and organisational).

At the same time, case research also has some inherent weaknesses. Because it involves no experimental control, internal validity of inferences remain weak. Of course, this is a common problem for all research methods except experiments. However, as described later, the problem of controls may be addressed in case research using ‘natural controls’. Second, the quality of inferences derived from case research depends heavily on the integrative powers of the researcher. An experienced researcher may see concepts and patterns in case data that a novice researcher may miss. Hence, the findings are sometimes criticised as being subjective. Finally, because the inferences are heavily contextualised, it may be difficult to generalise inferences from case research to other contexts or other organisations.

It is important to recognise that case research is different from case descriptions such as Harvard case studies discussed in business classes. While case descriptions typically describe an organisational problem in rich detail with the goal of stimulating classroom discussion and critical thinking among students, or analysing how well an organisation handled a specific problem, case research is a formal research technique that involves a scientific method to derive explanations of organisational phenomena.

Case research is a difficult research method that requires advanced research skills on the part of the researcher, and is therefore often prone to error. Benbasat, Goldstein and Mead (1987) [1] describe five problems frequently encountered in case research studies. First, many case research studies start without specific research questions, and therefore end up without having any specific answers or insightful inferences. Second, case sites are often chosen based on access and convenience, rather than based on the fit with the research questions, and are therefore cannot adequately address the research questions of interest. Third, researchers often do not validate or triangulate data collected using multiple means, which may lead to biased interpretation based on responses from biased interviewees. Fourth, many studies provide very little details on how data was collected (e.g., what interview questions were used, which documents were examined, the organisational positions of each interviewee, etc.) or analysed, which may raise doubts about the reliability of the inferences. Finally, despite its strength as a longitudinal research method, many case research studies do not follow through a phenomenon in a longitudinal manner, and hence present only a cross-sectional and limited view of organisational processes and phenomena that are temporal in nature.

Key decisions in case research

Several key decisions must be made by a researcher when considering a case research method. First, is this the right method for the research questions being studied? The case research method is particularly appropriate for exploratory studies, for discovering relevant constructs in areas where theory building is in the formative stages, for studies where the experiences of participants and context of actions are critical, and for studies aimed at understanding complex, temporal processes (why and how) rather than factors or causes (what). This method is well-suited for studying complex organisational processes that involve multiple participants and interacting sequences of events, such as organisational change and large-scale technology implementation projects.

Second, what is the appropriate unit of analysis for a case research study? Since case research can simultaneously examine multiple units of analyses, the researcher must decide whether she wishes to study a phenomenon at the individual, group, or organisational level or at multiple levels. For instance, a study of group decision-making or group work may combine individual-level constructs such as individual participation in group activities with group-level constructs, such as group cohesion and group leadership, to derive richer understanding than can be achieved from a single level of analysis.

Third, should the researcher employ a single-case or multiple-case design? The single-case design is more appropriate at the outset of theory generation, if the situation is unique or extreme, if it is revelatory (i.e., the situation was previously inaccessible for scientific investigation), or if it represents a critical or contrary case for testing a well-formulated theory. The multiple-case design is more appropriate for theory testing, for establishing generalisability of inferences, and for developing richer and more nuanced interpretations of a phenomenon. Yin (1984) [2] recommends the use of multiple case sites with replication logic, viewing each case site as similar to one experimental study, and following rules of scientific rigor similar to that used in positivist research.

Fourth, what sites should be chosen for case research? Given the contextualised nature of inferences derived from case research, site selection is a particularly critical issue because selecting the wrong site may lead to the wrong inferences. If the goal of the research is to test theories or examine generalisability of inferences, then dissimilar case sites should be selected to increase variance in observations. For instance, if the goal of the research is to understand the process of technology implementation in firms, a mix of large, mid-sized, and small firms should be selected to examine whether the technology implementation process differs with firm size. Site selection should not be opportunistic or based on convenience, but rather based on the fit with research questions though a process called ‘theoretical sampling’.

Fifth, what techniques of data collection should be used in case research? Although interview (either open-ended/unstructured or focused/structured) is by far the most popular data collection technique for case research, interview data can be supplemented or corroborated with other techniques such as direct observation (e.g., attending executive meetings, briefings, and planning sessions), documentation (e.g., internal reports, presentations, and memoranda, as well as external accounts such as newspaper reports), archival records (e.g., organisational charts, financial records, etc.), and physical artefacts (e.g., devices, outputs, tools). Furthermore, the researcher should triangulate or validate observed data by comparing responses between interviewees.

Conducting case research

Most case research studies tend to be interpretive in nature. Interpretive case research is an inductive technique where evidence collected from one or more case sites is systematically analysed and synthesised to allow concepts and patterns to emerge for the purpose of building new theories or expanding existing ones. Eisenhardt (1989) [3] proposed a ‘roadmap’ for building theories from case research—a slightly modified version of which is described below. For positivist case research, some of the following stages may need to be rearranged or modified, however sampling, data collection, and data analytic techniques should generally remain the same.

Define research questions. Like any other scientific research, case research must also start with defining research questions that are theoretically and practically interesting, and identifying some intuitive expectations about possible answers to those research questions or preliminary constructs to guide initial case design. In positivist case research, the preliminary constructs are based on theory, while no such theories or hypotheses should be considered ex ante in interpretive research. These research questions and constructs may be changed in interpretive case research later on, if needed, but not in positivist case research.

Select case sites. The researcher should use a process of ‘theoretical sampling’—not random sampling—to identify case sites. In this approach, case sites are chosen based on theoretical rather than statistical considerations—for instance, to replicate previous cases, to extend preliminary theories, or to fill theoretical categories or polar types. Care should be taken to ensure that the selected sites fit the nature of research questions, minimise extraneous variance or noise due to firm size, industry effects, and so forth, and maximise variance in the dependent variables of interest. For instance, if the goal of the research is to examine how some firms innovate better than others, the researcher should select firms of similar size within the same industry to reduce industry or size effects, and select some more innovative and some less innovative firms to increase variation in firm innovation. Instead of cold-calling or writing to a potential site, it is better to contact someone at executive level inside each firm who has the authority to approve the project, or someone who can identify a person of authority. During initial conversations, the researcher should describe the nature and purpose of the project, any potential benefits to the case site, how the collected data will be used, the people involved in data collection (other researchers, research assistants, etc.), desired interviewees, and the amount of time, effort, and expense required of the sponsoring organisation. The researcher must also assure confidentiality, privacy, and anonymity of both the firm and the individual respondents.

Create instruments and protocols. Since the primary mode of data collection in case research is interviews, an interview protocol should be designed to guide the interview process. This is essentially a list of questions to be asked. Questions may be open-ended (unstructured) or closed-ended (structured) or a combination of both. The interview protocol must be strictly followed, and the interviewer must not change the order of questions or skip any question during the interview process, although some deviations are allowed to probe further into a respondent’s comments if they are ambiguous or interesting. The interviewer must maintain a neutral tone, and not lead respondents in any specific direction—for example, by agreeing or disagreeing with any response. More detailed interviewing techniques are discussed in the chapter on surveys. In addition, additional sources of data—such as internal documents and memorandums, annual reports, financial statements, newspaper articles, and direct observations—should be sought to supplement and validate interview data.

Select respondents. Select interview respondents at different organisational levels, departments, and positions to obtain divergent perspectives on the phenomenon of interest. A random sampling of interviewees is most preferable, however a snowball sample is acceptable, as long as a diversity of perspectives is represented in the sample. Interviewees must be selected based on their personal involvement with the phenomenon under investigation and their ability and willingness to answer the researcher’s questions accurately and adequately, and not based on convenience or access.

Start data collection . It is usually a good idea to electronically record interviews for future reference. However, such recording must only be done with the interviewee’s consent. Even when interviews are being recorded, the interviewer should take notes to capture important comments or critical observations, behavioural responses (e.g., the respondent’s body language), and the researcher’s personal impressions about the respondent and his/her comments. After each interview is completed, the entire interview should be transcribed verbatim into a text document for analysis.

Conduct within-case data analysis. Data analysis may follow or overlap with data collection. Overlapping data collection and analysis has the advantage of adjusting the data collection process based on themes emerging from data analysis, or to further probe into these themes. Data analysis is done in two stages. In the first stage (within-case analysis), the researcher should examine emergent concepts separately at each case site and patterns between these concepts to generate an initial theory of the problem of interest. The researcher can use interview data subjectively to ‘make sense’ of the research problem in conjunction with using his/her personal observations or experience at the case site. Alternatively, a coding strategy such as Glaser and Strauss’ (1967) [4] grounded theory approach, using techniques such as open coding, axial coding, and selective coding, may be used to derive a chain of evidence and inferences. These techniques are discussed in detail in a later chapter. Homegrown techniques, such as graphical representation of data (e.g., network diagram) or sequence analysis (for longitudinal data) may also be used. Note that there is no predefined way of analysing the various types of case data, and the data analytic techniques can be modified to fit the nature of the research project.

Conduct cross-case analysis. Multi-site case research requires cross-case analysis as the second stage of data analysis. In such analysis, the researcher should look for similar concepts and patterns between different case sites, ignoring contextual differences that may lead to idiosyncratic conclusions. Such patterns may be used for validating the initial theory, or for refining it—by adding or dropping concepts and relationships—to develop a more inclusive and generalisable theory. This analysis may take several forms. For instance, the researcher may select categories (e.g., firm size, industry, etc.) and look for within-group similarities and between-group differences (e.g., high versus low performers, innovators versus laggards). Alternatively, they can compare firms in a pairwise manner listing similarities and differences across pairs of firms.

Build and test hypotheses. Tenative hypotheses are constructed based on emergent concepts and themes that are generalisable across case sites. These hypotheses should be compared iteratively with observed evidence to see if they fit the observed data, and if not, the constructs or relationships should be refined. Also the researcher should compare the emergent constructs and hypotheses with those reported in the prior literature to make a case for their internal validity and generalisability. Conflicting findings must not be rejected, but rather reconciled using creative thinking to generate greater insight into the emergent theory. When further iterations between theory and data yield no new insights or changes in the existing theory, ‘theoretical saturation’ is reached and the theory building process is complete.

Write case research report. In writing the report, the researcher should describe very clearly the detailed process used for sampling, data collection, data analysis, and hypotheses development, so that readers can independently assess the reasonableness, strength, and consistency of the reported inferences. A high level of clarity in research methods is needed to ensure that the findings are not biased by the researcher’s preconceptions.

Interpretive case research exemplar

Perhaps the best way to learn about interpretive case research is to examine an illustrative example. One such example is Eisenhardt’s (1989) [5] study of how executives make decisions in high-velocity environments (HVE). Readers are advised to read the original paper published in Academy of Management Journal before reading the synopsis in this chapter. In this study, Eisenhardt examined how executive teams in some HVE firms make fast decisions, while those in other firms cannot, and whether faster decisions improve or worsen firm performance in such environments. HVE was defined as one where demand, competition, and technology changes so rapidly and discontinuously that the information available is often inaccurate, unavailable or obsolete. The implicit assumptions were thatit is hard to make fast decisions with inadequate information in HVE, and fast decisions may not be efficient and may result in poor firm performance.

Reviewing the prior literature on executive decision-making, Eisenhardt found several patterns, although none of these patterns were specific to high-velocity environments. The literature suggested that in the interest of expediency, firms that make faster decisions obtain input from fewer sources, consider fewer alternatives, make limited analysis, restrict user participation in decision-making, centralise decision-making authority, and have limited internal conflicts. However, Eisenhardt contended that these views may not necessarily explain how decision makers make decisions in high-velocity environments, where decisions must be made quickly and with incomplete information, while maintaining high decision quality.

To examine this phenomenon, Eisenhardt conducted an inductive study of eight firms in the personal computing industry. The personal computing industry was undergoing dramatic changes in technology with the introduction of the UNIX operating system, RISC architecture, and 64KB random access memory in the 1980s, increased competition with the entry of IBM into the personal computing business, and growing customer demand with double-digit demand growth, and therefore fit the profile of the high-velocity environment. This was a multiple case design with replication logic, where each case was expected to confirm or disconfirm inferences from other cases. Case sites were selected based on their access and proximity to the researcher, however, all of these firms operated in the high-velocity personal computing industry in California’s Silicon Valley area. The collocation of firms in the same industry and the same area ruled out any ‘noise’ or variance in dependent variables (decision speed or performance) attributable to industry or geographic differences.

The study employed an embedded design with multiple levels of analysis: decision (comparing multiple strategic decisions within each firm), executive teams (comparing different teams responsible for strategic decisions), and the firm (overall firm performance). Data was collected from five sources:

Initial interviews with Chief Executive Officers . CEOs were asked questions about their firm’s competitive strategy, distinctive competencies, major competitors, performance, and recent/ongoing major strategic decisions. Based on these interviews, several strategic decisions were selected in each firm for further investigation. Four criteria were used to select decisions: the decisions must involve the firm’s strategic positioning, the decisions must have high stakes, the decisions must involve multiple functions, and the decisions must be representative of strategic decision-making process in that firm.

Interviews with divisional heads . Each divisional head was asked sixteen open-ended questions, ranging from their firm’s competitive strategy, functional strategy, top management team members, frequency and nature of interaction with team, typical decision-making processes, how each of the decisions were made, and how long it took them to make those decisions. Interviews lasted between one and a half and two hours, and sometimes extended to four hours. To focus on facts and actual events rather than respondents’ perceptions or interpretations, a ‘courtroom’ style questioning was employed, such as ‘When did this happen?’, ‘What did you do?’, etc. Interviews were conducted by two people, and the data was validated by cross-checking facts and impressions made by the interviewer and notetaker. All interview data was recorded, however notes were also taken during each interview, which ended with the interviewer’s overall impressions. Using a ‘24-hour rule’, detailed field notes were completed within 24 hours of the interview, so that some data or impressions were not lost to recall.

Questionnaires . Executive team members at each firm were asked tocomplete a survey questionnaire that captured quantitative data on the extent of conflict and power distribution in their firm.

Secondary data . Industry reports and internal documents such as demographics of the executive teams responsible for strategic decisions, financial performance of firms, and so forth, were examined.

Personal observation . Lastly, the researcher attended a one-day strategy session and a weekly executive meeting at two firms in her sample.

Data analysis involved a combination of quantitative and qualitative techniques. Quantitative data on conflict and power were analysed for patterns across firms/decisions. Qualitative interview data was combined into decision climate profiles, using profile traits (e.g., impatience) mentioned by more than one executive. For within-case analysis, decision stories were created for each strategic decision by combining executive accounts of the key decision events into a timeline. For cross-case analysis, pairs of firms were compared for similarities and differences, categorised along variables of interest such as decision speed and firm performance. Based on these analyses, tentative constructs and propositions were derived inductively from each decision story within firm categories. Each decision case was revisited to confirm the proposed relationships. The inferred propositions were compared with findings from the existing literature to examine differences, and to generate new insights from the case findings. Finally, the validated propositions were synthesised into an inductive theory of strategic decision-making by firms in high-velocity environments.

Inferences derived from this multiple case research contradicted several decision-making patterns expected from the existing literature. First, fast decision-makers in high-velocity environments used more information, and not less information as suggested by the previous literature. However, these decision-makers used more real-time information—an insight not available from prior research—which helped them identify and respond to problems, opportunities, and changing circumstances faster. Second, fast decision-makers examined more—not fewer—alternatives. However, they considered these multiple alternatives in a simultaneous manner, while slower decision-makers examined fewer alternatives in a sequential manner. Third, fast decision-makers did not centralise decision-making or restrict inputs from others as the literature suggested. Rather, these firms used a two-tiered decision process in which experienced counsellors were asked for inputs in the first stage, followed by a rapid comparison and decision selection in the second stage. Fourth, fast decision-makers did not have less conflict—as expected from the literature—but employed better conflict resolution techniques to reduce conflict and improve decision-making speed. Finally, fast decision-makers exhibited superior firm performance by virtue of their built-in cognitive, emotional, and political processes that led to rapid closure of major decisions.

Positivist case research exemplar

Case research can also be used in a positivist manner to test theories or hypotheses. Such studies are rare, but Markus (1983) [6] provides an exemplary illustration in her study of technology implementation at the pseudonymous Golden Triangle Company (GTC). The goal of this study was to understand why a newly implemented financial information system (FIS)—intended to improve the productivity and performance of accountants at GTC—was supported by accountants at GTC’s corporate headquarters, but resisted by divisional accountants at GTC branches. Given the uniqueness of the phenomenon of interest, this was a single-case research study.

To explore the reasons behind user resistance of FIS, Markus posited three alternative explanations:

System-determined theory : The resistance was caused by factors related to an inadequate system, such as its technical deficiencies, poor ergonomic design, or lack of user friendliness.

People-determined theory : The resistance was caused by factors internal to users, such as the accountants’ cognitive styles or personality traits that were incompatible with using the system.

Interaction theory : The resistance was not caused not by factors intrinsic to the system or the people, but by the interaction between the two set of factors. Specifically, interaction theory suggested that the FIS engendered a redistribution of intra-organisational power, and accountants who lost organisational status, relevance, or power as a result of FIS implementation resisted the system while those gaining power favoured it.

In order to test the three theories, Markus predicted alternative outcomes expected from each theoretical explanation and analysed the extent to which those predictions matched with her observations at GTC. For instance, the system-determined theory suggested that since user resistance was caused by an inadequate system, fixing the technical problems of the system would eliminate resistance. The computer running the FIS system was subsequently upgraded with a more powerful operating system, online processing (from initial batch processing, which delayed immediate processing of accounting information), and a simplified software for new account creation by managers. One year after these changes were made, the resistant users were still resisting the system and felt that it should be replaced. Hence, the system-determined theory was rejected.

The people-determined theory predicted that replacing individual resistors or co-opting them with less resistant users would reduce their resistance toward the FIS. Subsequently, GTC started a job rotation and mobility policy, moving accountants in and out of the resistant divisions, but resistance not only persisted, but in some cases increased. In one instance, an accountant who was one of the system’s designers and advocates when he worked for corporate accounting started resisting the system after he was moved to the divisional controller’s office. Failure to realise the predictions of the people-determined theory led to the rejection of this theory.

Finally, the interaction theory predicted that neither changing the system nor the people (i.e., user education or job rotation policies) would reduce resistance until the power imbalance and redistribution from the pre-implementation phase was addressed. Before FIS implementation, divisional accountants at GTC felt that they owned all accounting data related to their divisional operations. They maintained this data in thick, manual ledger books, controlled others’ access to the data, and could reconcile unusual accounting events before releasing those reports. Corporate accountants relied heavily on divisional accountants for access to the divisional data for corporate reporting and consolidation. Because the FIS system automatically collected all data at the source and consolidated it into a single corporate database, it obviated the need for divisional accountants, loosened their control and autonomy over their division’s accounting data, and making their job somewhat irrelevant. Corporate accountants could now query the database and access divisional data directly without going through the divisional accountants, analyse and compare the performance of individual divisions, and report unusual patterns and activities to the executive committee, resulting in further erosion of the divisions’ power. Though Markus did not empirically test this theory, her observations about the redistribution of organisational power, coupled with the rejection of the two alternative theories, led to the justification of interaction theory.

Comparisons with traditional research

Positivist case research, aimed at hypotheses testing, is often criticised by natural science researchers as lacking in controlled observations, controlled deductions, replicability, and generalisability of findings—the traditional principles of positivist research. However, these criticisms can be overcome through appropriate case research designs. For instance, the problem of controlled observations refers to the difficulty of obtaining experimental or statistical control in case research. However, case researchers can compensate for such lack of controls by employing ’natural controls’. This natural control in Markus’ (1983) study was the corporate accountant who was one of the system advocates initially, but started resisting it once he moved to the controlling division. In this instance, the change in his behaviour may be attributed to his new divisional position. However, such natural controls cannot be anticipated in advance, and case researchers may overlook them unless they are proactively looking for such controls. Incidentally, natural controls are also used in natural science disciplines such as astronomy, geology, and human biology—for example, waiting for comets to pass close enough to the earth in order to make inferences about comets and their composition.

