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Case Study – Methods, Examples and Guide

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Case Study Research

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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  • 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.

Case study examples
Research question Case study
What are the ecological effects of wolf reintroduction? Case study of wolf reintroduction in Yellowstone National Park
How do populist politicians use narratives about history to gain support? Case studies of Hungarian prime minister Viktor Orbán and US president Donald Trump
How can teachers implement active learning strategies in mixed-level classrooms? Case study of a local school that promotes active learning
What are the main advantages and disadvantages of wind farms for rural communities? Case studies of three rural wind farm development projects in different parts of the country
How are viral marketing strategies changing the relationship between companies and consumers? Case study of the iPhone X marketing campaign
How do experiences of work in the gig economy differ by gender, race and age? Case studies of Deliveroo and Uber drivers in London

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analysis method case study

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.

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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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Definition and Introduction

Case analysis is a problem-based teaching and learning method that involves critically analyzing complex scenarios within an organizational setting for the purpose of placing the student in a “real world” situation and applying reflection and critical thinking skills to contemplate appropriate solutions, decisions, or recommended courses of action. It is considered a more effective teaching technique than in-class role playing or simulation activities. The analytical process is often guided by questions provided by the instructor that ask students to contemplate relationships between the facts and critical incidents described in the case.

Cases generally include both descriptive and statistical elements and rely on students applying abductive reasoning to develop and argue for preferred or best outcomes [i.e., case scenarios rarely have a single correct or perfect answer based on the evidence provided]. Rather than emphasizing theories or concepts, case analysis assignments emphasize building a bridge of relevancy between abstract thinking and practical application and, by so doing, teaches the value of both within a specific area of professional practice.

Given this, the purpose of a case analysis paper is to present a structured and logically organized format for analyzing the case situation. It can be assigned to students individually or as a small group assignment and it may include an in-class presentation component. Case analysis is predominately taught in economics and business-related courses, but it is also a method of teaching and learning found in other applied social sciences disciplines, such as, social work, public relations, education, journalism, and public administration.

Ellet, William. The Case Study Handbook: A Student's Guide . Revised Edition. Boston, MA: Harvard Business School Publishing, 2018; Christoph Rasche and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Analysis . Writing Center, Baruch College; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

How to Approach Writing a Case Analysis Paper

The organization and structure of a case analysis paper can vary depending on the organizational setting, the situation, and how your professor wants you to approach the assignment. Nevertheless, preparing to write a case analysis paper involves several important steps. As Hawes notes, a case analysis assignment “...is useful in developing the ability to get to the heart of a problem, analyze it thoroughly, and to indicate the appropriate solution as well as how it should be implemented” [p.48]. This statement encapsulates how you should approach preparing to write a case analysis paper.

Before you begin to write your paper, consider the following analytical procedures:

  • Review the case to get an overview of the situation . A case can be only a few pages in length, however, it is most often very lengthy and contains a significant amount of detailed background information and statistics, with multilayered descriptions of the scenario, the roles and behaviors of various stakeholder groups, and situational events. Therefore, a quick reading of the case will help you gain an overall sense of the situation and illuminate the types of issues and problems that you will need to address in your paper. If your professor has provided questions intended to help frame your analysis, use them to guide your initial reading of the case.
  • Read the case thoroughly . After gaining a general overview of the case, carefully read the content again with the purpose of understanding key circumstances, events, and behaviors among stakeholder groups. Look for information or data that appears contradictory, extraneous, or misleading. At this point, you should be taking notes as you read because this will help you develop a general outline of your paper. The aim is to obtain a complete understanding of the situation so that you can begin contemplating tentative answers to any questions your professor has provided or, if they have not provided, developing answers to your own questions about the case scenario and its connection to the course readings,lectures, and class discussions.
  • Determine key stakeholder groups, issues, and events and the relationships they all have to each other . As you analyze the content, pay particular attention to identifying individuals, groups, or organizations described in the case and identify evidence of any problems or issues of concern that impact the situation in a negative way. Other things to look for include identifying any assumptions being made by or about each stakeholder, potential biased explanations or actions, explicit demands or ultimatums , and the underlying concerns that motivate these behaviors among stakeholders. The goal at this stage is to develop a comprehensive understanding of the situational and behavioral dynamics of the case and the explicit and implicit consequences of each of these actions.
  • Identify the core problems . The next step in most case analysis assignments is to discern what the core [i.e., most damaging, detrimental, injurious] problems are within the organizational setting and to determine their implications. The purpose at this stage of preparing to write your analysis paper is to distinguish between the symptoms of core problems and the core problems themselves and to decide which of these must be addressed immediately and which problems do not appear critical but may escalate over time. Identify evidence from the case to support your decisions by determining what information or data is essential to addressing the core problems and what information is not relevant or is misleading.
  • Explore alternative solutions . As noted, case analysis scenarios rarely have only one correct answer. Therefore, it is important to keep in mind that the process of analyzing the case and diagnosing core problems, while based on evidence, is a subjective process open to various avenues of interpretation. This means that you must consider alternative solutions or courses of action by critically examining strengths and weaknesses, risk factors, and the differences between short and long-term solutions. For each possible solution or course of action, consider the consequences they may have related to their implementation and how these recommendations might lead to new problems. Also, consider thinking about your recommended solutions or courses of action in relation to issues of fairness, equity, and inclusion.
  • Decide on a final set of recommendations . The last stage in preparing to write a case analysis paper is to assert an opinion or viewpoint about the recommendations needed to help resolve the core problems as you see them and to make a persuasive argument for supporting this point of view. Prepare a clear rationale for your recommendations based on examining each element of your analysis. Anticipate possible obstacles that could derail their implementation. Consider any counter-arguments that could be made concerning the validity of your recommended actions. Finally, describe a set of criteria and measurable indicators that could be applied to evaluating the effectiveness of your implementation plan.

Use these steps as the framework for writing your paper. Remember that the more detailed you are in taking notes as you critically examine each element of the case, the more information you will have to draw from when you begin to write. This will save you time.

NOTE : If the process of preparing to write a case analysis paper is assigned as a student group project, consider having each member of the group analyze a specific element of the case, including drafting answers to the corresponding questions used by your professor to frame the analysis. This will help make the analytical process more efficient and ensure that the distribution of work is equitable. This can also facilitate who is responsible for drafting each part of the final case analysis paper and, if applicable, the in-class presentation.

Framework for Case Analysis . College of Management. University of Massachusetts; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Rasche, Christoph and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Study Analysis . University of Arizona Global Campus Writing Center; Van Ness, Raymond K. A Guide to Case Analysis . School of Business. State University of New York, Albany; Writing a Case Analysis . Business School, University of New South Wales.

Structure and Writing Style

A case analysis paper should be detailed, concise, persuasive, clearly written, and professional in tone and in the use of language . As with other forms of college-level academic writing, declarative statements that convey information, provide a fact, or offer an explanation or any recommended courses of action should be based on evidence. If allowed by your professor, any external sources used to support your analysis, such as course readings, should be properly cited under a list of references. The organization and structure of case analysis papers can vary depending on your professor’s preferred format, but its structure generally follows the steps used for analyzing the case.

Introduction

The introduction should provide a succinct but thorough descriptive overview of the main facts, issues, and core problems of the case . The introduction should also include a brief summary of the most relevant details about the situation and organizational setting. This includes defining the theoretical framework or conceptual model on which any questions were used to frame your analysis.

Following the rules of most college-level research papers, the introduction should then inform the reader how the paper will be organized. This includes describing the major sections of the paper and the order in which they will be presented. Unless you are told to do so by your professor, you do not need to preview your final recommendations in the introduction. U nlike most college-level research papers , the introduction does not include a statement about the significance of your findings because a case analysis assignment does not involve contributing new knowledge about a research problem.

Background Analysis

Background analysis can vary depending on any guiding questions provided by your professor and the underlying concept or theory that the case is based upon. In general, however, this section of your paper should focus on:

  • Providing an overarching analysis of problems identified from the case scenario, including identifying events that stakeholders find challenging or troublesome,
  • Identifying assumptions made by each stakeholder and any apparent biases they may exhibit,
  • Describing any demands or claims made by or forced upon key stakeholders, and
  • Highlighting any issues of concern or complaints expressed by stakeholders in response to those demands or claims.

These aspects of the case are often in the form of behavioral responses expressed by individuals or groups within the organizational setting. However, note that problems in a case situation can also be reflected in data [or the lack thereof] and in the decision-making, operational, cultural, or institutional structure of the organization. Additionally, demands or claims can be either internal and external to the organization [e.g., a case analysis involving a president considering arms sales to Saudi Arabia could include managing internal demands from White House advisors as well as demands from members of Congress].

Throughout this section, present all relevant evidence from the case that supports your analysis. Do not simply claim there is a problem, an assumption, a demand, or a concern; tell the reader what part of the case informed how you identified these background elements.

Identification of Problems

In most case analysis assignments, there are problems, and then there are problems . Each problem can reflect a multitude of underlying symptoms that are detrimental to the interests of the organization. The purpose of identifying problems is to teach students how to differentiate between problems that vary in severity, impact, and relative importance. Given this, problems can be described in three general forms: those that must be addressed immediately, those that should be addressed but the impact is not severe, and those that do not require immediate attention and can be set aside for the time being.

All of the problems you identify from the case should be identified in this section of your paper, with a description based on evidence explaining the problem variances. If the assignment asks you to conduct research to further support your assessment of the problems, include this in your explanation. Remember to cite those sources in a list of references. Use specific evidence from the case and apply appropriate concepts, theories, and models discussed in class or in relevant course readings to highlight and explain the key problems [or problem] that you believe must be solved immediately and describe the underlying symptoms and why they are so critical.

Alternative Solutions

This section is where you provide specific, realistic, and evidence-based solutions to the problems you have identified and make recommendations about how to alleviate the underlying symptomatic conditions impacting the organizational setting. For each solution, you must explain why it was chosen and provide clear evidence to support your reasoning. This can include, for example, course readings and class discussions as well as research resources, such as, books, journal articles, research reports, or government documents. In some cases, your professor may encourage you to include personal, anecdotal experiences as evidence to support why you chose a particular solution or set of solutions. Using anecdotal evidence helps promote reflective thinking about the process of determining what qualifies as a core problem and relevant solution .

Throughout this part of the paper, keep in mind the entire array of problems that must be addressed and describe in detail the solutions that might be implemented to resolve these problems.

Recommended Courses of Action

In some case analysis assignments, your professor may ask you to combine the alternative solutions section with your recommended courses of action. However, it is important to know the difference between the two. A solution refers to the answer to a problem. A course of action refers to a procedure or deliberate sequence of activities adopted to proactively confront a situation, often in the context of accomplishing a goal. In this context, proposed courses of action are based on your analysis of alternative solutions. Your description and justification for pursuing each course of action should represent the overall plan for implementing your recommendations.

For each course of action, you need to explain the rationale for your recommendation in a way that confronts challenges, explains risks, and anticipates any counter-arguments from stakeholders. Do this by considering the strengths and weaknesses of each course of action framed in relation to how the action is expected to resolve the core problems presented, the possible ways the action may affect remaining problems, and how the recommended action will be perceived by each stakeholder.

In addition, you should describe the criteria needed to measure how well the implementation of these actions is working and explain which individuals or groups are responsible for ensuring your recommendations are successful. In addition, always consider the law of unintended consequences. Outline difficulties that may arise in implementing each course of action and describe how implementing the proposed courses of action [either individually or collectively] may lead to new problems [both large and small].

Throughout this section, you must consider the costs and benefits of recommending your courses of action in relation to uncertainties or missing information and the negative consequences of success.

The conclusion should be brief and introspective. Unlike a research paper, the conclusion in a case analysis paper does not include a summary of key findings and their significance, a statement about how the study contributed to existing knowledge, or indicate opportunities for future research.

Begin by synthesizing the core problems presented in the case and the relevance of your recommended solutions. This can include an explanation of what you have learned about the case in the context of your answers to the questions provided by your professor. The conclusion is also where you link what you learned from analyzing the case with the course readings or class discussions. This can further demonstrate your understanding of the relationships between the practical case situation and the theoretical and abstract content of assigned readings and other course content.

Problems to Avoid

The literature on case analysis assignments often includes examples of difficulties students have with applying methods of critical analysis and effectively reporting the results of their assessment of the situation. A common reason cited by scholars is that the application of this type of teaching and learning method is limited to applied fields of social and behavioral sciences and, as a result, writing a case analysis paper can be unfamiliar to most students entering college.

