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Case Study – Methods, Examples and Guide

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A case study is a research method that involves an in-depth examination and analysis of a particular phenomenon or case, such as an individual, organization, community, event, or situation.

It is a qualitative research approach that aims to provide a detailed and comprehensive understanding of the case being studied. Case studies typically involve multiple sources of data, including interviews, observations, documents, and artifacts, which are analyzed using various techniques, such as content analysis, thematic analysis, and grounded theory. The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions.

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to understand a specific phenomenon in detail.

For Example , A researcher might conduct a single-case study on a particular individual to understand their experiences with a particular health condition or a specific organization to explore their management practices. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a single-case study are often used to generate new research questions, develop theories, or inform policy or practice.

Multiple-Case Study

A multiple-case study involves the analysis of several cases that are similar in nature. This type of case study is useful when the researcher wants to identify similarities and differences between the cases.

For Example, a researcher might conduct a multiple-case study on several companies to explore the factors that contribute to their success or failure. The researcher collects data from each case, compares and contrasts the findings, and uses various techniques to analyze the data, such as comparative analysis or pattern-matching. The findings of a multiple-case study can be used to develop theories, inform policy or practice, or generate new research questions.

Exploratory Case Study

An exploratory case study is used to explore a new or understudied phenomenon. This type of case study is useful when the researcher wants to generate hypotheses or theories about the phenomenon.

For Example, a researcher might conduct an exploratory case study on a new technology to understand its potential impact on society. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as grounded theory or content analysis. The findings of an exploratory case study can be used to generate new research questions, develop theories, or inform policy or practice.

Descriptive Case Study

A descriptive case study is used to describe a particular phenomenon in detail. This type of case study is useful when the researcher wants to provide a comprehensive account of the phenomenon.

For Example, a researcher might conduct a descriptive case study on a particular community to understand its social and economic characteristics. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of a descriptive case study can be used to inform policy or practice or generate new research questions.

Instrumental Case Study

An instrumental case study is used to understand a particular phenomenon that is instrumental in achieving a particular goal. This type of case study is useful when the researcher wants to understand the role of the phenomenon in achieving the goal.

For Example, a researcher might conduct an instrumental case study on a particular policy to understand its impact on achieving a particular goal, such as reducing poverty. The researcher collects data from multiple sources, such as interviews, observations, and documents, and uses various techniques to analyze the data, such as content analysis or thematic analysis. The findings of an instrumental case study can be used to inform policy or practice or generate new research questions.

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

Interviews involve asking questions to individuals who have knowledge or experience relevant to the case study. Interviews can be structured (where the same questions are asked to all participants) or unstructured (where the interviewer follows up on the responses with further questions). Interviews can be conducted in person, over the phone, or through video conferencing.

Observations

Observations involve watching and recording the behavior and activities of individuals or groups relevant to the case study. Observations can be participant (where the researcher actively participates in the activities) or non-participant (where the researcher observes from a distance). Observations can be recorded using notes, audio or video recordings, or photographs.

Documents can be used as a source of information for case studies. Documents can include reports, memos, emails, letters, and other written materials related to the case study. Documents can be collected from the case study participants or from public sources.

Surveys involve asking a set of questions to a sample of individuals relevant to the case study. Surveys can be administered in person, over the phone, through mail or email, or online. Surveys can be used to gather information on attitudes, opinions, or behaviors related to the case study.

Artifacts are physical objects relevant to the case study. Artifacts can include tools, equipment, products, or other objects that provide insights into the case study phenomenon.

How to conduct Case Study Research

Conducting a case study research involves several steps that need to be followed to ensure the quality and rigor of the study. Here are the steps to conduct case study research:

• Define the research questions: The first step in conducting a case study research is to define the research questions. The research questions should be specific, measurable, and relevant to the case study phenomenon under investigation.
• Select the case: The next step is to select the case or cases to be studied. The case should be relevant to the research questions and should provide rich and diverse data that can be used to answer the research questions.
• Collect data: Data can be collected using various methods, such as interviews, observations, documents, surveys, and artifacts. The data collection method should be selected based on the research questions and the nature of the case study phenomenon.
• Analyze the data: The data collected from the case study should be analyzed using various techniques, such as content analysis, thematic analysis, or grounded theory. The analysis should be guided by the research questions and should aim to provide insights and conclusions relevant to the research questions.
• Draw conclusions: The conclusions drawn from the case study should be based on the data analysis and should be relevant to the research questions. The conclusions should be supported by evidence and should be clearly stated.
• Validate the findings: The findings of the case study should be validated by reviewing the data and the analysis with participants or other experts in the field. This helps to ensure the validity and reliability of the findings.
• Write the report: The final step is to write the report of the case study research. The report should provide a clear description of the case study phenomenon, the research questions, the data collection methods, the data analysis, the findings, and the conclusions. The report should be written in a clear and concise manner and should follow the guidelines for academic writing.

Examples of Case Study

Here are some examples of case study research:

• The Hawthorne Studies : Conducted between 1924 and 1932, the Hawthorne Studies were a series of case studies conducted by Elton Mayo and his colleagues to examine the impact of work environment on employee productivity. The studies were conducted at the Hawthorne Works plant of the Western Electric Company in Chicago and included interviews, observations, and experiments.
• The Stanford Prison Experiment: Conducted in 1971, the Stanford Prison Experiment was a case study conducted by Philip Zimbardo to examine the psychological effects of power and authority. The study involved simulating a prison environment and assigning participants to the role of guards or prisoners. The study was controversial due to the ethical issues it raised.
• The Challenger Disaster: The Challenger Disaster was a case study conducted to examine the causes of the Space Shuttle Challenger explosion in 1986. The study included interviews, observations, and analysis of data to identify the technical, organizational, and cultural factors that contributed to the disaster.
• The Enron Scandal: The Enron Scandal was a case study conducted to examine the causes of the Enron Corporation’s bankruptcy in 2001. The study included interviews, analysis of financial data, and review of documents to identify the accounting practices, corporate culture, and ethical issues that led to the company’s downfall.
• The Fukushima Nuclear Disaster : The Fukushima Nuclear Disaster was a case study conducted to examine the causes of the nuclear accident that occurred at the Fukushima Daiichi Nuclear Power Plant in Japan in 2011. The study included interviews, analysis of data, and review of documents to identify the technical, organizational, and cultural factors that contributed to the disaster.

Application of Case Study

Case studies have a wide range of applications across various fields and industries. Here are some examples:

Business and Management

Case studies are widely used in business and management to examine real-life situations and develop problem-solving skills. Case studies can help students and professionals to develop a deep understanding of business concepts, theories, and best practices.

Case studies are used in healthcare to examine patient care, treatment options, and outcomes. Case studies can help healthcare professionals to develop critical thinking skills, diagnose complex medical conditions, and develop effective treatment plans.

Case studies are used in education to examine teaching and learning practices. Case studies can help educators to develop effective teaching strategies, evaluate student progress, and identify areas for improvement.

Social Sciences

Case studies are widely used in social sciences to examine human behavior, social phenomena, and cultural practices. Case studies can help researchers to develop theories, test hypotheses, and gain insights into complex social issues.

Law and Ethics

Case studies are used in law and ethics to examine legal and ethical dilemmas. Case studies can help lawyers, policymakers, and ethical professionals to develop critical thinking skills, analyze complex cases, and make informed decisions.

Purpose of Case Study

The purpose of a case study is to provide a detailed analysis of a specific phenomenon, issue, or problem in its real-life context. A case study is a qualitative research method that involves the in-depth exploration and analysis of a particular case, which can be an individual, group, organization, event, or community.

The primary purpose of a case study is to generate a comprehensive and nuanced understanding of the case, including its history, context, and dynamics. Case studies can help researchers to identify and examine the underlying factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and detailed understanding of the case, which can inform future research, practice, or policy.

Case studies can also serve other purposes, including:

• Illustrating a theory or concept: Case studies can be used to illustrate and explain theoretical concepts and frameworks, providing concrete examples of how they can be applied in real-life situations.
• Developing hypotheses: Case studies can help to generate hypotheses about the causal relationships between different factors and outcomes, which can be tested through further research.
• Providing insight into complex issues: Case studies can provide insights into complex and multifaceted issues, which may be difficult to understand through other research methods.
• Informing practice or policy: Case studies can be used to inform practice or policy by identifying best practices, lessons learned, or areas for improvement.

Advantages of Case Study Research

There are several advantages of case study research, including:

• In-depth exploration: Case study research allows for a detailed exploration and analysis of a specific phenomenon, issue, or problem in its real-life context. This can provide a comprehensive understanding of the case and its dynamics, which may not be possible through other research methods.
• Rich data: Case study research can generate rich and detailed data, including qualitative data such as interviews, observations, and documents. This can provide a nuanced understanding of the case and its complexity.
• Holistic perspective: Case study research allows for a holistic perspective of the case, taking into account the various factors, processes, and mechanisms that contribute to the case and its outcomes. This can help to develop a more accurate and comprehensive understanding of the case.
• Theory development: Case study research can help to develop and refine theories and concepts by providing empirical evidence and concrete examples of how they can be applied in real-life situations.
• Practical application: Case study research can inform practice or policy by identifying best practices, lessons learned, or areas for improvement.
• Contextualization: Case study research takes into account the specific context in which the case is situated, which can help to understand how the case is influenced by the social, cultural, and historical factors of its environment.

Limitations of Case Study Research

There are several limitations of case study research, including:

• Limited generalizability : Case studies are typically focused on a single case or a small number of cases, which limits the generalizability of the findings. The unique characteristics of the case may not be applicable to other contexts or populations, which may limit the external validity of the research.
• Biased sampling: Case studies may rely on purposive or convenience sampling, which can introduce bias into the sample selection process. This may limit the representativeness of the sample and the generalizability of the findings.
• Subjectivity: Case studies rely on the interpretation of the researcher, which can introduce subjectivity into the analysis. The researcher’s own biases, assumptions, and perspectives may influence the findings, which may limit the objectivity of the research.
• Limited control: Case studies are typically conducted in naturalistic settings, which limits the control that the researcher has over the environment and the variables being studied. This may limit the ability to establish causal relationships between variables.
• Time-consuming: Case studies can be time-consuming to conduct, as they typically involve a detailed exploration and analysis of a specific case. This may limit the feasibility of conducting multiple case studies or conducting case studies in a timely manner.
• Resource-intensive: Case studies may require significant resources, including time, funding, and expertise. This may limit the ability of researchers to conduct case studies in resource-constrained settings.

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Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, 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 analyze the case, other interesting articles.

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.

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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

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

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.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

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

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

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.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

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 analyze 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.

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
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

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

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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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Methodology or method? A critical review of qualitative case study reports

Despite on-going debate about credibility, and reported limitations in comparison to other approaches, case study is an increasingly popular approach among qualitative researchers. We critically analysed the methodological descriptions of published case studies. Three high-impact qualitative methods journals were searched to locate case studies published in the past 5 years; 34 were selected for analysis. Articles were categorized as health and health services ( n= 12), social sciences and anthropology ( n= 7), or methods ( n= 15) case studies. The articles were reviewed using an adapted version of established criteria to determine whether adequate methodological justification was present, and if study aims, methods, and reported findings were consistent with a qualitative case study approach. Findings were grouped into five themes outlining key methodological issues: case study methodology or method, case of something particular and case selection, contextually bound case study, researcher and case interactions and triangulation, and study design inconsistent with methodology reported. Improved reporting of case studies by qualitative researchers will advance the methodology for the benefit of researchers and practitioners.

Case study research is an increasingly popular approach among qualitative researchers (Thomas, 2011 ). Several prominent authors have contributed to methodological developments, which has increased the popularity of case study approaches across disciplines (Creswell, 2013b ; Denzin & Lincoln, 2011b ; Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Current qualitative case study approaches are shaped by paradigm, study design, and selection of methods, and, as a result, case studies in the published literature vary. Differences between published case studies can make it difficult for researchers to define and understand case study as a methodology.

Experienced qualitative researchers have identified case study research as a stand-alone qualitative approach (Denzin & Lincoln, 2011b ). Case study research has a level of flexibility that is not readily offered by other qualitative approaches such as grounded theory or phenomenology. Case studies are designed to suit the case and research question and published case studies demonstrate wide diversity in study design. There are two popular case study approaches in qualitative research. The first, proposed by Stake ( 1995 ) and Merriam ( 2009 ), is situated in a social constructivist paradigm, whereas the second, by Yin ( 2012 ), Flyvbjerg ( 2011 ), and Eisenhardt ( 1989 ), approaches case study from a post-positivist viewpoint. Scholarship from both schools of inquiry has contributed to the popularity of case study and development of theoretical frameworks and principles that characterize the methodology.

The diversity of case studies reported in the published literature, and on-going debates about credibility and the use of case study in qualitative research practice, suggests that differences in perspectives on case study methodology may prevent researchers from developing a mutual understanding of practice and rigour. In addition, discussion about case study limitations has led some authors to query whether case study is indeed a methodology (Luck, Jackson, & Usher, 2006 ; Meyer, 2001 ; Thomas, 2010 ; Tight, 2010 ). Methodological discussion of qualitative case study research is timely, and a review is required to analyse and understand how this methodology is applied in the qualitative research literature. The aims of this study were to review methodological descriptions of published qualitative case studies, to review how the case study methodological approach was applied, and to identify issues that need to be addressed by researchers, editors, and reviewers. An outline of the current definitions of case study and an overview of the issues proposed in the qualitative methodological literature are provided to set the scene for the review.

Definitions of qualitative case study research

Case study research is an investigation and analysis of a single or collective case, intended to capture the complexity of the object of study (Stake, 1995 ). Qualitative case study research, as described by Stake ( 1995 ), draws together “naturalistic, holistic, ethnographic, phenomenological, and biographic research methods” in a bricoleur design, or in his words, “a palette of methods” (Stake, 1995 , pp. xi–xii). Case study methodology maintains deep connections to core values and intentions and is “particularistic, descriptive and heuristic” (Merriam, 2009 , p. 46).

As a study design, case study is defined by interest in individual cases rather than the methods of inquiry used. The selection of methods is informed by researcher and case intuition and makes use of naturally occurring sources of knowledge, such as people or observations of interactions that occur in the physical space (Stake, 1998 ). Thomas ( 2011 ) suggested that “analytical eclecticism” is a defining factor (p. 512). Multiple data collection and analysis methods are adopted to further develop and understand the case, shaped by context and emergent data (Stake, 1995 ). This qualitative approach “explores a real-life, contemporary bounded system (a case ) or multiple bounded systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information … and reports a case description and case themes ” (Creswell, 2013b , p. 97). Case study research has been defined by the unit of analysis, the process of study, and the outcome or end product, all essentially the case (Merriam, 2009 ).

The case is an object to be studied for an identified reason that is peculiar or particular. Classification of the case and case selection procedures informs development of the study design and clarifies the research question. Stake ( 1995 ) proposed three types of cases and study design frameworks. These include the intrinsic case, the instrumental case, and the collective instrumental case. The intrinsic case is used to understand the particulars of a single case, rather than what it represents. An instrumental case study provides insight on an issue or is used to refine theory. The case is selected to advance understanding of the object of interest. A collective refers to an instrumental case which is studied as multiple, nested cases, observed in unison, parallel, or sequential order. More than one case can be simultaneously studied; however, each case study is a concentrated, single inquiry, studied holistically in its own entirety (Stake, 1995 , 1998 ).

Researchers who use case study are urged to seek out what is common and what is particular about the case. This involves careful and in-depth consideration of the nature of the case, historical background, physical setting, and other institutional and political contextual factors (Stake, 1998 ). An interpretive or social constructivist approach to qualitative case study research supports a transactional method of inquiry, where the researcher has a personal interaction with the case. The case is developed in a relationship between the researcher and informants, and presented to engage the reader, inviting them to join in this interaction and in case discovery (Stake, 1995 ). A postpositivist approach to case study involves developing a clear case study protocol with careful consideration of validity and potential bias, which might involve an exploratory or pilot phase, and ensures that all elements of the case are measured and adequately described (Yin, 2009 , 2012 ).