Third, the problem of replicability refers to the difficulty of observing the same phenomenon considering the uniqueness and idiosyncrasy of a given case site. However, using Markus’ three theories as an illustration, a different researcher can test the same theories at a different case site, where three different predictions may emerge based on the idiosyncratic nature of the new case site, and the three resulting predictions may be tested accordingly. In other words, it is possible to replicate the inferences of case research, even if the case research site or context may not be replicable.

Fourth, case research tends to examine unique and non-replicable phenomena that may not be generalised to other settings. Generalisability in natural sciences is established through additional studies. Likewise, additional case studies conducted in different contexts with different predictions can establish generalisability of findings if such findings are observed to be consistent across studies.

Lastly, British philosopher Karl Popper described four requirements of scientific theories: theories should be falsifiable, they should be logically consistent, they should have adequate predictive ability, and they should provide better explanation than rival theories. In case research, the first three requirements can be improved by increasing the degrees of freedom of observed findings—for example, by increasing the number of case sites, the number of alternative predictions, and the number of levels of analysis examined. This was accomplished in Markus’ study by examining the behaviour of multiple groups (divisional accountants and corporate accountants) and providing multiple (three) rival explanations. Popper’s fourth condition was accomplished in this study when one hypothesis was found to match observed evidence better than the two rival hypotheses.

• Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS Quarterly , 11(3), 369–386. ↵
• Yin, R. (1984). Case study research: Design and methods . London: Sage Publications. ↵
• Eisenhardt, K. M. (1989). Building theories from case research. Academy of Management Review , 14(4), 532–550 ↵
• Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research . New York: Aldine Pub Co. ↵
• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Markus, M. L. (1983). Power, politics and MIS implementations. Communications of the ACM , 26(6), 430–444. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

• The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
• The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
• The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
• The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
• The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

• What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
• Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
• What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
• How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

• Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
• Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
• Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
• Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
• Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
• Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
• Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

• If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
• If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
• Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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The case study creation process

Types of case studies, benefits and limitations.

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case study , detailed description and assessment of a specific situation in the real world created for the purpose of deriving generalizations and other insights from it. A case study can be about an individual, a group of people, an organization, or an event, among other subjects.

By focusing on a specific subject in its natural setting, a case study can help improve understanding of the broader features and processes at work. Case studies are a research method used in multiple fields, including business, criminology , education , medicine and other forms of health care, anthropology , political science , psychology , and social work . Data in case studies can be both qualitative and quantitative. Unlike experiments, where researchers control and manipulate situations, case studies are considered to be “naturalistic” because subjects are studied in their natural context . ( See also natural experiment .)

The creation of a case study typically involves the following steps:

• The research question to be studied is defined, informed by existing literature and previous research. Researchers should clearly define the scope of the case, and they should compile a list of evidence to be collected as well as identify the nature of insights that they expect to gain from the case study.
• Once the case is identified, the research team is given access to the individual, organization, or situation being studied. Individuals are informed of risks associated with participation and must provide their consent , which may involve signing confidentiality or anonymity agreements.
• Researchers then collect evidence using multiple methods, which may include qualitative techniques, such as interviews, focus groups , and direct observations, as well as quantitative methods, such as surveys, questionnaires, and data audits. The collection procedures need to be well defined to ensure the relevance and accuracy of the evidence.
• The collected evidence is analyzed to come up with insights. Each data source must be reviewed carefully by itself and in the larger context of the case study so as to ensure continued relevance. At the same time, care must be taken not to force the analysis to fit (potentially preconceived) conclusions. While the eventual case study may serve as the basis for generalizations, these generalizations must be made cautiously to ensure that specific nuances are not lost in the averages.
• Finally, the case study is packaged for larger groups and publication. At this stage some information may be withheld, as in business case studies, to allow readers to draw their own conclusions. In scientific fields, the completed case study needs to be a coherent whole, with all findings and statistical relationships clearly documented.

Case studies have been used as a research method across multiple fields. They are particularly popular in the fields of law, business, and employee training; they typically focus on a problem that an individual or organization is facing. The situation is presented in considerable detail, often with supporting data, to discussion participants, who are asked to make recommendations that will solve the stated problem. The business case study as a method of instruction was made popular in the 1920s by instructors at Harvard Business School who adapted an approach used at Harvard Law School in which real-world cases were used in classroom discussions. Other business and law schools started compiling case studies as teaching aids for students. In a business school case study, students are not provided with the complete list of facts pertaining to the topic and are thus forced to discuss and compare their perspectives with those of their peers to recommend solutions.

In criminology , case studies typically focus on the lives of an individual or a group of individuals. These studies can provide particularly valuable insight into the personalities and motives of individual criminals, but they may suffer from a lack of objectivity on the part of the researchers (typically because of the researchers’ biases when working with people with a criminal history), and their findings may be difficult to generalize.

In sociology , the case-study method was developed by Frédéric Le Play in France during the 19th century. This approach involves a field worker staying with a family for a period of time, gathering data on the family members’ attitudes and interactions and on their income, expenditures, and physical possessions. Similar approaches have been used in anthropology . Such studies can sometimes continue for many years.

Case studies provide insight into situations that involve a specific entity or set of circumstances. They can be beneficial in helping to explain the causal relationships between quantitative indicators in a field of study, such as what drives a company’s market share. By introducing real-world examples, they also plunge the reader into an actual, concrete situation and make the concepts real rather than theoretical. They also help people study rare situations that they might not otherwise experience.

Because case studies are in a “naturalistic” environment , they are limited in terms of research design: researchers lack control over what they are studying, which means that the results often cannot be reproduced. Also, care must be taken to stay within the bounds of the research question on which the case study is focusing. Other limitations to case studies revolve around the data collected. It may be difficult, for instance, for researchers to organize the large volume of data that can emerge from the study, and their analysis of the data must be carefully thought through to produce scientifically valid insights. The research methodology used to generate these insights is as important as the insights themselves, for the latter need to be seen in the proper context. Taken out of context, they may lead to erroneous conclusions. Like all scientific studies, case studies need to be approached objectively; personal bias or opinion may skew the research methods as well as the results. ( See also confirmation bias .)

Business case studies in particular have been criticized for approaching a problem or situation from a narrow perspective. Students are expected to come up with solutions for a problem based on the data provided. However, in real life, the situation is typically reversed: business managers face a problem and must then look for data to help them solve it.

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Scientific Method Steps in Psychology Research

Steps, Uses, and Key Terms

Verywell / Theresa Chiechi

How do researchers investigate psychological phenomena? They utilize a process known as the scientific method to study different aspects of how people think and behave.

When conducting research, the scientific method steps to follow are:

• Observe what you want to investigate
• Ask a research question and make predictions
• Test the hypothesis and collect data
• Examine the results and draw conclusions
• Report and share the results 

This process not only allows scientists to investigate and understand different psychological phenomena but also provides researchers and others a way to share and discuss the results of their studies.

Generally, there are five main steps in the scientific method, although some may break down this process into six or seven steps. An additional step in the process can also include developing new research questions based on your findings.

What Is the Scientific Method?

What is the scientific method and how is it used in psychology?

The scientific method consists of five steps. It is essentially a step-by-step process that researchers can follow to determine if there is some type of relationship between two or more variables.

By knowing the steps of the scientific method, you can better understand the process researchers go through to arrive at conclusions about human behavior.

Scientific Method Steps

While research studies can vary, these are the basic steps that psychologists and scientists use when investigating human behavior.

The following are the scientific method steps:

Step 1. Make an Observation

Before a researcher can begin, they must choose a topic to study. Once an area of interest has been chosen, the researchers must then conduct a thorough review of the existing literature on the subject. This review will provide valuable information about what has already been learned about the topic and what questions remain to be answered.

A literature review might involve looking at a considerable amount of written material from both books and academic journals dating back decades.

The relevant information collected by the researcher will be presented in the introduction section of the final published study results. This background material will also help the researcher with the first major step in conducting a psychology study: formulating a hypothesis.

Step 2. Ask a Question

Once a researcher has observed something and gained some background information on the topic, the next step is to ask a question. The researcher will form a hypothesis, which is an educated guess about the relationship between two or more variables

For example, a researcher might ask a question about the relationship between sleep and academic performance: Do students who get more sleep perform better on tests at school?

In order to formulate a good hypothesis, it is important to think about different questions you might have about a particular topic.

You should also consider how you could investigate the causes. Falsifiability is an important part of any valid hypothesis. In other words, if a hypothesis was false, there needs to be a way for scientists to demonstrate that it is false.

Step 3. Test Your Hypothesis and Collect Data

Once you have a solid hypothesis, the next step of the scientific method is to put this hunch to the test by collecting data. The exact methods used to investigate a hypothesis depend on exactly what is being studied. There are two basic forms of research that a psychologist might utilize: descriptive research or experimental research.

Descriptive research is typically used when it would be difficult or even impossible to manipulate the variables in question. Examples of descriptive research include case studies, naturalistic observation , and correlation studies. Phone surveys that are often used by marketers are one example of descriptive research.

Correlational studies are quite common in psychology research. While they do not allow researchers to determine cause-and-effect, they do make it possible to spot relationships between different variables and to measure the strength of those relationships. 

Experimental research is used to explore cause-and-effect relationships between two or more variables. This type of research involves systematically manipulating an independent variable and then measuring the effect that it has on a defined dependent variable .

One of the major advantages of this method is that it allows researchers to actually determine if changes in one variable actually cause changes in another.

While psychology experiments are often quite complex, a simple experiment is fairly basic but does allow researchers to determine cause-and-effect relationships between variables. Most simple experiments use a control group (those who do not receive the treatment) and an experimental group (those who do receive the treatment).

Step 4. Examine the Results and Draw Conclusions

Once a researcher has designed the study and collected the data, it is time to examine this information and draw conclusions about what has been found.  Using statistics , researchers can summarize the data, analyze the results, and draw conclusions based on this evidence.

So how does a researcher decide what the results of a study mean? Not only can statistical analysis support (or refute) the researcher’s hypothesis; it can also be used to determine if the findings are statistically significant.

When results are said to be statistically significant, it means that it is unlikely that these results are due to chance.

Based on these observations, researchers must then determine what the results mean. In some cases, an experiment will support a hypothesis, but in other cases, it will fail to support the hypothesis.

So what happens if the results of a psychology experiment do not support the researcher's hypothesis? Does this mean that the study was worthless?

Just because the findings fail to support the hypothesis does not mean that the research is not useful or informative. In fact, such research plays an important role in helping scientists develop new questions and hypotheses to explore in the future.

After conclusions have been drawn, the next step is to share the results with the rest of the scientific community. This is an important part of the process because it contributes to the overall knowledge base and can help other scientists find new research avenues to explore.

Step 5. Report the Results

The final step in a psychology study is to report the findings. This is often done by writing up a description of the study and publishing the article in an academic or professional journal. The results of psychological studies can be seen in peer-reviewed journals such as  Psychological Bulletin , the  Journal of Social Psychology ,  Developmental Psychology , and many others.

The structure of a journal article follows a specified format that has been outlined by the  American Psychological Association (APA) . In these articles, researchers:

• Provide a brief history and background on previous research
• Present their hypothesis
• Identify who participated in the study and how they were selected
• Provide operational definitions for each variable
• Describe the measures and procedures that were used to collect data
• Explain how the information collected was analyzed
• Discuss what the results mean

Why is such a detailed record of a psychological study so important? By clearly explaining the steps and procedures used throughout the study, other researchers can then replicate the results. The editorial process employed by academic and professional journals ensures that each article that is submitted undergoes a thorough peer review, which helps ensure that the study is scientifically sound.

Once published, the study becomes another piece of the existing puzzle of our knowledge base on that topic.

Before you begin exploring the scientific method steps, here's a review of some key terms and definitions that you should be familiar with:

• Falsifiable : The variables can be measured so that if a hypothesis is false, it can be proven false
• Hypothesis : An educated guess about the possible relationship between two or more variables
• Variable : A factor or element that can change in observable and measurable ways
• Operational definition : A full description of exactly how variables are defined, how they will be manipulated, and how they will be measured

Uses for the Scientific Method

The  goals of psychological studies  are to describe, explain, predict and perhaps influence mental processes or behaviors. In order to do this, psychologists utilize the scientific method to conduct psychological research. The scientific method is a set of principles and procedures that are used by researchers to develop questions, collect data, and reach conclusions.

Goals of Scientific Research in Psychology

Researchers seek not only to describe behaviors and explain why these behaviors occur; they also strive to create research that can be used to predict and even change human behavior.

Psychologists and other social scientists regularly propose explanations for human behavior. On a more informal level, people make judgments about the intentions, motivations , and actions of others on a daily basis.

While the everyday judgments we make about human behavior are subjective and anecdotal, researchers use the scientific method to study psychology in an objective and systematic way. The results of these studies are often reported in popular media, which leads many to wonder just how or why researchers arrived at the conclusions they did.

Examples of the Scientific Method

Now that you're familiar with the scientific method steps, it's useful to see how each step could work with a real-life example.

Say, for instance, that researchers set out to discover what the relationship is between psychotherapy and anxiety .

• Step 1. Make an observation : The researchers choose to focus their study on adults ages 25 to 40 with generalized anxiety disorder.
• Step 2. Ask a question : The question they want to answer in their study is: Do weekly psychotherapy sessions reduce symptoms in adults ages 25 to 40 with generalized anxiety disorder?
• Step 3. Test your hypothesis : Researchers collect data on participants' anxiety symptoms . They work with therapists to create a consistent program that all participants undergo. Group 1 may attend therapy once per week, whereas group 2 does not attend therapy.
• Step 4. Examine the results : Participants record their symptoms and any changes over a period of three months. After this period, people in group 1 report significant improvements in their anxiety symptoms, whereas those in group 2 report no significant changes.
• Step 5. Report the results : Researchers write a report that includes their hypothesis, information on participants, variables, procedure, and conclusions drawn from the study. In this case, they say that "Weekly therapy sessions are shown to reduce anxiety symptoms in adults ages 25 to 40."

Of course, there are many details that go into planning and executing a study such as this. But this general outline gives you an idea of how an idea is formulated and tested, and how researchers arrive at results using the scientific method.

Erol A. How to conduct scientific research ? Noro Psikiyatr Ars . 2017;54(2):97-98. doi:10.5152/npa.2017.0120102

University of Minnesota. Psychologists use the scientific method to guide their research .

Shaughnessy, JJ, Zechmeister, EB, & Zechmeister, JS. Research Methods In Psychology . New York: McGraw Hill Education; 2015.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

Prevent plagiarism, run a free check.

Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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• Policy & Compliance
• Clinical Trials

NIH Definition of Clinical Trial Case Studies

The case studies provided below are designed to help you identify whether your study would be considered by NIH to be a clinical trial. Expect the case studies and related guidance to evolve over the upcoming year. For continuity and ease of reference, case studies will retain their original numbering and will not be renumbered if cases are revised or removed.

The simplified case studies apply the following four questions to determine whether NIH would consider the research study to be a clinical trial:

• Does the study involve human participants?
• Are the participants prospectively assigned to an intervention?
• Is the study designed to evaluate the effect of the intervention on the participants?
• Is the effect being evaluated a health-related biomedical or behavioral outcome?

If the answer to all four questions is “yes,” then the clinical study would be considered a clinical trial according to the NIH definition.

See this page for more information about the NIH definition of a clinical trial.

General Case Studies

Institute or center specific case studies.

The study involves the recruitment of research participants who are randomized to receive one of two approved drugs. It is designed to compare the effects of the drugs on the blood level of a protein.

• Does the study involve human participants? Yes, the study involves human participants.
• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, one of two drugs.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the drugs on the level of the protein in the participants’ blood.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, the level of a protein, is a health-related biomedical outcome.

The study involves the recruitment of research participants with condition Y to receive a drug that has been approved for another indication. It is designed to measure the drug’s effects on the level of a biomarker associated with the severity of condition Y.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, the approved drug.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the drug’s effect on the level of the biomarker.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, the level of a biomarker, is a health-related biomedical outcome.

The study involves the recruitment of research participants with condition X to receive investigational compound A. It is designed to assess the pharmacokinetic properties of compound A.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, compound A.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate how the body interacts with compound A
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, pharmacokinetic properties, is a health-related biomedical outcome.

The study involves the recruitment of research participants with disease X to receive an investigational drug. It is designed to assess safety and determine the maximum tolerated dose of the drug.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, the investigational drug.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to assess safety and determine the maximum tolerated dose of the investigational drug.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, safety and maximum tolerated dose, is a health-related biomedical outcome.

The study involves the recruitment of research participants with disease X to receive a chronic disease management program. It is designed to assess usability and to determine the maximum tolerated dose of the chronic disease program (e.g., how many in-person and telemedicine visits with adequate adherence).

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, the chronic disease management program.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to determine the maximum tolerated dose of the program to obtain adequate adherence.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, tolerable intensity and adequate adherence of the intervention, is a health-related outcome.

The study involves the recruitment of research participants with disease X to receive either an investigational drug or a placebo. It is designed to evaluate the efficacy of the investigational drug to relieve disease symptoms.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, the investigational drug or placebo.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the investigational drug on the participants’ symptoms.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, relief of symptoms, is a health-related outcome.

The study involves the recruitment of research participants with disease X to receive an investigational drug. It is designed to assess whether there is a change in disease progression compared to baseline. There is no concurrent control used in this study.

• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the investigational drug on the subject’s disease progression.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, disease progression, is a health-related outcome.

The study involves the recruitment of research participants with disease X to test an investigational in vitro diagnostic device (IVD). It is designed to evaluate the ability of the device to measure the level of an antibody in blood.

• Are the participants prospectively assigned to an intervention? No, in this context the IVD would not be considered an intervention. The IVD is being used to test its ability to measure antibody levels, but not to test its effects on any health-related biomedical or behavioral outcomes. 

The study involves the recruitment of research participants with disease X to be evaluated with an investigational in vitro diagnostic device (IVD). The study is designed to evaluate how knowledge of certain antibody levels impacts clinical management of disease.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to an intervention, measurement of an antibody level, with the idea that knowledge of that antibody level might affect clinical management.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate how knowledge of the level of an antibody might inform treatment.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being measured, how blood antibody levels inform treatment, is a health-related outcome.

The study involves the recruitment of healthy volunteers who will be randomized to different durations of sleep deprivation (including no sleep deprivation as a control) and who will have stress hormone levels measured. It is designed to determine whether the levels of stress hormones in blood rise in response to different durations of sleep deprivation.

• Does the study involve human participants? Yes, the healthy volunteers are human participants.
• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to an intervention, different durations of sleep deprivation followed by a blood draw.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to measure the effect of different durations of sleep deprivation on stress hormone levels.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, stress hormone levels, is a health-related biomedical outcome.

The study involves the analysis of de-identified, stored blood samples and de-identified medical records of patients with disease X who were treated with an approved drug. The study is designed to evaluate the level of a protein in the blood of patients that is associated with therapeutic effects of the drug.

• Does the study involve human participants? No, the study does not involve human participants because only de-identified samples and information are used.

The study involves the analysis of identifiable, stored blood samples and identified medical records of patients with disease X who were treated with an approved drug. The study is designed to evaluate the level of a protein in the blood of patients that is associated with therapeutic effects of the drug.

• Does the study involve human participants? Yes, patients are human participants because the blood and information are identifiable.
• Are the participants prospectively assigned to an intervention? No, secondary research with biospecimens or health information is not a clinical trial.

The study involves the recruitment of a healthy volunteers whose blood is drawn for genomic analysis. It is designed to identify the prevalence of a genetic mutation in the cohort and evaluate potential association between the presence of the mutation and the risk of developing a genetic disorder.