After you have drafted your paper, proofread the narrative flow and revise any of these common errors:

  • Unnecessary detail in the background section . The background section should highlight the essential elements of the case based on your analysis. Focus on summarizing the facts and highlighting the key factors that become relevant in the other sections of the paper by eliminating any unnecessary information.
  • Analysis relies too much on opinion . Your analysis is interpretive, but the narrative must be connected clearly to evidence from the case and any models and theories discussed in class or in course readings. Any positions or arguments you make should be supported by evidence.
  • Analysis does not focus on the most important elements of the case . Your paper should provide a thorough overview of the case. However, the analysis should focus on providing evidence about what you identify are the key events, stakeholders, issues, and problems. Emphasize what you identify as the most critical aspects of the case to be developed throughout your analysis. Be thorough but succinct.
  • Writing is too descriptive . A paper with too much descriptive information detracts from your analysis of the complexities of the case situation. Questions about what happened, where, when, and by whom should only be included as essential information leading to your examination of questions related to why, how, and for what purpose.
  • Inadequate definition of a core problem and associated symptoms . A common error found in case analysis papers is recommending a solution or course of action without adequately defining or demonstrating that you understand the problem. Make sure you have clearly described the problem and its impact and scope within the organizational setting. Ensure that you have adequately described the root causes w hen describing the symptoms of the problem.
  • Recommendations lack specificity . Identify any use of vague statements and indeterminate terminology, such as, “A particular experience” or “a large increase to the budget.” These statements cannot be measured and, as a result, there is no way to evaluate their successful implementation. Provide specific data and use direct language in describing recommended actions.
  • Unrealistic, exaggerated, or unattainable recommendations . Review your recommendations to ensure that they are based on the situational facts of the case. Your recommended solutions and courses of action must be based on realistic assumptions and fit within the constraints of the situation. Also note that the case scenario has already happened, therefore, any speculation or arguments about what could have occurred if the circumstances were different should be revised or eliminated.

Bee, Lian Song et al. "Business Students' Perspectives on Case Method Coaching for Problem-Based Learning: Impacts on Student Engagement and Learning Performance in Higher Education." Education & Training 64 (2022): 416-432; The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Georgallis, Panikos and Kayleigh Bruijn. "Sustainability Teaching using Case-Based Debates." Journal of International Education in Business 15 (2022): 147-163; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Georgallis, Panikos, and Kayleigh Bruijn. "Sustainability Teaching Using Case-based Debates." Journal of International Education in Business 15 (2022): 147-163; .Dean,  Kathy Lund and Charles J. Fornaciari. "How to Create and Use Experiential Case-Based Exercises in a Management Classroom." Journal of Management Education 26 (October 2002): 586-603; Klebba, Joanne M. and Janet G. Hamilton. "Structured Case Analysis: Developing Critical Thinking Skills in a Marketing Case Course." Journal of Marketing Education 29 (August 2007): 132-137, 139; Klein, Norman. "The Case Discussion Method Revisited: Some Questions about Student Skills." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 30-32; Mukherjee, Arup. "Effective Use of In-Class Mini Case Analysis for Discovery Learning in an Undergraduate MIS Course." The Journal of Computer Information Systems 40 (Spring 2000): 15-23; Pessoa, Silviaet al. "Scaffolding the Case Analysis in an Organizational Behavior Course: Making Analytical Language Explicit." Journal of Management Education 46 (2022): 226-251: Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Schweitzer, Karen. "How to Write and Format a Business Case Study." ThoughtCo. https://www.thoughtco.com/how-to-write-and-format-a-business-case-study-466324 (accessed December 5, 2022); Reddy, C. D. "Teaching Research Methodology: Everything's a Case." Electronic Journal of Business Research Methods 18 (December 2020): 178-188; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

Writing Tip

Ca se Study and Case Analysis Are Not the Same!

Confusion often exists between what it means to write a paper that uses a case study research design and writing a paper that analyzes a case; they are two different types of approaches to learning in the social and behavioral sciences. Professors as well as educational researchers contribute to this confusion because they often use the term "case study" when describing the subject of analysis for a case analysis paper. But you are not studying a case for the purpose of generating a comprehensive, multi-faceted understanding of a research problem. R ather, you are critically analyzing a specific scenario to argue logically for recommended solutions and courses of action that lead to optimal outcomes applicable to professional practice.

To avoid any confusion, here are twelve characteristics that delineate the differences between writing a paper using the case study research method and writing a case analysis paper:

  • Case study is a method of in-depth research and rigorous inquiry ; case analysis is a reliable method of teaching and learning . A case study is a modality of research that investigates a phenomenon for the purpose of creating new knowledge, solving a problem, or testing a hypothesis using empirical evidence derived from the case being studied. Often, the results are used to generalize about a larger population or within a wider context. The writing adheres to the traditional standards of a scholarly research study. A case analysis is a pedagogical tool used to teach students how to reflect and think critically about a practical, real-life problem in an organizational setting.
  • The researcher is responsible for identifying the case to study; a case analysis is assigned by your professor . As the researcher, you choose the case study to investigate in support of obtaining new knowledge and understanding about the research problem. The case in a case analysis assignment is almost always provided, and sometimes written, by your professor and either given to every student in class to analyze individually or to a small group of students, or students select a case to analyze from a predetermined list.
  • A case study is indeterminate and boundless; a case analysis is predetermined and confined . A case study can be almost anything [see item 9 below] as long as it relates directly to examining the research problem. This relationship is the only limit to what a researcher can choose as the subject of their case study. The content of a case analysis is determined by your professor and its parameters are well-defined and limited to elucidating insights of practical value applied to practice.
  • Case study is fact-based and describes actual events or situations; case analysis can be entirely fictional or adapted from an actual situation . The entire content of a case study must be grounded in reality to be a valid subject of investigation in an empirical research study. A case analysis only needs to set the stage for critically examining a situation in practice and, therefore, can be entirely fictional or adapted, all or in-part, from an actual situation.
  • Research using a case study method must adhere to principles of intellectual honesty and academic integrity; a case analysis scenario can include misleading or false information . A case study paper must report research objectively and factually to ensure that any findings are understood to be logically correct and trustworthy. A case analysis scenario may include misleading or false information intended to deliberately distract from the central issues of the case. The purpose is to teach students how to sort through conflicting or useless information in order to come up with the preferred solution. Any use of misleading or false information in academic research is considered unethical.
  • Case study is linked to a research problem; case analysis is linked to a practical situation or scenario . In the social sciences, the subject of an investigation is most often framed as a problem that must be researched in order to generate new knowledge leading to a solution. Case analysis narratives are grounded in real life scenarios for the purpose of examining the realities of decision-making behavior and processes within organizational settings. A case analysis assignments include a problem or set of problems to be analyzed. However, the goal is centered around the act of identifying and evaluating courses of action leading to best possible outcomes.
  • The purpose of a case study is to create new knowledge through research; the purpose of a case analysis is to teach new understanding . Case studies are a choice of methodological design intended to create new knowledge about resolving a research problem. A case analysis is a mode of teaching and learning intended to create new understanding and an awareness of uncertainty applied to practice through acts of critical thinking and reflection.
  • A case study seeks to identify the best possible solution to a research problem; case analysis can have an indeterminate set of solutions or outcomes . Your role in studying a case is to discover the most logical, evidence-based ways to address a research problem. A case analysis assignment rarely has a single correct answer because one of the goals is to force students to confront the real life dynamics of uncertainly, ambiguity, and missing or conflicting information within professional practice. Under these conditions, a perfect outcome or solution almost never exists.
  • Case study is unbounded and relies on gathering external information; case analysis is a self-contained subject of analysis . The scope of a case study chosen as a method of research is bounded. However, the researcher is free to gather whatever information and data is necessary to investigate its relevance to understanding the research problem. For a case analysis assignment, your professor will often ask you to examine solutions or recommended courses of action based solely on facts and information from the case.
  • Case study can be a person, place, object, issue, event, condition, or phenomenon; a case analysis is a carefully constructed synopsis of events, situations, and behaviors . The research problem dictates the type of case being studied and, therefore, the design can encompass almost anything tangible as long as it fulfills the objective of generating new knowledge and understanding. A case analysis is in the form of a narrative containing descriptions of facts, situations, processes, rules, and behaviors within a particular setting and under a specific set of circumstances.
  • Case study can represent an open-ended subject of inquiry; a case analysis is a narrative about something that has happened in the past . A case study is not restricted by time and can encompass an event or issue with no temporal limit or end. For example, the current war in Ukraine can be used as a case study of how medical personnel help civilians during a large military conflict, even though circumstances around this event are still evolving. A case analysis can be used to elicit critical thinking about current or future situations in practice, but the case itself is a narrative about something finite and that has taken place in the past.
  • Multiple case studies can be used in a research study; case analysis involves examining a single scenario . Case study research can use two or more cases to examine a problem, often for the purpose of conducting a comparative investigation intended to discover hidden relationships, document emerging trends, or determine variations among different examples. A case analysis assignment typically describes a stand-alone, self-contained situation and any comparisons among cases are conducted during in-class discussions and/or student presentations.

The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Yin, Robert K. Case Study Research and Applications: Design and Methods . 6th edition. Thousand Oaks, CA: Sage, 2017; Crowe, Sarah et al. “The Case Study Approach.” BMC Medical Research Methodology 11 (2011):  doi: 10.1186/1471-2288-11-100; Yin, Robert K. Case Study Research: Design and Methods . 4th edition. Thousand Oaks, CA: Sage Publishing; 1994.

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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.

Checklist for assessing the quality of a case study report
Relevant for all qualitative research
1. Is this report easy to read?
2. Does it fit together, each sentence contributing to the whole?
3. Does this report have a conceptual structure (i.e., themes or issues)?
4. Are its issues developed in a series and scholarly way?
5. Have quotations been used effectively?
6. Has the writer made sound assertions, neither over- or under-interpreting?
7. Are headings, figures, artefacts, appendices, indexes effectively used?
8. Was it edited well, then again with a last minute polish?
9. Were sufficient raw data presented?
10. Is the nature of the intended audience apparent?
11. Does it appear that individuals were put at risk?
High relevance to qualitative case study research
12. Is the case adequately defined?
13. Is there a sense of story to the presentation?
14. Is the reader provided some vicarious experience?
15. Has adequate attention been paid to various contexts?
16. Were data sources well-chosen and in sufficient number?
17. Do observations and interpretations appear to have been triangulated?
18. Is the role and point of view of the researcher nicely apparent?
19. Is empathy shown for all sides?
20. Are personal intentions examined?
Added from Merriam ( )
21. Is the case study particular?
22. Is the case study descriptive?
23. Is the case study heuristic?
Added from Creswell ( )
24. Was study design appropriate to methodology?

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.

Journal title2011 impact factor5-year impact factor
2.1882.432
1.426N/A
0.8391.850
0.780N/A
0.612N/A

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.

Journal titleDate of searchNumber of studies locatedNumber of full text studies extractedHealth sciencesSocial sciences and anthropologyMethods
4 Mar 20131816 Barone ( ); Bronken et al. ( ); Colón-Emeric et al. ( ); Fourie and Theron ( ); Gallagher et al. ( ); Gillard et al. ( ); Hooghe et al. ( ); Jackson et al. ( ); Ledderer ( ); Mawn et al. ( ); Roscigno et al. ( ); Rytterström et al. ( ) Nil Austin, Park, and Goble ( ); Broyles, Rodriguez, Price, Bayliss, and Sevick ( ); De Haene et al. ( ); Fincham et al. ( )
7 Mar 2013117Nil Adamson and Holloway ( ); Coltart and Henwood ( ) Buckley and Waring ( ); Cunsolo Willox et al. ( ); Edwards and Weller ( ); Gratton and O'Donnell ( ); Sumsion ( )
4 Mar 20131611Nil Buzzanell and D’Enbeau ( ); D'Enbeau et al. ( ); Nagar-Ron and Motzafi-Haller ( ); Snyder-Young ( ); Yeh ( ) Ajodhia-Andrews and Berman ( ); Alexander et al. ( ); Jorrín-Abellán et al. ( ); Nairn and Panelli ( ); Nespor ( ); Wimpenny and Savin-Baden ( )
Total453412715

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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What is the Case Study Method?

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Overview Dropdown up

Overview dropdown down, celebrating 100 years of the case method at hbs.

The 2021-2022 academic year marks the 100-year anniversary of the introduction of the case method at Harvard Business School. Today, the HBS case method is employed in the HBS MBA program, in Executive Education programs, and in dozens of other business schools around the world. As Dean Srikant Datar's says, the case method has withstood the test of time.

Case Discussion Preparation Details Expand All Collapse All

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How Cases Unfold In the Classroom

How cases unfold in the classroom dropdown up, how cases unfold in the classroom dropdown down, preparation guidelines expand all collapse all, read the professor's assignment or discussion questions read the professor's assignment or discussion questions dropdown down, read the first few paragraphs and then skim the case read the first few paragraphs and then skim the case dropdown down, reread the case, underline text, and make margin notes reread the case, underline text, and make margin notes dropdown down, note the key problems on a pad of paper and go through the case again note the key problems on a pad of paper and go through the case again dropdown down, how to prepare for case discussions dropdown up, how to prepare for case discussions dropdown down, read the professor's assignment or discussion questions, read the first few paragraphs and then skim the case, reread the case, underline text, and make margin notes, note the key problems on a pad of paper and go through the case again, case study best practices expand all collapse all, prepare prepare dropdown down, discuss discuss dropdown down, participate participate dropdown down, relate relate dropdown down, apply apply dropdown down, note note dropdown down, understand understand dropdown down, case study best practices dropdown up, case study best practices dropdown down, participate, what can i expect on the first day dropdown down.