Current methodological issues in qualitative case study research

The future of qualitative research will be influenced and constructed by the way research is conducted, and by what is reviewed and published in academic journals (Morse, 2011 ). If case study research is to further develop as a principal qualitative methodological approach, and make a valued contribution to the field of qualitative inquiry, issues related to methodological credibility must be considered. Researchers are required to demonstrate rigour through adequate descriptions of methodological foundations. Case studies published without sufficient detail for the reader to understand the study design, and without rationale for key methodological decisions, may lead to research being interpreted as lacking in quality or credibility (Hallberg, 2013 ; Morse, 2011 ).

There is a level of artistic license that is embraced by qualitative researchers and distinguishes practice, which nurtures creativity, innovation, and reflexivity (Denzin & Lincoln, 2011b ; Morse, 2009 ). Qualitative research is “inherently multimethod” (Denzin & Lincoln, 2011a , p. 5); however, with this creative freedom, it is important for researchers to provide adequate description for methodological justification (Meyer, 2001 ). This includes paradigm and theoretical perspectives that have influenced study design. Without adequate description, study design might not be understood by the reader, and can appear to be dishonest or inaccurate. Reviewers and readers might be confused by the inconsistent or inappropriate terms used to describe case study research approach and methods, and be distracted from important study findings (Sandelowski, 2000 ). This issue extends beyond case study research, and others have noted inconsistencies in reporting of methodology and method by qualitative researchers. Sandelowski ( 2000 , 2010 ) argued for accurate identification of qualitative description as a research approach. She recommended that the selected methodology should be harmonious with the study design, and be reflected in methods and analysis techniques. Similarly, Webb and Kevern ( 2000 ) uncovered inconsistencies in qualitative nursing research with focus group methods, recommending that methodological procedures must cite seminal authors and be applied with respect to the selected theoretical framework. Incorrect labelling using case study might stem from the flexibility in case study design and non-directional character relative to other approaches (Rosenberg & Yates, 2007 ). Methodological integrity is required in design of qualitative studies, including case study, to ensure study rigour and to enhance credibility of the field (Morse, 2011 ).

Case study has been unnecessarily devalued by comparisons with statistical methods (Eisenhardt, 1989 ; Flyvbjerg, 2006 , 2011 ; Jensen & Rodgers, 2001 ; Piekkari, Welch, & Paavilainen, 2009 ; Tight, 2010 ; Yin, 1999 ). It is reputed to be the “the weak sibling” in comparison to other, more rigorous, approaches (Yin, 2009 , p. xiii). Case study is not an inherently comparative approach to research. The objective is not statistical research, and the aim is not to produce outcomes that are generalizable to all populations (Thomas, 2011 ). Comparisons between case study and statistical research do little to advance this qualitative approach, and fail to recognize its inherent value, which can be better understood from the interpretive or social constructionist viewpoint of other authors (Merriam, 2009 ; Stake, 1995 ). Building on discussions relating to “fuzzy” (Bassey, 2001 ), or naturalistic generalizations (Stake, 1978 ), or transference of concepts and theories (Ayres, Kavanaugh, & Knafl, 2003 ; Morse et al., 2011 ) would have more relevance.

Case study research has been used as a catch-all design to justify or add weight to fundamental qualitative descriptive studies that do not fit with other traditional frameworks (Merriam, 2009 ). A case study has been a “convenient label for our research—when we ‘can't think of anything ‘better”—in an attempt to give it [qualitative methodology] some added respectability” (Tight, 2010 , p. 337). Qualitative case study research is a pliable approach (Merriam, 2009 ; Meyer, 2001 ; Stake, 1995 ), and has been likened to a “curious methodological limbo” (Gerring, 2004 , p. 341) or “paradigmatic bridge” (Luck et al., 2006 , p. 104), that is on the borderline between postpositivist and constructionist interpretations. This has resulted in inconsistency in application, which indicates that flexibility comes with limitations (Meyer, 2001 ), and the open nature of case study research might be off-putting to novice researchers (Thomas, 2011 ). The development of a well-(in)formed theoretical framework to guide a case study should improve consistency, rigour, and trust in studies published in qualitative research journals (Meyer, 2001 ).

Assessment of rigour

The purpose of this study was to analyse the methodological descriptions of case studies published in qualitative methods journals. To do this we needed to develop a suitable framework, which used existing, established criteria for appraising qualitative case study research rigour (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ). A number of qualitative authors have developed concepts and criteria that are used to determine whether a study is rigorous (Denzin & Lincoln, 2011b ; Lincoln, 1995 ; Sandelowski & Barroso, 2002 ). The criteria proposed by Stake ( 1995 ) provide a framework for readers and reviewers to make judgements regarding case study quality, and identify key characteristics essential for good methodological rigour. Although each of the factors listed in Stake's criteria could enhance the quality of a qualitative research report, in Table I we present an adapted criteria used in this study, which integrates more recent work by Merriam ( 2009 ) and Creswell ( 2013b ). Stake's ( 1995 ) original criteria were separated into two categories. The first list of general criteria is “relevant for all qualitative research.” The second list, “high relevance to qualitative case study research,” was the criteria that we decided had higher relevance to case study research. This second list was the main criteria used to assess the methodological descriptions of the case studies reviewed. The complete table has been preserved so that the reader can determine how the original criteria were adapted.

Framework for assessing quality in qualitative case study research.

Adapted from Stake ( 1995 , p. 131).

Study design

The critical review method described by Grant and Booth ( 2009 ) was used, which is appropriate for the assessment of research quality, and is used for literature analysis to inform research and practice. This type of review goes beyond the mapping and description of scoping or rapid reviews, to include “analysis and conceptual innovation” (Grant & Booth, 2009 , p. 93). A critical review is used to develop existing, or produce new, hypotheses or models. This is different to systematic reviews that answer clinical questions. It is used to evaluate existing research and competing ideas, to provide a “launch pad” for conceptual development and “subsequent testing” (Grant & Booth, 2009 , p. 93).

Qualitative methods journals were located by a search of the 2011 ISI Journal Citation Reports in Social Science, via the database Web of Knowledge (see m.webofknowledge.com). No “qualitative research methods” category existed in the citation reports; therefore, a search of all categories was performed using the term “qualitative.” In Table II , we present the qualitative methods journals located, ranked by impact factor. The highest ranked journals were selected for searching. We acknowledge that the impact factor ranking system might not be the best measure of journal quality (Cheek, Garnham, & Quan, 2006 ); however, this was the most appropriate and accessible method available.

International Journal of Qualitative Studies on Health and Well-being.

Search strategy

In March 2013, searches of the journals, Qualitative Health Research , Qualitative Research , and Qualitative Inquiry were completed to retrieve studies with “case study” in the abstract field. The search was limited to the past 5 years (1 January 2008 to 1 March 2013). The objective was to locate published qualitative case studies suitable for assessment using the adapted criterion. Viewpoints, commentaries, and other article types were excluded from review. Title and abstracts of the 45 retrieved articles were read by the first author, who identified 34 empirical case studies for review. All authors reviewed the 34 studies to confirm selection and categorization. In Table III , we present the 34 case studies grouped by journal, and categorized by research topic, including health sciences, social sciences and anthropology, and methods research. There was a discrepancy in categorization of one article on pedagogy and a new teaching method published in Qualitative Inquiry (Jorrín-Abellán, Rubia-Avi, Anguita-Martínez, Gómez-Sánchez, & Martínez-Mones, 2008 ). Consensus was to allocate to the methods category.

Outcomes of search of qualitative methods journals.

In Table III , the number of studies located, and final numbers selected for review have been reported. Qualitative Health Research published the most empirical case studies ( n= 16). In the health category, there were 12 case studies of health conditions, health services, and health policy issues, all published in Qualitative Health Research . Seven case studies were categorized as social sciences and anthropology research, which combined case study with biography and ethnography methodologies. All three journals published case studies on methods research to illustrate a data collection or analysis technique, methodological procedure, or related issue.

The methodological descriptions of 34 case studies were critically reviewed using the adapted criteria. All articles reviewed contained a description of study methods; however, the length, amount of detail, and position of the description in the article varied. Few studies provided an accurate description and rationale for using a qualitative case study approach. In the 34 case studies reviewed, three described a theoretical framework informed by Stake ( 1995 ), two by Yin ( 2009 ), and three provided a mixed framework informed by various authors, which might have included both Yin and Stake. Few studies described their case study design, or included a rationale that explained why they excluded or added further procedures, and whether this was to enhance the study design, or to better suit the research question. In 26 of the studies no reference was provided to principal case study authors. From reviewing the description of methods, few authors provided a description or justification of case study methodology that demonstrated how their study was informed by the methodological literature that exists on this approach.

The methodological descriptions of each study were reviewed using the adapted criteria, and the following issues were identified: case study methodology or method; case of something particular and case selection; contextually bound case study; researcher and case interactions and triangulation; and, study design inconsistent with methodology. An outline of how the issues were developed from the critical review is provided, followed by a discussion of how these relate to the current methodological literature.

Case study methodology or method

A third of the case studies reviewed appeared to use a case report method, not case study methodology as described by principal authors (Creswell, 2013b ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). Case studies were identified as a case report because of missing methodological detail and by review of the study aims and purpose. These reports presented data for small samples of no more than three people, places or phenomenon. Four studies, or “case reports” were single cases selected retrospectively from larger studies (Bronken, Kirkevold, Martinsen, & Kvigne, 2012 ; Coltart & Henwood, 2012 ; Hooghe, Neimeyer, & Rober, 2012 ; Roscigno et al., 2012 ). Case reports were not a case of something, instead were a case demonstration or an example presented in a report. These reports presented outcomes, and reported on how the case could be generalized. Descriptions focussed on the phenomena, rather than the case itself, and did not appear to study the case in its entirety.

Case reports had minimal in-text references to case study methodology, and were informed by other qualitative traditions or secondary sources (Adamson & Holloway, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nagar-Ron & Motzafi-Haller, 2011 ). This does not suggest that case study methodology cannot be multimethod, however, methodology should be consistent in design, be clearly described (Meyer, 2001 ; Stake, 1995 ), and maintain focus on the case (Creswell, 2013b ).

To demonstrate how case reports were identified, three examples are provided. The first, Yeh ( 2013 ) described their study as, “the examination of the emergence of vegetarianism in Victorian England serves as a case study to reveal the relationships between boundaries and entities” (p. 306). The findings were a historical case report, which resulted from an ethnographic study of vegetarianism. Cunsolo Willox, Harper, Edge, ‘My Word’: Storytelling and Digital Media Lab, and Rigolet Inuit Community Government (2013) used “a case study that illustrates the usage of digital storytelling within an Inuit community” (p. 130). This case study reported how digital storytelling can be used with indigenous communities as a participatory method to illuminate the benefits of this method for other studies. This “case study was conducted in the Inuit community” but did not include the Inuit community in case analysis (Cunsolo Willox et al., 2013 , p. 130). Bronken et al. ( 2012 ) provided a single case report to demonstrate issues observed in a larger clinical study of aphasia and stroke, without adequate case description or analysis.

Case study of something particular and case selection

Case selection is a precursor to case analysis, which needs to be presented as a convincing argument (Merriam, 2009 ). Descriptions of the case were often not adequate to ascertain why the case was selected, or whether it was a particular exemplar or outlier (Thomas, 2011 ). In a number of case studies in the health and social science categories, it was not explicit whether the case was of something particular, or peculiar to their discipline or field (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson, Botelho, Welch, Joseph, & Tennstedt, 2012 ; Mawn et al., 2010 ; Snyder-Young, 2011 ). There were exceptions in the methods category ( Table III ), where cases were selected by researchers to report on a new or innovative method. The cases emerged through heuristic study, and were reported to be particular, relative to the existing methods literature (Ajodhia-Andrews & Berman, 2009 ; Buckley & Waring, 2013 ; Cunsolo Willox et al., 2013 ; De Haene, Grietens, & Verschueren, 2010 ; Gratton & O'Donnell, 2011 ; Sumsion, 2013 ; Wimpenny & Savin-Baden, 2012 ).

Case selection processes were sometimes insufficient to understand why the case was selected from the global population of cases, or what study of this case would contribute to knowledge as compared with other possible cases (Adamson & Holloway, 2012 ; Bronken et al., 2012 ; Colón-Emeric et al., 2010 ; Jackson et al., 2012 ; Mawn et al., 2010 ). In two studies, local cases were selected (Barone, 2010 ; Fourie & Theron, 2012 ) because the researcher was familiar with and had access to the case. Possible limitations of a convenience sample were not acknowledged. Purposeful sampling was used to recruit participants within the case of one study, but not of the case itself (Gallagher et al., 2013 ). Random sampling was completed for case selection in two studies (Colón-Emeric et al., 2010 ; Jackson et al., 2012 ), which has limited meaning in interpretive qualitative research.

To demonstrate how researchers provided a good justification for the selection of case study approaches, four examples are provided. The first, cases of residential care homes, were selected because of reported occurrences of mistreatment, which included residents being locked in rooms at night (Rytterström, Unosson, & Arman, 2013 ). Roscigno et al. ( 2012 ) selected cases of parents who were admitted for early hospitalization in neonatal intensive care with a threatened preterm delivery before 26 weeks. Hooghe et al. ( 2012 ) used random sampling to select 20 couples that had experienced the death of a child; however, the case study was of one couple and a particular metaphor described only by them. The final example, Coltart and Henwood ( 2012 ), provided a detailed account of how they selected two cases from a sample of 46 fathers based on personal characteristics and beliefs. They described how the analysis of the two cases would contribute to their larger study on first time fathers and parenting.

Contextually bound case study

The limits or boundaries of the case are a defining factor of case study methodology (Merriam, 2009 ; Ragin & Becker, 1992 ; Stake, 1995 ; Yin, 2009 ). Adequate contextual description is required to understand the setting or context in which the case is revealed. In the health category, case studies were used to illustrate a clinical phenomenon or issue such as compliance and health behaviour (Colón-Emeric et al., 2010 ; D'Enbeau, Buzzanell, & Duckworth, 2010 ; Gallagher et al., 2013 ; Hooghe et al., 2012 ; Jackson et al., 2012 ; Roscigno et al., 2012 ). In these case studies, contextual boundaries, such as physical and institutional descriptions, were not sufficient to understand the case as a holistic system, for example, the general practitioner (GP) clinic in Gallagher et al. ( 2013 ), or the nursing home in Colón-Emeric et al. ( 2010 ). Similarly, in the social science and methods categories, attention was paid to some components of the case context, but not others, missing important information required to understand the case as a holistic system (Alexander, Moreira, & Kumar, 2012 ; Buzzanell & D'Enbeau, 2009 ; Nairn & Panelli, 2009 ; Wimpenny & Savin-Baden, 2012 ).

In two studies, vicarious experience or vignettes (Nairn & Panelli, 2009 ) and images (Jorrín-Abellán et al., 2008 ) were effective to support description of context, and might have been a useful addition for other case studies. Missing contextual boundaries suggests that the case might not be adequately defined. Additional information, such as the physical, institutional, political, and community context, would improve understanding of the case (Stake, 1998 ). In Boxes 1 and 2 , we present brief synopses of two studies that were reviewed, which demonstrated a well bounded case. In Box 1 , Ledderer ( 2011 ) used a qualitative case study design informed by Stake's tradition. In Box 2 , Gillard, Witt, and Watts ( 2011 ) were informed by Yin's tradition. By providing a brief outline of the case studies in Boxes 1 and 2 , we demonstrate how effective case boundaries can be constructed and reported, which may be of particular interest to prospective case study researchers.

Article synopsis of case study research using Stake's tradition

Ledderer ( 2011 ) used a qualitative case study research design, informed by modern ethnography. The study is bounded to 10 general practice clinics in Denmark, who had received federal funding to implement preventative care services based on a Motivational Interviewing intervention. The researcher question focussed on “why is it so difficult to create change in medical practice?” (Ledderer, 2011 , p. 27). The study context was adequately described, providing detail on the general practitioner (GP) clinics and relevant political and economic influences. Methodological decisions are described in first person narrative, providing insight on researcher perspectives and interaction with the case. Forty-four interviews were conducted, which focussed on how GPs conducted consultations, and the form, nature and content, rather than asking their opinion or experience (Ledderer, 2011 , p. 30). The duration and intensity of researcher immersion in the case enhanced depth of description and trustworthiness of study findings. Analysis was consistent with Stake's tradition, and the researcher provided examples of inquiry techniques used to challenge assumptions about emerging themes. Several other seminal qualitative works were cited. The themes and typology constructed are rich in narrative data and storytelling by clinic staff, demonstrating individual clinic experiences as well as shared meanings and understandings about changing from a biomedical to psychological approach to preventative health intervention. Conclusions make note of social and cultural meanings and lessons learned, which might not have been uncovered using a different methodology.