• Are the participants prospectively assigned to an intervention? No, sample collection (blood draw) is not an intervention in this context.

Physicians report that some patients being treated with drug A for disease X are also experiencing some improvement in a second condition, condition Y. The study involves the recruitment of research participants who have disease X and condition Y and are being treated with drug A. The participants are surveyed to ascertain whether they are experiencing an improvement in condition Y.

• Are the participants prospectively assigned to an intervention? No, participants are not prospectively assigned to receive an intervention as they are receiving drugs as part of their clinical care. The surveys are being used for measurement, not to modify a biomedical or behavioral outcome.

The study involves the recruitment of patients with disease X who are receiving one of three standard therapies as part of their clinical care. It is designed to assess the relative effectiveness of the three therapies by monitoring survival rates using medical records over a few years.

• Are the participants prospectively assigned to an intervention? No, there is no intervention. The therapies are prescribed as part of clinical care; they are not prospectively assigned for the purpose of the study. The study is observational.

The study involves the recruitment of research participants with disease X vs. healthy controls and comparing these participants on a range of health processes and outcomes including genomics, biospecimens, self-report measures, etc. to explore differences that may be relevant to the development of disease X.

• Are the participants prospectively assigned to an intervention? No, the measures needed to assess the outcomes are not interventions in this context, as the study is not intended to determine whether the measures modify a health-related biomedical or behavioral outcome.

The study involves the recruitment of healthy volunteers for a respiratory challenge study; participants are randomized to receive different combinations of allergens. The study evaluates the severity and mechanism of the immune response to different combinations of allergens introduced via inhalation.

• Does the study involve human participants? Yes, healthy volunteers are human participants.
• Are the participants prospectively assigned to an intervention? Yes, healthy volunteers are prospectively assigned to randomly selected combinations of allergens.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is evaluating the effects of different combinations of allergens on the immune response in healthy individuals.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the study evaluates the severity and mechanism of the immune reaction to allergens, which are health-related biomedical outcomes.

The study involves the recruitment of research participants with Alzheimer’s disease (AD) to evaluate the effects of an investigational drug on memory, and retention and recall of information.

• Are the participants prospectively assigned to an intervention? Yes, participants are prospectively assigned to receive the investigational drug.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is evaluating the effects of the drug on participants’ memory.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the study evaluates memory, and retention and recall of information in the context of AD.

The study involves the recruitment of individuals to receive a new behavioral intervention for sedentary behavior. It is designed to measure the effect of the intervention on hypothesized differential mediators of behavior change.

• Are the participants prospectively assigned to an intervention? Yes, participants are prospectively assigned to receive a behavioral intervention.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is evaluating the effects of the intervetion on mediators of behavior change.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, mediators of behavior change, are behavioral outcomes relevant to health.

The study involves the recruitment of patients with disease X to be evaluated with a new visual acuity task. It is designed to evaluate the ability of the new task to measure visual acuity as compared with the gold standard Snellen Test

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to an intervention, the new visual acuity test.
• Is the study designed to evaluate the effect of the intervention on the participants? No, the study is designed to evaluate the ability of the new visual acuity test to measure visual acuity as compared to the gold standard Snellen Test, but not to modify visual acuity.

The study involves the recruitment of research participants with CHF who were hospitalized before or after implementation of the Medicare incentives to reduce re-hospitalizations. Morbidity, mortality, and quality of life of these participants are evaluated to compare the effects of these Medicare incentives on these outcomes.

• Are the participants prospectively assigned to an intervention? No, the intervention (incentives to reduce re-hospitalization) were assigned by Medicare, not by the research study.

The study involves the recruitment of healthcare providers to assess the extent to which being provided with genomic sequence information about their patients informs their treatment of those patients towards improved outcomes.

• Does the study involve human participants? Yes, both the physicians and the patients are human participants.
• Are the participants prospectively assigned to an intervention? Yes, physicians are prospectively assigned to receive genomic sequence information, which is the intervention.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of intervening with physicians, on the treatment they provide to their patients.
• Is the effect being evaluated a health-related, biomedical, or behavioral outcome? Yes, the effect being evaluated, the extent to which providing specific information to physicians informs the treatment of patients, is a health-related outcome.

The study involves the recruitment of research participants with a behavioral condition to receive either an investigational behavioral intervention or a behavioral intervention in clinical use. It is designed to evaluate the effectiveness of the investigational intervention compared to the intervention in clinical use in reducing the severity of the obsessive compulsive disorder.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to an intervention, either the investigational intervention or an intervention in clinical use.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate whether the investigational intervention is as effective as the standard intervention, at changing behavior.
• Is the effect being evaluated a health-related, biomedical, or behavioral outcome? Yes, the effect being evaluated, the interventions’ effectiveness in reducing the severity of the condition, is a health-related behavioral outcome.

The study involves the recruitment of physicians who will be randomly assigned to use a new app or an existing app, which cues directed interviewing techniques. The study is designed to determine whether the new app is better than the existing app at assisting physicians in identifying families in need of social service support. The number of community service referrals will be measured.

• Does the study involve human participants? Yes, both the physicians and the families are human participants.
• Are the participants prospectively assigned to an intervention? Yes, physicians are prospectively assigned to use one of two apps, which are the interventions.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of intervening with physicians, on social service support referral for families.
• Is the effect being evaluated a health-related, biomedical, or behavioral outcome? Yes, the effect being evaluated, the number of referrals, is a health-related outcome.

The study involves the recruitment of parents to participate in focus groups to discuss topics related to parental self-efficacy and positive parenting behaviors. It is designed to gather information needed to develop an intervention to promote parental self-efficacy and positive parenting behaviors.

• Does the study involve human participants? Yes, the parents are human participants.
• Are the participants prospectively assigned to an intervention? No, a focus group is not an intervention.

The study involves the recruitment of healthy volunteers to test a new behavioral intervention. It is designed to evaluate the effect of a meditation intervention on adherence to exercise regimens and quality of life to inform the design of a subsequent, fully-powered trial.

• Does the study involve human participants? Yes, study participants are human participants.
• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to a behavioral intervention.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the intervention on adherence, and quality of life.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, adherence and quality of life are health-related outcomes.

A study will test the feasibility a mobile phone app designed to increase physical activity. A group of sedentary individuals will use the app for a week while their interactions with the app are monitored. The number of interactions with the app will be measured, as well as any software issues. Participants will also complete a survey indicating their satisfaction with and willingness to use the app, as well as any feedback for improvement. The app’s effect on physical activity, weight, or cardiovascular fitness will not be evaluated.

• Does the study involve human participants? Yes, sedentary individuals will be enrolled.
• Are the participants prospectively assigned to an intervention? The participants will interact with the app for a week.
• Is the study designed to evaluate the effect of the intervention on the participants? No. While the participants’ interactions are monitored (steps or heart rate may be recorded in this process), the study is NOT measuring the effect of using the app ON the participant. The study is only measuring the usability and acceptability of the app, and testing for bugs in the software. The effect on physical activity is NOT being measured.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? N/A

The study involves the recruitment of healthy family members of patients hospitalized for disease X to test two CPR training strategies. Participants will receive one of two training strategies. The outcome is improved CPR skills retention.

• Does the study involve human participants? Yes, family members of patients are human participants.
• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to one of two CPR educational strategies.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of educational strategies on CPR skills.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, retention of CPR skills is a health-related behavioral outcome.

The study involves the recruitment of research participants in three different communities (clusters) to test three CPR training strategies. The rate of out-of- hospital cardiac arrest survival will be compared.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive one of three types of CPR training, which is the intervention.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of different CPR training strategies on patient survival rates post cardiac arrest.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, out-of-hospital cardiac arrest survival is a health-related outcome.

A study involves the recruitment of school children to evaluate two different tools for monitoring food intake. Food consumption behavior will be measured by asking children to activate a pocket camera during meals and to use a diary to record consumed food. The accuracy of the two food monitoring methods in measuring energy intake will be assessed.

• Does the study involve human participants? Yes, children are human participants.
• Are the participants prospectively assigned to an intervention? No, in this context the monitoring methods would not be considered an intervention. The study is designed to test the accuracy of two monitoring methods, but not to test the effect on any health-related biomedical or behavioral outcomes. 

A study involves the recruitment of school children to evaluate two different tools for monitoring food intake. Food consumption behavior will be measured by asking children to activate a pocket camera during meals and to use a diary to record consumed food. Changes to eating behavior will be assessed.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to two food monitoring methods.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to determine whether using the monitoring methods changes eating behavior.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, eating behavior is a health-related outcome.

A study involves the recruitment of children at two schools to monitor eating behavior. Children’s food choices will be monitored using a remote food photography method. Food consumption and the accuracy of food monitoring methods will be assessed.

• Does the study involve human participants? Yes, the children participating in this study are human participants.
• Are the participants prospectively assigned to an intervention? No, not in this context. The study involves observing and measuring eating behavior, but not modifying it. This is an observational study.

A study involves the recruitment of children at two schools to evaluate their preferences for graphics and colors used in healthy food advertisements. Children will be presented with multiple health advertisements and their preferences for graphics and colors will be assessed.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to see different advertisements.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the advertisements.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? No, preferences are not health-related biomedical or behavioral outcomes.

The study involves ambulatory patients who have new-onset stable angina and who are recruited from community practices. They are randomized to undergo CT angiography or an exercise stress test of the doctor’s choice. To keep the trial pragmatic, the investigators do not prescribe a protocol for how physicians should respond to test results. The study is designed to determine whether the initial test (CT angiography or stress test) affects long-term rates of premature death, stroke, or myocardial infarctions.

• Are the participants prospectively assigned to an intervention? Yes, the participants are randomized to undergo CT angiography or an exercise stress test.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to determine whether the initial test done affects long-term rates of certain clinical events.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, premature death, stroke, and myocardial infarction are health-related biomedical outcomes.

The study involves patients who present with stable angina to community practices. As part of their routine care some of their physicians refer them for CT angiography, while others refer them for exercise stress tests. The study is designed to see whether or not there's an association between the type of test that is chosen and long-term risk of death, stroke, or myocardial infarction.

• Are the participants prospectively assigned to an intervention? No, the intervention is not prospectively assigned by the investigators. Rather, the intervention, in this case diagnostic study, occurs as part of routine clinical care.

The investigators conduct a longitudinal study of patients with schizophrenia. Their physicians, as part of their standard clinical care, prescribe antipsychotic medication. The investigators conduct an imaging session before starting treatment; they repeat imaging 4-6 weeks later.

• Does the study involve human participants? Yes.
• Are the participants prospectively assigned to an intervention? No, not in this context.  Antipsychotic medications are given as part of clinical care, not as part of a prospective, approved research protocol.  

The investigators conduct a longitudinal study of patients with schizophrenia. Their physicians, as part of their standard clinical care, prescribe antipsychotic medication. As part of the research protocol, all participants will be prescribed the same dose of the antipsychotic medication. The investigators conduct an imaging session before starting treatment; they repeat imaging 4-6 weeks later.

• Are the participants prospectively assigned to an intervention? Yes, although participants are all receiving antipsychotic medication as part of their standard medical care, the dose of the antipsychotic medication is determined by the research protocol, rather than individual clinical need.
• Is the study designed to evaluate the effect of the intervention on the participants?  Yes, the study is designed to evaluate the effect of a dose of antipsychotic medication on brain function.
• Is the effect being evaluated a health-related biomedical or behavioral outcome ? Yes, brain function measured by imaging is a health-related outcome.

The study involves recruitment of healthy volunteers who will wear a thermal compression device around their legs. This pilot study is designed to examine preliminary performance and safety of a thermal compression device worn during surgery. Investigators will measure core temperature, comfort, and presence of skin injury in 15-minute intervals.

• Are the participants prospectively assigned to an intervention? Yes, participants are assigned to wear a thermal compression device.
• Is the study designed to evaluate the effect of the intervention on the participants?  Yes, the study is designed to evaluate the effect of the thermal compression device on participant core temperature, comfort, and presence of skin injury.
• Is the effect being evaluated a health-related biomedical or behavioral outcome ? Yes, participant core temperature, comfort, and presence of skin injury are health-related biomedical outcomes.

The study involves collection of data on hospitalizations for various acute illnesses among people who live close to a border between two states that have recently implemented different laws related to public health (e.g. smoking regulations, soda taxes). The investigators want to take advantage of this “natural experiment” to assess the health impact of the laws.

• Does the study involve human participants?  Yes, the study involves human participants.
• Are the participants prospectively assigned to an intervention?  No, the interventions were assigned by state laws and state of residence, not by the research study.

The study involves recruitment of healthy volunteers to engage in working memory tasks while undergoing transcranial magnetic stimulation (TMS) to induce competing local neuronal activity. The study is measuring task performance to investigate the neural underpinnings of working memory storage and processing.

• Are the participants prospectively assigned to an intervention? Yes, healthy volunteers are prospectively assigned to receive TMS stimulation protocols during a working memory task.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is evaluating the effects of local TMS stimulation on working memory performance and oscillatory brain activity in healthy individuals.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the study evaluates working memory processes, which are health-related biomedical outcomes.

The study involves recruitment of healthy volunteers to engage in a social valuation task while dopamine tone in the brain is manipulated using tolcapone, an FDA-approved medication. The study aims to understand the role of dopamine in social decision-making and to search for neural correlates of this valuation using fMRI.

• Are the participants prospectively assigned to an intervention? Yes, healthy volunteers are prospectively assigned to receive tolcapone during a social valuation task.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is evaluating the effects of modulating dopamine tone on social decision-making. Although this study uses an FDA-approved drug to modulate dopamine tone, the goal of this intervention is to understand the role of dopamine in a fundamental phenomenon (social valuation), and not to study the mechanism of action of the drug or its clinical effects.

The career development candidate proposes to independently lead a study to test a new drug A on patients with disease X. Patients will be randomized to a test and control group, with the test group receiving one dose of drug A per week for 12 months and controls receiving placebo. To assess presence, number, and type of any polyps, a colonoscopy will be performed. To assess biomarkers of precancerous lesions, colon mucosal biopsies will be collected. Complete blood count will be measured, and plasma will be stored for potential biomarker evaluation.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, drug A or placebo.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of drug A and placebo on the presence and type of polyps.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, the presence and type of polyps, is a health-related biomedical outcome.

Ancillary Study to Case Study #42a: Some types of drug A being evaluated in Case Study #42a have been reported to impact renal function. An internal medicine fellow performs an ancillary study where stored plasma from Case Study #42a will be evaluated for multiple biomarkers of renal function.

• Does the study involve human participants? Yes, patients are human participants because the plasma and information are identifiable.
• Are the participants prospectively assigned to an intervention? No, because the assignment of participants to an intervention occurs as part of an existing, separately funded clinical trial. This proposal would be considered an ancillary study that is not an independent clinical trial.

Ancillary Study to Case Study #42a: An internal medicine fellow designs an independent ancillary trial where a subset of patients from the parent trial in Case Study #42a will also receive drug B, based on the assumption that a two-drug combination will work significantly better than a single drug at both improving renal function and reducing polyps. The test subjects will be evaluated for renal function via plasma clearance rates at 6 and 12 months after initiation of drugs A and B.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to receive an intervention, drugs A and B.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of drugs A and B on renal function.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the effect being evaluated, renal function, is a health-related biomedical outcome.

A group of healthy young adults will perform a Go/No-Go task while undergoing fMRI scans. The purpose of the study is to characterize the pattern of neural activation in the frontal cortex during response inhibition, and the ability of the participant to correctly withhold a response on no-go

• Does the study involve human participants? Yes, healthy young adults will be enrolled in this study.
• Are the participants prospectively assigned to an intervention? Yes, the participants will be prospectively assigned to perform a Go/No-Go task, which involves different levels of inhibitory control.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the Go/No-Go task on neural activation in the frontal cortex. The study will measure inhibitory control and the neural systems being engaged. In this study, the Go/No-Go task is the independent variable, and behavioral performance and the associated fMRI activations are the dependent variables.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the neural correlates of inhibitory control and behavioral performance are health-related biomedical outcomes.

A group of adolescents will participate in a longitudinal study examining changes in executive function over the course of a normal school year. Color naming performance on the standard version of the Stroop test will be obtained. All measures will be compared at multiple time points during the school year to examine changes in executive function. The purpose is to observe changes in executive function and to observe if differences exist in the Stroop effect over the course of the school year for these adolescents.

• Does the study involve human participants? Yes, adolescents will be enrolled in this study.
• Are the participants prospectively assigned to an intervention? No, there is no intervention in this study and no independent variable manipulated. The adolescents are not prospectively assigned to an intervention, but instead the investigator will examine variables of interest (including the Stroop test) over time. The Stroop effect is used as a measurement of point-in-time data.
• Is the study designed to evaluate the effect of the intervention on the participants? No, there is no intervention. Performance on the Stroop test is a well-established measure of executive function and the test is not providing an independent variable of interest here. It is not being used to manipulate the participants or their environment. The purpose is simply to obtain a measure of executive function in adolescents over the course of the school year.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? N/A. No effect of an intervention is being evaluated.

A group of participants with social anxiety will perform an experimentally manipulated Stroop test. In this variant of the Stroop test, the stimuli presented are varied to include emotional and neutral facial expressions presented in different colors. Participants are instructed to name the colors of the faces presented, with the expectation that they will be slower to name the color of the emotional face than the neutral face. The purpose of the study is to examine the degree to which participants with social anxiety will be slower to process emotional faces than neutral faces.

• Does the study involve human participants? Yes, participants with social anxiety will be enrolled in this study.
• Are the participants prospectively assigned to an intervention? Yes, the participants will be prospectively assigned to perform a modified Stroop test using different colored emotional/neutral faces to explore emotional processing in people with social anxiety. Note that the independent variable is the presentation of emotional vs neutral faces.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to measure the effect of emotional valence (i.e. emotional faces) on participant response time to name the color. The purpose is to determine whether the response time to emotional faces is exaggerated for people with social anxiety as compared to neutral faces. Note that the response time to name the colors is the dependent variable in this study.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the processing of emotional information is a health-related biomedical outcome.

The study involves healthy volunteers and compares temporal SNR obtained with a new fMRI pulse sequence with that from another sequence.

• Are the participants prospectively assigned to an intervention? No, in this context the different pulse sequences would not be considered an intervention. The pulse sequences are not being used to modify any biomedical or behavioral outcome; rather the investigator is comparing performance characteristics of the two pulse sequences.

The study is designed to demonstrate that a new imaging technology (e.g. MRI, PET, ultrasound technologies, or image processing algorithm) is equivalent to, or has better sensitivity/specificity than a standard of care imaging technology. Aim one will use the new imaging technology and the gold standard in ten healthy volunteers. Aim Two will use the new imaging technology and the gold standard before and after a standard care procedure in ten patients. In both aims the performance of the new technology will be compared to the gold standard. No clinical care decisions will be made based on the use of the device in this study.

• Does the study involve human participants? YES. Aim one will study ten healthy volunteers, and aim two will study ten patient volunteers.
• Are the participants prospectively assigned to an intervention? Yes, participants will be prospectively assigned to be evaluated with a new imaging technology and the gold standard technology.
• Is the study designed to evaluate the effect of the intervention on the participants? No, the study is not measuring the effect of the technologies ON the human subjects. The study is determining if the new technology is equivalent or better than the gold standard technology. No effect on the participant is being measured.

An investigator proposes to add secondary outcomes to an already funded clinical trial of a nutritional intervention. The trial is supported by other funding, but the investigator is interested in obtaining NIH funding for studying oral health outcomes. Participants in the existing trial would be assessed for oral health outcomes at baseline and at additional time points during a multi-week dietary intervention. The oral health outcomes would include measures of gingivitis and responses to oral health related quality of life questionnaires. Oral fluids would be collected for analysis of inflammatory markers and microbiome components.