Most programs begin with registration, followed by an opening session and a dinner. If your travel plans necessitate late arrival, please be sure to notify us so that alternate registration arrangements can be made for you. Please note the following about registration:

HBS campus programs – Registration takes place in the Chao Center.

India programs – Registration takes place outside the classroom.

Other off-campus programs – Registration takes place in the designated facility.

What happens in class if nobody talks? Dropdown down

Professors are here to push everyone to learn, but not to embarrass anyone. If the class is quiet, they'll often ask a participant with experience in the industry in which the case is set to speak first. This is done well in advance so that person can come to class prepared to share. Trust the process. The more open you are, the more willing you’ll be to engage, and the more alive the classroom will become.

Does everyone take part in "role-playing"? Dropdown down

Professors often encourage participants to take opposing sides and then debate the issues, often taking the perspective of the case protagonists or key decision makers in the case.

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Writing a Case Study

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What is a case study?

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A Case study is: 

  • An in-depth research design that primarily uses a qualitative methodology but sometimes​​ includes quantitative methodology.
  • Used to examine an identifiable problem confirmed through research.
  • Used to investigate an individual, group of people, organization, or event.
  • Used to mostly answer "how" and "why" questions.

What are the different types of case studies?

Man and woman looking at a laptop

Descriptive

This type of case study allows the researcher to:

How has the implementation and use of the instructional coaching intervention for elementary teachers impacted students’ attitudes toward reading?

Explanatory

This type of case study allows the researcher to:

Why do differences exist when implementing the same online reading curriculum in three elementary classrooms?

Exploratory

This type of case study allows the researcher to:

 

What are potential barriers to student’s reading success when middle school teachers implement the Ready Reader curriculum online?

Multiple Case Studies

or

Collective Case Study

This type of case study allows the researcher to:

How are individual school districts addressing student engagement in an online classroom?

Intrinsic

This type of case study allows the researcher to:

How does a student’s familial background influence a teacher’s ability to provide meaningful instruction?

Instrumental

This type of case study allows the researcher to:

How a rural school district’s integration of a reward system maximized student engagement?

Note: These are the primary case studies. As you continue to research and learn

about case studies you will begin to find a robust list of different types. 

Who are your case study participants?

Boys looking through a camera

 

This type of study is implemented to understand an individual by developing a detailed explanation of the individual’s lived experiences or perceptions.

 

 

 

This type of study is implemented to explore a particular group of people’s perceptions.

This type of study is implemented to explore the perspectives of people who work for or had interaction with a specific organization or company.

This type of study is implemented to explore participant’s perceptions of an event.

What is triangulation ? 

Validity and credibility are an essential part of the case study. Therefore, the researcher should include triangulation to ensure trustworthiness while accurately reflecting what the researcher seeks to investigate.

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How to write a Case Study?

When developing a case study, there are different ways you could present the information, but remember to include the five parts for your case study.

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analysis method case study

The Guide to Thematic Analysis

analysis method case study

  • What is Thematic Analysis?
  • Advantages of Thematic Analysis
  • Disadvantages of Thematic Analysis
  • Thematic Analysis Examples
  • How to Do Thematic Analysis
  • Thematic Coding
  • Collaborative Thematic Analysis
  • Thematic Analysis Software
  • Thematic Analysis in Mixed Methods Approach
  • Abductive Thematic Analysis
  • Deductive Thematic Analysis
  • Inductive Thematic Analysis
  • Reflexive Thematic Analysis
  • Thematic Analysis in Observations
  • Thematic Analysis in Surveys
  • Thematic Analysis for Interviews
  • Thematic Analysis for Focus Groups
  • Introduction

What is a case study?

How to do a thematic analysis for a case study research project.

  • Thematic Analysis of Secondary Data
  • Thematic Analysis Literature Review
  • Thematic Analysis vs. Phenomenology
  • Thematic vs. Content Analysis
  • Thematic Analysis vs. Grounded Theory
  • Thematic Analysis vs. Narrative Analysis
  • Thematic Analysis vs. Discourse Analysis
  • Thematic Analysis vs. Framework Analysis
  • Thematic Analysis in Social Work
  • Thematic Analysis in Psychology
  • Thematic Analysis in Educational Research
  • Thematic Analysis in UX Research
  • How to Present Thematic Analysis Results
  • Increasing Rigor in Thematic Analysis
  • Peer Review in Thematic Analysis

Thematic Analysis for Case Studies

Thematic analysis and case study research are widely used qualitative methods , each offering distinct ways to gather and interpret qualitative data . Thematic analysis allows researchers to identify patterns and themes within data sets, providing insight into shared experiences or perspectives. On the other hand, case study research focuses on in-depth analysis of a particular instance or case, offering detailed understanding of complex issues in real-life contexts. Combining these two methods can yield comprehensive insights, enabling researchers to analyze specific cases with a nuanced understanding of broader themes. This article provides a guide on conducting thematic analysis within the framework of case study research, outlining key steps and considerations to ensure rigorous and insightful outcomes to address your research objective .

A case study is a research strategy that involves an in-depth investigation of a single case or a number of cases within their real-life context. Unlike quantitative research , which seeks to quantify data and generalize results from a sample to a population, a case study approach allows for a more detailed and nuanced exploration of complex phenomena. This method is particularly useful in fields such as psychology, sociology, education, and business, where understanding the specifics of a single situation can require qualitative analysis to provide insights into broader patterns and issues.

Case studies can be based on various sources of evidence, including documents, archival records, interviews , direct observation , participant-observation, and physical artifacts. By employing multiple sources of data, case study research enhances the robustness of the findings, offering a more comprehensive view of the subject under study.

There are several types of case studies, each serving different purposes in research. These include exploratory, explanatory, and descriptive case studies. Exploratory case studies are often used as a prelude to further, more detailed research, allowing expert and novice researchers to gather initial insights and formulate hypotheses or propositions. Explanatory case studies are utilized to explain the mechanisms behind a particular phenomenon, often in response to theory-driven questions. Descriptive case studies, on the other hand, aim to provide a detailed account of the case within its context, without necessarily aiming to answer 'why' or 'how' questions.

One of the key strengths of case study research is its ability to provide insight into the context in which the case operates, which is often lost in larger-scale quantitative studies. This context can include social, economic, cultural, and other factors that significantly influence the case. Understanding these contextual factors is crucial for interpreting the findings accurately and can help to identify how the results of a case study might (or might not) be applicable in similar situations.

However, case study research is not without its challenges. The in-depth nature of the investigation often requires a significant amount of time and resources. Additionally, the findings from a case study are sometimes viewed as having limited generalizability due to the focus on a specific case or a small number of cases. To address this concern, researchers can employ a technique known as 'theoretical generalization,' where findings are related back to existing theories, contributing to a broader understanding of the phenomenon.

analysis method case study

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Thematic analysis is a method for identifying, analyzing, and reporting patterns (themes) within data. It provides a flexible and useful tool for qualitative research , especially within the context of case study research . This section outlines the steps for conducting a thematic analysis in a case study research project after data collection , ensuring a systematic and rigorous approach to data analysis . The process is divided into three key subsections: preparing your data, identifying themes, and reviewing and defining themes.

Preparing qualitative data

The first step in thematic analysis is to become familiar with your data. Usually this is textual data that can help you name relevant themes later on. This involves a detailed and immersive reading of the data collected from your case study. Data can include interview transcripts , observation notes , documents , and other relevant materials. During this phase, it's crucial to start making initial notes and marking ideas for coding. Remember to refer to important theories from your literature review to inform your subsequent analyses. Organizing your data systematically is also essential; this could mean arranging data into different types based on the source or nature of the information. This preparatory work lays the foundation for a more focused and efficient analysis process.

Identifying themes

After familiarizing yourself with the data, you can code the data by selecting interesting segments of data and attaching a code (or label) to capture the essence of each data segment and how it relates to your research question. After this initial coding, the next step is to begin theme development. This involves collating all the codes and the relevant data to identify themes that emerge across the dataset. A theme captures something important about the data in relation to the research question and represents some level of patterned response or underlying meaning within the data set. During this phase, it's important to be flexible - themes may evolve or merge as you refine your analysis and gain a deeper understanding of the data.

Reviewing and defining themes

Once potential themes have been identified from your qualitative study, the next step is to review and refine them. This involves a two-level review process: first, reviewing the themes identified in relation to the coded extracts, and then reviewing these themes in relation to the entire dataset. This step ensures that each theme is coherent, consistent, and distinct. It also involves determining the "story" that each theme tells about the data, which is critical for the next steps of analysis and for writing up the findings. Finally, it is necessary to define and name the themes, which involves a careful consideration of what each theme captures about the data and how it relates to the research questions and objectives .

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  • 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.

Peer Review reports

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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5 Benefits of Learning Through the Case Study Method

Harvard Business School MBA students learning through the case study method

  • 28 Nov 2023

While several factors make HBS Online unique —including a global Community and real-world outcomes —active learning through the case study method rises to the top.

In a 2023 City Square Associates survey, 74 percent of HBS Online learners who also took a course from another provider said HBS Online’s case method and real-world examples were better by comparison.

Here’s a primer on the case method, five benefits you could gain, and how to experience it for yourself.

Access your free e-book today.

What Is the Harvard Business School Case Study Method?

The case study method , or case method , is a learning technique in which you’re presented with a real-world business challenge and asked how you’d solve it. After working through it yourself and with peers, you’re told how the scenario played out.

HBS pioneered the case method in 1922. Shortly before, in 1921, the first case was written.

“How do you go into an ambiguous situation and get to the bottom of it?” says HBS Professor Jan Rivkin, former senior associate dean and chair of HBS's master of business administration (MBA) program, in a video about the case method . “That skill—the skill of figuring out a course of inquiry to choose a course of action—that skill is as relevant today as it was in 1921.”

Originally developed for the in-person MBA classroom, HBS Online adapted the case method into an engaging, interactive online learning experience in 2014.

In HBS Online courses , you learn about each case from the business professional who experienced it. After reviewing their videos, you’re prompted to take their perspective and explain how you’d handle their situation.

You then get to read peers’ responses, “star” them, and comment to further the discussion. Afterward, you learn how the professional handled it and their key takeaways.

HBS Online’s adaptation of the case method incorporates the famed HBS “cold call,” in which you’re called on at random to make a decision without time to prepare.

“Learning came to life!” said Sheneka Balogun , chief administration officer and chief of staff at LeMoyne-Owen College, of her experience taking the Credential of Readiness (CORe) program . “The videos from the professors, the interactive cold calls where you were randomly selected to participate, and the case studies that enhanced and often captured the essence of objectives and learning goals were all embedded in each module. This made learning fun, engaging, and student-friendly.”

If you’re considering taking a course that leverages the case study method, here are five benefits you could experience.

5 Benefits of Learning Through Case Studies

1. take new perspectives.

The case method prompts you to consider a scenario from another person’s perspective. To work through the situation and come up with a solution, you must consider their circumstances, limitations, risk tolerance, stakeholders, resources, and potential consequences to assess how to respond.

Taking on new perspectives not only can help you navigate your own challenges but also others’. Putting yourself in someone else’s situation to understand their motivations and needs can go a long way when collaborating with stakeholders.

2. Hone Your Decision-Making Skills

Another skill you can build is the ability to make decisions effectively . The case study method forces you to use limited information to decide how to handle a problem—just like in the real world.

Throughout your career, you’ll need to make difficult decisions with incomplete or imperfect information—and sometimes, you won’t feel qualified to do so. Learning through the case method allows you to practice this skill in a low-stakes environment. When facing a real challenge, you’ll be better prepared to think quickly, collaborate with others, and present and defend your solution.

3. Become More Open-Minded

As you collaborate with peers on responses, it becomes clear that not everyone solves problems the same way. Exposing yourself to various approaches and perspectives can help you become a more open-minded professional.

When you’re part of a diverse group of learners from around the world, your experiences, cultures, and backgrounds contribute to a range of opinions on each case.

On the HBS Online course platform, you’re prompted to view and comment on others’ responses, and discussion is encouraged. This practice of considering others’ perspectives can make you more receptive in your career.

“You’d be surprised at how much you can learn from your peers,” said Ratnaditya Jonnalagadda , a software engineer who took CORe.

In addition to interacting with peers in the course platform, Jonnalagadda was part of the HBS Online Community , where he networked with other professionals and continued discussions sparked by course content.

“You get to understand your peers better, and students share examples of businesses implementing a concept from a module you just learned,” Jonnalagadda said. “It’s a very good way to cement the concepts in one's mind.”

4. Enhance Your Curiosity

One byproduct of taking on different perspectives is that it enables you to picture yourself in various roles, industries, and business functions.