Article synopsis of case study research using Yin's tradition

Gillard et al. ( 2011 ) study of camps for adolescents living with HIV/AIDs provided a good example of Yin's interpretive case study approach. The context of the case is bounded by the three summer camps of which the researchers had prior professional involvement. A case study protocol was developed that used multiple methods to gather information at three data collection points coinciding with three youth camps (Teen Forum, Discover Camp, and Camp Strong). Gillard and colleagues followed Yin's ( 2009 ) principles, using a consistent data protocol that enhanced cross-case analysis. Data described the young people, the camp physical environment, camp schedule, objectives and outcomes, and the staff of three youth camps. The findings provided a detailed description of the context, with less detail of individual participants, including insight into researcher's interpretations and methodological decisions throughout the data collection and analysis process. Findings provided the reader with a sense of “being there,” and are discovered through constant comparison of the case with the research issues; the case is the unit of analysis. There is evidence of researcher immersion in the case, and Gillard reports spending significant time in the field in a naturalistic and integrated youth mentor role.

This case study is not intended to have a significant impact on broader health policy, although does have implications for health professionals working with adolescents. Study conclusions will inform future camps for young people with chronic disease, and practitioners are able to compare similarities between this case and their own practice (for knowledge translation). No limitations of this article were reported. Limitations related to publication of this case study were that it was 20 pages long and used three tables to provide sufficient description of the camp and program components, and relationships with the research issue.

Researcher and case interactions and triangulation

Researcher and case interactions and transactions are a defining feature of case study methodology (Stake, 1995 ). Narrative stories, vignettes, and thick description are used to provoke vicarious experience and a sense of being there with the researcher in their interaction with the case. Few of the case studies reviewed provided details of the researcher's relationship with the case, researcher–case interactions, and how these influenced the development of the case study (Buzzanell & D'Enbeau, 2009 ; D'Enbeau et al., 2010 ; Gallagher et al., 2013 ; Gillard et al., 2011 ; Ledderer, 2011 ; Nagar-Ron & Motzafi-Haller, 2011 ). The role and position of the researcher needed to be self-examined and understood by readers, to understand how this influenced interactions with participants, and to determine what triangulation is needed (Merriam, 2009 ; Stake, 1995 ).

Gillard et al. ( 2011 ) provided a good example of triangulation, comparing data sources in a table (p. 1513). Triangulation of sources was used to reveal as much depth as possible in the study by Nagar-Ron and Motzafi-Haller ( 2011 ), while also enhancing confirmation validity. There were several case studies that would have benefited from improved range and use of data sources, and descriptions of researcher–case interactions (Ajodhia-Andrews & Berman, 2009 ; Bronken et al., 2012 ; Fincham, Scourfield, & Langer, 2008 ; Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Snyder-Young, 2011 ; Yeh, 2013 ).

Study design inconsistent with methodology

Good, rigorous case studies require a strong methodological justification (Meyer, 2001 ) and a logical and coherent argument that defines paradigm, methodological position, and selection of study methods (Denzin & Lincoln, 2011b ). Methodological justification was insufficient in several of the studies reviewed (Barone, 2010 ; Bronken et al., 2012 ; Hooghe et al., 2012 ; Mawn et al., 2010 ; Roscigno et al., 2012 ; Yeh, 2013 ). This was judged by the absence, or inadequate or inconsistent reference to case study methodology in-text.

In six studies, the methodological justification provided did not relate to case study. There were common issues identified. Secondary sources were used as primary methodological references indicating that study design might not have been theoretically sound (Colón-Emeric et al., 2010 ; Coltart & Henwood, 2012 ; Roscigno et al., 2012 ; Snyder-Young, 2011 ). Authors and sources cited in methodological descriptions were inconsistent with the actual study design and practices used (Fourie & Theron, 2012 ; Hooghe et al., 2012 ; Jorrín-Abellán et al., 2008 ; Mawn et al., 2010 ; Rytterström et al., 2013 ; Wimpenny & Savin-Baden, 2012 ). This occurred when researchers cited Stake or Yin, or both (Mawn et al., 2010 ; Rytterström et al., 2013 ), although did not follow their paradigmatic or methodological approach. In 26 studies there were no citations for a case study methodological approach.

The findings of this study have highlighted a number of issues for researchers. A considerable number of case studies reviewed were missing key elements that define qualitative case study methodology and the tradition cited. A significant number of studies did not provide a clear methodological description or justification relevant to case study. Case studies in health and social sciences did not provide sufficient information for the reader to understand case selection, and why this case was chosen above others. The context of the cases were not described in adequate detail to understand all relevant elements of the case context, which indicated that cases may have not been contextually bounded. There were inconsistencies between reported methodology, study design, and paradigmatic approach in case studies reviewed, which made it difficult to understand the study methodology and theoretical foundations. These issues have implications for methodological integrity and honesty when reporting study design, which are values of the qualitative research tradition and are ethical requirements (Wager & Kleinert, 2010a ). Poorly described methodological descriptions may lead the reader to misinterpret or discredit study findings, which limits the impact of the study, and, as a collective, hinders advancements in the broader qualitative research field.

The issues highlighted in our review build on current debates in the case study literature, and queries about the value of this methodology. Case study research can be situated within different paradigms or designed with an array of methods. In order to maintain the creativity and flexibility that is valued in this methodology, clearer descriptions of paradigm and theoretical position and methods should be provided so that study findings are not undervalued or discredited. Case study research is an interdisciplinary practice, which means that clear methodological descriptions might be more important for this approach than other methodologies that are predominantly driven by fewer disciplines (Creswell, 2013b ).

Authors frequently omit elements of methodologies and include others to strengthen study design, and we do not propose a rigid or purist ideology in this paper. On the contrary, we encourage new ideas about using case study, together with adequate reporting, which will advance the value and practice of case study. The implications of unclear methodological descriptions in the studies reviewed were that study design appeared to be inconsistent with reported methodology, and key elements required for making judgements of rigour were missing. It was not clear whether the deviations from methodological tradition were made by researchers to strengthen the study design, or because of misinterpretations. Morse ( 2011 ) recommended that innovations and deviations from practice are best made by experienced researchers, and that a novice might be unaware of the issues involved with making these changes. To perpetuate the tradition of case study research, applications in the published literature should have consistencies with traditional methodological constructions, and deviations should be described with a rationale that is inherent in study conduct and findings. Providing methodological descriptions that demonstrate a strong theoretical foundation and coherent study design will add credibility to the study, while ensuring the intrinsic meaning of case study is maintained.

The value of this review is that it contributes to discussion of whether case study is a methodology or method. We propose possible reasons why researchers might make this misinterpretation. Researchers may interchange the terms methods and methodology, and conduct research without adequate attention to epistemology and historical tradition (Carter & Little, 2007 ; Sandelowski, 2010 ). If the rich meaning that naming a qualitative methodology brings to the study is not recognized, a case study might appear to be inconsistent with the traditional approaches described by principal authors (Creswell, 2013a ; Merriam, 2009 ; Stake, 1995 ; Yin, 2009 ). If case studies are not methodologically and theoretically situated, then they might appear to be a case report.

Case reports are promoted by university and medical journals as a method of reporting on medical or scientific cases; guidelines for case reports are publicly available on websites ( http://www.hopkinsmedicine.org/institutional_review_board/guidelines_policies/guidelines/case_report.html ). The various case report guidelines provide a general criteria for case reports, which describes that this form of report does not meet the criteria of research, is used for retrospective analysis of up to three clinical cases, and is primarily illustrative and for educational purposes. Case reports can be published in academic journals, but do not require approval from a human research ethics committee. Traditionally, case reports describe a single case, to explain how and what occurred in a selected setting, for example, to illustrate a new phenomenon that has emerged from a larger study. A case report is not necessarily particular or the study of a case in its entirety, and the larger study would usually be guided by a different research methodology.

This description of a case report is similar to what was provided in some studies reviewed. This form of report lacks methodological grounding and qualities of research rigour. The case report has publication value in demonstrating an example and for dissemination of knowledge (Flanagan, 1999 ). However, case reports have different meaning and purpose to case study, which needs to be distinguished. Findings of our review suggest that the medical understanding of a case report has been confused with qualitative case study approaches.

In this review, a number of case studies did not have methodological descriptions that included key characteristics of case study listed in the adapted criteria, and several issues have been discussed. There have been calls for improvements in publication quality of qualitative research (Morse, 2011 ), and for improvements in peer review of submitted manuscripts (Carter & Little, 2007 ; Jasper, Vaismoradi, Bondas, & Turunen, 2013 ). The challenging nature of editor and reviewers responsibilities are acknowledged in the literature (Hames, 2013 ; Wager & Kleinert, 2010b ); however, review of case study methodology should be prioritized because of disputes on methodological value.

Authors using case study approaches are recommended to describe their theoretical framework and methods clearly, and to seek and follow specialist methodological advice when needed (Wager & Kleinert, 2010a ). Adequate page space for case study description would contribute to better publications (Gillard et al., 2011 ). Capitalizing on the ability to publish complementary resources should be considered.

Limitations of the review

There is a level of subjectivity involved in this type of review and this should be considered when interpreting study findings. Qualitative methods journals were selected because the aims and scope of these journals are to publish studies that contribute to methodological discussion and development of qualitative research. Generalist health and social science journals were excluded that might have contained good quality case studies. Journals in business or education were also excluded, although a review of case studies in international business journals has been published elsewhere (Piekkari et al., 2009 ).

The criteria used to assess the quality of the case studies were a set of qualitative indicators. A numerical or ranking system might have resulted in different results. Stake's ( 1995 ) criteria have been referenced elsewhere, and was deemed the best available (Creswell, 2013b ; Crowe et al., 2011 ). Not all qualitative studies are reported in a consistent way and some authors choose to report findings in a narrative form in comparison to a typical biomedical report style (Sandelowski & Barroso, 2002 ), if misinterpretations were made this may have affected the review.

Case study research is an increasingly popular approach among qualitative researchers, which provides methodological flexibility through the incorporation of different paradigmatic positions, study designs, and methods. However, whereas flexibility can be an advantage, a myriad of different interpretations has resulted in critics questioning the use of case study as a methodology. Using an adaptation of established criteria, we aimed to identify and assess the methodological descriptions of case studies in high impact, qualitative methods journals. Few articles were identified that applied qualitative case study approaches as described by experts in case study design. There were inconsistencies in methodology and study design, which indicated that researchers were confused whether case study was a methodology or a method. Commonly, there appeared to be confusion between case studies and case reports. Without clear understanding and application of the principles and key elements of case study methodology, there is a risk that the flexibility of the approach will result in haphazard reporting, and will limit its global application as a valuable, theoretically supported methodology that can be rigorously applied across disciplines and fields.

Conflict of interest and funding

The authors have not received any funding or benefits from industry or elsewhere to conduct this study.

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews).

The case study research method originated in clinical medicine (the case history, i.e., the patient’s personal history). In psychology, case studies are often confined to the study of a particular individual.

The information is mainly biographical and relates to events in the individual’s past (i.e., retrospective), as well as to significant events that are currently occurring in his or her everyday life.

The case study is not a research method, but researchers select methods of data collection and analysis that will generate material suitable for case studies.

Freud (1909a, 1909b) conducted very detailed investigations into the private lives of his patients in an attempt to both understand and help them overcome their illnesses.

This makes it clear that the case study is a method that should only be used by a psychologist, therapist, or psychiatrist, i.e., someone with a professional qualification.

There is an ethical issue of competence. Only someone qualified to diagnose and treat a person can conduct a formal case study relating to atypical (i.e., abnormal) behavior or atypical development.

 Famous Case Studies

• Anna O – One of the most famous case studies, documenting psychoanalyst Josef Breuer’s treatment of “Anna O” (real name Bertha Pappenheim) for hysteria in the late 1800s using early psychoanalytic theory.
• Little Hans – A child psychoanalysis case study published by Sigmund Freud in 1909 analyzing his five-year-old patient Herbert Graf’s house phobia as related to the Oedipus complex.
• Bruce/Brenda – Gender identity case of the boy (Bruce) whose botched circumcision led psychologist John Money to advise gender reassignment and raise him as a girl (Brenda) in the 1960s.
• Genie Wiley – Linguistics/psychological development case of the victim of extreme isolation abuse who was studied in 1970s California for effects of early language deprivation on acquiring speech later in life.
• Phineas Gage – One of the most famous neuropsychology case studies analyzes personality changes in railroad worker Phineas Gage after an 1848 brain injury involving a tamping iron piercing his skull.

Clinical Case Studies

• Studying the effectiveness of psychotherapy approaches with an individual patient
• Assessing and treating mental illnesses like depression, anxiety disorders, PTSD
• Neuropsychological cases investigating brain injuries or disorders

Child Psychology Case Studies

• Studying psychological development from birth through adolescence
• Cases of learning disabilities, autism spectrum disorders, ADHD
• Effects of trauma, abuse, deprivation on development

Types of Case Studies

• Explanatory case studies : Used to explore causation in order to find underlying principles. Helpful for doing qualitative analysis to explain presumed causal links.
• Exploratory case studies : Used to explore situations where an intervention being evaluated has no clear set of outcomes. It helps define questions and hypotheses for future research.
• Descriptive case studies : Describe an intervention or phenomenon and the real-life context in which it occurred. It is helpful for illustrating certain topics within an evaluation.
• Multiple-case studies : Used to explore differences between cases and replicate findings across cases. Helpful for comparing and contrasting specific cases.
• Intrinsic : Used to gain a better understanding of a particular case. Helpful for capturing the complexity of a single case.
• Collective : Used to explore a general phenomenon using multiple case studies. Helpful for jointly studying a group of cases in order to inquire into the phenomenon.

Where Do You Find Data for a Case Study?

There are several places to find data for a case study. The key is to gather data from multiple sources to get a complete picture of the case and corroborate facts or findings through triangulation of evidence. Most of this information is likely qualitative (i.e., verbal description rather than measurement), but the psychologist might also collect numerical data.

1. Primary sources

• Interviews – Interviewing key people related to the case to get their perspectives and insights. The interview is an extremely effective procedure for obtaining information about an individual, and it may be used to collect comments from the person’s friends, parents, employer, workmates, and others who have a good knowledge of the person, as well as to obtain facts from the person him or herself.
• Observations – Observing behaviors, interactions, processes, etc., related to the case as they unfold in real-time.
• Documents & Records – Reviewing private documents, diaries, public records, correspondence, meeting minutes, etc., relevant to the case.

2. Secondary sources

• News/Media – News coverage of events related to the case study.
• Academic articles – Journal articles, dissertations etc. that discuss the case.
• Government reports – Official data and records related to the case context.
• Books/films – Books, documentaries or films discussing the case.

3. Archival records

Searching historical archives, museum collections and databases to find relevant documents, visual/audio records related to the case history and context.

Public archives like newspapers, organizational records, photographic collections could all include potentially relevant pieces of information to shed light on attitudes, cultural perspectives, common practices and historical contexts related to psychology.

4. Organizational records

Organizational records offer the advantage of often having large datasets collected over time that can reveal or confirm psychological insights.

Of course, privacy and ethical concerns regarding confidential data must be navigated carefully.

However, with proper protocols, organizational records can provide invaluable context and empirical depth to qualitative case studies exploring the intersection of psychology and organizations.

• Organizational/industrial psychology research : Organizational records like employee surveys, turnover/retention data, policies, incident reports etc. may provide insight into topics like job satisfaction, workplace culture and dynamics, leadership issues, employee behaviors etc.
• Clinical psychology : Therapists/hospitals may grant access to anonymized medical records to study aspects like assessments, diagnoses, treatment plans etc. This could shed light on clinical practices.
• School psychology : Studies could utilize anonymized student records like test scores, grades, disciplinary issues, and counseling referrals to study child development, learning barriers, effectiveness of support programs, and more.

How do I Write a Case Study in Psychology?