• Are the participants prospectively assigned to an intervention? No, because the assignment of participants to an intervention (and the administration of the intervention) occur as part of an existing, separately funded clinical trial. This proposal would be considered an ancillary study that leverages an already existing clinical trial.

The goal of the project is to use functional neuroimaging to distinguish patients with temporomandibular disorders (TMD) who experience TMD pain through centralized pain processes from those with TMD related to peripheral pain. Pain processing in a study cohort of TMD patients and healthy controls will be measured through functional magnetic resonance neuroimaging (fMRI) following transient stimulation of pain pathways through multimodal automated quantitative sensory testing (MAST QST). TMD patients will receive study questionnaires to better correlate the extent to which TMD pain centralization influences TMD prognosis and response to standard of care peripherally targeted treatment (prescribed by physicians, independently of the study).

• Are the participants prospectively assigned to an intervention? No, not in this context. The transient stimulation of pain pathways and the fMRI are being performed to measure and describe brain activity, but not to modify it.

An investigator proposes to perform a study of induced gingivitis in healthy humans, to study microbial colonization and inflammation under conditions of health and disease. During a 3-week gingivitis induction period, each study participant will use a stent to cover the teeth in one quadrant during teeth brushing. A contralateral uncovered quadrant will be exposed to the individual's usual oral hygiene procedures, to serve as a control. Standard clinical assessments for gingivitis will be made and biospecimens will be collected at the point of maximal induced gingivitis, and again after normal oral hygiene is resumed. Biospecimens will be assessed for microbial composition and levels of inflammation-associated chemokines.

• Are the participants prospectively assigned to an intervention? Yes, the participants are prospectively assigned to an intervention, abstaining from normal oral hygiene for a portion of the mouth, to induce gingivitis.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to evaluate the effect of the induced gingivitis on microbial composition and levels of inflammatory chemokines in oral samples.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, the microbial composition and chemokine levels in oral samples are health-related biomedical outcomes.

The study will enroll older adults with hearing loss, comparing the effectiveness of enhanced hearing health care (HHC) to usual HHC. In addition to routine hearing-aid consultation and fitting, participants randomized to enhanced HCC will be provided patient-centered information and education about a full range of hearing assistive technologies and services. Study outcomes include the utilization of technology or services, quality of life, communication abilities, and cognitive function.

• Does the study involve human participants? Yes, the study enrolls older adults with hearing loss.
• Are the participants prospectively assigned to an intervention? Yes, participants are randomized to receive enhanced HCC or usual HCC interventions.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study will evaluate enhanced HCC’s effectiveness in modifying participant behavior and biomedical outcomes.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, rate of technology/service utilization is a behavioral outcome and quality of life, communications, and cognition are biomedical outcomes that may be impacted by the interventions.

The study involves the recruitment of obese individuals who will undergo a muscle biopsy before and after either exercise training or diet-induced weight loss. Sarcolemmal 1,2-disaturated DAG and C18:0 ceramide species and mitochondrial function will be measured. Levels will be correlated with insulin sensitivity.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to either exercise training or a diet.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to compare the effects of the interventions on muscle metabolism.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, muscle metabolism/signaling is a health-related outcome.

The study involves the recruitment of participants with type 2 diabetes who will undergo a muscle biopsy before and after a fast to measure acetylation on lysine 23 of the mitochondrial solute carrier adenine nucleotide translocase 1 (ANT1). Levels will be related to rates of fat oxidation.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to undergo a fast.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to compare the effects of the fast on molecular parameters of metabolism.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, metabolism is a health-related outcome.

Insulin-resistant and insulin-sensitive nondiabetic adults who have a parent with type 2 diabetes will be followed over time to understand the role of mitochondrial dysfunction in the development of diabetes. Oral glucose tolerance tests will be performed annually to measure insulin sensitivity and glycemic status. Participants will also undergo a brief bout of exercise, and mitochondrial ATP synthesis rates will be measured by assessing the rate of recovery of phosphocreatine in the leg muscle, using 31P magnetic resonance spectroscopy.

• Are the participants prospectively assigned to an intervention? No, the participants are not assigned to an intervention; the OGTT and 31P MRS are measures.

Participants with chronic kidney disease will be recruited to receive one of two drug agents. After 6 weeks of therapy, subjects will undergo vascular function testing and have measures of oxidative stress evaluated in their plasma and urine. Results of the function testing and the oxidative stress biomarkers will be related to drug treatment.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to receive two different drugs.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to compare the effects of the drugs on vascular function.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, vascular function is a health-related outcome.

Participants with Autosomal Dominant Polycystic Kidney Disease will be recruited to receive an oral curcumin therapy or placebo and the participants will undergo vascular function testing, renal imaging to assess kidney size, and assessment of oxidative stress biomarkers in urine and plasma after an ascorbic acid challenge. Changes in these outcomes will be related to oral therapy.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to receive medication or placebo.
• Is the study designed to evaluate the effect of the intervention on the participants? Yes, the study is designed to compare the effects of the drugs on vascular function and kidney size.
• Is the effect being evaluated a health-related biomedical or behavioral outcome? Yes, vascular function and kidney size are health-related outcomes.

Kidney transplant recipients will be recruited to undergo an experimental imaging procedure at several timepoints up to 4 months post-transplantation. Output from the images will be related to pathological assessments of the transplant as well as clinical measures of renal function.

• Are the participants prospectively assigned to an intervention? No, the participants are not assigned to receive an intervention. They undergo transplantation as part of their routine clinical care. The imaging procedure is a measure and not an intervention.

The study proposes the development of a novel probe to assess clearance of a nutritional metabolite in a given disease state. The probe is a GMP grade, deuterated, intravenously administered tracer and clearance is assessed by mass spectrometry analysis of serial blood draws. Participants will either receive a micronutrient supplement or will receive no supplementation. The clearance rate of the probe will be compared in the two groups, to understand the performance of the probe.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to receive either a micronutrient supplement or nothing.
• Is the study designed to evaluate the effect of the intervention on the participants? No, the intervention is being used to assess the performance of the probe and is not looking at an effect on the participant.

In order to assess the contribution of ingested glycolate to oxalate production, healthy participants will be recruited to a study involving the consumption of a controlled diet for three days, followed by an infusion of 13C2-glycolate. Blood and urine will be collected during the subsequent 24 hours to assess the amount of labeled glycolate in plasma and urine oxalate.

• Are the participants prospectively assigned to an intervention? Yes, the participants are assigned to receive a controlled diet for three days.
• Is the study designed to evaluate the effect of the intervention on the participants? No, the intervention (controlled diet) is being used to minimize exogenous dietary sources of oxalate in the participants prior to the labeled tracer infusion. The study will not be evaluating the effect of the diet on the participants.

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• Ethical Considerations in Research | Types & Examples

Ethical Considerations in Research | Types & Examples

Published on October 18, 2021 by Pritha Bhandari . Revised on May 9, 2024.

Ethical considerations in research are a set of principles that guide your research designs and practices. Scientists and researchers must always adhere to a certain code of conduct when collecting data from people.

The goals of human research often include understanding real-life phenomena, studying effective treatments, investigating behaviors, and improving lives in other ways. What you decide to research and how you conduct that research involve key ethical considerations.

These considerations work to

• protect the rights of research participants
• enhance research validity
• maintain scientific or academic integrity

Table of contents

Why do research ethics matter, getting ethical approval for your study, types of ethical issues, voluntary participation, informed consent, confidentiality, potential for harm, results communication, examples of ethical failures, other interesting articles, frequently asked questions about research ethics.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe for research subjects.

You’ll balance pursuing important research objectives with using ethical research methods and procedures. It’s always necessary to prevent permanent or excessive harm to participants, whether inadvertent or not.

Defying research ethics will also lower the credibility of your research because it’s hard for others to trust your data if your methods are morally questionable.

Even if a research idea is valuable to society, it doesn’t justify violating the human rights or dignity of your study participants.

Prevent plagiarism. Run a free check.

Before you start any study involving data collection with people, you’ll submit your research proposal to an institutional review board (IRB) .

An IRB is a committee that checks whether your research aims and research design are ethically acceptable and follow your institution’s code of conduct. They check that your research materials and procedures are up to code.

If successful, you’ll receive IRB approval, and you can begin collecting data according to the approved procedures. If you want to make any changes to your procedures or materials, you’ll need to submit a modification application to the IRB for approval.

If unsuccessful, you may be asked to re-submit with modifications or your research proposal may receive a rejection. To get IRB approval, it’s important to explicitly note how you’ll tackle each of the ethical issues that may arise in your study.

There are several ethical issues you should always pay attention to in your research design, and these issues can overlap with each other.

You’ll usually outline ways you’ll deal with each issue in your research proposal if you plan to collect data from participants.

Voluntary participation means that all research subjects are free to choose to participate without any pressure or coercion.

All participants are able to withdraw from, or leave, the study at any point without feeling an obligation to continue. Your participants don’t need to provide a reason for leaving the study.

It’s important to make it clear to participants that there are no negative consequences or repercussions to their refusal to participate. After all, they’re taking the time to help you in the research process , so you should respect their decisions without trying to change their minds.

Voluntary participation is an ethical principle protected by international law and many scientific codes of conduct.

Take special care to ensure there’s no pressure on participants when you’re working with vulnerable groups of people who may find it hard to stop the study even when they want to.

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See an example

Informed consent refers to a situation in which all potential participants receive and understand all the information they need to decide whether they want to participate. This includes information about the study’s benefits, risks, funding, and institutional approval.

You make sure to provide all potential participants with all the relevant information about

• what the study is about
• the risks and benefits of taking part
• how long the study will take
• your supervisor’s contact information and the institution’s approval number

Usually, you’ll provide participants with a text for them to read and ask them if they have any questions. If they agree to participate, they can sign or initial the consent form. Note that this may not be sufficient for informed consent when you work with particularly vulnerable groups of people.

If you’re collecting data from people with low literacy, make sure to verbally explain the consent form to them before they agree to participate.

For participants with very limited English proficiency, you should always translate the study materials or work with an interpreter so they have all the information in their first language.

In research with children, you’ll often need informed permission for their participation from their parents or guardians. Although children cannot give informed consent, it’s best to also ask for their assent (agreement) to participate, depending on their age and maturity level.

Anonymity means that you don’t know who the participants are and you can’t link any individual participant to their data.

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, and videos.

In many cases, it may be impossible to truly anonymize data collection . For example, data collected in person or by phone cannot be considered fully anonymous because some personal identifiers (demographic information or phone numbers) are impossible to hide.

You’ll also need to collect some identifying information if you give your participants the option to withdraw their data at a later stage.

Data pseudonymization is an alternative method where you replace identifying information about participants with pseudonymous, or fake, identifiers. The data can still be linked to participants but it’s harder to do so because you separate personal information from the study data.

Confidentiality means that you know who the participants are, but you remove all identifying information from your report.

All participants have a right to privacy, so you should protect their personal data for as long as you store or use it. Even when you can’t collect data anonymously, you should secure confidentiality whenever you can.

Some research designs aren’t conducive to confidentiality, but it’s important to make all attempts and inform participants of the risks involved.

As a researcher, you have to consider all possible sources of harm to participants. Harm can come in many different forms.

• Psychological harm: Sensitive questions or tasks may trigger negative emotions such as shame or anxiety.
• Social harm: Participation can involve social risks, public embarrassment, or stigma.
• Physical harm: Pain or injury can result from the study procedures.
• Legal harm: Reporting sensitive data could lead to legal risks or a breach of privacy.

It’s best to consider every possible source of harm in your study as well as concrete ways to mitigate them. Involve your supervisor to discuss steps for harm reduction.

Make sure to disclose all possible risks of harm to participants before the study to get informed consent. If there is a risk of harm, prepare to provide participants with resources or counseling or medical services if needed.

Some of these questions may bring up negative emotions, so you inform participants about the sensitive nature of the survey and assure them that their responses will be confidential.

The way you communicate your research results can sometimes involve ethical issues. Good science communication is honest, reliable, and credible. It’s best to make your results as transparent as possible.

Take steps to actively avoid plagiarism and research misconduct wherever possible.

Plagiarism means submitting others’ works as your own. Although it can be unintentional, copying someone else’s work without proper credit amounts to stealing. It’s an ethical problem in research communication because you may benefit by harming other researchers.

Self-plagiarism is when you republish or re-submit parts of your own papers or reports without properly citing your original work.

This is problematic because you may benefit from presenting your ideas as new and original even though they’ve already been published elsewhere in the past. You may also be infringing on your previous publisher’s copyright, violating an ethical code, or wasting time and resources by doing so.

In extreme cases of self-plagiarism, entire datasets or papers are sometimes duplicated. These are major ethical violations because they can skew research findings if taken as original data.

You notice that two published studies have similar characteristics even though they are from different years. Their sample sizes, locations, treatments, and results are highly similar, and the studies share one author in common.

Research misconduct

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement about data analyses.

Research misconduct is a serious ethical issue because it can undermine academic integrity and institutional credibility. It leads to a waste of funding and resources that could have been used for alternative research.

Later investigations revealed that they fabricated and manipulated their data to show a nonexistent link between vaccines and autism. Wakefield also neglected to disclose important conflicts of interest, and his medical license was taken away.

This fraudulent work sparked vaccine hesitancy among parents and caregivers. The rate of MMR vaccinations in children fell sharply, and measles outbreaks became more common due to a lack of herd immunity.

Research scandals with ethical failures are littered throughout history, but some took place not that long ago.

Some scientists in positions of power have historically mistreated or even abused research participants to investigate research problems at any cost. These participants were prisoners, under their care, or otherwise trusted them to treat them with dignity.

To demonstrate the importance of research ethics, we’ll briefly review two research studies that violated human rights in modern history.

These experiments were inhumane and resulted in trauma, permanent disabilities, or death in many cases.

After some Nazi doctors were put on trial for their crimes, the Nuremberg Code of research ethics for human experimentation was developed in 1947 to establish a new standard for human experimentation in medical research.

In reality, the actual goal was to study the effects of the disease when left untreated, and the researchers never informed participants about their diagnoses or the research aims.

Although participants experienced severe health problems, including blindness and other complications, the researchers only pretended to provide medical care.

When treatment became possible in 1943, 11 years after the study began, none of the participants were offered it, despite their health conditions and high risk of death.

Ethical failures like these resulted in severe harm to participants, wasted resources, and lower trust in science and scientists. This is why all research institutions have strict ethical guidelines for performing research.

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.

• Normal distribution
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias
• Social desirability bias

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

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Are case studies considered as scientific research?

This a good question because it could be considered a type of scientific research. Discovery type research exmines many cases of an event and often comes up with statistical information from which one can draw a conclusion. For instance tornadoes occur when the wind shear in the lowest kilometer is strong and thunderstorms occur.

The case study looks at one praticular event and shows how laws or statistical studies successfully apply to the single event. Certainly a type of scientific research.

I gave this a lot of thought after my initial answer and want to say that it is arguable that case studeies should not be considered scientific research. The case study (and I have done many of them) can use scientific processes to examine their application in real life, but often there is no new discovery. Nevertheless, I did find a commonality in case studies that lead to a conclusion that was useful in my discipline. The finding though fail to examine all of the other contributing factors. In other words, why did the technique fail sometimes.

A very good question for philosophic discussion in terminology. All I wanted was successful results. Sorry to give a kind of yes and know answer.

Add your answer:

A strength of the case study approach in sex research is that case studies?

I need this answer too! I bet you're taking human sexuality

Why do scientists need governmental funding?

(a) The scientists involved might not have tried to make a business case for their research to secure funding from business, inspite of its potential commercial or industrial value. (b) Although the outcomes of the research might have value to business it might be too expensive or risky to be of interest to business. (c) There might be political reasons for supporting the research. (d) There might be no business value for the results of the research, or that business value might be unclear. (e) Similar to (c), there is student demand for studies in many university faculties, and public interest in their results, in spite of the absence of any commercial or practical value for them.

When was Clinical Case Studies created?

Clinical Case Studies was created in 2002.

Which of the following is an example of a case studies of standard?

teacher standards

Nursing Case studies on Status epilepticus?

Continuous seizure

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• Published: 04 September 2024

Science convergence in affective research is associated with impactful multidisciplinary appeal rather than multidisciplinary content

• Vitalii Zhukov 1 ,
• Alexander M. Petersen 2 ,
• Daniel Dukes   ORCID: orcid.org/0000-0001-8360-849X 3 , 4 ,
• David Sander   ORCID: orcid.org/0000-0003-1266-9361 3 , 4 ,
• Panagiotis Tsiamyrtzis 5 , 6 &
• Ioannis Pavlidis   ORCID: orcid.org/0000-0001-8025-2600 1  

Communications Psychology volume  2 , Article number:  83 ( 2024 ) Cite this article

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Affectivism is a research trend dedicated to the study of emotions and their role in cognition and human behavior. Affectivism both complements and competes with cognitivism, which typically neglects affect in explaining behavior. By the nature of their subject, both affectivism and cognitivism constitute fertile grounds for studying the confluence of conceptual knowledge from diverse disciplines, which is often credited with major breakthroughs and is known as convergence science. Analyzing over half a million relevant publications from PubMed, selected according to psychologist chosen MeSH terms, we find that affectivism yields higher impact than cognitivism, as measured through normalized citations. Importantly, this higher impact is strongly associated with higher multidisciplinarity in the citations of affectivism publications but lower multidisciplinarity in the papers themselves. Hence, the case of affectivism suggests that research content of low topical diversity but broad value can generate strong and wide-ranging scholarly impact, feeding downstream convergence.

Introduction

For the first half of the 20th century, behaviorism held strong in psychological sciences as the preferred method of understanding human behaviors. Per behaviorism, behaviors are either innate or formed through conditioning, which is interaction with the environment 1 . This viewpoint carries the following important implication: behavior can be studied through external observations alone; cognition and emotions are considered subjective and thus, not reliable explanatory variables of behavior.

By the 1950s, the cognitive sciences began emerging as a response to behaviorism’s limitations 2 . Cognitivism argued that cognitive representations and information processing could be used to explain behavior 3 , while still typically neglecting emotion and other affective processes. Cognitivism was central to psychological theory and practice in the second half of the 20th century. Because cognitivism was, early on, linked to brain science—a melting pot of various scientific fields 4 , 5 , 6 —and to other disciplines such as philosophy and linguistics, cognitivism could arguably be considered as a convergence science paradigm 7 .

Since the later part of the 20th century, complementing the cognitive sciences, the field of affective sciences emerged precisely to understand those phenomena that were typically neglected by the cognitive sciences: emotions and other affective processes 8 . It has recently been proposed that, as a result of the emergence of affective sciences with foundations in the cognitive sciences, the framework of affectivism now brings into the fold emotions, feelings, and other affective processes to explain both cognition and behavior. In a recent consensus paper, over 60 scientists from various disciplines suggested that affectivism is not only on the rise but is also characterized by increasing multi-disciplinary interactions 9 . Per this view, affectivism is cast as a natural experiment in convergence science. The capacity of convergence science to address grand research challenges is widely acknowledged 10 , but its inner workings are not yet completely understood. This motivates a deeper study of affectivism and the affective sciences vis-à-vis cognitivism and the cognitive sciences to reveal the role of convergent processes in the development of these two fields, and ultimately the interdisciplinary understanding of mind, brain, and behavior.