“Each case offers an opportunity for students to see what resonates with them, what excites them, what bores them, which role they could imagine inhabiting in their careers,” says former HBS Dean Nitin Nohria in the Harvard Business Review . “Cases stimulate curiosity about the range of opportunities in the world and the many ways that students can make a difference as leaders.”

Through the case method, you can “try on” roles you may not have considered and feel more prepared to change or advance your career .

5. Build Your Self-Confidence

Finally, learning through the case study method can build your confidence. Each time you assume a business leader’s perspective, aim to solve a new challenge, and express and defend your opinions and decisions to peers, you prepare to do the same in your career.

According to a 2022 City Square Associates survey , 84 percent of HBS Online learners report feeling more confident making business decisions after taking a course.

“Self-confidence is difficult to teach or coach, but the case study method seems to instill it in people,” Nohria says in the Harvard Business Review . “There may well be other ways of learning these meta-skills, such as the repeated experience gained through practice or guidance from a gifted coach. However, under the direction of a masterful teacher, the case method can engage students and help them develop powerful meta-skills like no other form of teaching.”

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How to Experience the Case Study Method

If the case method seems like a good fit for your learning style, experience it for yourself by taking an HBS Online course. Offerings span seven subject areas, including:

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No matter which course or credential program you choose, you’ll examine case studies from real business professionals, work through their challenges alongside peers, and gain valuable insights to apply to your career.

Are you interested in discovering how HBS Online can help advance your career? Explore our course catalog and download our free guide —complete with interactive workbook sections—to determine if online learning is right for you and which course to take.

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What is Case Study Analysis? (Explained With Examples)

Oct 11, 2023

What is Case Study Analysis? (Explained With Examples)

Case Study Analysis is a widely used research method that examines in-depth information about a particular individual, group, organization, or event. It is a comprehensive investigative approach that aims to understand the intricacies and complexities of the subject under study. Through the analysis of real-life scenarios and inquiry into various data sources, Case Study Analysis provides valuable insights and knowledge that can be used to inform decision-making and problem-solving strategies.

1°) What is Case Study Analysis?

Case Study Analysis is a research methodology that involves the systematic investigation of a specific case or cases to gain a deep understanding of the subject matter. This analysis encompasses collecting and analyzing various types of data, including qualitative and quantitative information. By examining multiple aspects of the case, such as its context, background, influences, and outcomes, researchers can draw meaningful conclusions and provide valuable insights for various fields of study.

When conducting a Case Study Analysis, researchers typically begin by selecting a case or multiple cases that are relevant to their research question or area of interest. This can involve choosing a specific organization, individual, event, or phenomenon to study. Once the case is selected, researchers gather relevant data through various methods, such as interviews, observations, document analysis, and artifact examination.

The data collected during a Case Study Analysis is then carefully analyzed and interpreted. Researchers use different analytical frameworks and techniques to make sense of the information and identify patterns, themes, and relationships within the data. This process involves coding and categorizing the data, conducting comparative analysis, and drawing conclusions based on the findings.

One of the key strengths of Case Study Analysis is its ability to provide a rich and detailed understanding of a specific case. This method allows researchers to delve deep into the complexities and nuances of the subject matter, uncovering insights that may not be captured through other research methods. By examining the case in its natural context, researchers can gain a holistic perspective and explore the various factors and variables that contribute to the case.

1.1 - Definition of Case Study Analysis

Case Study Analysis can be defined as an in-depth examination and exploration of a particular case or cases to unravel relevant details and complexities associated with the subject being studied. It involves a comprehensive and detailed analysis of various factors and variables that contribute to the case, aiming to answer research questions and uncover insights that can be applied in real-world scenarios.

When conducting a Case Study Analysis, researchers employ a range of research methods and techniques to collect and analyze data. These methods can include interviews, surveys, observations, document analysis, and experiments, among others. By using multiple sources of data, researchers can triangulate their findings and ensure the validity and reliability of their analysis.

Furthermore, Case Study Analysis often involves the use of theoretical frameworks and models to guide the research process. These frameworks provide a structured approach to analyzing the case and help researchers make sense of the data collected. By applying relevant theories and concepts, researchers can gain a deeper understanding of the underlying factors and dynamics at play in the case.

1.2 - Advantages of Case Study Analysis

Case Study Analysis offers numerous advantages that make it a popular research method across different disciplines. One significant advantage is its ability to provide rich and detailed information about a specific case, allowing researchers to gain a holistic understanding of the subject matter. Additionally, Case Study Analysis enables researchers to explore complex issues and phenomena in their natural context, capturing the intricacies and nuances that may not be captured through other research methods.

Moreover, Case Study Analysis allows researchers to investigate rare or unique cases that may not be easily replicated or studied through experimental methods. This method is particularly useful when studying phenomena that are complex, multifaceted, or involve multiple variables. By examining real-world cases, researchers can gain insights that can be applied to similar situations or inform future research and practice.

Furthermore, this research method allows for the analysis of multiple sources of data, such as interviews, observations, documents, and artifacts, which can contribute to a comprehensive and well-rounded examination of the case. Case Study Analysis also facilitates the exploration and identification of patterns, trends, and relationships within the data, generating valuable insights and knowledge for future reference and application.

1.3 - Disadvantages of Case Study Analysis

While Case Study Analysis offers various advantages, it also comes with certain limitations and challenges. One major limitation is the potential for researcher bias, as the interpretation of data and findings can be influenced by preconceived notions and personal perspectives. Researchers must be aware of their own biases and take steps to minimize their impact on the analysis.

Additionally, Case Study Analysis may suffer from limited generalizability, as it focuses on specific cases and contexts, which might not be applicable or representative of broader populations or situations. The findings of a case study may not be easily generalized to other settings or individuals, and caution should be exercised when applying the results to different contexts.

Moreover, Case Study Analysis can require significant time and resources due to its in-depth nature and the need for meticulous data collection and analysis. This can pose challenges for researchers working with limited budgets or tight deadlines. However, the thoroughness and depth of the analysis often outweigh the resource constraints, as the insights gained from a well-conducted case study can be highly valuable.

Finally, ethical considerations also play a crucial role in Case Study Analysis, as researchers must ensure the protection of participant confidentiality and privacy. Researchers must obtain informed consent from participants and take measures to safeguard their identities and personal information. Ethical guidelines and protocols should be followed to ensure the rights and well-being of the individuals involved in the case study.

2°) Examples of Case Study Analysis

Real-world examples of Case Study Analysis demonstrate the method's practical application and showcase its usefulness across various fields. The following examples provide insights into different scenarios where Case Study Analysis has been employed successfully.

2.1 - Example in a Startup Context

In a startup context, a Case Study Analysis might explore the factors that contributed to the success of a particular startup company. It would involve examining the organization's background, strategies, market conditions, and key decision-making processes. This analysis could reveal valuable lessons and insights for aspiring entrepreneurs and those interested in understanding the intricacies of startup success.

2.2 - Example in a Consulting Context

In the consulting industry, Case Study Analysis is often utilized to understand and develop solutions for complex business problems. For instance, a consulting firm might conduct a Case Study Analysis on a company facing challenges in its supply chain management. This analysis would involve identifying the underlying issues, evaluating different options, and proposing recommendations based on the findings. This approach enables consultants to apply their expertise and provide practical solutions to their clients.

2.3 - Example in a Digital Marketing Agency Context

Within a digital marketing agency, Case Study Analysis can be used to examine successful marketing campaigns. By analyzing various factors such as target audience, message effectiveness, channel selection, and campaign metrics, this analysis can provide valuable insights into the strategies and tactics that contribute to successful marketing initiatives. Digital marketers can then apply these insights to optimize future campaigns and drive better results for their clients.

2.4 - Example with Analogies

Case Study Analysis can also be utilized with analogies to investigate specific scenarios and draw parallels to similar situations. For instance, a Case Study Analysis could explore the response of different countries to natural disasters and draw analogies to inform disaster management strategies in other regions. These analogies can help policymakers and researchers develop more effective approaches to mitigate the impact of disasters and protect vulnerable populations.

In conclusion, Case Study Analysis is a powerful research method that provides a comprehensive understanding of a particular individual, group, organization, or event. By analyzing real-life cases and exploring various data sources, researchers can unravel complexities, generate valuable insights, and inform decision-making processes. With its advantages and limitations, Case Study Analysis offers a unique approach to gaining in-depth knowledge and practical application across numerous fields.

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Qualitative Data Analysis Methods

In the following, we will discuss basic approaches to analyzing data in all six of the acceptable qualitative designs.

After reviewing the information in this document, you will be able to:

  • Recognize the terms for data analysis methods used in the various acceptable designs.
  • Recognize the data preparation tasks that precede actual analysis in all the designs.
  • Understand the basic analytic methods used by the respective qualitative designs.
  • Identify and apply the methods required by your selected design.

Terms Used in Data Analysis by the Six Designs

Each qualitative research approach or design has its own terms for methods of data analysis:

  • Ethnography—uses modified thematic analysis and life histories.
  • Case study—uses description, categorical aggregation, or direct interpretation.
  • Grounded theory—uses open, axial, and selective coding (although recent writers are proposing variations on those basic analysis methods).
  • Phenomenology—describes textures and structures of the essential meaning of the lived experience of the phenomenon
  • Heuristics—patterns, themes, and creative synthesis along with individual portraits.
  • Generic qualitative inquiry—thematic analysis, which is really a foundation for all the other analytic methods. Thematic analysis is the starting point for the other five, and the endpoint for generic qualitative inquiry. Because it is the basic or foundational method, we'll take it first.

Preliminary Tasks in Analysis in all Methods

In all the approaches—case study, grounded theory, generic inquiry, and phenomenology—there are preliminary tasks that must be performed prior to the analysis itself. For each, you will need to:

  • Arrange for secure storage of original materials. Storage should be secure and guaranteed to protect the privacy and confidentiality of the participants' information and identities.
  • Transcribe interviews or otherwise transform raw data into usable formats.
  • Make master copies and working copies of all materials. Master copies should be kept securely with the original data. Working copies will be marked up, torn apart, and used heavily: make plenty.
  • Arrange secure passwords or other protection for all electronic data and copies.
  • When ready to begin, read all the transcripts repeatedly—at least three times—for a sense of the whole. Don't force it—allow the participants' words to speak to you.

These tasks are done in all forms of qualitative analysis. Now let's look specifically at generic qualitative inquiry.

Data Analysis in Generic Qualitative Inquiry: Thematic Analysis

The primary tool for conducting the analysis of data when using the generic qualitative inquiry approach is thematic analysis, a flexible analytic method for deriving the central themes from verbal data. A thematic analysis can also be used to conduct analysis of the qualitative data in some types of case study.

Thematic analysis essentially creates theme-statements for ideas or categories of ideas (codes) that the researcher extracts from the words of the participants.

There are two main types of thematic analysis:

  • Inductive thematic analysis, in which the data are interpreted inductively, that is, without bringing in any preselected theoretical categories.
  • Theoretical thematic analysis, in which the participants' words are interpreted according to categories or constructs from the existing literature.

Analytic Steps in Thematic Analysis: Reading

Remember that the last preliminary task listed above was to read the transcripts for a sense of the whole. In this discussion, we'll assume you're working with transcribed data, usually from interviews. You can apply each step, with changes, to any kind of qualitative data. Now, before you start analyzing, take the first transcript and read it once more, as often as necessary, for a sense of what this participant told you about the topic of your study. If you're using other sources of data, spend time with them holistically.

Thematic Analysis: Steps in the Process

When you have a feel for the data,

  • Underline any passages (phases, sentences, or paragraphs) that appear meaningful to you. Don't make any interpretations yet! Review the underlined data.
  • Decide if the underlined data are relevant to the research question and cross out or delete all data unrelated to the research question. Some information in the transcript may be interesting but unrelated to the research question.
  • Create a name or "code" for each remaining underlined passage (expressions or meaning units) that focus on one single idea. The code should be:
  • Briefer than the passage, should
  • Sum up its meaning, and should be
  • Supported by the meaning unit (the participant's words).
  • Find codes that recur; cluster these together. Now begin the interpretation, but only with the understanding that the codes or patterns may shift and change during the process of analysis.
  • After you have developed the clusters or patterns of codes, name each pattern. The pattern name is a theme. Use language supported by the original data in the language of your discipline and field.
  • Write a brief description of each theme. Use brief direct quotations from the transcript to show the reader how the patterns emerged from the data.
  • Compose a paragraph integrating all the themes you developed from the individual's data.
  • Repeat this process for each participant, the "within-participant" analysis.
  • Finally, integrate all themes from all participants in "across-participants" analysis, showing what general themes are found across all the data.

Some variation of thematic analysis will appear in most of the other forms of qualitative data analysis, but the other methods tend to be more complex. Let's look at them one at a time. If you are already clear as to which approach or design your study will use, you can skip to the appropriate section below.