Follow specified case study guidelines provided by a journal or your psychology tutor. General components of clinical case studies include: background, symptoms, assessments, diagnosis, treatment, and outcomes. Interpreting the information means the researcher decides what to include or leave out. A good case study should always clarify which information is the factual description and which is an inference or the researcher’s opinion.

1. Introduction

• Provide background on the case context and why it is of interest, presenting background information like demographics, relevant history, and presenting problem.
• Compare briefly to similar published cases if applicable. Clearly state the focus/importance of the case.

2. Case Presentation

• Describe the presenting problem in detail, including symptoms, duration,and impact on daily life.
• Include client demographics like age and gender, information about social relationships, and mental health history.
• Describe all physical, emotional, and/or sensory symptoms reported by the client.
• Use patient quotes to describe the initial complaint verbatim. Follow with full-sentence summaries of relevant history details gathered, including key components that led to a working diagnosis.
• Summarize clinical exam results, namely orthopedic/neurological tests, imaging, lab tests, etc. Note actual results rather than subjective conclusions. Provide images if clearly reproducible/anonymized.
• Clearly state the working diagnosis or clinical impression before transitioning to management.

3. Management and Outcome

• Indicate the total duration of care and number of treatments given over what timeframe. Use specific names/descriptions for any therapies/interventions applied.
• Present the results of the intervention,including any quantitative or qualitative data collected.
• For outcomes, utilize visual analog scales for pain, medication usage logs, etc., if possible. Include patient self-reports of improvement/worsening of symptoms. Note the reason for discharge/end of care.

4. Discussion

• Analyze the case, exploring contributing factors, limitations of the study, and connections to existing research.
• Analyze the effectiveness of the intervention,considering factors like participant adherence, limitations of the study, and potential alternative explanations for the results.
• Identify any questions raised in the case analysis and relate insights to established theories and current research if applicable. Avoid definitive claims about physiological explanations.
• Offer clinical implications, and suggest future research directions.

5. Additional Items

• Thank specific assistants for writing support only. No patient acknowledgments.
• References should directly support any key claims or quotes included.
• Use tables/figures/images only if substantially informative. Include permissions and legends/explanatory notes.
• Provides detailed (rich qualitative) information.
• Provides insight for further research.
• Permitting investigation of otherwise impractical (or unethical) situations.

Case studies allow a researcher to investigate a topic in far more detail than might be possible if they were trying to deal with a large number of research participants (nomothetic approach) with the aim of ‘averaging’.

Because of their in-depth, multi-sided approach, case studies often shed light on aspects of human thinking and behavior that would be unethical or impractical to study in other ways.

Research that only looks into the measurable aspects of human behavior is not likely to give us insights into the subjective dimension of experience, which is important to psychoanalytic and humanistic psychologists.

Case studies are often used in exploratory research. They can help us generate new ideas (that might be tested by other methods). They are an important way of illustrating theories and can help show how different aspects of a person’s life are related to each other.

The method is, therefore, important for psychologists who adopt a holistic point of view (i.e., humanistic psychologists ).

Limitations

• Lacking scientific rigor and providing little basis for generalization of results to the wider population.
• Researchers’ own subjective feelings may influence the case study (researcher bias).
• Difficult to replicate.
• Time-consuming and expensive.
• The volume of data, together with the time restrictions in place, impacted the depth of analysis that was possible within the available resources.

Because a case study deals with only one person/event/group, we can never be sure if the case study investigated is representative of the wider body of “similar” instances. This means the conclusions drawn from a particular case may not be transferable to other settings.

Because case studies are based on the analysis of qualitative (i.e., descriptive) data , a lot depends on the psychologist’s interpretation of the information she has acquired.

This means that there is a lot of scope for Anna O , and it could be that the subjective opinions of the psychologist intrude in the assessment of what the data means.

For example, Freud has been criticized for producing case studies in which the information was sometimes distorted to fit particular behavioral theories (e.g., Little Hans ).

This is also true of Money’s interpretation of the Bruce/Brenda case study (Diamond, 1997) when he ignored evidence that went against his theory.

Breuer, J., & Freud, S. (1895).  Studies on hysteria . Standard Edition 2: London.

Curtiss, S. (1981). Genie: The case of a modern wild child .

Diamond, M., & Sigmundson, K. (1997). Sex Reassignment at Birth: Long-term Review and Clinical Implications. Archives of Pediatrics & Adolescent Medicine , 151(3), 298-304

Freud, S. (1909a). Analysis of a phobia of a five year old boy. In The Pelican Freud Library (1977), Vol 8, Case Histories 1, pages 169-306

Freud, S. (1909b). Bemerkungen über einen Fall von Zwangsneurose (Der “Rattenmann”). Jb. psychoanal. psychopathol. Forsch ., I, p. 357-421; GW, VII, p. 379-463; Notes upon a case of obsessional neurosis, SE , 10: 151-318.

Harlow J. M. (1848). Passage of an iron rod through the head.  Boston Medical and Surgical Journal, 39 , 389–393.

Harlow, J. M. (1868).  Recovery from the Passage of an Iron Bar through the Head .  Publications of the Massachusetts Medical Society. 2  (3), 327-347.

Money, J., & Ehrhardt, A. A. (1972).  Man & Woman, Boy & Girl : The Differentiation and Dimorphism of Gender Identity from Conception to Maturity. Baltimore, Maryland: Johns Hopkins University Press.

Money, J., & Tucker, P. (1975). Sexual signatures: On being a man or a woman.

Further Information

• Case Study Approach
• Case Study Method
• Enhancing the Quality of Case Studies in Health Services Research
• “We do things together” A case study of “couplehood” in dementia
• Using mixed methods for evaluating an integrative approach to cancer care: a case study

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Writing A Case Study

Types Of Case Study

Understand the Types of Case Study Here

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A Complete Case Study Writing Guide With Examples

Simple Case Study Format for Students to Follow

Brilliant Case Study Examples and Templates For Your Help

Case studies are effective research methods that focus on one specific case over time. This gives a detailed view that's great for learning.

Writing a case study is a very useful form of study in the educational process. With real-life examples, students can learn more effectively. 

A case study also has different types and forms. As a rule of thumb, all of them require a detailed and convincing answer based on a thorough analysis.

In this blog, we are going to discuss the different types of case study research methods in detail.

So, let’s dive right in!

• 1. Understanding Case Studies
• 2. What are the Types of Case Study?
• 3. Types of Subjects of Case Study 
• 4. Benefits of Case Study for Students

Understanding Case Studies

Case studies are a type of research methodology. Case study research designs examine subjects, projects, or organizations to provide an analysis based on the evidence.

It allows you to get insight into what causes any subject’s decisions and actions. This makes case studies a great way for students to develop their research skills.

A case study focuses on a single project for an extended period, which allows students to explore the topic in depth.

What are the Types of Case Study?

Multiple case studies are used for different purposes. The main purpose of case studies is to analyze problems within the boundaries of a specific organization, environment, or situation. 

Many aspects of a case study such as data collection and analysis, qualitative research questions, etc. are dependent on the researcher and what the study is looking to address. 

Case studies can be divided into the following categories:

Illustrative Case Study

Exploratory case study, cumulative case study, critical instance case study, descriptive case study, intrinsic case study, instrumental case study.

Let’s take a look at the detailed description of each type of case study with examples. 

An illustrative case study is used to examine a familiar case to help others understand it. It is one of the main types of case studies in research methodology and is primarily descriptive. 

In this type of case study, usually, one or two instances are used to explain what a situation is like. 

Here is an example to help you understand it better:

Illustrative Case Study Example

An exploratory case study is usually done before a larger-scale research. These types of case studies are very popular in the social sciences like political science and primarily focus on real-life contexts and situations.

This method is useful in identifying research questions and methods for a large and complex study. 

Let’s take a look at this example to help you have a better understanding:

Exploratory Case Study Example

A cumulative case study is one of the main types of case studies in qualitative research. It is used to collect information from different sources at different times.

This case study aims to summarize the past studies without spending additional cost and time on new investigations. 

Let’s take a look at the example below:

Cumulative Case Study Example

Critical instances case studies are used to determine the cause and consequence of an event. 

The main reason for this type of case study is to investigate one or more sources with unique interests and sometimes with no interest in general. 

Take a look at this example below:

Critical Instance Case Study Example

When you have a hypothesis, you can design a descriptive study. It aims to find connections between the subject being studied and a theory.

After making these connections, the study can be concluded. The results of the descriptive case study will usually suggest how to develop a theory further.

This example can help you understand the concept better:

Descriptive Case Study Example

Intrinsic studies are more commonly used in psychology, healthcare, or social work. So, if you were looking for types of case studies in sociology, or types of case studies in social research, this is it.

The focus of intrinsic studies is on the individual. The aim of such studies is not only to understand the subject better but also their history and how they interact with their environment.

Here is an example to help you understand;

Intrinsic Case Study Example

This type of case study is mostly used in qualitative research. In an instrumental case study, the specific case is selected to provide information about the research question.

It offers a lens through which researchers can explore complex concepts, theories, or generalizations.

Take a look at the example below to have a better understanding of the concepts:

Instrumental Case Study Example

Review some case study examples to help you understand how a specific case study is conducted.

Types of Subjects of Case Study 

In general, there are 5 types of subjects that case studies address. Every case study fits into the following subject categories. 

• Person: This type of study focuses on one subject or individual and can use several research methods to determine the outcome. 
• Group: This type of study takes into account a group of individuals. This could be a group of friends, coworkers, or family. 
• Location: The main focus of this type of study is the place. It also takes into account how and why people use the place. 
• Organization: This study focuses on an organization or company. This could also include the company employees or people who work in an event at the organization. 
• Event: This type of study focuses on a specific event. It could be societal or cultural and examines how it affects the surroundings. 

Benefits of Case Study for Students

Here's a closer look at the multitude of benefits students can have with case studies:

Real-world Application

Case studies serve as a crucial link between theory and practice. By immersing themselves in real-world scenarios, students can apply theoretical knowledge to practical situations.

Critical Thinking Skills

Analyzing case studies demands critical thinking and informed decision-making. Students cultivate the ability to evaluate information, identify key factors, and develop well-reasoned solutions – essential skills in both academic and professional contexts.

Enhanced Problem-solving Abilities

Case studies often present complex problems that require creative and strategic solutions. Engaging with these challenges refines students' problem-solving skills, encouraging them to think innovatively and develop effective approaches.

Holistic Understanding

Going beyond theoretical concepts, case studies provide a holistic view of a subject. Students gain insights into the multifaceted aspects of a situation, helping them connect the dots and understand the broader context.

Exposure to Diverse Perspectives

Case studies often encompass a variety of industries, cultures, and situations. This exposure broadens students' perspectives, fostering a more comprehensive understanding of the world and the challenges faced by different entities.

So there you have it!

We have explored different types of case studies and their examples. Case studies act as the tools to understand and deal with the many challenges and opportunities around us.

Case studies are being used more and more in colleges and universities to help students understand how a hypothetical event can influence a person, group, or organization in real life. 

Not everyone can handle the case study writing assignment easily. It is even scary to think that your time and work could be wasted if you don't do the case study paper right. 

Our essay writing service online  is here to make your academic journey easier. 

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The Case Study as Research Method: A Practical Handbook

Qualitative Research in Accounting & Management

ISSN : 1176-6093

Article publication date: 21 June 2011

Scapens, R.W. (2011), "The Case Study as Research Method: A Practical Handbook", Qualitative Research in Accounting & Management , Vol. 8 No. 2, pp. 201-204. https://doi.org/10.1108/11766091111137582

Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited

This book aims to provide case‐study researchers with a step‐by‐step practical guide to “help them conduct the study with the required degree of rigour” (p. xi).

It seeks to “demonstrate that the case study is indeed a scientific method” (p. 104) and to show “the usefulness of the case method as one tool in the researcher's methodological arsenal” (p. 105). The individual chapters cover the various stages in conducting case‐study research, and each chapter sets out a number of practical steps which have to be taken by the researcher. The following are the eight stages/chapters and, in brackets, the number of steps in each stages:

Assessing appropriateness and usefulness (4).

Ensuring accuracy of results (21).

Preparation (6).

Selecting cases (4).

Collecting data (7).

Analyzing data (4).

Interpreting data (3).

Reporting results (4).

It is particularly noticeable that ensuring accuracy of results has by far the largest number of number of steps – 21 steps compared to seven or fewer steps in the other stages. This reflects Gagnon's concern to demonstrate the scientific rigour of case‐study research. In the forward, he explains that the book draws on his experience in conducting his own PhD research, which was closely supervised by three professors, one of whom was inclined towards quantitative research. Consequently, his research was underpinned by the principles and philosophy of quantitative research. This is clearly reflected in the approach taken in this book, which seeks to show that case‐study research is just as rigorous and scientific as quantitative research, and it can produce an objective and accurate representation of the observed reality.

There is no discussion of the methodological issues relating to the use of case‐study research methods. This is acknowledged in the forward, although Gagnon refers to them as philosophical or epistemological issues (p. xii), as he tends to use the terms methodology and method interchangeably – as is common in quantitative research. Although he starts (step 1.1) by trying to distance case and other qualitative research from the work of positivists, arguing that society is socially constructed, he nevertheless sees social reality as objective and independent of the researcher. So for Gagnon, the aim of case research is to accurately reflect that reality. At various points in the book the notion of interpretation is used – evidence is interpreted and the (objective) case findings have to be interpreted.

So although there is a distancing from positivist research (p. 1), the approach taken in this book retains an objective view of the social reality which is being researched; a view which is rather different to the subjective view of reality taken by many interpretive case researchers. This distinction between an objective and a subjective view of the social reality being researched – and especially its use in contrasting positivist and interpretive research – has its origins the taxonomy of Burrell and Morgan (1979) . Although there have been various developments in the so‐called “objective‐subjective debate”, and recently some discussion in relation to management accounting research ( Kakkuri‐Knuuttila et al. , 2008 ; Ahrens, 2008 ), this debate is not mentioned in the book. Nevertheless, it is clear that Gagnon is firmly in the objective camp. In a recent paper, Johnson et al. (2006, p. 138) provide a more contemporary classification of the different types of qualitative research. In their terms, the approach taken in this book could be described as neo‐empiricist – an approach which they characterise as “qualitative positivists”.

The approach taken in this handbook leaves case studies open to the criticisms that they are a small sample, and consequently difficult to generalise, and to arguments that case studies are most appropriate for exploratory research which can subsequently be generalised though quantitative research. Gagnon explains that this was the approach he used after completing his thesis (p. xi). The handbook only seems to recognise two types of case studies, namely exploratory and raw empirical case studies – the latter being used where “the researcher is interested in a subject without having formed any preconceived ideas about it” (p. 15) – which has echoes of Glaser and Strauss (1967) . However, limiting case studies to these two types ignores other potential types; in particular, explanatory case studies which are where interpretive case‐study research can make important contributions ( Ryan et al. , 2002 ).

This limited approach to case studies comes through in the practical steps which are recommended in the handbook, and especially in the discussion of reliability and validity. The suggested steps seem to be designed to keep very close to the notions of reliability and validity used in quantitative research. There is no mention of the recent discussion of “validity” in interpretive accounting research, which emphasises the importance of authenticity and credibility and their implications for writing up qualitative and case‐study research ( Lukka and Modell, 2010 ). Although the final stage of Gagnon's handbook makes some very general comments about reporting the results, it does not mention, for example, Baxter and Chua's (2008) paper in QRAM which discusses the importance of demonstrating authenticity, credibility and transferability in writing qualitative research.

Despite Gagnon's emphasis on traditional notions of reliability and validity the handbook provides some useful practical advice for all case‐study researchers. For example, case‐study research needs a very good research design; case‐study researchers must work hard to gain access to and acceptance in the research settings; a clear strategy is needed for data collection; the case researcher should create field notes (in a field notebook, or otherwise) to record all the thoughts, ideas, observations, etc. that would not otherwise be collected; and the vast amount of data that case‐study research can generate needs to be carefully managed. Furthermore, because of what Gagnon calls the “risk of mortality” (p. 54) (i.e. the risk that access to a research site may be lost – for instance, if the organisation goes bankrupt) it is crucial for some additional site(s) to be selected at the outset to ensure that the planned research can be completed. This is what I call “insurance cases” when talking to my own PhD students. Interestingly, Gagnon recognises the ethical issues involved in doing case studies – something which is not always mentioned by the more objectivist type of case‐study researchers. He emphasises that it is crucial to honour confidentiality agreements, to ensure data are stored securely and that commitments are met and promises kept.