A key issue that drives our investigation is the nature of convergence in affectivism vs. cognitivism and how it is associated to the impact of these two schools. In this respect, our study could be viewed as an effort to put to test some of the ideas proposed by the recent consensus paper on the rise of affectivism 9 . Thematically, we differentiate between Affective papers (i.e., those papers that focus on topics that are typical of the affective sciences), Cognitive papers (i.e., those papers that focus on topics that are typical of the cognitive sciences), and Mixed papers that seem to draw from both affective and cognitive sciences. The Affective and Mixed categories fall under the affectivism trend, while the Cognitive category falls under the cognitivism trend. Methodologically, we differentiate between the convergent content of a paper vs. the convergent interest this paper generates in the literature after it has been published. This analytical approach is meant to address a profound and heretofore open research question regarding convergence’s generative mechanism:

Because convergence science is associated with research advances 10 , investigating the generative mechanisms of convergence is akin to looking for the mother lode.

We seek to understand how thematic diversity (aka multidisciplinary content), which is a fundamental measure of convergence science, maps onto research outcomes in affectivism and cognitivism. We quantify such outcomes via citation impact, employing normalization methods consistent with best practices 11 . To ameliorate confounding effects and increase trust in any association between citation impact and thematic diversity, we seek to include in our models well-known citation controls. In this direction, Tahamtan & Bornmann proposed a set of article-level factors that can influence citing behavior 12 . These factors include in order of importance:

Topical composition of article: The topical composition of an article is not only a broadly recognized factor of citation impact, but also a fundamental element of convergence science analysis. In every science of science investigation we performed thus far, the topical composition of articles emerged as a strong predictor of citation impact. These investigations included analysis of the genomics 13 and brain science 4 literature. As described in subsequent sections, we account for the topical composition of an article through its Medical Subject Headings (MeSH) keywords.

Authorship of article: We account for author factors by including into our model the author count A ( p i ) for each publication p i . It has been reported in the literature that the number of authors in papers positively correlates with the citations these papers receive 12 . We had the opportunity to confirm this relationship in our prior research, when investigating the genomics literature 13 . The said effect is partly related to the visibility of the research in the scientific community, which grows in proportion to each author being an advocate of the published work.

Publishing venue of article: Our accounting of the article’s topical composition also serves as a proxy for the disciplinary orientation of the publishing journal. We avoid incorporating additional journal-level metrics, like the journal’s impact factor, because of dramatic changes in the ecosystem of publishing venues in recent years, which complicate consideration of such metrics. These changes include the meteoric rise of articles in open access journals and arXiv, two categories for whom impact factor considerations are confounded by open access status and publication fee/no fee requirements 14 , 15 .

Next, we describe the construction of the dataset and the computation of the model’s key predictors and response variable.

Bibliographic data collection and annotation

This study was not preregistered. PubMed served as our preferred bibliographic database for two reasons: First, both affective and cognitive scholarship are largely represented in PubMed, ensuring good coverage. Second, bibliographic records in PubMed are authoritatively annotated with MeSH keywords by the National Library of Medicine 16 . MeSH is a controlled and hierarchically-organized vocabulary with nearly orthogonal definitions 17 . Thus, it leaves little room for ambiguity in selecting search keywords. Accordingly, PubMed has both the items and ground-truth needed to power the present study.

Two of the co-authors, experts from the psychological sciences, agreed on a set of MeSH terms that comprehensively describe affective and cognitive research topics (Table  1 ). The said experts used as guidance for the selection of said terms the distinctions provided elsewhere 9 between what traditionally constitutes a topic associated with cognitive vs. affective sciences. For instance, typical topics associated with cognitive sciences include attention, decision-making, executive functioning, language learning, memory, perception, and reasoning, while typical topics associated with affective sciences include emotion, empathy, feeling, mood, motivation, preferences, stress, and well-being.

Using the selected MeSH terms, we searched PubMed, which had 34,944,599 records at the time of our inquiry in May 2023. The said search yielded in total 649,033 publications; out of these 314,665 were classified as Affective and 314,968 were classified as Cognitive publications, because they were annotated with at least one of the MeSH terms shown in Table  1 attributed to topics that are particularly typical of the cognitive and affective sciences, respectively. The remaining 19,400 publications were classified as Mixed, because they were annotated with at least one MeSH term from each of the Affective and Cognitive categories. Such co-occurrence of affective and cognitive terms is suggestive of non-independent treatment of affective and cognitive topics. Hence, Mixed publications fall in line with the principles espoused by affectivism, where any complete model of what is typically considered a cognitive topic (e.g., attention, memory, or decision-making) should include affective processes.

Each PubMed publication is annotated with both major and non-major topic terms, with the major topic terms indicating primary themes in the paper. We used only major topic terms to reduce noise levels. Furthermore, and consistent with other reports in the science convergence literature 4 , 5 , we proceeded into thematic consolidation. In more detail, the MeSH tree ontology 16 is organized around 16 major branches: [A] Anatomy; [B] Organisms; [C] Diseases; [D] Chemicals and Drugs; [E] Techniques and Equipment; [F] Psychiatry and Psychology; [G] Phenomena and Processes; [H] Disciplines and Occupations; [I] Anthropology, Education, Sociology, and Social Phenomena; [J] Technology; [K] Humanities; [L] Information Science; [M] Named Groups; [N] Health Care; [V] Publication Characteristics; and [Z] Geographicals. The first 14 branches hold terms relevant to our study. We consolidated these 14 branches into five subject areas (SA):

SA1  ≡ Biological Sciences corresponding to [A, B, G]

SA2  ≡ Psychological Sciences corresponding to [F]

SA3  ≡ Medical Sciences corresponding to [C, N]

SA4  ≡ Technical Methods corresponding to [D, E, J, L]

SA5  ≡ Humanities corresponding to [H, I, K, M]

Next, we will describe how we used this five-class thematic annotation scheme to represent the topical nature and estimate the degree of thematic confluence (aka convergence science) in each publication and its citations.

Key predictors: multidisciplinary content and appeal of publications

The thematic content of each publication p i is represented by a five element vector \(\overrightarrow {{\mathscr{T}}}({p}_{i})=\{{e}_{1},{e}_{2},{e}_{3},{e}_{4},{e}_{5}\}\) , where e 1 ,  e 2 ,  e 3 ,  e 4 ,  e 5 indicate the number of subject area terms from SA1, SA2, SA3, SA4, SA5, respectively, associated with this paper. For instance, a hypothetical paper p h with thematic vector \(\overrightarrow {{\mathscr{T}}}({p}_{h})=\{2,1,0,0,0\}\) indicates that its PubMed MeSH annotation features two major topic terms falling under SA1 and one under SA2. This suggests that the said paper’s content is multidisciplinary, featuring a mixture of biological and psychological knowledge.

The question now arising is how can we quantify thematic diversity out of such thematic representation? Two types of diversity indices are common in the literature—the Blau index and the Stirling index 18 , 19 , 20 . Diversity indices typically capture both categorical variety and categorical distances. Accordingly, they differ in the way they derive categorical variety and the way they compute categorical distances. Typical derivation methods include repeated sampling and combinations.

Our diversity index derives categorical diversity but leaves out computation of categorical distances. This is because the labeling of publications in our dataset is based on MeSH, which is a hierarchical ontology with well-defined distinctions between categories. Hence, there is little need to define categorical distances. In more detail, our diversity index computes categorical diversity through a combinatorial measure 5 . For each paper p i , we apply the outer tensor product \(\overrightarrow {{\mathscr{T}}}({p}_{i})\bigotimes \overrightarrow {{\mathscr{T}}}({p}_{i})\) to represent all pair-wise co-occurrences in a matrix D ( p i ). The order of any vector elements e i and e k in these pairs plays no meaningful role. Hence, we only keep the co-occurrence matrix’s upper triangular portion: D u ( p i ) = triu( D ( p i )). We normalize the sum of the elements of D u ( p i ) to unity, so that each \({{{\bf{D}}}}_{N}^{u}({p}_{i})\) contributes equally to means computed over selected publication groups. Normalization is implemented through Eq. ( 1 ), where the notation ∥ ⋯ ∥ indicates summation of all matrix elements.

Since the off-diagonal elements of \({{{\bf{D}}}}_{N}^{u}({p}_{i})\) represent cross-thematic combinations, their relative weight given by \(D({p}_{i})=1-\,{{\mbox{tr}}}\,({{{\bf{D}}}}_{N}^{u}({p}_{i}))\) can be used as a measure of thematic diversity or multidisciplinarity. In essence, D ( p i ) quantifies the probability of two randomly-selected elements of the thematic vector belonging in different categories.

When it comes to the citations paper p i has received, each of these citations c i j features its own thematic diversity vector \(\overrightarrow {{\mathscr{T}}}({c}_{ij})\) and diversity index D ( c i j ). We compute the mean thematic diversity \({\bar{D}}_{c}({p}_{i})\) of all citations c i j ,  j  = 1… m associated with publication p i through Eq. ( 2 ). One can view \({\bar{D}}_{c}({p}_{i})\) as a measure of multidisciplinary appeal of publication p i .

Response variable: citation impact

We used the iCite tool 21 to collect reference and citation data for the publications in our dataset. iCite draws citation numbers from the PubMed database. Unlike PubMed, iCite provides for each publication detailed records of all the papers that cite this publication. In our case, such information is necessary for tracing the thematic composition of the citing papers. We found, however, that out of the 649,033 publications in the dataset 39,972 featured zero references and/or citations—a 6.15% of the whole. We chose to keep such uncited articles in our analysis for their contribution to bibliographic patterns as evidenced in recent bibliometric work 22 .

The dataset’s papers were published over the 73-year period between January 1950 and December 2022. Naturally, the longer a publication exists, the more opportunity it has to receive citations. This creates a temporal bias in citation records, which in our case is significant, because of our dataset’s long time span. To account for this bias, we normalize citations following the standard methodology reported in other science of science research 4 . Specifically, the distribution of citations for papers published the same year t has an approximately log-normal form 23 . Hence, we use the properties of the log-normal transformation to standardize the distribution of citations by applying the formula shown in Eq. ( 3 ). Given that c ( p i ) stands for the citations of a given publication p i , we use \({c}^{{\prime} }({p}_{i})=c({p}_{i})+1\) to avoid the singularity of \(\ln 0\) associated with uncited publications - a standard method that does not affect results 4 . Furthermore, \(\overline{\ln {c}_{t}^{{\prime} }}\) represents the mean of the log of citations calculated across all publications from the same year t as publication p i , and \({s}_{t}[\ln {c}_{t}^{{\prime} }]\) represents the standard deviation of \(\ln {c}_{t}^{{\prime} }\) calculated for the same publication cohort.

According to Eq. ( 3 ), C N ( p i ) is a standard log-transformed quantity that is approximately normally distributed, bearing the advantageous properties of z-score (i.e., mean = 0 and standard deviation = 1). In this way, citation impact is measured relative to the within-cohort baseline, such that values with C N ( p i ) > 0 are rated above average relative to other research published at approximately the same time. It has been shown in literature that properly normalized citations assume a universal form 23 . Indeed, when we apply Eq. ( 3 ) to our citation data, the citation distributions per production year assume the standard normal form (Supplementary Fig.  S1 ).

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Descriptive statistics

The dataset of this study contains bibliographic records for n p  = 649, 033 publications. In this set, \({n}_{{p}_{a}}=314,665\) publications have been classified as Affective, \({n}_{{p}_{c}}=314,968\) publications as Cognitive, and \({n}_{{p}_{m}}=19,400\) as Mixed. Figure  1 A shows the evolution of publication production over time. The Affective and Cognitive groups appear to follow similar patterns and also feature similar volumes. The Mixed group is the smallest among the three and has grown into non-trivial numbers relatively recently.

a Histogram of the number of Affective ( \({n}_{{p}_{a}}=314,665\) ), Cognitive ( \({n}_{{p}_{c}}=314,968\) ), and Mixed ( \({n}_{{p}_{m}}=19,400\) ) publications per epoch; epochs represent non-overlapping 5-year intervals, spanning from 1 (corresponding to 1950) to 14; just the last epoch spans eight years, from 2015 to 2022. b Cumulative distribution function (CDF) of the normalized citations and the log of the number of authors per article. c Boxplots indicating the inter-quartile range of D p and \({\bar{D}}_{C}\) for n p  = 649, 033 publications. d Probability density function (PDF) of the major topic MeSH terms and their subject area aggregates (SA). e Percent difference of SA occurrences between the Affective and Mixed groups. f Percent difference of SA occurrences between the Affective and Cognitive groups. g Percent difference of SA occurrences between the Cognitive and Mixed groups. Note that SA1  ≡ Biological Sciences, SA2  ≡ Psychological Sciences, SA3  ≡ Medical Sciences, SA4  ≡ Technical Methods, and SA5  ≡ Humanities.

Figure  1 B shows the cumulative distribution function (CDF) calculated for both the normalized citations ( C N ) and the number of authors per publication ( A ). The descriptive statistics of the normalized citation count per publication C N ( p i ) are \({\bar{C}}_{N}\pm {s}_{{C}_{N}}=0.00\pm 1.00\) . This result indicates that the normalization process was carried out correctly, as it rendered C N to be a standard normal distribution with mean zero and standard deviation one - see also Supplementary Fig.  S1 for year by year validation of citation normalization. The number of authors per publication A ( p i ) is a right skewed distribution with median \(\tilde{A}=4\) , interquartile range A IQR  = [2, 5], and maximum value A m a x  = 460. Since the variation in A ( p i ) across various domains of scientific research follows a log-normal distribution 24 , we comply with normality assumptions by applying the logarithmic transformation \(\ln A\) . The descriptive statistics of the transformed author distribution are \(\overline{\ln A}\pm {s}_{\ln A}=1.22\pm 0.67\) .

Figure  1 C juxtaposes the distribution of the thematic diversity of publication p i (denoted by D p ) with the distribution of the average thematic diversity of those papers that cited p i (denoted by \({\bar{D}}_{C}\) ). The descriptive statistics of the thematic diversity per publication are \({D}_{p}\pm {s}_{{D}_{p}}=0.39\pm 0.17\) . The descriptive statistics of the mean thematic diversity of citations per publication are \({\bar{\bar{D}}}_{c}\pm {s}_{{\bar{D}}_{c}}=0.43\pm 0.21\) . Thus, the thematic diversity of citing papers tends to be broader than the cited papers. Models will show this effect to be more strongly associated with the Mixed and Affective groups (Publication Type Model section).

As we detailed in the Key Predictors section, the source data for computing the thematic diversity of publications in our dataset are the major topic MeSH terms associated with these publications. Figure  1 D shows the distribution of the number of MeSH terms per publication vs. the distribution of the number of their subject area aggregates; the corresponding descriptive statistics are 2.91 ± 1.15 vs. 2.53 ± 0.78. It is evident that subject area aggregation curtails the excessive right skeweness found in the original major MeSH term cardinality distribution.

Figures  1 E–G visualize the relative thematic diversity of Affective vs. Mixed, Affective vs. Cognitive, and Cognitive vs. Mixed research, respectively. We report the relative differences by calculating the percent difference in terms of subject area occurrences between the applicable groups in each case. We observe that with respect to the Cognitive and Affective literature, the Mixed literature has richer biological (SA1) and psychological (SA2) content, while lags in nearly all other subject areas (Fig.  1 E and G). In doing so, the Mixed literature group brings together the biological (SA1) content advantage of the Cognitive group with the psychological (SA2) content advantage of the Affective group (Fig.  1 F). This fusion advantage of the two core themes may be narrow in scope but consequential for the Mixed literature, as the citation impact model in the next section indicates.

Citation impact model

As we observed in the Descriptive Statistics section, the Affective and Cognitive groups appear to have remarkably similar productivity levels in terms of publication volumes, while the Mixed group is a more recent development. Questions, however, remain about other aspects of research productivity for the studied scholarly system. Here we seek to identify factors that correlate with the normalized citation impact of a given publication, C N ( p i ). To this end, we constructed a multiple linear regression model featuring predictors relevant to our research question, as well as control variables aiming to ameliorate confounding effects:

The unit of analysis is a single publication p i . The first row of Eq. ( 4 ) lists the key predictors T A ( p i ), T C ( p i ), D p ( p i ), and \({\bar{D}}_{c}({p}_{i})\) . The dummy variables T A ( p i ) and T C ( p i ) represent the Affective and Cognitive publication groups, respectively; the Mixed publication group serves as the reference level. The variable D p ( p i ) represents the thematic diversity of p i , which is akin to its multidisciplinary content. The variable \({\bar{D}}_{c}({p}_{i})\) represents the mean thematic diversity of the papers that cited p i , which is akin to its multidisciplinary appeal. The second row of Eq. ( 4 ) lists the control variables A ( p i ), F SA1 ( p i ), F SA2 ( p i ), F SA3 ( p i ), F SA4 ( p i ), and F SA5 ( p i ). The variable A ( p i ) represents the number of authors per publication. As this control variable is heavily right-skewed, we apply logarithmic transformation. F SA1 ( p i ), F SA2 ( p i ), F SA3 ( p i ), F SA4 ( p i ), and F SA5 ( p i ) are binary control variables indicating for publication p i the presence ( = 1) or absence ( = 0) of major MeSH terms associated with subject areas SA1, SA2, SA3, SA4, and SA5, respectively.

Table  2 shows the full set of parameter estimates specified in Eq. ( 4 ). Figure  2 A provides a visual representation of the marginal effects associated with shifts in publication categorical levels, with all other covariates held at their mean values. Results indicate that Affective publications have lower citation impact than Mixed publications, corresponding to roughly 100*( −0.045) = −4.5% difference in nominal citations, c ( p i ). Cognitive publications have even lower citation impact than Mixed publications, corresponding to roughly 100*( −0.065) = −6.5% difference in nominal citations, c ( p i ). And consistent with prior studies 4 , the number of authors positively correlates with citation impact, such that a 100% increase in A ( p i ) correlates to a 100*(0.223) = 22.3% increase in c ( p i ). Interestingly, we identify a negative correlation between C N ( p i ) and D p ( p i ), meaning that the higher the thematic diversity of a publication the lower its citation impact. Thus, rich multidisciplinary content appears to be unhelpful to a publication’s impact. By contrast, the higher the mean thematic diversity of papers citing p i , the higher the citation impact of p i (Fig.  2 B). Consequently, impact seems to be helped by the publication’s multidisciplinary appeal. Regarding the controlling role of topical content, as manifested by subject area keywords, the model results in Table  2 indicate that biological (SA1) content is associated with higher citation impact, psychological (SA2) content makes no difference, while medical (SA3), technical (SA4), and humanities (SA5) content is associated with lower citation impact. Since the thematic epicenter of Cognitive, Affective, and Mixed publications is psycho-biology (SA1 + SA2), thematic diversity is stemming from SA3, SA4, and SA5. Thus, the negative coefficients of F SA3 , F SA4 , and F SA5 are consistent with the negative coefficient of D p ( p i ), manifesting the overall suppressing effect of thematic diversity on citation impact. At the same time, the citation advantage associated with SA1 content brings to mind the Mixed group’s strong incorporation of biological (SA1) into psychological (SA2) knowledge (Fig.  1 E and G), which may partly explain the said group’s superior impact.

a Marginal means with 95% confidence intervals for Mixed ( \({n}_{{p}_{m}}=19,400\) ), Affective ( \({n}_{{p}_{a}}=314,665\) ), and Cognitive ( \({n}_{{p}_{c}}=314,968\) ) publications. The plot shows that Mixed publications (magenta) are more impactful than Affective publications (black), which in turn are more impactful than Cognitive publications (grey). b The red line depicting \({\bar{D}}_{c}\) is another key result of the citation impact model, demonstrating that the more diverse the citations of a publication are, the higher the impact of this publication will be.

Publication type model

To identify any significant structural differences among the Mixed, Affective, and Cognitive literature groups, we operationalized a multinomial regression model, specified as:

The response variable is the odds P ( T ( p i )) of publication p i being an Affective or Cognitive type vs. Mixed type. As in the first model: a) the predictor D p ( p i ) ∈ [0, 1] represents the thematic diversity of a given publication p i , that is, p i ’s degree of multidisciplinarity; b) the predictor \({\bar{D}}_{c}({p}_{i})\in [0,1]\) represents the mean thematic diversity of the papers citing p i , that is, p i ’s multidisciplinary appeal.