Ethnographic Data Analysis

Ethnographic data analysis relies on a modified thematic analysis. It is called modified because it combines standard thematic analysis as previously described for interview data with modified thematic methods applied to artifacts, observational notes, and other non-interview data.

Depending on the kinds of data to be interpreted (for instance pictures and historical documents) Ethnographers devise unique ways to find patterns or themes in the data. Finally, the themes must be integrated across all sources and kinds of data to arrive at a composite thematic picture of the culture.

(Adapted from Bogdan and Taylor, 1975; Taylor and Bogdan, 1998; Aronson, 1994.)

Data Analysis in Grounded Theory

Going beyond the descriptive and interpretive goals of many other qualitative models, grounded theory's goal is building a theory. It seeks explanation, not simply description.

It uses a constant comparison method of data analysis that begins as soon as the researcher starts collecting data. Each data collection event (for example, an interview) is analyzed immediately, and later data collection events can be modified to seek more information on emerging themes.

In other words, analysis goes on during each step of the data collection, not merely after data collection.

The heart of the grounded theory analysis is coding, which is analogous to but more rigorous than coding in thematic analysis.

Coding in Grounded Theory Method

There are three different types of coding used in a sequential manner.

  • The first type of coding is open coding, which is like basic coding in thematic analysis. During open coding, the researcher performs:
  • A line-by-line analysis (or sentence or paragraph analysis) of the data.
  • Labels and categorizes the dimensions or aspects of the phenomenon being studied.
  • The researcher also uses memos to describe the categories that are found.
  • The second type of coding is axial coding, which involves finding links between categories and subcategories found in the open coding.
  • The open codes are examined for their relationships: cause and effect, co-occurrence, and so on.
  • The goal here is to picture how the various dimensions or categories of data interact with one another in time and space.
  • The third type of coding is selective coding, which identifies a core category and relates the categories subsidiary to this core.
  • Selective coding selects the main phenomenon, (core category) around which subsidiary phenomena, (all other categories) are grouped, arranging the groupings, studying the results, and rearranging where the data require it.

The Final Stages of Grounded Theory Analysis, after Coding

From selective coding, the grounded theory researcher develops:

  • A model of the process, which is the description of which actions and interactions occur in a sequence or series.
  • A transactional system, which is the description of how the interactions of different events explain the phenomenon being investigated.
  • Finally, A conditional matrix is diagrammed to help consider the conditions and consequences related to the phenomenon under study.

These three essentially tell the story of the outcome of the research, in other words, the description of the process by which the phenomenon seems to happen, the transactional system supporting it, and the conditional matrix that pictures the explanation of the phenomenon are the findings of a grounded theory study.

(Adapted from Corbin and Strauss, 2008; Strauss and Corbin, 1990, 1998.)

Data Analysis in Qualitative Case Study: Background

There are a few points to consider in analyzing case study data:

  • Analysis can be:
  • Holistic—the entire case.
  • Embedded—a specific aspect of the case.
  • Multiple sources and kinds of data must be collected and analyzed.
  • Data must be collected, analyzed, and described about both:
  • The contexts of the case (its social, political, economic contexts, its affiliations with other organizations or cases, and so on).
  • The setting of the case (geography, location, physical grounds, or set-up, business organization, etc.).

Qualitative Case Study Data Analysis Methods

Data analysis is detailed in description and consists of an analysis of themes. Especially for interview or documentary analysis, thematic analysis can be used (see the section on generic qualitative inquiry). A typical format for data analysis in a case study consists of the following phases:

  • Description: This entails developing a detailed description of each instance of the case and its setting. The words "instance" and "case" can be confusing. Let's say we're conducting a case study of gay and lesbian members of large urban evangelical Christian congregations in the Southeast. The case would be all such people and their congregations. Instances of the case would be any individual person or congregation. In this phase, all the congregations (the settings) and their larger contexts would be described in detail, along with the individuals who are interviewed or observed.
  • Categorical Aggregation: This involves seeking a collection of themes from the data, hoping that relevant meaning about lessons to be learned about the case will emerge. Using our example, a kind of thematic analysis from all the data would be performed, looking for common themes.
  • Direct Interpretation: By looking at the single instance or member of the case and drawing meaning from it without looking for multiple instances, direct interpretation pulls the data apart and puts it together in more meaningful ways. Here, the interviews with all the gay and lesbian congregation members would be subjected to thematic analysis or some other form of analysis for themes.
  • Within-Case Analysis: This would identify the themes that emerge from the data collected from each instance of the case, including connections between or among the themes. These themes would be further developed using verbatim passages and direct quotation to elucidate each theme. This would serve as the summary of the thematic analysis for each individual participant.
  • Cross-Case Analysis: This phase develops a thematic analysis across cases as well as assertions and interpretations of the meaning of the themes emerging from all participants in the study.
  • Interpretive Phase: In the final phase, this is the creation of naturalistic generalizations from the data as a whole and reporting on the lesson learned from the case study.

(Adapted from Creswell, 1998; Stake, 1995.)

Data Analysis in Phenomenological Research

There are a few existing models of phenomenological research, and they each propose slightly different methods of data analysis. They all arrive at the same goal, however. The goal of phenomenological analysis is to describe the essence or core structures and textures of some conscious psychological experience. One such model, empirical, was developed at Duquesne University. This method of analysis consists of five essential steps and represents the other variations well. Whichever model is chosen, those wishing to conduct phenomenological research must choose a model and abide by its procedures. Empirical phenomenology is presented as an example.

  • Sense of the whole. One reads the entire description in order to get a general sense of the whole statement. This often takes a few readings, which should be approached contemplatively.
  • Discrimination of meaning units. Once the sense of the whole has been grasped, the researcher returns to the beginning and reads through the text once more, delineating each transition in meaning.
  • The researcher adopts a psychological perspective to do this. This means that the researcher looks for shifts in psychological meaning.
  • The researcher focuses on the phenomenon being investigated. This means that the researcher keeps in mind the study's topic and looks for meaningful passages related to it.
  • The researcher next eliminates redundancies and unrelated meaning units.
  • Transformation of subjects' everyday expressions (meaning units) into psychological language. Once meaning units have been delineated,
  • The researcher reflects on each of the meaning units, which are still expressed in the concrete language of the participants, and describes the essence of the statement for the participant.
  • The researcher makes these descriptions in the language of psychological science.
  • Synthesis of transformed meaning units into a consistent statement of the structure of the experience.
  • Using imaginative variation on these transformed meaning units, the researcher discovers what remains unchanged when variations are imaginatively applied, and
  • From this develops a consistent statement regarding the structure of the participant's experience.
  • The researcher completes this process for each transcript in the study.
  • Final synthesis. Finally, the researcher synthesizes all of the statements regarding each participant's experience into one consistent statement that describes and captures [of] the essence of the experience being studied.

(Adapted from Giorgi, 1985, 1997; Giorgi and Giorgi, 2003.)

Data Analysis in Heuristics

Six steps typically characterize the heuristic process of data analysis, consisting of:

  • Initial engagement.
  • Incubation.
  • Illumination.
  • Explication.

To start, place all the material drawn from one participant before you (recordings, transcriptions, journals, notes, poems, artwork, and so on). This material may either be data gathered by self-search or by interviews with co-researchers.

  • Immerse yourself fully in the material until you are aware of and understand everything that is before you.
  • Incubate the material. Put the material aside for a while. Let it settle in you. Live with it but without particular attention or focus. Return to the immersion process. Make notes where they would enable you to remember or classify the material. Continue this rhythm of working with the data and resting until an illumination or essential configuration emerges. From your core or global sense, list the essential components or patterns and themes that characterize the fundamental nature and meaning of the experience. Reflectively study the patterns and themes, dwell inside them, and develop a full depiction of the experience. The depiction must include the essential components of the experience.
  • Illustrate the depiction of the experience with verbatim samples, poems, stories, or other materials to highlight and accentuate the person's lived experience.
  • Return to the raw material of your co-researcher (participant). Does your depiction of the experience fit the data from which you have developed it? Does it contain all that is essential?
  • Develop a full reflective depiction of the experience, one that characterizes the participant's experience reflecting core meanings for the individuals as a whole. Include in the depiction, verbatim samples, poems, stories, and the like to highlight and accentuate the lived nature of the experience. This depiction will serve as the creative synthesis, which will combine the themes and patterns into a representation of the whole in an aesthetically pleasing way. This synthesis will communicate the essence of the lived experience under inquiry. The synthesis is more than a summary: it is like a chemical reaction, a creation anew.
  • Return to the data and develop a portrait of the person in such a way that the phenomenon and the person emerge as real.

(Adapted from Douglass and Moustakas, l985; Moustakas, 1990.)

Bogdan, R., & Taylor, S. J. (1975). Introduction to qualitative research methods: A phenomenological approach (3rd ed.). New York, NY: Wiley.

Corbin, J., & Strauss, A. (2008). Basics of qualitative research: Techniques and procedures for developing grounded theory (3rd ed.). Los Angeles, CA: Sage.

Creswell, J. W. (1998). Qualitative inquiry and research design: Choosing among five traditions . Thousand Oaks, CA: Sage.

Douglass, B. G., & Moustakas, C. (1985). Heuristic inquiry: The internal search to know. Journal of Humanistic Psychology , 25(3), 39–55.

Giorgi, A. (Ed.). (1985). Phenomenology and psychological research . Pittsburgh, PA: Duquesne University Press.

Giorgi, A. (1997). The theory, practice and evaluation of phenomenological methods as a qualitative research procedure. Journal of Phenomenological Psychology , 28, 235–260.

Giorgi, A. P., & Giorgi, B. M. (2003). The descriptive phenomenological psychological method. In P. M. Camic, J. E. Rhodes, & L. Yardley (Eds.), Qualitative research in psychology: Expanding perspectives in methodology and design (pp. 243–273). Washington, DC: American Psychological Association.

Moustakas, C. (1990). Heuristic research: Design, methodology, and applications . Newbury Park, CA: Sage.

Stake, R. E. (1995). The art of case study research . Thousand Oaks, CA: Sage.

Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques . Newbury Park, CA: Sage.

Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Techniques and theory for developing grounded theory (2nd ed.). Thousand Oaks, CA: Sage.

Taylor, S. J., & Bogdan, R. (1998). Introduction to qualitative research methods: A guidebook and resource (3rd ed.). New York: Wiley.

Doc. reference: phd_t3_u06s6_qualanalysis.html

analysis method case study

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 Method

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.

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  • Open access
  • Published: 17 June 2024

The effectiveness of problem-based learning and case-based learning teaching methods in clinical practical teaching in TACE treatment for hepatocellular carcinoma in China: a bayesian network meta-analysis

  • Jingxin Yan 1   na1 ,
  • Yonghao Wen 2 , 3   na1 ,
  • Xinlian Liu 4   na1 ,
  • Manjun Deng 2 , 3 ,
  • Ting Li 6 ,
  • Huanwei Wang 7 ,
  • Cui Jia 4 ,
  • Jinsong Liao 8 &
  • Lushun Zhang 4  

BMC Medical Education volume  24 , Article number:  665 ( 2024 ) Cite this article

Metrics details

To investigate the effectiveness of problem-based learning (PBL) and case-based learning (CBL) teaching methods in clinical practical teaching in transarterial chemoembolization (TACE) treatment in China.

Materials and methods

A comprehensive search of PubMed, the Chinese National Knowledge Infrastructure (CNKI) database, the Weipu database and the Wanfang database up to June 2023 was performed to collect studies that evaluate the effectiveness of problem-based learning and case-based learning teaching methods in clinical practical teaching in TACE treatment in China. Statistical analysis was performed by R software (4.2.1) calling JAGS software (4.3.1) in a Bayesian framework using the Markov chain-Monte Carlo method for direct and indirect comparisons. The R packages “gemtc”, “rjags”, “openxlsx”, and “ggplot2” were used for statistical analysis and data output.

Finally, 7 studies (five RCTs and two observational studies) were included in the meta-analysis. The combination of PBL and CBL showed more effectiveness in clinical thinking capacity, clinical practice capacity, knowledge understanding degree, literature reading ability, method satisfaction degree, learning efficiency, learning interest, practical skills examination scores and theoretical knowledge examination scores.

Conclusions

Network meta-analysis revealed that the application of PBL combined with the CBL teaching mode in the teaching of liver cancer intervention therapy significantly improves the teaching effect and significantly improves the theoretical and surgical operations, meeting the requirements of clinical education.

Peer Review reports

Introduction

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide, and newly diagnosed cases increase annually [ 1 ]. More than 50% of newly diagnosed patients are reported in China, with an age-standardized incidence rate of 8.6 per 100,000 individuals annually [ 2 ]. China is a country with a high burden of hepatitis, which indicates that HCC is one of the main focuses of medical investment in China. According to Western and Eastern experts’ consensus and guidelines [ 3 , 4 , 5 ], transarterial chemoembolization (TACE), an interventional method that embolizes the tumor-feeding vascular with embolization materials and chemotherapy drugs, is considered the first choice for most patients with advanced-stage HCC, providing opportunities for surgery. In addition, clinical evidence has also confirmed the effectiveness of TACE and its related protocol in different clinical settings [ 6 ].