There is an interesting discussion of the advantages and disadvantages of using computer methods in analysing data (in stage 6). However, the discussion of coding appears to be heavily influenced by grounded theory, and is clearly concerned with producing an accurate reflection of an objective reality. In addition, Gagnon's depiction of case analysis is overly focussed on content analysis – possibly because it is a quantitative type of technique. There is no reference to the other approaches available to qualitative researchers. For example, there is no mention of the various visualisation techniques set out in Miles and Huberman (1994) .

To summarise, Gagnon's book is particularly useful for case‐study researchers who see the reality they are researching as objective and researcher independent. However, this is a sub‐set of case‐study researchers. Although some of the practical guidance offered is relevant for other types of case‐study researchers, those who see multiple realities in the social actors and/or recognise the subjectivity of the research process might have difficulty with some of the steps in this handbook. Gagnon's aim to show that the case study is a scientific method, gives the handbook a focus on traditional (quantitatively inspired) notions rigour and validity, and a tendency to ignore (or at least marginalise) other types of case study research. For example, the focus on exploratory cases, which need to be supplemented by broad based quantitative research, overlooks the real potential of case study research which lies in explanatory cases. Furthermore, Gagnon is rather worried about participant research, as the researcher may play a role which is “not consistent with scientific method” (p. 42), and which may introduce researcher bias and thereby damage “the impartiality of the study” (p. 53). Leaving aside the philosophical question about whether any social science research, including quantitative research, can be impartial, this stance could severely limit the potential of case‐study research and it would rule out both the early work on the sociology of mass production and the recent calls for interventionist research. Clearly, there could be a problem where a researcher is trying to sell consulting services, but there is a long tradition of social researchers working within organisations that they are studying. Furthermore, if interpretive research is to be relevant for practice, researchers may have to work with organisations to introduce new ideas and new ways of analysing problems. Gagnon would seem to want to avoid all such research – as it would not be “impartial”.

Consequently, although there is some good practical advice for case study researchers in this handbook, some of the recommendations have to be treated cautiously, as it is a book which sees case‐study research in a very specific way. As mentioned earlier, in the Forward Gagnon explicitly recognises that the book does not take a position on the methodological debates surrounding the use of case studies as a research method, and he says that “The reader should therefore use and judge this handbook with these considerations in mind” (p. xii). This is very good advice – caveat emptor .

Ahrens , T. ( 2008 ), “ A comment on Marja‐Liisa Kakkuri‐Knuuttila ”, Accounting, Organizations and Society , Vol. 33 Nos 2/3 , pp. 291 ‐ 7 , Kari Lukka and Jaakko Kuorikoski.

Baxter , J. and Chua , W.F. ( 2008 ), “ The field researcher as author‐writer ”, Qualitative Research in Accounting & Management , Vol. 5 No. 2 , pp. 101 ‐ 21 .

Burrell , G. and Morgan , G. ( 1979 ), Sociological Paradigms and Organizational Analysis , Heinneman , London .

Glaser , B.G. and Strauss , A.L. ( 1967 ), The Discovery of Grounded Theory: Strategies for Qualitative Research , Aldine , New York, NY .

Johnson , P. , Buehring , A. , Cassell , C. and Symon , G. ( 2006 ), “ Evaluating qualitative management research: towards a contingent critieriology ”, International Journal of Management Reviews , Vol. 8 No. 3 , pp. 131 ‐ 56 .

Kakkuri‐Knuuttila , M.‐L. , Lukka , K. and Kuorikoski , J. ( 2008 ), “ Straddling between paradigms: a naturalistic philosophical case study on interpretive research in management accounting ”, Accounting, Organizations and Society , Vol. 33 Nos 2/3 , pp. 267 ‐ 91 .

Lukka , K. and Modell , S. ( 2010 ), “ Validation in interpretive management accounting research ”, Accounting, Organizations and Society , Vol. 35 , pp. 462 ‐ 77 .

Miles , M.B. and Huberman , A.M. ( 1994 ), Qualitative Data Analysis: A Source Book of New Methods , 2nd ed. , Sage , London .

Ryan , R.J. , Scapens , R.W. and Theobald , M. ( 2002 ), Research Methods and Methodology in Finance and Accounting , 2nd ed. , Thomson Learning , London .

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Case Studies

Case studies are a popular research method in business area. Case studies aim to analyze specific issues within the boundaries of a specific environment, situation or organization.

According to its design, case studies in business research can be divided into three categories: explanatory, descriptive and exploratory.

Explanatory case studies aim to answer ‘how’ or ’why’ questions with little control on behalf of researcher over occurrence of events. This type of case studies focus on phenomena within the contexts of real-life situations. Example: “An investigation into the reasons of the global financial and economic crisis of 2008 – 2010.”

Descriptive case studies aim to analyze the sequence of interpersonal events after a certain amount of time has passed. Studies in business research belonging to this category usually describe culture or sub-culture, and they attempt to discover the key phenomena. Example: “Impact of increasing levels of multiculturalism on marketing practices: A case study of McDonald’s Indonesia.”

Exploratory case studies aim to find answers to the questions of ‘what’ or ‘who’. Exploratory case study data collection method is often accompanied by additional data collection method(s) such as interviews, questionnaires, experiments etc. Example: “A study into differences of leadership practices between private and public sector organizations in Atlanta, USA.”

Advantages of case study method include data collection and analysis within the context of phenomenon, integration of qualitative and quantitative data in data analysis, and the ability to capture complexities of real-life situations so that the phenomenon can be studied in greater levels of depth. Case studies do have certain disadvantages that may include lack of rigor, challenges associated with data analysis and very little basis for generalizations of findings and conclusions.

John Dudovskiy

• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

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Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

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Case Study Method: Definition, Research Types, Advantages

by  Antony W

May 29, 2024

Case study method, or simply case study research methodology, is a technique that employs investigative inquiry to get data from specific individuals, organizations, groups, events, or demography.

Every participant in a case study method gets a similar engagement with hopes that he or she will provide information that helps with the discovery of novel insights on patterns, ideas, or hypothesis.

What’s The Origin of Case Study Method?

Frederic Le Play in France developed the case study method in sociology in 1829. Field workers would stay with families for a specific time and gather significant data such as income, expenditure, and interaction to understand the family in question.

The case study method was equally popular in clinical medicine, as it helped to generate, analyze, and support hypotheses .

Researchers adapted and integrated the technique to other sectors because of the benefits it uncovered in sociology, anthropology, and clinical medicine. The technique allows for the analysis of outcome through suggested decisions, procedures, and outcomes. 

What Research Types are Used in Case Study Method?

Your case study can be collective, descriptive, exploratory, explanatory, instrumental, or intrinsic.

These case study types require a comprehensive research methodology, which refers to procedures and techniques used to process and evaluate data to solve a problem and achieve a specific goal.

There are 2 types of research approaches for case studies: qualitative and quantitative research . These methods focus on different goals, data, and study.

Qualitative Research for Case Study

Qualitative research focuses on the collection and analysis of non-numerical data and it mostly applies to health sciences, anthropology, history, sociology, and education.

Examples of non-numerical data include audio, text, and video. You can collect qualitative data from focus groups, interviews, surveys, and observations.

Qualitative research for case studies enables you to generate new ideas and helpful insights with relevance and meaning.

Quantitative Research for Case Study

Quantitative research focuses on the collection and analysis of numbers, and it’s common in marketing, psychology, political science, economics, and sociology. Researchers use qualitative research to measure relationships and to test and track averages and patterns.

To do a comprehensive quantitative research:

• Come up with a theory.
• Develop a hypothesis.
• Create a research pattern.
• Operationalize a concept.
• Find a research environment (site).
• Choose your responders.
• Gather, process, and analyze data.
• Record your key findings and publish the results.

What are the Advantages of Case Study Methodology?

The following are the six advantages of the case study methodology:

1. Detailed Examination of a Specific Unit

The case study method enables researchers to document independently verifiable data from firsthand observations. The results provide information on the input mechanism that contributes to a proposed explanation under consideration.

2. Formation of Hypothesis

Researchers use the case study method to test a proposed hypothesis . More often than not, the information acquired from the study may inspire the formation of new concepts and allow further research because it supports change in social and physical settings.

You may collect a comprehensive data set depending on your ability and the openness of the study participants.

3. Constant Examination of Facts

You can use the case study methodology to examine facts about a social group continuously. The constant examination of facts ensures no disruption compromises the authenticity of the data obtained for the project.

Here, researchers don’t need to make assumptions when making conclusions from the collected data, thus ensuring the long-term validity of the findings. The conclusion made becomes significant to both sides of the equation, as it may confirm or reject the theory under investigation.

The constant examination of facts in case study methodology is subject to inefficiency because of the sheer volume of data under examination. Therefore, researchers have the responsibility to determine what information is helpful and what is insignificant.

4. Case Study Method Supports Comparison

Every demographic thinks, behaves, and responds to stimuli in unique ways, but each member of the group will contribute a little portion to a whole. Ideally, individual insights from different settings are a culmination of unique human experiences.

In this case, the case study method allows researchers to compare information from each demographic group, leading to ideas that either support or disapprove a theory.

5. Support for Knowledge Expansion

Researchers can use the case study methodology to expand their knowledge through analysis thanks to the range of methods used to collect data and evaluate hypothesis.

Many researchers collect data from interviews and observations, but even surveys can be just as useful. They may record participants’ experiences and use the information to analyze behavior and decisions. In some instances, a researcher may use memory test and experimental activities to predict how social groups would interact with or respond to given situations.

The information collected then serves to confirm the hypothesized possibilities.

6. Data Sampling Isn’t a Requirement

The case study method looks at social units holistically rather than isolating and analyzing individual data pieces. Therefore, the technique doesn’t require any sampling. The case study method supports the proposition under examination, as it transforms views into facts by validating or rejecting ideas that outside observers may use.

You may heed to specific incidences or results based on broader behavior or concepts. However, the study itself will not sample such instance. The methodology looks at the larger picture instead.

Where Can I Get Help With Case Study Writing?

You can get help with case study writing from Help for Assessment. We have the best case study writers who are only a click away to get you the writing you need to complete your paper on time.

It doesn’t matter if your deadline is closing in or you haven’t started working on the project yet. We can take you from a completely blank page to a well-written document before your due date. 

Help for Assessment charges $12.99 to $40 per page depending on the urgency. You get up to 10% discount if you’re new to this platform. So you can save money and still benefit from the convenience of our custom writing.

About the author 

Antony W is a professional writer and coach at Help for Assessment. He spends countless hours every day researching and writing great content filled with expert advice on how to write engaging essays, research papers, and assignments.

Case Study Research: Methods and Designs

Case study research is a type of qualitative research design. It’s often used in the social sciences because it involves…

Case study research is a type of qualitative research design. It’s often used in the social sciences because it involves observing subjects, or cases, in their natural setting, with minimal interference from the researcher.

In the case study method , researchers pose a specific question about an individual or group to test their theories or hypothesis. This can be done by gathering data from interviews with key informants.

Here’s what you need to know about case study research design .

What Is The Case Study Method?

Main approaches to data collection, case study research methods, how case studies are used, case study model.

Case study research is a great way to understand the nuances of a matter that can get lost in quantitative research methods. A case study is distinct from other qualitative studies in the following ways:

• It’s interested in the effect of a set of circumstances on an individual or group.
• It begins with a specific question about one or more cases.
• It focuses on individual accounts and experiences.

Here are the primary features of case study research:

• Case study research methods typically involve the researcher asking a few questions of one person or a small number of people—known as respondents—to test one hypothesis.
• Case study in research methodology may apply triangulation to collect data, in which the researcher uses several sources, including documents and field data. This is then analyzed and interpreted to form a hypothesis that can be tested through further research or validated by other researchers.
• The case study method requires clear concepts and theories to guide its methods. A well-defined research question is crucial when conducting a case study because the results of the study depend on it. The best approach to answering a research question is to challenge the existing theories, hypotheses or assumptions.
• Concepts are defined using objective language with no reference to preconceived notions that individuals might have about them. The researcher sets out to discover by asking specific questions on how people think or perceive things in their given situation.

They commonly use the case study method in business, management, psychology, sociology, political science and other related fields.

A fundamental requirement of qualitative research is recording observations that provide an understanding of reality. When it comes to the case study method, there are two major approaches that can be used to collect data: document review and fieldwork.

A case study in research methodology also includes literature review, the process by which the researcher collects all data available through historical documents. These might include books, newspapers, journals, videos, photographs and other written material. The researcher may also record information using video cameras to capture events as they occur. The researcher can also go through materials produced by people involved in the case study to gain an insight into their lives and experiences.

Field research involves participating in interviews and observations directly. Observation can be done during telephone interviews, events or public meetings, visits to homes or workplaces, or by shadowing someone for a period of time. The researcher can conduct one-on-one interviews with individuals or group interviews where several people are interviewed at once.

Let’s look now at case study methodology.

The case study method can be divided into three stages: formulation of objectives; collection of data; and analysis and interpretation. The researcher first makes a judgment about what should be studied based on their knowledge. Next, they gather data through observations and interviews. Here are some of the common case study research methods:

One of the most basic methods is the survey. Respondents are asked to complete a questionnaire with open-ended and predetermined questions. It usually takes place through face-to-face interviews, mailed questionnaires or telephone interviews. It can even be done by an online survey.

2. Semi-structured Interview

For case study research a more complex method is the semi-structured interview. This involves the researcher learning about the topic by listening to what others have to say. This usually occurs through one-on-one interviews with the sample. Semi-structured interviews allow for greater flexibility and can obtain information that structured questionnaires can’t.

3. Focus Group Interview

Another method is the focus group interview, where the researcher asks a few people to take part in an open-ended discussion on certain themes or topics. The typical group size is 5–15 people. This method allows researchers to delve deeper into people’s opinions, views and experiences.

4. Participant Observation

Participant observation is another method that involves the researcher gaining insight into an experience by joining in and taking part in normal events. The people involved don’t always know they’re being studied, but the researcher observes and records what happens through field notes.

Case study research design can use one or several of these methods depending on the context.

Case studies are widely used in the social sciences. To understand the impact of socio-economic forces, interpersonal dynamics and other human conditions, sometimes there’s no other way than to study one case at a time and look for patterns and data afterward.

It’s for the same reasons that case studies are used in business. Here are a few uses:

• Case studies can be used as tools to educate and give examples of situations and problems that might occur and how they were resolved. They can also be used for strategy development and implementation.
• Case studies can evaluate the success of a program or project. They can help teams improve their collaboration by identifying areas that need improvements, such as team dynamics, communication, roles and responsibilities and leadership styles.
• Case studies can explore how people’s experiences affect the working environment. Because the study involves observing and analyzing concrete details of life, they can inform theories on how an individual or group interacts with their environment.
• Case studies can evaluate the sustainability of businesses. They’re useful for social, environmental and economic impact studies because they look at all aspects of a business or organization. This gives researchers a holistic view of the dynamics within an organization.
• We can use case studies to identify problems in organizations or businesses. They can help spot problems that are invisible to customers, investors, managers and employees.
• Case studies are used in education to show students how real-world issues or events can be sorted out. This enables students to identify and deal with similar situations in their lives.

And that’s not all. Case studies are incredibly versatile, which is why they’re used so widely.

Human beings are complex and they interact with each other in their everyday life in various ways. The researcher observes a case and tries to find out how the patterns of behavior are created, including their causal relations. Case studies help understand one or more specific events that have been observed. Here are some common methods:

1. Illustrative case study

This is where the researcher observes a group of people doing something. Studying an event or phenomenon this way can show cause-and-effect relationships between various variables.

2. Cumulative case study

A cumulative case study is one that involves observing the same set of phenomena over a period. Cumulative case studies can be very helpful in understanding processes, which are things that happen over time. For example, if there are behavioral changes in people who move from one place to another, the researcher might want to know why these changes occurred.

3. Exploratory case study

An exploratory case study collects information that will answer a question. It can help researchers better understand social, economic, political or other social phenomena.

There are several other ways to categorize case studies. They may be chronological case studies, where a researcher observes events over time. In the comparative case study, the researcher compares one or more groups of people, places, or things to draw conclusions about them. In an intervention case study, the researcher intervenes to change the behavior of the subjects. The study method depends on the needs of the research team.