Table  3 lists the full set of parameter estimates specified in Eq. ( 5 ), when the response variable is the probability of being Affective or Cognitive publication. Results indicate that papers with higher thematic diversity are more likely to be of Cognitive or Affective type rather than Mixed type. The most consequential distinction among the three groups, however, lies in the SA diversity of the downstream citing research. The higher the thematic diversity of citing research, the more likely the research is of Mixed type, which is congruent with the results of the citation impact model in Eq. ( 4 ). Nevertheless, as evidenced by the corresponding regression coefficients, lower levels of thematic diversity in citations are more pronounced in Cognitive ( \({\bar{D}}_{c}({p}_{i})=-1.264\) ) rather than Affective publications ( \({\bar{D}}_{c}({p}_{i})=-0.945\) ). Altogether, there is a rank order of multidisciplinary appeal, with Mixed publications at the top, Affective publications next, and Cognitive publications at the bottom.

Behind the numbers

Mixed literature group.

To give a tangible sense of the modeling results, we visit a few characteristic examples from our dataset. From the Mixed group, a representative publication is “Effects of Stress Throughout the Lifespan on the Brain Behaviour and Cognition”, authored by Lupien et al. and published in Nature Reviews Neuroscience in 2009 25 . As of April 29, 2023, this paper had 3299 citations per iCite and a normalized citation score C N  = 3.69 per Eq. ( 3 ). The paper is a treatise on the origins and effects of chronic stress. It examines how sustained exposure to stress hormones affects the brain, behavior, and cognition. As the major MeSH terms include among others Behavior [D001519], Stress, Psychological [D013315] and Cognition [D003071], it is clear per Table  1 that this is indeed a Mixed publication. Furthermore, the publication’s content features a measure of convergence, drawing upon two subject areas: a) Biological Sciences (SA1), owing to its hypothalamus-pituitary-adrenal content, that is, a key brain system underlying the generation of stress responses. b) Psychological Sciences (SA2), owing to its content on the effects of stress on behavior and cognition. Indeed, the SA vector for this publication is \(\overrightarrow {{\mathscr{T}}}(p)=\{1,1,0,0,0\}\) and thus its thematic diversity stands at D p  = 0.33 per Eq. ( 1 ). This is a relatively low thematic diversity, focused on the core areas of biology and psychology. The mean thematic diversity of the paper’s citations, however, stands at \({\bar{D}}_{c}=0.64\) per Eq. ( 2 ). This is twice the size of D p .

The typical pattern of Mixed publications is that they combine features from the Affective and Cognitive groups, delivering outstanding impact and featuring citations with high thematic diversity. To substantiate the last point, we will comment on a few representative articles that cite Lupien’s paper. First, we visit the citation by Herman et al. titled “Regulation of the Hypothalamic-Pituitary-Adrenocortical Stress Response” 26 . The paper was published in 2016 in Comprehensive Physiology and examines the role of previous stress history and current environmental demands on the regulation of the hypothalamo-pituitary-adrenocortical (HPA) axis. This HPA axis is key to stress adaptation and thus plays a major role in the onset or avoidance of chronic stress. Herman brings up Lupien’s paper with respect to maladaptive effects on HPA during the stress hyporesponsive period (SHRP) early in life. As evidenced by its major topic MeSH terms, the said citation covers the SA1  ≡ Biological Sciences area, owing to its focus on the neural mechanisms associated with stress regulating hormones.

Second, we visit the citation by Epel et al. titled “More Than a Feeling: A Unified View of Stress Measurement for Population Science” 27 . The paper was published in 2018 in Frontiers in Neuroendoecrinology and proposes a stress model that incorporates epidemiological, affective, and psychophysiological perspectives. Epel brings up Lupien’s paper in the context of developmental factors for which their stress model must account. As evidenced by its major topic MeSH terms, the said citation covers three subject areas: SA1  ≡ Biological Sciences, owing to its treatment of physiological regulation as a key stress modeling factor. SA2  ≡ Psychological Sciences, owing to its treatment of emotions as another key stress modeling factor. SA4  ≡ Technical Methods, owing to its model construction content.

Third, we visit the citation by Chanda and Levitin titled “The Neurochemistry of Music” 28 . The paper was published in 2013 in Trends in Cognitive Sciences and examines the effect of music in pleasure, stress, immunity, and social affiliation, effected through neurochemical changes. Chanda and Levitin bring up Lupien’s paper when they lay out the neurotoxic and other serious effects of chronic stress, for which Lupien’s work comprehensively accounts. As evidenced by its major topic MeSH terms, the said citation covers two subject areas: SA1  ≡ Biological Sciences, owing to its examination of music effects on the hypothalamic-pituitary-adrenal (HPA) axis and other brain systems. SA5  ≡ Humanities, owing to its analysis of music.

Altogether, the thematic diversity of the representative citations we discussed draws from a set that includes nearly all subject areas, that is, SA1, SA2, SA4, and SA5. Hence, the citations of Lupien’s paper have thematic diversity that far exceeds the paper’s own thematic diversity, which is limited to just SA1  ≡ Biological Sciences and SA2  ≡ Psychological Sciences.

Affective literature group

From the Affective group, a representative publication is the “Netherlands Study of Depression and Anxiety (NESDA)”, which was published in the International Journal in Psychiatric Research in 2008 29 . As of April 29, 2023, this paper had 733 citations per iCite and a normalized citation score C N  = 2.81 per Eq. ( 3 ). The paper describes a naturalistic study involving the longitudinal collection of multimodal participant data. The study’s aim was to understand the evolution and consequences of depressive and anxiety disorders. Accordingly, the publication’s content is mono-thematic, situated in SA2  ≡ Psychological Sciences. Indeed, the SA vector for this publication is \(\overrightarrow {{\mathscr{T}}}(p)=\{0,1,0,0,0\}\) and thus, its thematic diversity stands at D p  = 0 per Eq. ( 1 ). In contradistinction, the mean thematic diversity of the paper’s citations stands at \({\bar{D}}_{c}=0.62\) per Eq. ( 2 ) and is on par with the Mixed group example we gave in the previous section.

Combing the data, we found that firstly Mixed and secondly Affective publications, even with mono-thematic psychological pedigree (like NESDA), attain strong impact rooted in broad appeal - something that is in agreement with the modeling results (Tables  2 and 3 ). We argue that this is due to two reasons: First, affective conditions, like anxiety, are widespread and thus of broad interest. Second, affective conditions are complex and poorly understood, forcing researchers to collect multimodal data (e.g., psychological, physiological, and other channels), in the hope of acquiring much needed insights. This rich multi-channel information can feed studies in more than one disciplines. To substantiate these points, we will comment on three thematically dissimilar articles that cite the NESDA paper.

First, we visit the citation by Gromley et al., which aims to identify genomic loci associated with migraines 30 . Although the paper has little to do with anxiety and depression, it uses NESDA data in its meta-analysis, because NESDA features DNA and migraine information for its study participants. As evidenced by its major topic MeSH terms, the said migraine citation covers three subject areas: SA1  ≡ Biological Sciences due to polymorphism content, SA3  ≡ Medical Sciences due to migraine content, and SA4  ≡ Technical Methods due to computational content. For a psychological study like NESDA, this citation represents an impressive cross-disciplinary outreach.

Second, we visit the citation by Jacobson et al., which aims to predict the onset of anxiety disorders through deep learning of participants’ digital biomarkers 31 . In this case, the digital biomarkers were actigraphy data acquired through wearable devices to feed a deep autoencoder and ensemble model. Papers like Jacobson’s represent a growing new trend. Recognizing the importance of anxiety and associated longitudinal studies, the motivation of these nascent efforts is to substitute labor-intensive data collection like NESDA, with studies based on data collected through ubiquitous sensors, which are more amenable to automation. As evidenced by its major topic MeSH terms, Jacobson’s citation connects psychological content (SA2) with a strong technical component (SA4), owing to its deep learning approach.

Third, we visit the citation by Dijkstra-Kersten et al., which aims to investigate the association between depressive/anxiety disorders and perceived financial strain 32 . The paper uses data from the NESDA cohort to document that not only income, but also perceived financial strain irrespective of income is a predictor of depressive and anxiety disorders. As evidenced by its major topic MeSH terms, the citation connects humanities (SA5), owing to its socioeconomic considerations, with psychological sciences (SA2), owing to its use of NESDA data.

Altogether, the thematic diversity of the citations we discussed draws from a set that includes all five subject areas. Hence, the citations of the NESDA paper have thematic diversity that either exceeds or is totally different than its own thematic diversity, which is constrained to just SA2  ≡ Psychological Sciences.

Cognitive literature group

From the Cognitive group, a representative publication is the “Requirement for Hippocampal CA3 NMDA Receptors in Associative Memory Recall”, authored by Nakazawa et al. and published in Science in 2002 33 . As of April 29, 2023, this paper had 745 citations per iCite and a normalized citation score C N  = 2.47 per Eq. ( 3 ). The paper provides indirect evidence for the involvement of the CA3 area of hippocampus in associative memory recall based on partial cues. The experiments that led to this conclusion were carried out with mutant mice with ablated CA3 cells. The mice exhibited radically different maze activities when presented with full cues versus partial cues. Accordingly, the publication’s content features a measure of convergence, drawing upon three subject areas: Biological Sciences (SA1) owing to its hippocampal content; Psychological Sciences (SA2) owing to its memory content; and, Technical Methods (SA4) owing to the genetic engineering of the mice involved in the experiments. Indeed, the SA vector for this publication is \(\overrightarrow {{\mathscr{T}}}(p)=\{1,1,0,1,0\}\) and thus, its thematic diversity stands at D p  = 0.50 per Eq. ( 1 ). The mean thematic diversity of the paper’s citations stands at \({\bar{D}}_{c}=0.52\) per Eq. ( 2 ). Accordingly, D p and \({\bar{D}}_{c}\) are on par, in contrast to the representative publications we analyzed from the Mixed and Affective groups, where the thematic diversity of the citations far exceeded the thematic diversity of the cited paper.

This is a typical pattern with many Cognitive publications, that is, they feature moderate convergence and they attract citations that are their mirror image. We believe this is due to the fact that Cognitive publications usually focus on brain science issues. These issues are quite complex and require a measure of convergent knowledge to be addressed. Unlike affective issues, however, brain issues are very specialized, and thus of interest mainly to the brain science community. For instance, consider memory function versus anxiety and depression. Memory function is an important question, but unlike anxiety and depression, is not directly related to a major societal problem. To substantiate these points, we will comment on three thematically similar articles that cite Nakazawa’s paper

First, we visit the citation by Neves et al. titled “Synaptic plasticity, memory, and the hippocampus: a neural network approach to causality” 34 . The paper was published in 2008 in Nature Reviews Neuroscience and addresses the role of hippocampus in memory, that is, a superset of the issues addressed in Nakazawa’s paper. As evidenced by its major topic MeSH terms, the said citation covers two subject areas: SA1  ≡ Biological Sciences, owing to its treatment of hippocampal anatomy and physiology; SA2  ≡ Psychological Sciences, owing to its treatment of memory.

Second, we visit the citation by Laura Lee Coglin titled “Rhythms of the hippocampal network” 35 . The paper was published in 2016 in Nature Reviews Neuroscience and addresses hippocampal rhythms in the form of theta, sharp wave-ripples, and gamma. These rhythms are believed to carry distinct functions in hippocampal memory processing. Coglin brings up Nakazawa’s paper because it points to the central role of the CA3 network in storage and retrieval of memories, and in this respect offers clues about the types of rhythms involved in such processes. As evidenced by its major topic MeSH terms, the said citation covers two subject areas: SA1  ≡ Biological Sciences, owing to its treatment of hippocampal anatomy and physiology; SA4  ≡ Technical Methods, owing to its treatment of electroencephalography.

Third, we visit the citation by Neunuebel and Knierim titled “CA3 retrieves coherent representations from degraded input: direct evidence for CA3 pattern completion and dentate gyrus pattern separation” 36 . The paper was published in 2014 in Neuron and provides direct neurophysiological evidence for pattern completion of severely degraded inputs in the DG-CA3 circuit. In this respect, Neunuebel and Knierim’s paper complements Nakazawa’s paper, which provided only indirect behavioral evidence for the functionality of CA3. As evidenced by its major topic MeSH terms, the said citation covers two subject areas: SA1  ≡ Biological Sciences, owing to its treatment of hippocampal anatomy and physiology; SA2  ≡ Psychological Sciences, owing to its treatment of memory.

Altogether, the thematic diversity of the representative citations we discussed draws from the thematic diversity of Nakazawa’s paper without ever exceeding it, that is, from the subject area set that includes SA1, SA2, and SA4.

Research teams designed to harness the integrative advantages of convergence have emerged as a prominent mode of scientific production 10 . Such developments have been partly spurred by convergence’s successes in addressing certain grand challenges, such as the Human Genome Project (HGP) 13 . Nevertheless, the positive role of convergence has not always proved to be clear-cut. For instance, convergence in brain science has had mixed results 4 , 5 , 6 , motivating deeper studies of convergence in additional disciplines, particularly ones that appear to be on the march. In this context, affectivism is an ideal target of convergence investigation, because it is rooted in the affective sciences and attempts to bridge over to cognitive approaches 9 .

Accordingly, we set out to examine convergence in Cognitive vis-à-vis Affective vis-à-vis Mixed literature in psychological sciences and allied fields. In this analytic study design, the Cognitive literature group serves as control. The Affective and Mixed literature groups, which constitute affectivism trends, serve as neighboring groups but with purported broader reach 9 . This tri-field ecosystem is a natural experiment in convergence that brings insights not afforded by single field studies. Adding to that, a key methodological innovation of our work is accounting for convergence not only in the thematic content of publications but also in the thematic content of their citations. This approach relates to the following profound question: Does convergence feed upon convergence?

To address this question, we collected over half a million Affective, Cognitive, and Mixed publications, which provide a comprehensive reconstruction of convergent research in neighboring fields, but evolving from different perspectives and methodologies. The publication-level regression models indicate that: (a) The Mixed group is more impactful than the Affective group, and both are more impactful than the Cognitive group. (b) The Mixed group has the least convergent content. (c) The Cognitive group has the least convergent following.

In other words, the literature groups that represent affectivism not only have stronger citation impact but also broader reach across scientific fields. Notably, the Mixed group attains this broad reach despite its significantly more limited convergent content. Looking behind the numbers and in the actual publications indexed in our dataset, we traced this effect into broadly useful concepts that can be leveraged across scientific communities, from medicine to socioeconomic inquiry. Finally, these modeling results stand after controlling for number of authors and subject content in publications - two factors known to affect citation impact per other science of science research 12 , 13 .

Limitations

Our study reveals that convergence is not necessarily an omnipresent phenomenon in the fields that is encountered. The assumption thus far in the literature has been that in order to breed convergence you need to start with convergence 37 . This belief does not appear to hold. On the contrary, broadly useful tools of even mono-disciplinary origin can percolate into multiple fields creating a far richer convergent ecosystem than convergent tools of moderate utility. Although due to the regressional nature of our modeling it is not possible to claim causality, we can at least hypothesize that the rise of affectivism may be partly due to its multidisciplinary impact rather than its multidisciplinary pedigree.

Data availability

The data collected for this study are available in the Open Science Framework: https://osf.io/v8qxs/ with https://doi.org/10.17605/OSF.IO/V8QXS .

Code availability

The R code used for analysis is available in GitHub: https://github.com/vvzhukov/Convergence-in-Affective-and-Cognitive-Sciences with https://doi.org/10.5281/zenodo.11284448 .

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Acknowledgements

Part of this research was funded through the Eckhard-Pfeiffer Distinguished Professorship Fund at the University of Houston. The fund’s administration had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Zhukov, V., Petersen, A.M., Dukes, D. et al. Science convergence in affective research is associated with impactful multidisciplinary appeal rather than multidisciplinary content. Commun Psychol 2 , 83 (2024). https://doi.org/10.1038/s44271-024-00129-x

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Jiangping Chen

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Interim Executive Associate Dean and Visiting Professor

PhD, Information Transfer, Syracuse University

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(217) 333-3280

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• Regents Professor, University of North Texas, 2024
• Outstanding Department Award, University of North Texas, 2022
• LIBINF Top 10 Cited Article (IF 2019-2020), ELSEVIER, 2022
• Star Performer Award, University of North Texas, 2021
• Recognition of Service Award, Association for Computing Machinery (ACM), 2018
• ISI/ASIS&T Doctoral Dissertation Proposal Award, 2003

Dr. Chen is currently the interim executive associate dean and visiting professor at the iSchool. Before joining UIUC in August 2024, she was Regents professor and the chair of the Department of Information Science in the College of Information at the University of North Texas (UNT). She conducts interdisciplinary research, spanning information science, data science, and health informatics. She is the founder of UNT's Intelligent Information Access (IIA) Lab, which explores methods for access, interaction, and analysis of large, distributed, heterogeneous, multimedia, and multilingual information. 

Her professional contributions include authoring numerous publications, including a monograph on multilingual digital libraries,  journal articles, book chapters, and conference proceedings as well as giving invited presentations and talks. She served as the editor-in-chief for The Electronic Library for seven years and as chair of the Joint Conference on Digital Libraries (JCDL) in 2018. Dr. Chen holds a PhD in information transfer from Syracuse University, a master's degree in information science from the Library of Chinese Academy of Sciences, and a bachelor's degree in information science from Wuhan University.

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Ogbadu-Oladapo, L., Chung, H., Li, J., & Chen, J. (2023). An investigation of the use of theories in misinformation studies. Proceedings of 2023 annual conference of the American Society for Information Science and Technology , London, UK, October 27-31. https://doi.org/10.1002/pra2.790 . Nguyen, H., Ogbadu-Oladapo, L., Irhamni, A., Chen, H., & Chen, J. (2023). Fighting misinformation: where are we and where to go? Proceedings of iConference 2023 , Barcelona, Spain, March 27-29. https://doi.org/10.1007/978-3-031-28035-1_27 . Wu, A. & Chen, J. (2022). Sustaining multilinguality: case studies of two multilingual digital libraries. The Electronic Library , 40(6), 625-645. https://doi.org/10.1108/EL-03-2022-0061 . Chen, H., Wu, L., Lu, W., Chen, J., & Ding, J. (2022). A comparative study of automated legal text classification using random forests and deep learning. Information Processing and Management , 59(2). https://doi.org/10.1016/j.ipm.2021.102798 . Chen, H., Nguyen, H., & Chen, J. (2021). Demystifying COVID-19 publications: researchers, topics, diseases, and therapeutics. Journal of the Medical Library Association , 109(3), 395-405. https://doi.org/10.5195/jmla.2021.1141 . Chen, J. (2020). Beyond information organization and evaluation: how can information scientists contribute to independent thinking. Data and Information Management , 4(3), 171-176. https://doi.org/10.2478/dim-2020-0017 . Wang, C., Huang, R., Li, J., & Chen, J. (2020). Towards better information services: A framework for immigrant information needs and library services. Library and Information Science Research , 42(1), https://doi.org/10.1016/j.lisr.2019.101000 . Brenda, R., Knudson, R., Chen, J., Cao, G., & Wang, X. (2018). Metadata records machine translation combining multi-engine outputs with limited parallel data. Journal of the Association for Information Science and Technology . 69(1), 47-59, 2018. https://doi.org/10.1002/asi.23925 . Chen, J. 2016. Multilingual Access And Services For Digital Collections . Santa Barbara, CA: Libraries Unlimited. https://www.amazon.com/Multilingual-Access-Services-Digital-Collections/dp/1440839549 .   

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In brief: what types of studies are there.