With the rapid development of medical education, therefore, cultivating excellent medical professionals is particularly crucial. In clinical education, traditional lecture-based teaching has shortcomings; for example, teachers place too much emphasis on knowledge and passive student learning [ 7 ], resulting in low learning efficiency, insufficient clinical thinking ability, and poor clinical practice ability for students. Moreover, the teaching of interventional radiology, including TACE and other related disciplines, is highly specialized, with relatively few class hours and relatively short internship times, making it difficult to master the outline knowledge in a short period of time. Therefore, to improve teaching effectiveness, it is necessary to break the constraints of traditional teaching methods and strive to find more effective teaching methods.

The problem-based learning (PBL) teaching method emphasizes students’ active learning as the main focus, rather than the traditional lecture-based teaching method. It is based on a student-centered education approach, guided by teachers and based on questions, to introduce relevant basic knowledge [ 8 ]. Through group discussions, students independently collect data and discover and solve problems, and this teaching model can cultivate students’ active learning and innovation. The case-based learning (CBL) teaching method is based on typical cases, using real cases from clinical work in teaching. Before the teacher systematically explains, students are asked to contact the patient themselves in advance and carefully inquire about their medical history and clinical examinations [ 9 ]. Then, relevant information is collected based on the patient’s specific situation (such as similar patient onset factors, diagnosis and treatment plans, treatment clinical reactions, and posttreatment effects). Finally, a preliminary treatment plan will be formed by students, and teachers will continuously improve treatment plans and apply relevant theoretical knowledge for analysis.

Regarding the use of PBL and CBL for TACE teaching, only several Chinese studies found that PBL and CBL could benefit the students and trainees, as TACE teaching requires mastery of various benign and malignant tumors of the liver, including atypical cases, and interspersed with different teaching contents. Besides, TACE is a discipline that requires not only solid theoretical knowledge, but also high mastery and proficiency in practical operational skills. Therefore, the requirements for teaching methods should also be increased [ 10 ].

Although some published randomized controlled trials and observational studies have examined CBL and PBL in clinical education in TACE, there is currently no consensus on the advantages or disadvantages of these two methods. With our study, We hope to provide the optimum educational method for TACE. Therefore, in this study, we conducted a high-quality Bayesian network meta-analysis and systematic review to explore the effectiveness of the PBL and CBL methods in the clinical practical teaching of TACE in China, with the aim of providing a new perspective for the clinical education of TACE.

Study design

In this study, the Bayesian network meta-analysis was performed following the Preferred Reporting Items for Systematic reviews and Meta-analyses statement [ 11 ]. We used a Bayesian network meta-analysis because of its superiority in accounting for the pooled effect and providing precise calculations for related data.

Data sources and search

A comprehensive search of PubMed, Chinese National Knowledge Infrastructure database (CNKI), Weipu database and Wanfang database up to June 2023 was performed. Table S1 lists the search strategy, inclusion criteria, and exclusion criteria.

Data extraction and risk of bias assessment

Two independent reviewers carried out the research and data extraction, and any disagreements were resolved by a third author. Data on study details (first author, study design, year of publication, study population and sample size.) and primary outcomes were extracted into an Excel sheet. We also extracted data on the performance of the difference teaching method. We used the methods of the Cochrane Handbook for Systematic Reviews of Interventions to assess the risk of the randomized controlled trials [ 12 ]. In addition, the Newcastle–Ottawa scale was adopted to evaluate observational studies [ 13 ].

Data synthesis and statistical analysis

We conducted the network meta-analyses for theoretical knowledge examination scores, practical skills examination scores, and the questionnaire entry using a random-effect model in a Bayesian framework.

Statistical analysis was performed by R software (4.2.1) calling JAGS software (4.3.1) in a Bayesian framework using the Markov chain-Monte Carlo method for direct and indirect comparisons. The R packages “gemtc”, “rjags”, “openxlsx”, and “ggplot2” were used for statistical analysis and data output. Parameter settings: the number of chains was 6, the initial value was 2.5, the number of adaptation (or tuning) iterations was 50,000, the number of simulation iterations was 200,000, and the thinning factor was 10.

The network plot and funnel plot were drawn using Stata software (version 16).

Furthermore, statistical heterogeneity and inconsistency were evaluated using the Q test and the statistic inconsistency index (I 2 ). An I 2 value greater than 50% is generally considered to indicate a substantial level of heterogeneity, which consequently initiates sensitivity analysis to identify the source [ 14 ]. Discontinuous data in a Bayesian framework were calculated with the risk ratio (RR) and its 95% confidence interval (CI), and the natural logarithm of RR (LnRR) was used to estimate the outcomes. Continuous data in a Bayesian framework were calculated with the mean difference (MD) and its 95% CI. Accordingly, we performed a pairwise meta-analysis on comparisons on the basis of the frequentist approach to compare with the corresponding pooled results from the Bayesian framework. We used a line diagram to calculate the rank probability of different therapies, in which the X axis represents probability, while the Y axis represents ranking from first to last [ 15 , 16 ].

Study selection and characteristics of included studies

A preliminary search yielded 248 articles, of which 107 were duplicates. After removing duplicates by automated tools, we reviewed the abstracts of the remaining studies, and 134 articles did not meet the inclusion criteria. Finally, 7 studies (five RCTs [ 10 , 17 , 18 , 19 , 20 ] and two observational studies [ 21 , 22 ]) were included in the meta-analysis. Figure  1 shows the study selection flowchart of the literature search process.

figure 1

Flowchart of the literature search process

Description of the selected studies: first author, year of publication, country, intervention, the most important results. In Table  1 . The study quality of the included studies is shown in Tables  2 and 3 .

Findings of the bayesian network meta-analysis

Bayesian network meta-analysis of theoretical knowledge examination scores.

Theoretical knowledge examination scores were reported in all studies. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 a). We used a table (Table S2 ) to describe the effect of 5 interventions on the theoretical knowledge examination scores in participants with a total of 6 comparisons with LnRR. No significant publication bias was found (Fig.  3 a). PBL in combination with TBL showed the best improvement in the theoretical knowledge examination scores, followed by PBL in combination with CBL (Figure S1 ).

figure 2

Network plot. ( A ) Theoretical knowledge examination scores; ( B ) practical skills examination scores; ( C ) learning interest; ( D ): learning efficiency; ( E ) method satisfaction degree; ( F ) literature reading ability; ( G ) knowledge understanding degree; ( H ) clinical practice capacity; ( I ) clinical thinking capacity

figure 3

Funnel plot of outcomes. ( A ) Theoretical knowledge examination scores; ( B ) practical skills examination scores; ( C ) learning interest; ( D ): learning efficiency; ( E ) method satisfaction degree; ( F ) literature reading ability; ( G ) knowledge understanding degree; ( H ) clinical practice capacity; ( I ) clinical thinking capacity

Bayesian network meta-analysis of practical skills examination scores

Practical skills examination scores were reported in 6 studies [ 10 , 18 , 19 , 20 , 21 , 22 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 b). We used a table (Table S3 ) to describe the effect of 5 interventions on the practical skills examination scores in participants with a total of 6 comparisons. No significant publication bias was found (Fig.  3 b). PBL in combination with TBL showed the best improvement in the practical skills examination scores, followed by PBL (Figure S2 ).

Bayesian network meta-analysis of learning interest

Learning interest was reported in 3 studies [ 18 , 20 , 22 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 c). We used a table (Table S4 ) to describe the effect of 5 interventions on learning interest in participants with a total of 5 comparisons. No significant publication bias was found (Fig.  3 c). PBL in combination with TBL showed the best improvement in learning interest, followed by PBL in combination with CBL (Figure S3 ).

Bayesian network meta-analysis of learning efficiency

Learning efficiency was reported in 2 studies [ 20 , 22 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 d). We used a table (Table S5 ) to describe the effect of 3 interventions on learning efficiency in participants with a total of 2 comparisons. No significant publication bias was found (Fig.  3 d). PBL in combination with TBL showed the best improvement in learning efficiency, followed by PBL in combination with CBL (Figure S4 ).

Bayesian network meta-analysis of method satisfaction degree

Method satisfaction degree were reported in 2 studies [ 10 , 18 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 e). We used a table (Table S6 ) to describe the effect of 4 interventions for the method satisfaction degree in participants with a total of 4 comparisons. No significant publication bias was found (Fig.  3 e). PBL in combination with CBL is the most satisfied among students, followed by PBL (Figure S5 ).

Bayesian network meta-analysis of literature reading ability

Literature reading ability was reported in 2 studies [ 18 , 20 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 f). We used a (Table S7 ) to describe the effect of 4 interventions on the literature reading ability in participants with a total of 4 comparisons. No significant publication bias was found (Fig.  3 f). PBL in combination with CBL showed the best improvement in literature reading ability, followed by PBL (Figure S6 ).

Bayesian network meta-analysis of knowledge understanding degree

Knowledge understanding degree were reported in 2 studies [ 17 , 18 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 g). We used a league matrix table (Table S8 ) to describe the effect of 3 interventions for the knowledge understanding degree in participants with a total of 3 comparisons. No significant publication bias was found (Fig.  3 g). PBL in combination with CBL showed the best improvement in the knowledge understanding degree, followed by PBL (Figure S7 ).

Bayesian network meta-analysis of clinical practice capacity

Clinical practice capacity was reported in 2 studies [ 17 , 18 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 h). We used a (Table S9 ) to describe the effect of 3 interventions on the clinical practice capacity in participants with a total of 3 comparisons. No significant publication bias was found (Fig.  3 h). PBL in combination with CBL showed the best improvement in the clinical practice capacity, followed by PBL (Figure S8 ).

Bayesian network meta-analysis of clinical thinking capacity

Clinical thinking capacity was reported in 4 studies [ 17 , 18 , 20 , 22 ]. Eligible comparisons of outcomes are presented in the network plot (Fig.  2 i). We used a table (Table S10 ) to describe the effect of 5 interventions on the clinical thinking capacity in participants with a total of 5 comparisons. No significant publication bias was found (Fig.  3 i). PBL in combination with CBL showed the best improvement in the clinical thinking capacity, followed by CBL (Figure S9 ).

In this meta-analysis of randomized controlled trials and observational studies, we found that the combination of PBL and CBL is the most effective teaching method in TACE treatment in China. The combination of PBL and CBL showed more effectiveness in clinical thinking capacity, clinical practice capacity, knowledge understanding degree, literature reading ability, method satisfaction degree, learning efficiency, learning interest, practical skills examination scores and theoretical knowledge examination scores. In China, interventional therapy has been widely carried out since the 1980s [ 23 ], but the education method is still at an early stage. With this systematic review and meta-analysis, we summarized the current educational practice in China in terms of TACE.

To our knowledge, this is the first network evidence-based study investigating the effectiveness of different teaching methods of TACE in China. In addition, this is also the first systematic review and meta-analysis that has been carried out to investigate the interventional teaching method of TACE.

Since PBL was posted in the 1960s in response to dissatisfaction with traditional medical education, scholars have found that PBL can contribute to knowledge retention, student satisfaction, motivation, and critical thinking from many perspectives on teaching [ 24 , 25 , 26 , 27 , 28 ] In addition, PBL is currently widely used in North America and Asia, and PBL is considered a successful implementation of current medical education, but the utilization of PBL is different in different regions, showing no difference in geographical origin [ 29 ]. Even though some studies have been published, the heterogeneity within the method, region, individuals and outcomes left some difficulties for medical educational researchers. As a result, some studies showed inconsistent research results in the outcomes when PBL was used [ 30 , 31 , 32 ]. It should be noted that the current definition of CBL is not completely clear, and researchers from different countries have proposed definitions of CBL with different details but the same core [ 33 ]. CBL and PBL allow students to obtain and integrate clinical knowledge before their internship career. However, none of the studies mentioned above investigated interventional treatment teaching methods, so our meta-analysis provides value in this vacuum field.

With the rapid development of clinical medicine, traditional medical teaching methods cannot meet the needs of the medical education system. For instance, medical students who cannot master the content of anatomy classes solely through books and lecture teaching need to dissect cadavers to understand the structure of the human body. Similarly, they cannot master the methods and procedures of TACE solely through traditional education methods. There are some possible reasons that may explain why the combination of PBL and CBL showed a better effectiveness in TACE teaching in China. Unlike traditional teaching methods, the combination of PBL and CBL allows for more interaction between students and teachers, improving students’ perceptions of learning [ 34 , 35 ]. In addition, the combination of PBL and CBL may inspire students to engage in theoretical knowledge learning and practical skills, forging a preliminary mind of clinical logic and a stronger grasp of experimental processes [ 36 ].