Deciding how to analyze the information at our disposal is an important part of effective management. An understanding of the case study model can help. With Harappa’s Thinking Critically course, managers and young professionals receive input and training on how to level up their analytic skills. Knowledge of frameworks, reading real-life examples and lived wisdom of faculty come together to create a dynamic and exciting course that helps teams leap to the next level.

Explore Harappa Diaries to learn more about topics such as Objectives Of Research , What are Qualitative Research Methods , How To Make A Problem Statement and How To Improve your Cognitive Skills to upgrade your knowledge and skills.

Method vs Methodology: What are the Key Differences?

Explore the key differences between method and methodology in research. Learn how to effectively apply these concepts for rigorous and impactful results.

Kate Windsor

Jun 23, 2024

Introduction 

Have you ever found yourself confused about the terms "method" and "methodology" while conducting research or writing a scientific paper ? You're not alone. Many researchers, students, and professionals often use these terms (methodology and method) interchangeably, but they actually have distinct meanings and implications. 

In this article, we'll explore the key differences between method vs methodology, and why understanding this distinction is crucial for effective research and writing, especially when trying to answer your research question.

What is a Method?

A method including research method refers to a specific procedure, technique, or tool used to collect, analyze, or interpret data within a research study. It is a concrete, well-defined set of steps that researchers use to gather and process information to support or reject the research hypothesis.

Methods are often specific to a particular discipline or field of study, and they can be either quantitative methods (involving numerical data and statistical analysis) or qualitative methods (involving non-numerical data, such as observations or interviews).

Examples of methods include surveys, experiments, case studies, and statistical analysis techniques, such as regression or factor analysis. These are all examples of when to use specific methods to collect your data and conduct your research. For more information on different types of research, check out our article on theoretical vs. applied research .

What is a Methodology?

In contrast to a method, a methodology refers to the overarching approach to both quantitative research and qualitative research. It encompasses the overall strategy, design, and philosophical assumptions that guide the selection and application of specific methods.

A methodology provides a framework for understanding the research topic, formulating research questions, and interpreting the findings. It considers factors such as the researcher's theoretical perspective, the nature of the research problem, and the intended audience for the research. 

Examples of methodologies include grounded theory, ethnography, phenomenology, and action research. These methodologies serve as a justification for using a particular set of methods to conduct your research and answer your research question. If you're a PhD student looking to strengthen your research skills, our writing tips for PhD students may be helpful.

Easily pronounces technical words in any field

Key Differences between Method and Methodology

• Scope and focus: A method focuses on the specific tools and techniques used to collect and analyze data, while a methodology encompasses the broader approach to a particular research, including the philosophical assumptions and theoretical perspectives that guide choice of methods.
• Level of abstraction: Methods are concrete and specific, providing a step-by-step guide for data collection and analysis methods. Methodologies, on the other hand, are more abstract and conceptual, dealing with the overarching principles and strategies that inform the research process.
• Role in the research process: Methods are applied during the data collection and analysis stages of research, while methodologies shape the entire research process, from the formulation of the research question to the interpretation of the findings. Understanding this difference is essential when writing a research proposal or a research paper in your research approach.
• Flexibility and adaptability: While methods are often fixed and standardized, methodologies can be more flexible and adaptable to the specific needs and contexts of a research study. Researchers may combine or modify methodologies to better suit their research aims or objectives and the nature of the problem being investigated.

The Importance of Understanding the Difference Understanding the difference between method and methodology is crucial for several reasons:

• Clarity in research design and communication: Clearly distinguishing between methods and methodologies helps researchers design more coherent and rigorous studies. It also enables them to communicate their research effectively to others, including peers, funding agencies, and the wider public. If you struggle with writing efficiently, our article on how to write faster may offer some useful strategies.
• Proper selection and application of methods and methodologies: By understanding the distinction between methods and methodologies, researchers can more effectively select and apply the appropriate tools and approaches for their specific research goals. This helps ensure that the research is valid, reliable, and relevant to the problem being investigated.
• Implications for the quality and reliability of research findings: Confusing methods and methodologies can lead to inconsistencies, errors, or limitations in the research process, which can ultimately affect the quality and reliability of the findings. By properly understanding and applying these concepts, researchers can produce more robust and trustworthy results. The use of AI in research is also becoming increasingly important for enhancing the accuracy and efficiency of data analysis.

Real-World Examples

Let's consider a couple of examples to illustrate the difference between method and methodology in practice:

**Example 1:  **A researcher wants to investigate the impact of social media on adolescent mental health. The researcher's methodology may be a mixed-methods approach, combining quantitative surveys with qualitative interviews to gain a comprehensive understanding of the issue.

The specific methods used could include an online questionnaire to collect data or any type of data on social media usage and mental health outcomes, as well as semi-structured interviews with a subset of participants to explore their experiences in-depth.

**Example 2: **A researcher plans to study the effectiveness of a new teaching strategy in primary schools. The research methodologies may be a quasi-experimental design, comparing the performance of students in classrooms using the new strategy with those using traditional methods.

The specific methods used could include pre- and post-tests to measure student learning outcomes, classroom observations to assess teacher implementation of the strategy, and focus groups with teachers and students to gather qualitative feedback.

In both examples, the methodology provides the overarching framework and approach for the research, while the methods are the specific tools and techniques used to collect and analyze data within that framework.

Confusing or conflating these concepts could lead to a misalignment between the research objectives and the actual data collected, potentially undermining the validity and impact of the findings.

Methods research is a crucial aspect of conducting effective and reliable studies. By carefully selecting and applying the appropriate methods, researchers can gather the necessary data and methods to support or reject their hypotheses and contribute to the broader body of knowledge in their field. Whether conducting medical research, social science research, or any other type of inquiry, a well-designed research strategy that incorporates suitable methods is essential for achieving meaningful results.

In summary, while methods and methodologies are closely related, they serve distinct purposes in the research process. Methods are the specific tools and techniques used to collect and analyze data, while methodologies are the broader approaches that guide the selection and application of those methods.

Understanding this distinction is essential for designing rigorous and effective research studies, communicating research findings clearly, and ensuring the reliability and impact of the results. As you embark on your own research journey, whether you're writing a PhD proposal or conducting a study, keep this important distinction in mind to strengthen your research skills and outcomes.

Q: What is the purpose of the methods section in a section of a research paper? A: The methods section in a research paper describes the specific procedures, techniques, and tools used to collect and analyze data in a study. It provides a detailed account of how the research was conducted, allowing other researchers to understand, evaluate, and potentially replicate the study.

**Q: Is the study of methods the same as methodology? **A: No, the study of methods focuses on the specific tools and techniques used in research, while methodology refers to the broader philosophical and strategic approach that guides the selection and application of those methods.

Q: What is the difference between the methodology section and the method and methodology section in a research paper? A: The methodology section discusses the overall approach to the research, including the philosophical assumptions, research design, and rationale for the chosen methods. The method and methodology section, on the other hand, combines the description of the specific methods used with the broader methodological framework.

Q: Can several methods be used in research? A: Yes, researchers often apply several methods in a single study to gather and analyze data from different perspectives. This approach, known as triangulation, can help increase the validity and reliability of the findings.

Q: How are methods and methodologies used in research? A: Methods are the specific tools and techniques used in research to collect and analyze data, such as surveys, experiments, interviews, or statistical tests. Methodologies, in contrast, provide the overarching framework and approach that guide the selection and application of these methods based on the research objectives, philosophical assumptions, and the nature of the problem being investigated.

**Q: Can methods and methodologies be applied to UX research? **A: Yes, UX research relies on various methods and methodologies to gather insights into user behavior, preferences, and experiences. For example, user interviews, usability testing, and surveys are common methods used in UX research, while user-centered design and lean UX are examples of methodologies that guide the overall approach to UX research and design.

Q: What methods and methodologies are used in experimental research? A: Experimental research typically involves methods such as randomized controlled trials, A/B testing, and factorial designs to manipulate variables and measure their effects on outcomes. The methodology guiding experimental research is often rooted in the scientific method, which emphasizes hypothesis testing, control groups, and the systematic manipulation of variables to establish cause-and-effect relationships. These methods are crucial for conducting rigorous analysis of the research methods and ensuring the validity of the findings.

Understanding the difference between method and methodology is crucial for conducting effective research. While methodology refers to the overarching approach and strategy guiding the research process, methods are the tools and techniques used to collect and analyze data. When deciding on using a particular research method, it's essential to consider the nature of your research question and the type of data you want to measure.

Whether you employ quantitative and qualitative methods or a combination of both, the ultimate goal is to select the most appropriate methods to answer your research question effectively. Remember, research deals with complex issues, and no single method is simply a one-size-fits-all solution.

By carefully evaluating your research objectives and the resources available, you can determine which method or alternative method might be best suited for your study. With a well-designed methodology and carefully chosen methods, you can contribute valuable insights to your field and advance our understanding of the world around us. 

Method vs Methodology

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Calculation of the minimum clinically important difference (MCID) using different methodologies: case study and practical guide

• Original Article
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• Published: 28 June 2024

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• Anita M. Klukowska 1 , 2 ,
• W. Peter Vandertop 1 ,
• Marc L. Schröder 3 &
• Victor E. Staartjes   ORCID: orcid.org/0000-0003-1039-2098 4  

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Introduction

Establishing thresholds of change that are actually meaningful for the patient in an outcome measurement instrument is paramount. This concept is called the minimum clinically important difference (MCID). We summarize available MCID calculation methods relevant to spine surgery, and outline key considerations, followed by a step-by-step working example of how MCID can be calculated, using publicly available data, to enable the readers to follow the calculations themselves.

Thirteen MCID calculations methods were summarized, including anchor-based methods, distribution-based methods, Reliable Change Index, 30% Reduction from Baseline, Social Comparison Approach and the Delphi method. All methods, except the latter two, were used to calculate MCID for improvement of Zurich Claudication Questionnaire (ZCQ) Symptom Severity of patients with lumbar spinal stenosis. Numeric Rating Scale for Leg Pain and Japanese Orthopaedic Association Back Pain Evaluation Questionnaire Walking Ability domain were used as anchors.

The MCID for improvement of ZCQ Symptom Severity ranged from 0.8 to 5.1. On average, distribution-based methods yielded lower MCID values, than anchor-based methods. The percentage of patients who achieved the calculated MCID threshold ranged from 9.5% to 61.9%.

Conclusions

MCID calculations are encouraged in spinal research to evaluate treatment success. Anchor-based methods, relying on scales assessing patient preferences, continue to be the “gold-standard” with receiver operating characteristic curve approach being optimal. In their absence, the minimum detectable change approach is acceptable. The provided explanation and step-by-step example of MCID calculations with statistical code and publicly available data can act as guidance in planning future MCID calculation studies.

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The notion of minimum clinically important difference (MCID) was introduced to establish thresholds of change in an outcome measurement instrument that are actually meaningful for the patient. Jaeschke et al . originally defined it “as the smallest difference in score in the domain of interest which the patient perceives as beneficial and which would mandate, in the absence of troublesome side-effects and excessive cost, a change in the patient’s management” [ 1 ].

In many clinical trials statistical analyses only focuses on intergroup comparisons of raw outcome scores using parametric/non-parametric tests and deriving conclusions based on the p -value. Using the classical threshold of p- value < 0.05 only suggests that the observed effect is unlikely to have occurred by chance, but it does not equate to a change that is clinically meaningful for the patient [ 2 ]. Calculating MCID scores, and using them as thresholds for “treatment success”, ensures that patients’ needs and preferences are considered and allows for comparison of proportion of patients experiencing a clinically relevant improvement among different groups [ 3 ]. Through MCID, clinicians can better understand the impact of an intervention on their patients’ lives, sample size calculations can become more robust and health policy makers may decide which treatments deserve reimbursement [ 4 , 5 , 6 ].

The MCID can be determined from the patient’s perspective, where it is the patient who decides whether a change in their health was meaningful [ 4 , 7 , 8 , 9 ]. This is the most common “gold-standard” approach and one that we will focus on. Occasionally, the clinician’s perspective can also be used to determine MCID. However, MCID for a clinician may not necessarily mean an increase in a patient’s functionality, but rather a change in disease survival or treatment planning [ 10 ]. MCID can also be defined at a societal level, as e.g. improvement in a patient’s functionality significant enough to aid their return to work [ 11 ].

MCID thresholds are intended to assess an individual’s clinical improvement and ought not to be applied to mean scores of entire groups post-intervention, as doing so may falsely over-estimate treatment effectiveness. It is also noteworthy to mention that obtained MCID values are not treatment-specific but broadly disease category-specific. They rely on a patient’s perception of clinical benefit, which is influenced by their diagnosis and subsequent symptoms, not just treatment modality.

In this study, we summarize available MCID calculation methods and outline key considerations when designing a MCID study, followed by a step-by-step working example of how MCID can be calculated.

Navigating the case study

To illustrate the MCID methods and to enable the reader to follow the practical calculation guide of different MCID values, based on the described methods along the way, a previously published data set of 84 patients, as described in Minetama et al ., was used based on CC0.10 license [ 12 ]. Data can be downloaded at https://data.mendeley.com/datasets/vm8rg6rvsw/1 . The statistical R code can be found in Supplementry content  1 including instructions on formatting the data set for MCID calculations The title of different MCID methods in the paper (listed below) and their number correspond to the same title and respective number in the R code. All analyses in this case study were carried out using R version 2023.12 + 402 (The R Foundation for Statistical Computing, Vienna Austria) [ 13 ].

The aim of Minetama et al . was to assess the effectiveness of supervised physical therapy (PT) with unsupervised at-home-exercises (HE) in patients with lumbar spinal stenosis (LSS). The main inclusion criteria were presence of neurogenic intermittent claudication and pain/or numbness in the lower extremities with or without back pain and > 50 years of age; diagnosis of LSS confirmed on MRI and a history of ineffective response to therapy for ≥ 3 months. Patients were then randomized into a 6-week PT or HE programme [ 12 ]. All data was pooled, as a clinically significant benefit for patients is independent of group allocation and because MCID is disease-specific. Therefore, the derived MCID will be applicable to most patients with lumbar spinal stenosis, irrespective of treatment modality. Change scores were calculated by subtracting baseline scores from follow-up scores.

MCID calculation methods

There are multiple approaches to calculate MCID, mainly divided into anchor-based and distribution-based methods (Fig.  1 ) [ 4 , 10 , 14 , 15 , 16 , 17 ]. Before deciding on the method, it needs to be defined whether the calculated MCID will be for improvement or deterioration [ 18 ]. Most commonly, MCID is used to measure improvement (as per Jaeschke et al . definition) [ 1 , 4 , 7 , 14 , 15 , 16 , 19 , 20 ]. The value of MCID for improvement should not be directly applied in reverse to determine whether a decrease in patients' scores signifies a clinically meaningful deterioration – those are two separate concepts [ 18 ]. In addition, the actual MCID value ought to be applied to post-intervention score of an individual patient (not the overall score for the whole group), to determine whether, at follow-up, he or she experienced a change equating to MCID or more, compared to their baseline score. Such patient is then classified as “responders”.