Last Update: September 8, 2016 ; Next update: 2024.

There are various types of scientific studies such as experiments and comparative analyses, observational studies, surveys, or interviews. The choice of study type will mainly depend on the research question being asked.

When making decisions, patients and doctors need reliable answers to a number of questions. Depending on the medical condition and patient's personal situation, the following questions may be asked:

• What is the cause of the condition?
• What is the natural course of the disease if left untreated?
• What will change because of the treatment?
• How many other people have the same condition?
• How do other people cope with it?

Each of these questions can best be answered by a different type of study.

In order to get reliable results, a study has to be carefully planned right from the start. One thing that is especially important to consider is which type of study is best suited to the research question. A study protocol should be written and complete documentation of the study's process should also be done. This is vital in order for other scientists to be able to reproduce and check the results afterwards.

The main types of studies are randomized controlled trials (RCTs), cohort studies, case-control studies and qualitative studies.

• Randomized controlled trials

If you want to know how effective a treatment or diagnostic test is, randomized trials provide the most reliable answers. Because the effect of the treatment is often compared with "no treatment" (or a different treatment), they can also show what happens if you opt to not have the treatment or diagnostic test.

When planning this type of study, a research question is stipulated first. This involves deciding what exactly should be tested and in what group of people. In order to be able to reliably assess how effective the treatment is, the following things also need to be determined before the study is started:

• How long the study should last
• How many participants are needed
• How the effect of the treatment should be measured

For instance, a medication used to treat menopause symptoms needs to be tested on a different group of people than a flu medicine. And a study on treatment for a stuffy nose may be much shorter than a study on a drug taken to prevent strokes .

“Randomized” means divided into groups by chance. In RCTs participants are randomly assigned to one of two or more groups. Then one group receives the new drug A, for example, while the other group receives the conventional drug B or a placebo (dummy drug). Things like the appearance and taste of the drug and the placebo should be as similar as possible. Ideally, the assignment to the various groups is done "double blinded," meaning that neither the participants nor their doctors know who is in which group.

The assignment to groups has to be random in order to make sure that only the effects of the medications are compared, and no other factors influence the results. If doctors decided themselves which patients should receive which treatment, they might – for instance – give the more promising drug to patients who have better chances of recovery. This would distort the results. Random allocation ensures that differences between the results of the two groups at the end of the study are actually due to the treatment and not something else.

Randomized controlled trials provide the best results when trying to find out if there is a cause-and-effect relationship. RCTs can answer questions such as these:

• Is the new drug A better than the standard treatment for medical condition X?
• Does regular physical activity speed up recovery after a slipped disk when compared to passive waiting?
• Cohort studies

A cohort is a group of people who are observed frequently over a period of many years – for instance, to determine how often a certain disease occurs. In a cohort study, two (or more) groups that are exposed to different things are compared with each other: For example, one group might smoke while the other doesn't. Or one group may be exposed to a hazardous substance at work, while the comparison group isn't. The researchers then observe how the health of the people in both groups develops over the course of several years, whether they become ill, and how many of them pass away. Cohort studies often include people who are healthy at the start of the study. Cohort studies can have a prospective (forward-looking) design or a retrospective (backward-looking) design. In a prospective study, the result that the researchers are interested in (such as a specific illness) has not yet occurred by the time the study starts. But the outcomes that they want to measure and other possible influential factors can be precisely defined beforehand. In a retrospective study, the result (the illness) has already occurred before the study starts, and the researchers look at the patient's history to find risk factors.

Cohort studies are especially useful if you want to find out how common a medical condition is and which factors increase the risk of developing it. They can answer questions such as:

• How does high blood pressure affect heart health?
• Does smoking increase your risk of lung cancer?

For example, one famous long-term cohort study observed a group of 40,000 British doctors, many of whom smoked. It tracked how many doctors died over the years, and what they died of. The study showed that smoking caused a lot of deaths, and that people who smoked more were more likely to get ill and die.

• Case-control studies

Case-control studies compare people who have a certain medical condition with people who do not have the medical condition, but who are otherwise as similar as possible, for example in terms of their sex and age. Then the two groups are interviewed, or their medical files are analyzed, to find anything that might be risk factors for the disease. So case-control studies are generally retrospective.

Case-control studies are one way to gain knowledge about rare diseases. They are also not as expensive or time-consuming as RCTs or cohort studies. But it is often difficult to tell which people are the most similar to each other and should therefore be compared with each other. Because the researchers usually ask about past events, they are dependent on the participants’ memories. But the people they interview might no longer remember whether they were, for instance, exposed to certain risk factors in the past.

Still, case-control studies can help to investigate the causes of a specific disease, and answer questions like these:

• Do HPV infections increase the risk of cervical cancer ?
• Is the risk of sudden infant death syndrome (“cot death”) increased by parents smoking at home?

Cohort studies and case-control studies are types of "observational studies."

• Cross-sectional studies

Many people will be familiar with this kind of study. The classic type of cross-sectional study is the survey: A representative group of people – usually a random sample – are interviewed or examined in order to find out their opinions or facts. Because this data is collected only once, cross-sectional studies are relatively quick and inexpensive. They can provide information on things like the prevalence of a particular disease (how common it is). But they can't tell us anything about the cause of a disease or what the best treatment might be.

Cross-sectional studies can answer questions such as these:

• How tall are German men and women at age 20?
• How many people have cancer screening?
• Qualitative studies

This type of study helps us understand, for instance, what it is like for people to live with a certain disease. Unlike other kinds of research, qualitative research does not rely on numbers and data. Instead, it is based on information collected by talking to people who have a particular medical condition and people close to them. Written documents and observations are used too. The information that is obtained is then analyzed and interpreted using a number of methods.

Qualitative studies can answer questions such as these:

• How do women experience a Cesarean section?
• What aspects of treatment are especially important to men who have prostate cancer ?
• How reliable are the different types of studies?

Each type of study has its advantages and disadvantages. It is always important to find out the following: Did the researchers select a study type that will actually allow them to find the answers they are looking for? You can’t use a survey to find out what is causing a particular disease, for instance.

It is really only possible to draw reliable conclusions about cause and effect by using randomized controlled trials. Other types of studies usually only allow us to establish correlations (relationships where it isn’t clear whether one thing is causing the other). For instance, data from a cohort study may show that people who eat more red meat develop bowel cancer more often than people who don't. This might suggest that eating red meat can increase your risk of getting bowel cancer. But people who eat a lot of red meat might also smoke more, drink more alcohol, or tend to be overweight. The influence of these and other possible risk factors can only be determined by comparing two equal-sized groups made up of randomly assigned participants.

That is why randomized controlled trials are usually the only suitable way to find out how effective a treatment is. Systematic reviews, which summarize multiple RCTs , are even better. In order to be good-quality, though, all studies and systematic reviews need to be designed properly and eliminate as many potential sources of error as possible.

• German Network for Evidence-based Medicine. Glossar: Qualitative Forschung.  Berlin: DNEbM; 2011. 
• Greenhalgh T. Einführung in die Evidence-based Medicine: kritische Beurteilung klinischer Studien als Basis einer rationalen Medizin. Bern: Huber; 2003. 
• Institute for Quality and Efficiency in Health Care (IQWiG, Germany). General methods . Version 5.0. Cologne: IQWiG; 2017.
• Klug SJ, Bender R, Blettner M, Lange S. Wichtige epidemiologische Studientypen. Dtsch Med Wochenschr 2007; 132:e45-e47. [ PubMed : 17530597 ]
• Schäfer T. Kritische Bewertung von Studien zur Ätiologie. In: Kunz R, Ollenschläger G, Raspe H, Jonitz G, Donner-Banzhoff N (eds.). Lehrbuch evidenzbasierte Medizin in Klinik und Praxis. Cologne: Deutscher Ärzte-Verlag; 2007.

IQWiG health information is written with the aim of helping people understand the advantages and disadvantages of the main treatment options and health care services.

Because IQWiG is a German institute, some of the information provided here is specific to the German health care system. The suitability of any of the described options in an individual case can be determined by talking to a doctor. informedhealth.org can provide support for talks with doctors and other medical professionals, but cannot replace them. We do not offer individual consultations.

Our information is based on the results of good-quality studies. It is written by a team of health care professionals, scientists and editors, and reviewed by external experts. You can find a detailed description of how our health information is produced and updated in our methods.

• Cite this Page InformedHealth.org [Internet]. Cologne, Germany: Institute for Quality and Efficiency in Health Care (IQWiG); 2006-. In brief: What types of studies are there? [Updated 2016 Sep 8].

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Acupuncture: Effectiveness and Safety

.header_greentext{color:green!important;font-size:24px!important;font-weight:500!important;}.header_bluetext{color:blue!important;font-size:18px!important;font-weight:500!important;}.header_redtext{color:red!important;font-size:28px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;font-size:28px!important;font-weight:500!important;}.header_purpletext{color:purple!important;font-size:31px!important;font-weight:500!important;}.header_yellowtext{color:yellow!important;font-size:20px!important;font-weight:500!important;}.header_blacktext{color:black!important;font-size:22px!important;font-weight:500!important;}.header_whitetext{color:white!important;font-size:22px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;}.Green_Header{color:green!important;font-size:24px!important;font-weight:500!important;}.Blue_Header{color:blue!important;font-size:18px!important;font-weight:500!important;}.Red_Header{color:red!important;font-size:28px!important;font-weight:500!important;}.Purple_Header{color:purple!important;font-size:31px!important;font-weight:500!important;}.Yellow_Header{color:yellow!important;font-size:20px!important;font-weight:500!important;}.Black_Header{color:black!important;font-size:22px!important;font-weight:500!important;}.White_Header{color:white!important;font-size:22px!important;font-weight:500!important;} What is acupuncture?

Acupuncture is a technique in which practitioners insert fine needles into the skin to treat health problems. The needles may be manipulated manually or stimulated with small electrical currents (electroacupuncture). Acupuncture has been in use in some form for at least 2,500 years. It originated from  traditional Chinese medicine but has gained popularity worldwide since the 1970s.

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According to the World Health Organization, acupuncture is used in 103 of 129 countries that reported data.

In the United States, data from the National Health Interview Survey show that the use of acupuncture by U.S. adults more than doubled between 2002 and 2022. In 2002, 1.0 percent of U.S. adults used acupuncture; in 2022, 2.2 percent used it. 

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National survey data indicate that in the United States, acupuncture is most commonly used for pain, such as back, joint, or neck pain.

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How acupuncture works is not fully understood. However, there’s evidence that acupuncture may have effects on the nervous system, effects on other body tissues, and nonspecific (placebo) effects. 

• Studies in animals and people, including studies that used imaging methods to see what’s happening in the brain, have shown that acupuncture may affect nervous system function.
• Acupuncture may have direct effects on the tissues where the needles are inserted. This type of effect has been seen in connective tissue.
• Acupuncture has nonspecific effects (effects due to incidental aspects of a treatment rather than its main mechanism of action). Nonspecific effects may be due to the patient’s belief in the treatment, the relationship between the practitioner and the patient, or other factors not directly caused by the insertion of needles. In many studies, the benefit of acupuncture has been greater when it was compared with no treatment than when it was compared with sham (simulated or fake) acupuncture procedures, such as the use of a device that pokes the skin but does not penetrate it. These findings suggest that nonspecific effects contribute to the beneficial effect of acupuncture on pain or other symptoms. 
• In recent research, a nonspecific effect was demonstrated in a unique way: Patients who had experienced pain relief during a previous acupuncture session were shown a video of that session and asked to imagine the treatment happening again. This video-guided imagery technique had a significant pain-relieving effect.

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Research has shown that acupuncture may be helpful for several pain conditions, including back or neck pain, knee pain associated with osteoarthritis, and postoperative pain. It may also help relieve joint pain associated with the use of aromatase inhibitors, which are drugs used in people with breast cancer. 

An analysis of data from 20 studies (6,376 participants) of people with painful conditions (back pain, osteoarthritis, neck pain, or headaches) showed that the beneficial effects of acupuncture continued for a year after the end of treatment for all conditions except neck pain.

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• In a 2018 review, data from 12 studies (8,003 participants) showed acupuncture was more effective than no treatment for back or neck pain, and data from 10 studies (1,963 participants) showed acupuncture was more effective than sham acupuncture. The difference between acupuncture and no treatment was greater than the difference between acupuncture and sham acupuncture. The pain-relieving effect of acupuncture was comparable to that of nonsteroidal anti-inflammatory drugs (NSAIDs).
• A 2017 clinical practice guideline from the American College of Physicians included acupuncture among the nondrug options recommended as first-line treatment for chronic low-back pain. Acupuncture is also one of the treatment options recommended for acute low-back pain. The evidence favoring acupuncture for acute low-back pain was judged to be of low quality, and the evidence for chronic low-back pain was judged to be of moderate quality.

For more information, see the  NCCIH webpage on low-back pain .

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• In a 2018 review, data from 10 studies (2,413 participants) showed acupuncture was more effective than no treatment for osteoarthritis pain, and data from 9 studies (2,376 participants) showed acupuncture was more effective than sham acupuncture. The difference between acupuncture and no treatment was greater than the difference between acupuncture and sham acupuncture. Most of the participants in these studies had knee osteoarthritis, but some had hip osteoarthritis. The pain-relieving effect of acupuncture was comparable to that of NSAIDs.
• A 2018 review evaluated 6 studies (413 participants) of acupuncture for hip osteoarthritis. Two of the studies compared acupuncture with sham acupuncture and found little or no difference between them in terms of effects on pain. The other four studies compared acupuncture with a variety of other treatments and could not easily be compared with one another. However, one of the trials indicated that the addition of acupuncture to routine care by a physician may improve pain and function in patients with hip osteoarthritis.
• A 2019 clinical practice guideline from the American College of Rheumatology and the Arthritis Foundation conditionally recommends acupuncture for osteoarthritis of the knee, hip, or hand. The guideline states that the greatest number of studies showing benefits have been for knee osteoarthritis.

For more information, see the  NCCIH webpage on osteoarthritis .

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• A 2020   review of nine studies that compared acupuncture with various drugs for preventing migraine found that acupuncture was slightly more effective, and study participants who received acupuncture were much less likely than those receiving drugs to drop out of studies because of side effects.
• There’s moderate-quality evidence that acupuncture may reduce the frequency of migraines (from a 2016 evaluation of 22 studies with almost 5,000 people). The evidence from these studies also suggests that acupuncture may be better than sham acupuncture, but the difference is small. There is moderate- to low-quality evidence that acupuncture may reduce the frequency of tension headaches (from a 2016 evaluation of 12 studies with about 2,350 people).

For more information, see the  NCCIH webpage on headache .

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• Myofascial pain syndrome is a common form of pain derived from muscles and their related connective tissue (fascia). It involves tender nodules called “trigger points.” Pressing on these nodules reproduces the patient’s pattern of pain.
• A combined analysis of a small number of studies of acupuncture for myofascial pain syndrome showed that acupuncture applied to trigger points had a favorable effect on pain intensity (5 studies, 215 participants), but acupuncture applied to traditional acupuncture points did not (4 studies, 80 participants).  

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• Sciatica involves pain, weakness, numbness, or tingling in the leg, usually on one side of the body, caused by damage to or pressure on the sciatic nerve—a nerve that starts in the lower back and runs down the back of each leg.
• Two 2015 evaluations of the evidence, one including 12 studies with 1,842 total participants and the other including 11 studies with 962 total participants, concluded that acupuncture may be helpful for sciatica pain, but the quality of the research is not good enough to allow definite conclusions to be reached.

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• A 2016 evaluation of 11 studies of pain after surgery (with a total of 682 participants) found that patients treated with acupuncture or related techniques 1 day after surgery had less pain and used less opioid pain medicine after the operation.

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• A 2016 review of 20 studies (1,639 participants) indicated that acupuncture was not more effective in relieving cancer pain than conventional drug therapy. However, there was some evidence that acupuncture plus drug therapy might be better than drug therapy alone.
• A 2017 review of 5 studies (181 participants) of acupuncture for aromatase inhibitor-induced joint pain in breast cancer patients concluded that 6 to 8 weeks of acupuncture treatment may help reduce the pain. However, the individual studies only included small numbers of women and used a variety of acupuncture techniques and measurement methods, so they were difficult to compare.
• A larger 2018 study included 226 women with early-stage breast cancer who were taking aromatase inhibitors. The study found that the women who received 6 weeks of acupuncture treatment, given twice each week, reported less joint pain than the participants who received sham or no acupuncture.

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• Chronic prostatitis/chronic pelvic pain syndrome is a condition in men that involves inflammation of or near the prostate gland; its cause is uncertain.
• A review of 3 studies (204 total participants) suggested that acupuncture may reduce prostatitis symptoms, compared with a sham procedure. Because follow-up of the study participants was relatively brief and the numbers of studies and participants were small, a definite conclusion cannot be reached about acupuncture’s effects.

.header_greentext{color:green!important;font-size:24px!important;font-weight:500!important;}.header_bluetext{color:blue!important;font-size:18px!important;font-weight:500!important;}.header_redtext{color:red!important;font-size:28px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;font-size:28px!important;font-weight:500!important;}.header_purpletext{color:purple!important;font-size:31px!important;font-weight:500!important;}.header_yellowtext{color:yellow!important;font-size:20px!important;font-weight:500!important;}.header_blacktext{color:black!important;font-size:22px!important;font-weight:500!important;}.header_whitetext{color:white!important;font-size:22px!important;font-weight:500!important;}.header_darkred{color:#803d2f!important;}.Green_Header{color:green!important;font-size:24px!important;font-weight:500!important;}.Blue_Header{color:blue!important;font-size:18px!important;font-weight:500!important;}.Red_Header{color:red!important;font-size:28px!important;font-weight:500!important;}.Purple_Header{color:purple!important;font-size:31px!important;font-weight:500!important;}.Yellow_Header{color:yellow!important;font-size:20px!important;font-weight:500!important;}.Black_Header{color:black!important;font-size:22px!important;font-weight:500!important;}.White_Header{color:white!important;font-size:22px!important;font-weight:500!important;} Irritable Bowel Syndrome

• A 2019 review of 41 studies (3,440 participants) showed that acupuncture was no more effective than sham acupuncture for symptoms of irritable bowel syndrome, but there was some evidence that acupuncture could be helpful when used in addition to other forms of treatment.

For more information, see the  NCCIH webpage on irritable bowel syndrome .

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• A 2019 review of 12 studies (824 participants) of people with fibromyalgia indicated that acupuncture was significantly better than sham acupuncture for relieving pain, but the evidence was of low-to-moderate quality.

For more information, see the  NCCIH webpage on fibromyalgia . 

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In addition to pain conditions, acupuncture has also been studied for at least 50 other health problems. There is evidence that acupuncture may help relieve seasonal allergy symptoms, stress incontinence in women, and nausea and vomiting associated with cancer treatment. It may also help relieve symptoms and improve the quality of life in people with asthma, but it has not been shown to improve lung function.

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• A 2015 evaluation of 13 studies of acupuncture for allergic rhinitis, involving a total of 2,365 participants, found evidence that acupuncture may help relieve nasal symptoms. The study participants who received acupuncture also had lower medication scores (meaning that they used less medication to treat their symptoms) and lower blood levels of immunoglobulin E (IgE), a type of antibody associated with allergies.
• A 2014 clinical practice guideline from the American Academy of Otolaryngology–Head and Neck Surgery included acupuncture among the options health care providers may offer to patients with allergic rhinitis.

For more information, see the  NCCIH webpage on seasonal allergies .

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• Stress incontinence is a bladder control problem in which movement—coughing, sneezing, laughing, or physical activity—puts pressure on the bladder and causes urine to leak.
• In a 2017 study of about 500 women with stress incontinence, participants who received electroacupuncture treatment (18 sessions over 6 weeks) had reduced urine leakage, with about two-thirds of the women having a decrease in leakage of 50 percent or more. This was a rigorous study that met current standards for avoiding bias.