Recent research highlights the significance of problem-based learning (PBL) and case-based learning (CBL) in education. Studies show that PBL and CBL enhance students’ motivation, engagement, and knowledge construction. Furthermore, longitudinal analyses indicate that social learning dynamics within PBL groups contribute to learning outcomes [ 37 ]. Additionally, utilizing case-based learning has been shown to improve clinical reasoning skills in medical education [ 38 ]. Realist methods are also increasingly utilized in medical education research to gain deeper insights into learning processes [ 39 ]. These findings underscore the importance of incorporating PBL, CBL, and realist methodologies in educational practices.

The regional nature of the study results warrants consideration due to China’s distinct educational environment, cultural context, and medical system. China’s evolving educational landscape, influenced by cultural factors and a shift towards student-centered learning approaches, may impact the applicability of findings on problem-based learning (PBL) and case-based learning (CBL) effectiveness [ 40 ]. Additionally, variations in healthcare systems and medical education practices highlight the need for caution in generalizing results beyond China. Future research should explore the transferability of PBL and CBL to diverse international contexts, considering cultural and educational differences [ 41 , 42 ].

We used Bayesian method to perform this network meta-analysis, as Bayesian method provides more accurate estimates for small samples because this method takes into account possible bias, reaching more accurate estimates for small samples [ 43 ]. After analyzing data through prior information, the resulting posterior information can be used again as prior information in the next statistical calculation process, especially in the process of clinical decision-making, which is more efficient and reliable [ 44 , 45 ]. Besides, the parameter settings is chosen based on our previous studies, which reduce errors caused by insufficient iterations [ 46 ].

The inconsistences of the findings across individual studies should be noted. For example, all included studies did not adopt uniform outcome measures, as there is no standard examination to test the theoretical scores and practical skills. Hence, a standard examination should be established in the future. In this meta-analysis, we synthesized the results to assess the total effectiveness; however, these differences with the results may lead to significant heterogeneity.

Similar to any meta-analysis and evidence-based study, the limitations of this meta-analysis should be noted. First, we included both RCTs and observational studies in this meta-analysis, which will undoubtedly lead to bias in the results and conclusions. Second, some of the outcomes were evaluated subjectively, which may lead to inconsistent results among individuals. Third, as only seven studies were included in this meta-analysis, the sample size of the included studies was exceedingly small, which undoubtedly led to bias that affect the accuracy of the study. Fourth, all participants were from China, so researchers outside China should interpret our results with caution. Fifth, the inconsistencies within included studies might arise from subjective evaluation metrics.

In conclusion, our study found that the combination of PBL and CBL in TACE teaching education was able to improve knowledge learning, practical skills and other important skills in teaching. However, due to the small sample size of the included individuals and the limitations within the study, further high-quality studies are needed to verify our results and conclusions.

Data availability

The datasets used and analyzed during this study are available from the corresponding author on reasonable request.

Abbreviations

Chinese National Knowledge Infrastructure

  • Transarterial chemoembolization

Problem-based Learning

Case-based Learning Teaching

Hepatocellular carcinoma

Confidence interval

Natural logarithm of RR

Mean difference

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Acknowledgements

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This work was supported by Chengdu Medical College’s undergraduate education reform project in 2020: Practice of online and offline hybrid teaching mode in pathology experiment teaching (JG202038); Chengdu Medical College’s graduate education and teaching reform project in 2023(YJG202304); Virtual Teaching and Research Project on Neurology and Diseases at Chengdu Medical College in 2023.

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Jingxin Yan, Yonghao Wen and Xinlian Liu contributed equally to this work.

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West China Hospital, Sichuan University, Chengdu, China

Jingxin Yan

Department of Hepatopancreatobiliary Surgery, Affiliated Hospital of Qinghai University, Xining, China

Yonghao Wen & Manjun Deng

Department of Postgraduate, Qinghai University, Xining, China

Department of Pathology and Pathophysiology, Chengdu Medical College, Chengdu, China

Xinlian Liu, Cui Jia & Lushun Zhang

Department of General Surgery, Rongxian People’s Hospital, Zigong, China

Department of Orthopedics, Sichuan Provincial People’s Hospital, Chengdu, China

Department of Ultrasonography, Hainan General Hospital/Hainan Affiliated Hospital of Hainan Medical University, Haikou, 570100, China

Huanwei Wang

Department of Anesthesiology, Affiliated Hospital of Chengdu University, Chengdu University, Chengdu, China

Jinsong Liao

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Conceptualization: Jingxin Yan and Lushun Zhang; validation: Jingxin Yan, Yonghao Wen, Xinlian Liu, Manjun Deng, Bin Ye, Ting Li, Huanwei Wang, Cui Jia, Jinsong Liao, Lushun Zhang; writing – original draft preparation: Jingxin Yan, Manjun Deng, Ting Li; writing – review and editing: Jingxin Yan, Yonghao Wen, Xinlian Liu, Manjun Deng, Bin Ye, Ting Li, Huanwei Wang, Cui Jia, Jinsong Liao, Lushun Zhang; software: Jingxin Yan, Yonghao Wen, Xinlian Liu, Manjun Deng, Bin Ye, Ting Li, Huanwei Wang, Cui Jia, Jinsong Liao, Lushun Zhang.

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Yan, J., Wen, Y., Liu, X. et al. The effectiveness of problem-based learning and case-based learning teaching methods in clinical practical teaching in TACE treatment for hepatocellular carcinoma in China: a bayesian network meta-analysis. BMC Med Educ 24 , 665 (2024). https://doi.org/10.1186/s12909-024-05615-8

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analysis method case study

Multi-task Chinese aspect-based sentiment analysis framework for service improvement: a case study on BNB reviews

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User-generated content has become an essential factor influencing customer choice in the selection of hotel and bed and breakfast (BNB) accommodation. It is important for entrepreneurs to effectively analyze customer reviews. From the perspective of BNB managers, it is necessary to know customer opinions relating to specific aspects of the services they have received. Aspect-based sentiment analysis (ABSA) evaluates customer sentiments and opinions and can be used to improve services. We propose a framework for automated ABSA of reviews. The framework contains modules for data preprocessing, a multi-task Chinese aspect-based sentiment analysis module, and a Kano module. The Kano module divided service attributes into several distinct categories including must-be, one-dimensional, and attractive attributes… and so on. This module is integrated into our analytical framework to elucidate the relationships between hotel service offerings and customer attributes. The framework is used for a dataset crawled from Google Maps hotel reviews with aspect categories labeled by domain experts. The experimental results demonstrate the excellent performance of this method. We categorize customer requirements based on the aggregate consumer preferences estimated by the Kano module. The effectiveness of the proposed framework is demonstrated in an empirical evaluation and the utility of the proposed Kano module demonstrated.

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This study is supported by National Science and Technology Council (MOST 111-2410-H-027-011-MY3, MOST 109-2410-H-027-009-MY2).

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Cheng, LC., Huang, HY. & Huang, YW. Multi-task Chinese aspect-based sentiment analysis framework for service improvement: a case study on BNB reviews. Electron Commer Res (2024). https://doi.org/10.1007/s10660-024-09871-0

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Determination of accuracy and usability of a slam scanner geoslam zeb horizon: a bridge structure case study.

analysis method case study

1. Introduction

2. materials and methods, 2.1. testing area, 2.2. used instruments, 2.3. terrestrial measurements and data acquisition, 2.4. data processing, 2.5. precision and accuracy evaluation.

  • Absolute comparison (includes the effect of inaccuracy in the determination of GCPs)
  • Relative comparison (comparison of shape and size—after ICP transformation of the whole GeoSLAM cloud on the reference cloud)
  • Absolute (overall profile location, showing local systematic errors)
  • Relative (determination of local deformation and local accuracy)

4. Discussion

5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Click here to enlarge figure

DataNumber
of Points
Subsampling
[m]
Number
of GCPs
RMSE
[m]
Acquisition TimeProcessing
Time
Leica P4039,078,8020.00370.0033 h30 min
GeoSLAM 119,605,824-70.05930 min45 min
GeoSLAM 28,170,880-70.06430 min45 min
DataOriginal
Cloud
RMSD [m]
Denoised (MLS)
Cloud
RMSD [m]
Original Data
ICP
RMSD [m]
Denoised (MLS) Data
ICP
RMSD [m]
GeoSLAM 10.0210.0170.0150.010
GeoSLAM 20.0250.0230.0190.015
DataGCP-TransformedICP-Transformed
Original
RMSD
MLS
RMSD
Shift
dX
Shift
dY
Shift
dZ
Original
RMSD
MLS ICP
RMSD
10.0280.0240.024−0.030−0.0080.0150.005
20.0130.010 −0.0140.0050.0090.005
30.0230.0180.0270.0090.0160.0140.006
40.0300.023 0.0240.0190.0190.006
50.0230.0200.0110.0220.0210.0110.005
60.0220.019 0.0140.0190.0120.004
70.0200.0140.0070.0170.0110.0150.005
80.0160.010 0.0160.0040.0130.004
90.0140.008−0.0050.012−0.0050.0110.004
Mean0.0200.014---0.0130.005
DataGCP-TransformedICP-Transformed
Original
RMSD
MLS
RMSD
Shift
dX
Shift
dY
Shift
dZ
Original
RMSD
MLS ICP
RMSD
10.0210.0180.006−0.033−0.0170.0130.005
20.0160.014 −0.021−0.0040.0100.006
30.0170.0110.009−0.0020.0100.0150.006
40.0240.021 0.0110.0220.0120.005
50.0280.026−0.0070.0250.0310.0120.005
60.0310.027 0.0270.0260.0130.005
70.0380.028−0.0150.0350.0190.0240.010
80.0180.013 0.0230.0020.0090.005
90.0170.014−0.0130.005−0.0070.0100.005
Mean0.0220.017---0.0120.005
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Share and Cite

Urban, R.; Štroner, M.; Braun, J.; Suk, T.; Kovanič, Ľ.; Blistan, P. Determination of Accuracy and Usability of a SLAM Scanner GeoSLAM Zeb Horizon: A Bridge Structure Case Study. Appl. Sci. 2024 , 14 , 5258. https://doi.org/10.3390/app14125258

Urban R, Štroner M, Braun J, Suk T, Kovanič Ľ, Blistan P. Determination of Accuracy and Usability of a SLAM Scanner GeoSLAM Zeb Horizon: A Bridge Structure Case Study. Applied Sciences . 2024; 14(12):5258. https://doi.org/10.3390/app14125258

Urban, Rudolf, Martin Štroner, Jaroslav Braun, Tomáš Suk, Ľudovít Kovanič, and Peter Blistan. 2024. "Determination of Accuracy and Usability of a SLAM Scanner GeoSLAM Zeb Horizon: A Bridge Structure Case Study" Applied Sciences 14, no. 12: 5258. https://doi.org/10.3390/app14125258

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This paper is in the following e-collection/theme issue:

Published on 18.6.2024 in Vol 26 (2024)

Monitoring Adverse Drug Events in Web Forums: Evaluation of a Pipeline and Use Case Study

Authors of this article:

Author Orcid Image

Original Paper

  • Pierre Karapetiantz 1 , PhD   ; 
  • Bissan Audeh 1 , PhD   ; 
  • Akram Redjdal 1 , PhD   ; 
  • Théophile Tiffet 2, 3 , MD   ; 
  • Cédric Bousquet 1, 2 , PhD, PharmD   ; 
  • Marie-Christine Jaulent 1 , PhD  

1 Inserm, Sorbonne Université, université Paris 13, Laboratoire d’informatique médicale et d’ingénierie des connaissances en e-santé, LIMICS, F-75006, Paris, France

2 Service de santé publique et information médicale, CHU de Saint Etienne, 42000 Saint-Etienne, France

3 Institut National de la Santé et de la Recherche Médicale, Université Jean Monnet, SAnté INgéniérie BIOlogie St-Etienne, SAINBIOSE, 42270 Saint-Priest-en-Jarez, France

Corresponding Author:

Marie-Christine Jaulent, PhD

Sorbonne Université

université Paris 13, Laboratoire d’informatique médicale et d’ingénierie des connaissances en e-santé, LIMICS, F-75006

15 rue de l'école de Médecine

Paris, 75006

Phone: 33 144279108

Email: [email protected]

Background: To mitigate safety concerns, regulatory agencies must make informed decisions regarding drug usage and adverse drug events (ADEs). The primary pharmacovigilance data stem from spontaneous reports by health care professionals. However, underreporting poses a notable challenge within the current system. Explorations into alternative sources, including electronic patient records and social media, have been undertaken. Nevertheless, social media’s potential remains largely untapped in real-world scenarios.

Objective: The challenge faced by regulatory agencies in using social media is primarily attributed to the absence of suitable tools to support decision makers. An effective tool should enable access to information via a graphical user interface, presenting data in a user-friendly manner rather than in their raw form. This interface should offer various visualization options, empowering users to choose representations that best convey the data and facilitate informed decision-making. Thus, this study aims to assess the potential of integrating social media into pharmacovigilance and enhancing decision-making with this novel data source. To achieve this, our objective was to develop and assess a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. The goal was to create a user-friendly tool that enables regulatory authorities to make better-informed decisions effectively.