Flow diagram presenting range of Minimum clinically important difference calculation methods stratified into anchor, distribution-based and “other” described in the study. MCID, Minimum Clinically Important Difference; MIC, Minimal Important Change

According to the Consensus-based Standards for the selection of health measurement instruments (COSMIN) guidelines, the “anchor-based” approach is regarded as the “gold-standard” [ 21 , 22 , 23 ]. In this approach, we determine the MCID of a chosen outcome measurement, based on whether a pre-defined MCID (usually derived from another published study) was achieved by an external criterion, known as the anchor, usually another patient-reported outcome measure (PROM) or an objective test of functionality [ 4 , 7 , 8 , 15 , 16 , 17 , 18 , 20 ]. It is best to use scales which allow the patient to rate the specific aspect of their health related to the disease of interest post-intervention compared to baseline on a Likert-type scale. This scale may range, for example, from “much worse”, “somewhat worse”, “about the same”, “somewhat better”, to “much better”, such as the established Global Assessment Rating tool [ 7 , 8 , 24 , 25 ]. Depending on the scale, some studies determine MCID by calculating change scores for patients who only ranked themselves as “somewhat better”, and some only consider patients who ranked themselves as “much better” [ 7 , 25 , 26 , 27 , 28 , 29 ]. This discrepancy is likely an explanation for a range of MCID for a single outcome measure dependent on the methodology. There appears to be no singular “correct” approach. One of the alternatives to the Global assessment rating is the use of the health transition item (HTI) from the SF-36 questionnaire, where patients are asked about their overall health compared to one year ago [ 7 , 30 , 31 ]. Although quick and easy to conduct, the patient’s response may be influenced by comorbid health issues other than those targeted by intervention. Nevertheless, any anchor where the patient is the one to decide what change is clinically meaningful, captures the true essence of the MCID. One should however, be mindful of the not easily addressed recall bias with such anchors – patients at times do not reliably remember their baseline health status [ 32 ]. Moreover, what the above anchors do not consider is, whether the patient would still choose the intervention for the same condition despite experiencing side-effects or cost. That can be addressed through implementing anchors such as the Satisfaction with Results scale described in Copay et al ., who found that MCID values based on the Satisfaction with Results scale were slightly higher than those derived from HTI-SF-36 [ 7 , 33 ].

Other commonly used outcome scales, such as Oswestry Disability Index (ODI), Roland–Morris Disability Questionnaire (RMDQ), Visual Analogue Scale (VAS), or EQ5D-3L Health-Related Quality of Life, can also act as anchors [ 7 , 14 , 16 , 34 , 35 ]. In such instances, patients complete the “anchor” questionnaire at baseline and post-intervention and the MCID of that anchor is derived from a previous publication [ 12 , 16 , 35 ]. Before deciding on the MCID, full understanding of how it was derived in that previous publication is crucial. Ideally, this should be done for a population similar to our study cohort, with comparable follow-up periods [ 18 , 20 ]. Correlations between the anchor instrument and the investigated outcome measurement instrument must be recorded, and ought to be at least moderate (> 0.05), as that is the best indicator of construct validity (whether both the anchor instrument and outcome instrument represent a similar construct of patient health) [ 18 , 36 ]. If such correlation is not available, the anchor-based MCID credibility instrument is available to aid in assessing construct proximity between the two [ 36 , 37 ].

Once the process for selecting an anchor and classifying “responders” and “non-responders” is established, the MCID can be calculated. The outcome instrument of interest will be defined as an outcome for which we want to calculate the MCID. The first anchor-based method (within-patient change) focuses on the average improvement seen among clear responders in the anchor. The between-patient change anchor-based method additionally subtracts the average improvement seen among non-responders (unchanged and/or worsened) and consequently ends up with a smaller MCID value. Finally, an anchor-based method based on Receiver Operating Characteristic (ROC) curve analysis–that can be considered the current “gold standard”- also exists, which effectively looks at the MCID calculation as a sort of diagnostic instrument and aims to improve the discriminatory performance of our MCID threshold. In the following paragraphs, the three anchor-based methods are described in more detail. The R code (Supplementry Content  1 ) enables the reader to follow the text and to calculate MCID for the Zurich Claudication Questionnaire (ZCQ) Symptom Severity domain, based on a publicly available dataset [ 12 ].

Choice of outcome measurement instruments for MCID calculation case study

The chosen outcome measurement instrument in this case study for which MCID for improvement will be calculated is ZCQ Symptom Severity domain [ 12 ]. The ZCQ is composed of three subscales: symptom severity (7 questions, score per question ranging from 1 to 5 points); physical function (5 questions, score per question ranging from 1 to 4 points) and patient satisfaction with treatment scale (6 questions, score per question ranging from to 4 points). Higher scores indicate greater disability/worse satisfaction [ 38 ]. To visualize different MCID values, Numeric Rating Scale (NRS) for Leg Pain (score from 0 “no pain” to 10 “worse possible pain) and Japanese Orthopaedic Association Back Pain Evaluation Questionnaire (JOABPEQ) Walking Ability domain are chosen, as they showed high responsiveness in patients with LSS post-operatively [ 39 ].Through 25 questions, the JOABPEQ assesses five distinctive domains: pain-related symptoms, lumbar spine dysfunction, walking ability, impairment in social functioning and psychological disturbances. The score for each domain ranges from 0 to 100 points (higher score indicating better health status) [ 40 ]. The correlation of ZCQ symptom severity with NRS Leg Pain and JOABPEQ Walking Ability domain, is 0.56 and − 0.51, respectively [ 39 ]. For a patient to be classified as a “responder”, using the NRS for Leg pain or JOABPEQ walking ability, the score at 6-week follow-up must have improved by 1.6 points or 20 points, respectively [ 7 , 40 , 41 ].

This publicly available dataset does not report patient satisfaction or any kind of global assessment rating.

To enable calculation of global assessment rating-based MCID methods for educational purposes, despite very limited availability of studies providing MCID for deterioration of JOABPEQ, we decided to stratify patients in this dataset into the three following groups, based on the JOABPEQ Walking Ability as an anchor: likely improved (change score above 20 points according to Kasai et al . ), no significant change (− 20– + 20 points change score), and likely deteriorated (lower than − 20 points change score) [ 41 ]. As obtained MCID values were expected to be negative, all values, for clarity of presentation, were multiplied by − 1, except in Method (IX), where graphical data distribution was shown.

The different methods in detail

Method (i) calculating mcid using “within-patient” score change.

The first method focuses on calculating the change between baseline and post-intervention score of our outcome instrument, for each patient classified as a “responder”. A “responder” is a patient who, at follow-up, has achieved the pre-defined MCID of the anchor (or ranks themselves high enough on Global assessment rating type scale based on our methodology). The MCID is then defined as the mean change in the outcome instrument of interest of those classified as “responders” [ 4 , 7 , 16 , 31 ].

The corresponding R-Code formula is described in Step 5a of Supplementry Content  1 . Calculated within-patient MCID of ZCQ Symptom Severity based on NRS Leg Pain and JOABPEQ Walking Ability domain was 4.4 and 4.2, respectively.

Method (II) calculating MCID using “between-patient” score change

In this approach, the mean change in our outcome instrument is calculated for not only “responders” but also for “non-responders”. “Non-responders” are patients who did not achieve the pre-defined MCID of our anchor or who did not rank themselves high enough (unchanged, or sometimes: unchanged + worsened) on Global Assessment Rating type scale according to our methodology. The minimum clinically important difference of our outcome instrument is then defined as the difference between the mean change scores of “responders” and “non-responders” [ 4 , 7 , 16 , 19 ].

The corresponding R-Code formula is described in Step 5b of Supplementry content  1 . Calculated between-patient MCID of ZCQ Symptom Severity based on NRS Leg Pain and JOABPEQ Walking Ability domain was 3.5 and 2.8, respectively.

Method (III) calculating MCID using the ROC analysis

Here the MCID is derived through ROC analysis to identify the “threshold” score of our outcome instrument that best discriminates between “responders” and “non-responders” of the anchor [ 4 , 7 , 16 , 19 , 27 ]. To understand ROC, one must familiarize oneself with the concept of sensitivity and specificity. In ROC analysis, sensitivity is defined as the ability of the test to correctly detect “true positives”, which in this context refers to patients who have achieved a clinically meaningful change.

“False negative” would be a patient, who was classified as “non-responder” but is really a “responder”. Specificity is defined as the ability of a test to correctly detect a “true negative” result- a patient who did not achieve a clinically meaningful change – a “non-responder” [ 25 ].

A “false positive” would be a patient, who was classified as a “responder” but who was a “non-responder”. Values for sensitivity and specificity range from 0 to 1. Sensitivity of 1 means that the test can detect 100% of “true positives”’ (“responders”), while specificity of 1 reflects the ability to detect 100% of “true negatives” (“non-responders”). It is unclear what the minimum sensitivity and specificity should be for a “gold-standard” MCID, which is why the most established approach is to opt for a MCID threshold that maximizes both sensitivity and specificity at the same time, which can be done using ROC analysis [ 4 , 7 , 25 , 31 , 42 ]. During ROC analysis, the “closest-to-(0,1)-criterion” (the top left most point of the curve) or the Youden index are the two methods to automatically determine the optimal threshold point [ 43 ].

When conducting the ROC analysis, the Area under the curve (AUC) is also determined–a measure of how well the MCID threshold discriminates responders and non-responders in general. Values in AUC can range 0–1. An AUC of 0.5 signifies that the score discriminates no better than random chance, whereas a value of 1 means that the score perfectly discriminates between responders and non-responders. In the literature, an AUC of 0.7 and 0.8 is deemed fair (acceptable), while ≥ 0.8 to < 0.9 is considered good and values ≥ 0.9 are considered excellent [ 44 ]. Calculating the AUC provides a rough estimate of how well the chosen MCID threshold performs. The corresponding R-Code formula is described in Step 5c of Supplementry content  1 . Statistical package pROC was used. The calculated MCID of ZCQ symptom severity based on NRS Leg Pain and JOABPEQ Walking Ability domain was for both 1.5.

Calculation of MCID through distribution-based methods

Calculation of MCID using the distribution-based approach focuses on statistical properties of the dataset [ 7 , 14 , 16 , 27 , 45 ]. Those methods are objective, easy to calculate, and in some cases, yield values close to anchor-based MCID. The advantage of this approach is that it does not rely on any external criterion or require additional studies on previously established MCIDs or other validated “gold standard” questionnaires for the specific disease in each clinical setting. However, it fails to include the patient’s perspective of a clinically meaningful change, which will be discussed later in this study. In this sense, distribution-based methods focus on finding MCID thresholds that enable mathematical distinction of what is considered a changed vs. unchanged score, whereas anchor-based methods focus on finding MCID thresholds which represent a patient-centered, meaningful improvement.

Method (IV) calculating MCID through Standard Error of Measurement (SEM)

The standard error of measurement conceptualizes the reliability of the outcome measure, by determining how repeated measurements of an outcome may differ from the “true score”. Greater SEM equates to lower reliability, which is suggestive of meaningful inconsistencies in the values produced by the outcome instrument despite similar measuring conditions. Hence, it has been theorized that 1 SEM is equal to MCID, because a change score ≥ 1 SEM, is unlikely to be due to measurement error and therefore is also more likely to be clinically meaningful [ 46 , 47 ]. The following formula is used: [ 1 , 7 , 35 , 46 , 48 ].

The ICC, also called reliability coefficient, signifies level of agreement or consistency between measurements taken on different occasions or by different raters [ 49 ]. There are various ways of calculating the ICC depending on the used model with values < 0.5, 0.5– 0.75, 0.75–0.9 and > 0.90 indicating poor, moderate, good and excellent reliability, respectively [ 49 ]. While a value of 1 × SEM is probably the most established way to calculate MCID, in the literature, a range of multiplication factors for SEM-based MCID have been used, including 1.96 SEM or even 2.77 SEM to identify a more specific threshold for improvement [ 48 , 50 ]. The corresponding R-Code formula is described in Step 6a of Supplementry Content  1 . The chosen ZCQ Symptom Severity ICC was 0.81 [ 51 ]. The SEM-based MCID was 1.9.

Method (V) calculating MCID through Effect Size (ES)

Effect size (ES) is a standardized measure of the strength of the relationship or difference between two variables [ 52 ]. It is described by Cohen et al . as “degree to which the null hypothesis (there is no difference between the two groups) is false”. It allows for direct comparison of different instruments with different units between studies. There are multiple forms to calculate ES, but for the purpose of MCID calculations, the ES represents the number of SDs by which the post-intervention score has changed from baseline score. It is calculated based on the following formula incorporating the average change score divided by the SD of the baseline score: [ 52 ].

According to Cohen et al . 0.2 is considered small ES, 0.5 is moderate ES and 0.8 or more is large ES [ 53 ]. Most commonly, a change score with an ES of 0.2 is considered equivalent to MCID [ 7 , 16 , 31 , 54 , 55 , 56 ]. Using this method, we are basically identifying the mean change score (in this case reflecting the MCID) that equates to an ES of 0.2: [ 7 , 55 ].

Practically, if a patient experienced small improvement in an outcome measure post intervention, the ES will be smaller than for a patient who experienced a large improvement in outcomes measure. The corresponding R-Code formula is described in Step 6b of Supplementry Content  1 . The ES-based MCID was 0.9.

Method (VI) calculating MCID through Standardized Response Mean (SRM)

The Standardized Response Mean (SRM) aims to gauge the responsiveness of an outcome similarly to ES. Initially described by Cohen et al . as a derivative of ES assessing differences of paired observations in a single sample, later renamed as SRM, it is also considered an “index of responsiveness” [ 38 , 53 ]. However, the denominator is SD of the change scores–not the SD of the baseline scores–while the numerator remains the average change score from baseline to follow-up: [ 10 , 45 , 57 , 58 , 59 ].

Similarly, to Cohen’s rule of interpreting ES, it has been theorized that responsiveness can be considered low if SRM is 0.2–0.5, moderate if > 0.5–0.8 and large if > 0.8 [ 58 , 59 , 60 ]. Again, a change score equating to SRM of 0.2 (although SRM of 1/3 or 0.5 were also proposed) can be considered MCID, although studies have used the overall SRM as MCID as well [ 45 , 54 , 56 , 61 ]. However, since SRM is a standardized index, similarly to ES, the aim of the SRM-based method ought to be to identify a change score that indicates responsiveness of 0.2: [ 61 ].

Similar to the ES-based method, the SRM-based approach for calculating the MCID is not commonly used in in spine surgery studies [ 14 ]. It is a measure of responsiveness, which is the ability to detect change over time in a construct to be measured by the instrument, and ought to be therefore calculated for the study-specific change score rather than extrapolated as a “universal” MCID threshold to other studies. The corresponding R-Code formula is described in Step 6c of Supplementry Content  1 . The SRM-based MCID was 0.8.

The limitation of using Method (V) and (VI) in MCID calculations will be later described in Discussion.

Method (VII) calculating MCID through SD

Standard Deviation represents the average spread of individual data points around the mean value of the outcome measure. Norman et al . found in their review of studies using MCID in health-related quality of life instruments that most studies had an average ES of 0.5, which equated to clinically meaningful change score of 0.5 × SD of baseline score [ 7 , 16 ,  30 ].

The corresponding R-Code formula is described in Step 6d of Supplementry content  1 . The SD-based MCID was 2.1.

Method (VIII) calculating MCID through 95% Minimum Detectable Change (MDC)

The MDC is defined as the minimal change below which there is a 95% chance that it is due to measurement error of the outcome measurement instrument: [ 7 , 61 ].

Usually, value corresponding to z is the desired level of confidence, which for 95% confidence level is 1.96. Although MDC–like all distribution-based methods–does not consider whether a change is clinically meaningful, the calculated MCID should be at least the same or greater than MDC to enable distinguishing true mathematical change from measurement noise. The 95% MDC calculation, is the most common distribution-based approach in spinal surgery, and it appears to most closely resemble anchor-derived MCID values, as demonstrated by Copay et al . [ 7 , 14 , 62 ]. The corresponding R-Code formula is described in Step 6e of Supplementry Content  1 . The 95% MDC was 5.1.

Method (IX) calculating MCID through Reliable Change Index

Another less frequently applied method through which “responders and “non-responders” can be classified but which does not rely on an external criterion is the Reliable Change Index (RCI), also called the Jacobson–Truax index [ 63 , 64 ]. It indicates whether an individual change score is statistically significantly greater than a change in score that could have occurred due to random measurement error alone [ 63 ].

In theory, a patient can be considered to experience a statistically reliably identifiable improvement ( p  < 0.05), if the individual RCI is > 1.96. Again, it does not reflect whether the change is clinically meaningful for the patient but rather that the change should not be attributed to measurement error alone and likely has a component of true score change. Therefore, this method is discouraged in MCID calculations as it relies on statistical properties of the sample and not patient preferences–as all distribution-based methods do [ 65 ]. In the example of Bolton et al . who focused on the Bournemouth Questionnaire in patients with neck pain, RCI was subsequently used to discriminate between “responders” and “non-responders”. The ROC analysis approach was then used to determine the MCID [ 64 ]. The corresponding R-Code formula is described in Step 6f of Supplementry Content  1 . Again, pROC package was used. The ROC-derived MCID was 2.5.

Other methods

Method (x) calculating mcid through anchor-based minimal important change (mic) distribution model.