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• Experts generally agree that acupuncture is helpful for treatment-related nausea and vomiting in cancer patients, but this conclusion is based primarily on research conducted before current guidelines for treating these symptoms were adopted. It’s uncertain whether acupuncture is beneficial when used in combination with current standard treatments for nausea and vomiting.

For more information, see the  NCCIH webpage on cancer .

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• In a study conducted in Germany in 2017, 357 participants receiving routine asthma care were randomly assigned to receive or not receive acupuncture, and an additional 1,088 people who received acupuncture for asthma were also studied. Adding acupuncture to routine care was associated with better quality of life compared to routine care alone.
• A review of 9 earlier studies (777 participants) showed that adding acupuncture to conventional asthma treatment improved symptoms but not lung function.

For more information, see the  NCCIH webpage on asthma .

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• A 2018 review of 64 studies (7,104 participants) of acupuncture for depression indicated that acupuncture may result in a moderate reduction in the severity of depression when compared with treatment as usual or no treatment. However, these findings should be interpreted with caution because most of the studies were of low or very low quality.

For more information, see the  NCCIH webpage on depression .

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• In recommendations on smoking cessation treatment issued in 2021, the U.S. Preventive Services Task Force, a panel of experts that makes evidence-based recommendations about disease prevention, did not make a recommendation about the use of acupuncture as a stop-smoking treatment because only limited evidence was available. This decision was based on a 2014 review of 9 studies (1,892 participants) that looked at the effect of acupuncture on smoking cessation results for 6 months or more and found no significant benefit. Some studies included in that review showed evidence of a possible small benefit of acupuncture on quitting smoking for shorter periods of time.

For more information, see the  NCCIH webpage on quitting smoking .

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• A 2021 review evaluated 6 studies (2,507 participants) that compared the effects of acupuncture versus sham acupuncture on the success of in vitro fertilization as a treatment for infertility. No difference was found between the acupuncture and sham acupuncture groups in rates of pregnancy or live birth.
• A 2020 review evaluated 12 studies (1,088 participants) on the use of acupuncture to improve sperm quality in men who had low sperm numbers and low sperm motility. The reviewers concluded that the evidence was inadequate for firm conclusions to be drawn because of the varied design of the studies and the poor quality of some of them. 

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• A 2018 review of 12 studies with 869 participants concluded that acupuncture and laser acupuncture (a treatment that uses lasers instead of needles) may have little or no effect on carpal tunnel syndrome symptoms in comparison with sham acupuncture. It’s uncertain how the effects of acupuncture compare with those of other treatments for this condition.    
• In a 2017 study not included in the review described above, 80 participants with carpal tunnel syndrome were randomly assigned to one of three interventions: (1) electroacupuncture to the more affected hand; (2) electroacupuncture at “distal” body sites, near the ankle opposite to the more affected hand; and (3) local sham electroacupuncture using nonpenetrating placebo needles. All three interventions reduced symptom severity, but local and distal acupuncture were better than sham acupuncture at producing desirable changes in the wrist and the brain.

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• A 2018 review of studies of acupuncture for vasomotor symptoms associated with menopause (hot flashes and related symptoms such as night sweats) analyzed combined evidence from an earlier review of 15 studies (1,127 participants) and 4 newer studies (696 additional participants). The analysis showed that acupuncture was better than no acupuncture at reducing the frequency and severity of symptoms. However, acupuncture was not shown to be better than sham acupuncture.

For more information, see the  NCCIH webpage on menopause .

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• Auricular acupuncture is a type of acupuncture that involves stimulating specific areas of the ear. 
• In a 2019 review of 15 studies (930 participants) of auricular acupuncture or auricular acupressure (a form of auricular therapy that does not involve penetration with needles), the treatment significantly reduced pain intensity, and 80 percent of the individual studies showed favorable effects on various measures related to pain.
• A 2020 review of 9 studies (783 participants) of auricular acupuncture for cancer pain showed that auricular acupuncture produced better pain relief than sham auricular acupuncture. Also, pain relief was better with a combination of auricular acupuncture and drug therapy than with drug therapy alone.
• An inexpensive, easily learned form of auricular acupuncture called “battlefield acupuncture” has been used by the U.S. Department of Defense and Department of Veterans Affairs to treat pain. However, a 2021 review of 9 studies (692 participants) of battlefield acupuncture for pain in adults did not find any significant improvement in pain when this technique was compared with no treatment, usual care, delayed treatment, or sham battlefield acupuncture.

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• Relatively few complications from using acupuncture have been reported. However, complications have resulted from use of nonsterile needles and improper delivery of treatments.
• When not delivered properly, acupuncture can cause serious adverse effects, including infections, punctured organs, and injury to the central nervous system.
• The U.S. Food and Drug Administration (FDA) regulates acupuncture needles as medical devices and requires that they be sterile and labeled for single use only.

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• Some health insurance policies cover acupuncture, but others don’t. Coverage is often limited based on the condition being treated.
• An analysis of data from the Medical Expenditure Panel Survey, a nationally representative U.S. survey, showed that the share of adult acupuncturist visits with any insurance coverage increased from 41.1 percent in 2010–2011 to 50.2 percent in 2018–2019.
• Medicare covers acupuncture only for the treatment of chronic low-back pain. Coverage began in 2020. Up to 12 acupuncture visits are covered, with an additional 8 visits available if the first 12 result in improvement. Medicaid coverage of acupuncture varies from state to state.

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• Most states license acupuncturists, but the requirements for licensing vary from state to state. To find out more about licensing of acupuncturists and other complementary health practitioners, visit the NCCIH webpage  Credentialing, Licensing, and Education . 

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NCCIH funds research to evaluate acupuncture’s effectiveness for various kinds of pain and other conditions and to further understand how the body responds to acupuncture and how acupuncture might work. Some recent NCCIH-supported studies involve:

• Evaluating the feasibility of using acupuncture in hospital emergency departments.
• Testing whether the effect of acupuncture on chronic low-back pain can be enhanced by combining it with transcranial direct current stimulation.
• Evaluating a portable acupuncture-based nerve stimulation treatment for anxiety disorders.

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• Don’t use acupuncture to postpone seeing a health care provider about a health problem.
• Take charge of your health—talk with your health care providers about any complementary health approaches you use. Together, you can make shared, well-informed decisions.

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Nccih clearinghouse.

The NCCIH Clearinghouse provides information on NCCIH and complementary and integrative health approaches, including publications and searches of Federal databases of scientific and medical literature. The Clearinghouse does not provide medical advice, treatment recommendations, or referrals to practitioners.

Toll-free in the U.S.: 1-888-644-6226

Telecommunications relay service (TRS): 7-1-1

Website: https://www.nccih.nih.gov

Email: [email protected] (link sends email)

Know the Science

NCCIH and the National Institutes of Health (NIH) provide tools to help you understand the basics and terminology of scientific research so you can make well-informed decisions about your health. Know the Science features a variety of materials, including interactive modules, quizzes, and videos, as well as links to informative content from Federal resources designed to help consumers make sense of health information.

Explaining How Research Works (NIH)

Know the Science: How To Make Sense of a Scientific Journal Article

Understanding Clinical Studies (NIH)

A service of the National Library of Medicine, PubMed® contains publication information and (in most cases) brief summaries of articles from scientific and medical journals. For guidance from NCCIH on using PubMed, see How To Find Information About Complementary Health Approaches on PubMed .

Website: https://pubmed.ncbi.nlm.nih.gov/

NIH Clinical Research Trials and You

The National Institutes of Health (NIH) has created a website, NIH Clinical Research Trials and You, to help people learn about clinical trials, why they matter, and how to participate. The site includes questions and answers about clinical trials, guidance on how to find clinical trials through ClinicalTrials.gov and other resources, and stories about the personal experiences of clinical trial participants. Clinical trials are necessary to find better ways to prevent, diagnose, and treat diseases.

Website: https://www.nih.gov/health-information/nih-clinical-research-trials-you

Research Portfolio Online Reporting Tools Expenditures & Results (RePORTER)

RePORTER is a database of information on federally funded scientific and medical research projects being conducted at research institutions.

Website: https://reporter.nih.gov

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• Befus D, Coeytaux RR, Goldstein KM, et al.  Management of menopause symptoms with acupuncture: an umbrella systematic review and meta-analysis . Journal of Alternative and Complementary Medicine. 2018;24(4):314-323.
• Bleck   R, Marquez E, Gold MA, et al.  A scoping review of acupuncture insurance coverage in the United States . Acupuncture in Medicine. 2020;964528420964214.
• Briggs JP, Shurtleff D.  Acupuncture and the complex connections between the mind and the body. JAMA. 2017;317(24):2489-2490.
• Brinkhaus B, Roll S, Jena S, et al.  Acupuncture in patients with allergic asthma: a randomized pragmatic trial. Journal of Alternative and Complementary Medicine. 2017;23(4):268-277.
• Chan MWC, Wu XY, Wu JCY, et al.  Safety of acupuncture: overview of systematic reviews. Scientific Reports. 2017;7(1):3369.
• Coyle ME, Stupans I, Abdel-Nour K, et al.  Acupuncture versus placebo acupuncture for in vitro fertilisation: a systematic review and meta-analysis. Acupuncture in Medicine. 2021;39(1):20-29.
• Hershman DL, Unger JM, Greenlee H, et al.  Effect of acupuncture vs sham acupuncture or waitlist control on joint pain related to aromatase inhibitors among women with early-stage breast cancer: a randomized clinical trial. JAMA. 2018;320(2):167-176.
• Linde K, Allais G, Brinkhaus B, et al.  Acupuncture for the prevention of episodic migraine. Cochrane Database of Systematic Reviews. 2016;(6):CD001218. Accessed at  cochranelibrary.com on February 12, 2021.
• Linde K, Allais G, Brinkhaus B, et al.  Acupuncture for the prevention of tension-type headache. Cochrane Database of Systematic Reviews. 2016;(4):CD007587. Accessed at  cochranelibrary.com on February 12, 2021.
• MacPherson H, Vertosick EA, Foster NE, et al. The persistence of the effects of acupuncture after a course of treatment: a meta-analysis of patients with chronic pain . Pain. 2017;158(5):784-793.
• Qaseem A, Wilt TJ, McLean RM, et al.  Noninvasive treatments for acute, subacute, and chronic low back pain: a clinical practice guideline from the American College of Physicians. Annals of Internal Medicine. 2017;166(7):514-530.
• Seidman MD, Gurgel RK, Lin SY, et al.  Clinical practice guideline: allergic rhinitis. Otolaryngology—Head and Neck Surgery. 2015;152(suppl 1):S1-S43.
• Vickers AJ, Vertosick EA, Lewith G, et al. Acupuncture for chronic pain: update of an individual patient data meta-analysis . The Journal of Pain. 2018;19(5):455-474.
• White AR, Rampes H, Liu JP, et al.  Acupuncture and related interventions for smoking cessation. Cochrane Database of Systematic Reviews. 2014;(1):CD000009. Accessed at  cochranelibrary.com on February 17, 2021.
• Zia FZ, Olaku O, Bao T, et al.  The National Cancer Institute’s conference on acupuncture for symptom management in oncology: state of the science, evidence, and research gaps. Journal of the National Cancer Institute. Monographs. 2017;2017(52):lgx005.

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• Adams D, Cheng F, Jou H, et al. The safety of pediatric acupuncture: a systematic review. Pediatrics. 2011;128(6):e1575-1587.
• Candon M, Nielsen A, Dusek JA. Trends in insurance coverage for acupuncture, 2010-2019. JAMA Network Open. 2022;5(1):e2142509.
• Cao J, Tu Y, Orr SP, et al. Analgesic effects evoked by real and imagined acupuncture: a neuroimaging study. Cerebral Cortex. 2019;29(8):3220-3231.
• Centers for Medicare & Medicaid Services. Decision Memo for Acupuncture for Chronic Low Back Pain (CAG-00452N). Accessed at https://www.cms.gov/medicare-coverage-database/details/nca-decision-memo.aspx?NCAId=295 on June 25, 2021.
• Chen L, Lin C-C, Huang T-W, et al. Effect of acupuncture on aromatase inhibitor-induced arthralgia in patients with breast cancer: a meta-analysis of randomized controlled trials . The Breast. 2017;33:132-138. 
• Choi G-H, Wieland LS, Lee H, et al. Acupuncture and related interventions for the treatment of symptoms associated with carpal tunnel syndrome. Cochrane Database of Systematic Reviews. 2018;(12):CD011215. Accessed at cochranelibrary.com on January 28, 2021.
• Cui J, Wang S, Ren J, et al. Use of acupuncture in the USA: changes over a decade (2002–2012). Acupuncture in Medicine. 2017;35(3):200-207.
• Federman DG, Zeliadt SB, Thomas ER, et al. Battlefield acupuncture in the Veterans Health Administration: effectiveness in individual and group settings for pain and pain comorbidities. Medical Acupuncture. 2018;30(5):273-278.
• Feng S, Han M, Fan Y, et al. Acupuncture for the treatment of allergic rhinitis: a systematic review and meta-analysis. American Journal of Rhinology & Allergy. 2015;29(1):57-62.
• Franco JV, Turk T, Jung JH, et al. Non-pharmacological interventions for treating chronic prostatitis/chronic pelvic pain syndrome. Cochrane Database of Systematic Reviews. 2018;(5):CD012551. Accessed at cochranelibrary.com on January 28, 2021.
• Freeman MP, Fava M, Lake J, et al. Complementary and alternative medicine in major depressive disorder: the American Psychiatric Association task force report. The Journal of Clinical Psychiatry . 2010;71(6):669-681.
• Giovanardi CM, Cinquini M, Aguggia M, et al. Acupuncture vs. pharmacological prophylaxis of migraine: a systematic review of randomized controlled trials. Frontiers in Neurology. 2020;11:576272.
• Hu C, Zhang H, Wu W, et al. Acupuncture for pain management in cancer: a systematic review and meta-analysis. Evidence-Based Complementary and Alternative Medicine. 2016;2016;1720239.
• Jiang C, Jiang L, Qin Q. Conventional treatments plus acupuncture for asthma in adults and adolescent: a systematic review and meta-analysis. Evidence-Based Complementary and Alternative Medicine . 2019;2019:9580670.
• Ji M, Wang X, Chen M, et al. The efficacy of acupuncture for the treatment of sciatica: a systematic review and meta-analysis. Evidence-Based Complementary and Alternative Medicine.  2015;2015:192808.
• Kaptchuk TJ. Acupuncture: theory, efficacy, and practice. Annals of Internal Medicine . 2002;136(5):374-383.
• Kolasinski SL, Neogi T, Hochberg MC, et al. 2019 American College of Rheumatology/Arthritis Foundation guideline for the management of osteoarthritis of the hand, hip, and knee. Arthritis Care & Research. 2020;72(2):149-162. 
• Langevin H. Fascia mobility, proprioception, and myofascial pain. Life. 2021;11(7):668. 
• Liu Z, Liu Y, Xu H, et al. Effect of electroacupuncture on urinary leakage among women with stress urinary incontinence: a randomized clinical trial. JAMA. 2017;317(24):2493-2501.
• MacPherson H, Hammerschlag R, Coeytaux RR, et al. Unanticipated insights into biomedicine from the study of acupuncture. Journal of Alternative and Complementary Medicine. 2016;22(2):101-107.
• Maeda Y, Kim H, Kettner N, et al. Rewiring the primary somatosensory cortex in carpal tunnel syndrome with acupuncture. Brain. 2017;140(4):914-927.
• Manheimer E, Cheng K, Wieland LS, et al. Acupuncture for hip osteoarthritis. Cochrane Database of Systematic Reviews. 2018;(5):CD013010. Accessed at cochranelibrary.com on February 17, 2021. 
• Moura CC, Chaves ECL, Cardoso ACLR, et al. Auricular acupuncture for chronic back pain in adults: a systematic review and metanalysis. Revista da Escola de Enfermagem da U S P. 2019;53:e03461.
• Nahin RL, Rhee A, Stussman B. Use of complementary health approaches overall and for pain management by US adults. JAMA. 2024;331(7):613-615.
• Napadow V. Neuroimaging somatosensory and therapeutic alliance mechanisms supporting acupuncture. Medical Acupuncture. 2020;32(6):400-402.
• Patnode CD, Henderson JT, Coppola EL, et al. Interventions for tobacco cessation in adults, including pregnant persons: updated evidence report and systematic review for the US Preventive Services Task Force. JAMA. 2021;325(3):280-298.
• Qin Z, Liu X, Wu J, et al. Effectiveness of acupuncture for treating sciatica: a systematic review and meta-analysis. Evidence-Based Complementary and Alternative Medicine. 2015;2015;425108.
• Smith CA, Armour M, Lee MS, et al. Acupuncture for depression. Cochrane Database of Systematic Reviews. 2018;(3):CD004046. Accessed at cochranelibrary.com on January 20, 2021.
• US Preventive Services Task Force. Interventions for tobacco smoking cessation in adults, including pregnant persons. US Preventive Services Task Force recommendation statement. JAMA. 2021;325(3):265-279.
• Vase L, Baram S, Takakura N, et al. Specifying the nonspecific components of acupuncture analgesia. Pain. 2013;154(9):1659-1667.
• Wang R, Li X, Zhou S, et al. Manual acupuncture for myofascial pain syndrome: a systematic review and meta-analysis. Acupuncture in Medicine. 2017;35(4):241-250.
• World Health Organization. WHO Traditional Medicine Strategy: 2014–2023. Geneva, Switzerland: World Health Organization, 2013. Accessed at https://www.who.int/publications/i/item/9789241506096 on February 2, 2021.
• Wu M-S, Chen K-H, Chen I-F, et al. The efficacy of acupuncture in post-operative pain management: a systematic review and meta-analysis. PLoS One. 2016;11(3):e0150367.
• Xu S, Wang L, Cooper E, et al. Adverse events of acupuncture: a systematic review of case reports. Evidence-Based Complementary and Alternative Medicine. 2013;2013:581203.
• Yang J, Ganesh R, Wu Q, et al. Battlefield acupuncture for adult pain: a systematic review and meta-analysis of randomized controlled trials. The American Journal of Chinese Medicine. 2021;49(1):25-40.
• Yang Y, Wen J, Hong J. The effects of auricular therapy for cancer pain: a systematic review and meta-analysis. Evidence-Based Complementary and Alternative Medicine. 2020;2020:1618767.  
• Yeh CH, Morone NE, Chien L-C, et al. Auricular point acupressure to manage chronic low back pain in older adults: a randomized controlled pilot study. Evidence-Based Complementary and Alternative Medicine. 2014;2014;375173.
• You F, Ruan L, Zeng L, et al. Efficacy and safety of acupuncture for the treatment of oligoasthenozoospermia: a systematic review. Andrologia. 2020;52(1):e13415.
• Zhang X-C, Chen H, Xu W-T, et al. Acupuncture therapy for fibromyalgia: a systematic review and meta-analysis of randomized controlled trials. Journal of Pain Research. 2019;12:527-542.
• Zheng H, Chen R, Zhao X, et al. Comparison between the effects of acupuncture relative to other controls on irritable bowel syndrome: a meta-analysis. Pain Research and Management. 2019;2019:2871505.

Acknowledgments

NCCIH thanks Pete Murray, Ph.D., David Shurtleff, Ph.D., and Helene M. Langevin, M.D., NCCIH for their review of the 2022 update of this fact sheet. 

This publication is not copyrighted and is in the public domain. Duplication is encouraged.

NCCIH has provided this material for your information. It is not intended to substitute for the medical expertise and advice of your health care provider(s). We encourage you to discuss any decisions about treatment or care with your health care provider. The mention of any product, service, or therapy is not an endorsement by NCCIH.

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