In theory, combining anchor- and distribution-based methods could yield superior results. Some suggestions include averaging the values of various methods, simply combining two different methods (i.e. both an anchor-based criterion such as ROC-based MCID from patient satisfaction and 95% MDC-based MCID have to both be met to consider a patient as having achieved MCID) [ 25 ]. In 2007, de Vet et al . introduced a new visual method of MCID calculations that does not only combine but also integrates both anchor- and distribution-based calculations [ 25 ]. In addition, their method allows the calculation of both MCID for improvement and for deterioration, as these can differ.

In short form, using an anchor, patients were divided into three “importantly improved”, “not importantly changed” and “importantly deteriorated” groups (Fig.  2 ) . Then distribution expressed in percentiles of patients who “importantly improved”, “importantly deteriorated” and “not importantly changed” were plotted on a graph. This is the anchor-based part of the approach, ensuring that MCID thresholds chosen have clinical value.

Distribution of the Zurich Claudication Questionnaire Symptom Severity change scores for patients categorized as experiencing “important improvement”, “no important change” or “important deterioration” in JOABPEQ walking ability as an anchor (Method (X)). For ZCQ Symptom Severity score to improve, the actual value must decrease explaining the negative values in the model. ROC , Receiver Operating Characteristic; ZCQ , Zurich Claudication Questionnaire; JOABPEQ , Japanese Orthopaedic Association Back Pain Evaluation Questionnaire

The second part of the approach is then entirely focused on the group of patients determined by the anchor to be “unchanged”, and can be either distribution- or anchor-based:

In the first and more anchor-based method, the ROC-based method described in Method (III) is applied to find the threshold for improvement (by finding the ROC-based threshold point that optimizes sensitivity and specificity of identifying improved vs unchanged patients) or for deterioration (by finding the ROC-based threshold point that optimizes sensitivity and specificity of identifying deteriorated vs unchanged patients). For example, the threshold for improvement is found by combining the improved and unchanged groups, and then testing out different thresholds for discriminating those two groups from each other. The optimal point on the resulting ROC curve based on the closest-to-(0,1)-criterion is then found.

In the second method, which is distribution-based, the upper 95% (for improvement) and lower 95% (for deterioration) limits are found based solely on the group of patients determined to be unchanged. The following formula is used (instead, subtracting instead of adding the 1.645 × SD for deterioration or improvement, respectively): [ 25 ]

The corresponding R-Code formula can be found under Step 7a in Supplementry Content  1 . The model is presented in Fig.  2 . The 95% upper limit and 95% lower limit was 4.1 and − 7.2 respectively. The ROC-derived MCID using RCI was − 2.5 (important improvement vs unchanged) and − 0.5 (important deterioration vs unchanged). For the purpose of the model, MCID values were not multiplied by − 1 but remained in original form.

Method (XI) calculating MCID as 30% Reduction from Baseline

In recent years, a simple 30% reduction from baseline values has been introduced as an alternative to MCID calculations [ 66 ]. It has been speculated that absolute-point changes are difficult to interpret and have limited value in context of “ceiling” and “floor” effects (i.e. values that are on the extreme spectra of the measurement scale) [ 4 ]. To overcome this, Khan et al . found that 30% reduction in PROMs has similar effectiveness as traditional anchored or distribution-based methods in detecting patients with clinically meaningful differences post lumbar spine surgery [ 15 ]. The corresponding R-Code formula can be found under Step 7b in Supplementry Content  1 .

Method (XII) Calculating MCID through Delphi method

The Delphi Method is a systemic approach using the collective opinion of experts to establish a consensus regarding a medical issue [ 67 ]. It has mostly been used to develop best practice guidelines [ 68 ]. However, it can also be used to aid MCID determination [ 69 ]. The method focuses on distributing questionnaires or surveys to panel of members. The anonymized answers are grouped together and shared again with the expert panel in subsequent rounds. This allows the experts to reflect on their opinions and consider strengths and weaknesses of the others response. The process is repeated until consensus is reached. Ensuring anonymity, this prevents any potential bias linked to a specific participant’s concern about their own opinion being viewed or influenced by other personal factors [ 67 ].

Method (XIII) calculating MCID through Social Comparison Approach

The final approach is asking patients to compare themselves to other patients, which requires time and resources [ 70 ]. In a study by Redelmeier et al . patients with chronic obstructive pulmonary disease in a rehabilitation program were organized into small groups and observed each other at multiple occasions [ 70 ]. Additionally, each patient was paired with another participant and had a one-to-one interview with them discussing different aspects of their health. Finally, each patient anonymously rated themselves against their partner on a scale “much better”, “somewhat better”, “a little bit better”, “about the same”, “a little bit worse” “somewhat worse” and “much worse”. MCID was then calculated based on the mean change score of patients who graded themselves as “a little bit better” (MCID for improvement) or a “little bit worse” (MCID for deterioration), like in the within-patient change and between-patient change method described in Method (I) and (II) [ 70 ].

Substantial Clinical Benefit

Over the years, it has been noted that MCID calculations based either purely on distribution-based method or only group of patients rating themselves as “somewhat better” or “slightly better” does not necessarily constitute a change that patients would consider beneficial enough “to mandate, in the absence of troublesome side effects and excessive cost, to undergo the treatment again” [ 3 , 24 ]. Therefore, the concept of substantial clinical benefit (SCB) has been introduced as a way of identifying a threshold of clinical success of intervention rather than a “floor” value for improvement- that is MCID [ 24 ]. For example, in Carreon et al ., ROC derived SCB “thresholds” were defined as a change score with equal sensitivity and specificity to distinguish “much better” from “somewhat better” patients post cervical spinal fusion [ 71 ]. Glassman et al . on the other hand used ROC derived SCB thresholds to discriminate between “much better” and “about the same” patients following lumbar spinal fusion. The authors stress that SCB and MCID are indeed separate entities, and one should not be used to derive the other [ 24 ]. Thus, while the methods to derive SCB and MCID thresholds can be carried out similarly based on anchors, the ultimate goal of applying SCB versus MCID is different.

Using the various methods explained above, overall, MCID for improvement for ZCQ Symptoms Severity domain ranged from 0.8 to 5.1 (Table  1 ). Here, the readers obtained results can be checked for correctness. On average distribution-based MCID values were lower than anchor-based MCID values. Within distribution-based approach, method (VIII) “Minimum detectable change” resulted in MCID of 5.1, which exceeded the MCID’s derived using the “gold-standard” anchor-based approaches. The average MCID based on anchor of NRS Leg pain and JOABPEQ walking ability was 3.1 and 2.8, respectively. Dependent on methods used, percentage of responders to HE and PT intervention fell within range of 9.5% for “30% Reduction from Baseline” method to 61.9% using ES- and SRM-based method (Table  2 ). Method (X) is graphically presented in Fig.  2 .

As demonstrated above, the MCID is dependent upon the methodology and the chosen anchor, highlighting the necessity for careful preparation in MCID calculations. The lowest MCID of 0.8 was calculated for Method (VI) being SRM. Logically, if a patient on average had a baseline ZCQ Symptom Severity score of 23.2, an improvement of 0.8 is unlikely to be clinically meaningful, even if rounded up. It rather informs on the measurement error property of our instrument as explained by COSMIN. Additionally, the distribution-based methods rely on statistical properties of the sample, which varies from cohort to cohort making it only generalizable to patient groups with similar SD but not applicable to others with a different spread of data [ 52 ]. Not surprisingly, anchor-based methods considering patient preferences yielded on average higher MCID values than distribution-based methods, which again varied from anchor to anchor. The mean MCID for improvement calculated for NPRS Leg Pain was 3.1, while for JOABPEQ Walking Ability it was 2.8—such similar values prove the importance of selecting responsive anchors with at least moderate correlations. Despite assessing different aspects of LSS disease, the MCID remained comparable in this specific case.

Interestingly, Method (VIII) MDC yielded the highest value of 5.1, exceeding the “gold-standard” ROC-derived MCID. This suggests that, in this example, using this ROC-derived MCID in clinical practice would be illogical, as the value falls within the measurement error determined by MDC. Here it would be appropriate to choose MDC approach as the MCID. Interestingly, ROC-derived MCID values based on Global Assessment Rating like stratification of patients based on their JOABPEQ Walking Ability (Method X) yielded higher MCID, than in Method (III). This may be attributed to a more a balanced distribution of “responders” and “non-responders” (only unchanged patients) in Method (X), unlike in the latter (Method III) where patients were strictly categorized into “responders” and “non-responders” (including both deteriorated and unchanged). This further highlights the importance of using global assessment rating type scales in determining the extent of clinical benefit.

Although ES-based (Method (V)) and SRM-based (Method (VI)) MCID calculations have been described in the literature, ES and SRM were originally created to quantify the strength of relationship between scores of two samples (in case of ES) and change score of paired observations in one sample (in case of SRM) [ 53 , 58 , 59 ]. They do offer an alternative to MCID calculations. However, verification with other MCID calculation methods, ideally anchor-based, is strongly recommended. As seen in this case study and other MCID’s derived similarly, they often result small estimates [ 7 , 55 ]. There is also no consensus regarding the choice of SD of Change Score vs. SD of Baseline Score as denominator. Additionally, whether the calculated MCID (mean change score) should represent value, such as the ES is 0.2 indicating small effect, or value should be 0.5 suggesting moderate effect is currently arbitrary and often relies on the researcher’s preference [ 53 , 55 , 59 ]. Both ES and SRM can be used to assess whether the overall change score observed in single study is suggestive of a clinically meaningful benefit in that specific cohort or in case of SRM, whether the outcome measure is responsive. However, it is our perspective that extending such value as “MCID” from one study to another is not recommended.

One can argue whether there is even a place for distribution-based methods in MCID calculations. They ultimately fail to provide an MCID value that meets the original definition of Jaeschke et al . “of smallest change in the outcome that the patient would identify as important”. At no point are patients asked about what constitutes a meaningful change for them, and the value is derived from statistical properties of the sample solely [ 1 ]. Nevertheless, conduction of studies on MCID implementing scales such as Global Assessment Rating is time-consuming and performing studies for each patient outcome and each disease is likely not feasible. Distribution-based methods still have some merit in that they–like the 95% MDC method—can help distinguish measurement noise and inaccuracy from true change. Even if anchor-based methods should probably be used to define MCID thresholds, they ought to be supported by a calculation of MDC so that it can be decided whether the chosen threshold makes sense mathematically (i.e., can reliably be distinguished from measurement inaccuracies) as seen in our case study.

Calculating MCID for different diagnoses

Previously, MCID thresholds for outcome measurement instruments were calculated for generic populations, such as patients suffering from low back pain. More recently, MCID values for commonly used PROMs in spine surgery, such as ODI, RMDQ or NRS have been calculated for more narrowly defined diagnoses, such as lumbar disc herniation (LDH) or LSS. The question arises as to whether a separate MCID is needed for all the different spinal conditions. In general, establishing an MCID specific to these patient groups is only recommended if these patient’s perception of meaningful change is different from that of low back pain in general. Importantly, again, the MCID should not be treatment-specific, but rather broadly disease specific. Therefore, it is advisable to use MCID based on patients who had the most similar disease characteristics to our cohort. For example, an MCID for NRS Back Pain based on study group composed of different types of lumbar degenerative disease, may in some cases, be applied to study cohort composed solely of patients with LDH. However, no such extrapolation should be performed for populations with back pain secondary to malignancy, due to a totally different pathogenesis and associated symptoms that may influence the ability to detect a clinically meaningful change in the above NRS Back Pain such as fatigue or anorexia.

Study cohort characteristics that influence MCID

Regardless of robust methodology, it can be expected that it is impossible to obtain the same MCID on different occasions even in the same population due to the inherent subjectivity of what is perceived as “clinically beneficial” and day-to-day symptom fluctuation. However, it was found that patients who have worse baseline scores, reflecting e.g., more advanced disease, require greater overall change at follow-up to report it as clinically meaningful [ 72 ]. One should also be mindful of “regression to the mean” where extremely high or low-scoring patients then subsequently score closer to baseline at second measurement [ 73 ]. Therefore, adequate cohort characteristics need to be presented, for the readers to judge how generalizable the MCID may be to their study cohort. If a patient pre-operatively experiences NRS Leg Pain of 1, and the MCID is 1.6, they cannot achieve MCID at all, as the maximum possible change score is smaller than the MCID threshold (“floor effect”). A similar situation can occur with patients closer to the higher end of the scale (“ceiling effect”). The general rule is, that if at least 15% of the study cohort has the highest or lowest possible score for a given outcome instrument, one can expect significant “ceiling/floor effects” [ 50 ]. One way to overcome this, is through transferring absolute MCID scores to percentage change scores [ 4 , 45 ]. However, percentage change scores only account for high baseline scores, if high baseline scores indicate larger disability (as seen with ODI) and have a possibility of larger change. If a high score in an instruments reflects better health status (as seen in in SF-36), than percentage change scores will increase the association with baseline score [ 4 ]. In general, it is important to consider which patient to exclude from certain analyses when applying MCID: For example, patients without relevant disease preoperatively (for example, those exhibiting so-called “patient-accepted symptom states”, PASS) should probably be excluded altogether when reporting the percentage of patients achieving MCID [ 74 ].

Establishing reliable thresholds for MCID is key in clinical research and forms the basis of patient-centered treatment evaluations when using patient-reported outcome measures or objective functional tests. Calculation of MCID thresholds can be achieved using a variety of different methods, each yielding completely different results, as is demonstrated in this practical guide. Generally, anchor-based methods relying on scales assessing patient preferences/satisfaction or global assessment ratings continue to be the “gold-standard” approach- the most common being ROC analysis. In the absence of appropriate anchors, the distribution-based MCID based on the 95% MDC approach is acceptable, as it appears to yield the most similar results compared to anchor-based approaches. Moreover, we recommend using it as a supplement to any anchor-based MCID thresholds to check if they can reliably distinguish true change from measurement inaccuracies. The explanation provided in this practical guide with step-by-step examples along with public data and statistical code can add as guidance for future studies calculating MCID thresholds.

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Klukowska, A.M., Vandertop, W.P., Schröder, M.L. et al. Calculation of the minimum clinically important difference (MCID) using different methodologies: case study and practical guide. Eur Spine J (2024). https://doi.org/10.1007/s00586-024-08369-5

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DOI : https://doi.org/10.1007/s00586-024-08369-5

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Interpreting digital transformation from a psychological perspective: a case study of the oil and gas industry.

1. Introduction

2. goals of digital transformation, 2.1. background of digital transformation—information explosion, 2.2. ict interpretation of transformation goals, 2.3. psychological interpretation of transformation goals, 3. direction of digital transformation, 3.1. ict interpretation of transformation direction, 3.2. psychological interpretation of transformation direction, 4. methodology, 4.1. qualitative analysis, 4.2. quantitative analysis, 4.3. case studies, 4.3.1. information digitalization stage, 4.3.2. business digitalization stage, 4.3.3. digital transformation stage, 5.1. qualitative findings, 5.2. quantitative findings, 5.3. case study analyses, 6. contributions and innovations, 6.1. bridging cognitive barriers, 6.2. integration of psychological perspectives, 6.3. empirical evidence from mixed-methods approach, 6.4. practical implications for the oil and gas industry, 6.5. comparative analysis with the existing literature, 7. conclusions, author contributions, data availability statement, conflicts of interest.

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Zhang, J.; Yang, Y.; Zhang, Y.; Liu, S.; Qiu, M.; Zhang, H. Interpreting Digital Transformation from a Psychological Perspective: A Case Study of the Oil and Gas Industry. Processes 2024 , 12 , 1388. https://doi.org/10.3390/pr12071388

Zhang J, Yang Y, Zhang Y, Liu S, Qiu M, Zhang H. Interpreting Digital Transformation from a Psychological Perspective: A Case Study of the Oil and Gas Industry. Processes . 2024; 12(7):1388. https://doi.org/10.3390/pr12071388

Zhang, Jiaming, Yan Yang, Yundong Zhang, Shuaiqi Liu, Maoxin Qiu, and Huazhen Zhang. 2024. "Interpreting Digital Transformation from a Psychological Perspective: A Case Study of the Oil and Gas Industry" Processes 12, no. 7: 1388. https://doi.org/10.3390/pr12071388

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