Methods: To enhance pharmacovigilance efforts, we have devised a pipeline comprising 4 distinct modules, each independently editable, aimed at efficiently analyzing health-related French web forums. These modules were (1) web forums’ posts extraction, (2) web forums’ posts annotation, (3) statistics and signal detection algorithm, and (4) a graphical user interface (GUI). We showcase the efficacy of the GUI through an illustrative case study involving the introduction of the new formula of Levothyrox in France. This event led to a surge in reports to the French regulatory authority.

Results: Between January 1, 2017, and February 28, 2021, a total of 2,081,296 posts were extracted from 23 French web forums. These posts contained 437,192 normalized drug-ADE couples, annotated with the Anatomical Therapeutic Chemical (ATC) Classification and Medical Dictionary for Regulatory Activities (MedDRA). The analysis of the Levothyrox new formula revealed a notable pattern. In August 2017, there was a sharp increase in posts related to this medication on social media platforms, which coincided with a substantial uptick in reports submitted by patients to the national regulatory authority during the same period.

Conclusions: We demonstrated that conducting quantitative analysis using the GUI is straightforward and requires no coding. The results aligned with prior research and also offered potential insights into drug-related matters. Our hypothesis received partial confirmation because the final users were not involved in the evaluation process. Further studies, concentrating on ergonomics and the impact on professionals within regulatory agencies, are imperative for future research endeavors. We emphasized the versatility of our approach and the seamless interoperability between different modules over the performance of individual modules. Specifically, the annotation module was integrated early in the development process and could undergo substantial enhancement by leveraging contemporary techniques rooted in the Transformers architecture. Our pipeline holds potential applications in health surveillance by regulatory agencies or pharmaceutical companies, aiding in the identification of safety concerns. Moreover, it could be used by research teams for retrospective analysis of events.

Introduction

Social media as a complementary data source for pharmacovigilance.

One primary mission of regulatory agencies such as the FDA (Food and Drug Administration) or the EMA (European Medicines Agency) is to monitor drug usage and adverse drug events (ADEs) to mitigate the risks associated with drugs within the population. This task entails analyzing diverse data sources, including clinical trials, postmarketing surveillance, spontaneous reporting systems, and published scientific literature. Despite the wealth of available data, some ADEs are not always detected promptly, largely because of underreporting. In France, for instance, underreporting was estimated to range between 78% and 99% from 1997 to 2002 [ 1 ]. To tackle this challenge, several countries have implemented systems allowing patients to report ADEs.

Additional sources for detecting ADEs have been under exploration, such as electronic patient records [ 2 - 4 ] and social media platforms [ 5 - 9 ]. While some argue that social media alone cannot serve as a primary source for signal detection [ 10 ], it can be viewed as a valuable secondary source for monitoring emerging adverse drug reactions or reinforcing signals previously identified through spontaneous reports stored in traditional pharmacovigilance databases [ 11 ]. In a prior study by the authors, patient profiles and reported ADEs found in web forums were compared with those in the French Pharmacovigilance Database (FPVD). The forums tended to represent younger patients, more women, less severe cases, and a higher incidence of psychiatric disorder–related ADEs compared with the FPVD [ 12 ]. Moreover, forums reported a greater number of unexpected ADEs. Over the past decade, several tools for evaluating social media posts have been described in the literature [ 13 ]. Specifically, effective ADE detection in social media necessitates both quantitative and qualitative analyses of data [ 14 ].

Qualitative Approach for Individual Assessment of Posts

Qualitative assessment entails evaluating whether users’ messages contain pertinent information for an assessment akin to a pharmacovigilance case report. This includes details such as the patient’s age and gender, the severity of the case, the expectedness and timeline of the adverse event, time-to-onset, dechallenge (outcome upon drug withdrawal), and rechallenge (outcome upon drug reintroduction). For instance, GlaxoSmithKline Inc. implemented the qualitative approach Insight Explorer, which facilitates the collection of extensive data for causality and quality assessment. Users can input data including personal information (eg, age range, gender) and product details (eg, name, route of administration, duration of use, dosage). This approach was adapted for the WEB-RADR (Recognizing Adverse Drug Reactions) project to manually construct a gold standard of curated patient-authored text [ 15 ].

Quantitative Approach for Monitoring Adverse Drug Events on Social Media

Quantitative evaluation involves analyzing extracted data using descriptive and analytical statistics, such as signal detection and change-point analysis. Numerous projects have been undertaken to monitor ADEs on social media. One of the earliest projects is the PREDOSE (Prescription Drug Abuse Online Surveillance and Epidemiology) project [ 5 ], which investigates the illicit use of pharmaceutical opioids reported in web forums. While the PREDOSE project showcased the potential of leveraging social media for opioid monitoring, notable limitations are the lack of deidentification and signal detection methods. MedWatcher Social, a monitoring platform for health-related web forums, Twitter, and Facebook, represents a prototype application developed in 2014 [ 16 ]. Yeleswarapu et al [ 6 ] outlined a semiautomatic pipeline that applies natural language processing (NLP) tasks to extract ADEs from MEDLINE abstracts and user comments from health-related websites. However, this pipeline was not intended for routine use.

The Domino’s interface [ 17 ], developed in 2018 by the University of Bordeaux in France and funded by the French Medicines Agency (Agence nationale de sécurité du médicament et des produits de santé [ANSM]), was designed to analyze drug misuses in health-related web forums using NLP methods and the summary of product characteristics. Initially tailored for antidepressant drugs, this tool does not primarily focus on ADE surveillance.

Another pipeline, described by Nikfarjam et al in 2019 [ 7 ], used a neural network–based named entity recognition system specifically designed for user-generated content in social media. This platform is dedicated to identifying the association of cutaneous ADEs with cancer therapy drugs. The study focused on a selection of drugs and only examined 8 ADEs.

Magge et al [ 8 ] described a pipeline aimed at the extraction and normalization of adverse drug mentions on Twitter. Their pipeline consisted of an ADE classifier designed to identify tweets mentioning an ADE, which were then mapped to a MedDRA (Medical Dictionary for Regulatory Activities Terminology) code. However, the normalization process was confined to the ADEs present in the training set. Neither Nikfarjam’s nor Magge’s pipeline provides a graphical user interface.

Some private companies also offer tools for analyzing social media for pharmacovigilance purposes. For instance, the DETECT platform was developed as part of a collaborative project in France by Kappa Santé [ 18 ]. This system enabled the labeling of posts with known controlled vocabulary concepts, and signal detection was conducted [ 19 ]. Within the scope of this project, Expert System Company implemented BIOPHARMA Navigator to extract web forum posts, while the Luxid Annotation Server provided web services for the automatic annotation of posts.

An important finding from the studies of the last decade is that while regulatory agencies have begun using data sources beyond spontaneous reports, social media has yet to be fully leveraged in real-world settings due to the immaturity of available solutions. Primarily, these solutions are essentially proofs of concept that lack scalability and are challenging for experts to evaluate routinely, primarily due to the absence of a graphical user interface to present information.

Our aim was to assess the potential of integrating social media into pharmacovigilance and enhancing decision-making with this novel data source. To achieve this, our objective was to develop and assess a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. The goal was to create a user-friendly tool that enables regulatory authorities to make better-informed decisions effectively.

This article presents the design and implementation of our pipeline dedicated to harnessing posts from social media. In addition, we showcase the use of the pipeline through a specific use case, emphasizing the importance of monitoring drugs in social media to better address patients’ expectations.

The PHARES project (Pharmacovigilance in Social Networks), funded from 2017 to 2019 by the French ANSM, aimed to develop a software suite (a pipeline) enabling pharmacovigilance users to analyze social networks, particularly messages posted on forums. The objective of the pipeline is to facilitate routine use through continuous post extraction and quantitative data analysis from web forums, specifically tailored for the French language.

The pipeline is made up of 4 modules, each referring to its own methods ( Figure 1 ):

The Scraper module, which extracts posts from forums using a previously developed tool, Vigi4Med (V4M) scraper [ 9 ], and produces a comma-separated values (CSV) file filled with the texts extracted.

The Annotation module, which extracts elements of interest from the posts and registers annotations in CSV files, with each line representing an annotation of an ADE or a drug. When a causality relationship is identified, both an ADE and a drug are annotated on the same line.

The Statistical module, which performs quantitative analysis on the annotated posts, generating numerical data, tables, or figures.

analysis method case study

The Interface module, which supports query definition and visualization of results.

The methodology used to evaluate the PHARES pipeline involved comparing its performance with existing platforms mentioned above, in accordance with a set of criteria established with prospective PHARES users. The criteria, specific to each module, are as follows:

  • General level: focus on ADEs, designed for routine usage.
  • Scraper: collects all posts of a selected website, performs deidentification, allows to extract posts from web forums, and is open source.
  • Statistics: the temporal evolution of posts or annotations is displayed and a change-point analysis (detecting breakpoints) is possible.
  • Signal detection: allows to apply at least one signal detection method, displays the temporal evolution of the proportional reporting ratio (PRR), and allows to perform a logistic regression–based signal detection method.
  • Graphical user interface: has an interface for users.

Scraper Module

V4M Scraper is an open-source tool designed for data extraction from web forums [ 9 ]. Its primary functions are optimizing scraping time, filtering out posts primarily focused on advertisements, and structuring the extracted data semantically. The module operates by taking a configuration file as input, which contains the URL of the targeted forum. The algorithm navigates through forum pages and generates resource description framework (RDF) triplets for each extracted element, allowing for potential alignment with external semantic resources. A caching mechanism has been integrated into this tool to maintain a local copy of previously visited pages, thereby avoiding redundant requests to websites for already scraped web pages, particularly in cases of errors or testing, for example. Vigi4Med V4M Scraper was customized for the PHARES project, as indicated by the red elements in Figure S1 in Multimedia Appendix 1 . The database format (Figure S2 in Multimedia Appendix 1 ) was implemented to enhance interaction with the interface. Specifically, the main scraping script was adjusted to produce a simplified tabular format (CSV) of the extracted data and to store these data in a database. This modification aims to facilitate input to the subsequent module of the pipeline (annotation). V4M Scraper was customized to enable a continuous scraping routine, wherein data extracted from web forums are automatically and regularly annotated and registered. A log file was integrated into the scraper structure to maintain a record of the last scraped element. This log file ensures that the daily routine scraping always begins from the last scraped point. An automation tool (crontab) is used to schedule the execution of the pipeline for each forum on a daily basis at a specific time.

A total of 23 public French health-related web forums were selected through a combination of Google searches and from a list of certified health websites provided by the HON Foundation, in collaboration with the French National Health Authority (HAS). The selection criteria included the requirement for websites to be hosted in France, feature a discussion board or space for sharing experiences, and have more than 10 patient contributions. Furthermore, Twitter posts are collected and analyzed by the pipeline. This is achieved using the Twitter API for data collection, followed by employing the same modules used for processing web forum posts.

Annotation Module

Entities corresponding to drugs and pathological conditions in social media were identified and annotated using an NLP pipeline [ 20 ]. Initially, conditional random fields were used to account for global dependencies [ 21 ]. Specifically, the model considers the entire sequence when making predictions for individual tokens. This approach is advantageous for entity extraction tasks, as the presence of an entity in one part of the text can influence the likelihood of other entities in the vicinity. Second, a support vector machine is used to predict the causality relationship between an entity identified as a drug and another entity identified as an ADE. The annotation method used in this module was implemented at an early stage of the pipeline’s design. Currently, the named entity recognition task of this module is undergoing revision to incorporate more recent advancements in NLP algorithms [ 22 - 26 ].

In a third step, the detected annotations were normalized using codes from the MedDRA and the Anatomical Therapeutic Classification (ATC) to ensure they were suitable for signal detection purposes.

MedDRA is an international medical hierarchical terminology comprising 5 levels used to code potential ADEs in pharmacovigilance. The highest level is the system organ class, which is further divided into high-level group terms, then into high-level terms, preferred terms (PTs), and finally lowest level terms. Typically, the PT level is used in pharmacovigilance signal detection.

The ATC classification system is a drug classification used in France for pharmacovigilance purposes. It categorizes the active ingredients of drugs based on the organ system they primarily affect. The classification comprises 5 levels: the anatomical main group (consisting of 14 main groups), the therapeutic subgroup, the therapeutic/pharmacological subgroup, the chemical/therapeutic/pharmacological subgroup, and the chemical substance. Typically, the fifth level (chemical substance) is used in pharmacovigilance signal detection.

The outputs of the annotation module are CSV files with the following variables:

  • Concerning the post: forum name, post ID, and date
  • Concerning the ADE: verbatim, normalized term, unified medical language system’s concept unique identifier, and MedDRA code
  • Concerning the drug: verbatim, normalized term, active ingredient, and ATC code

In these CSV files, each line can consist of either an adverse event (ADE) annotation, a drug annotation, or both when a causality relationship has been identified between the drug and the ADE. Table 1 provides a sample of the database.

In a prior study, we selected posts where at least one ADE associated with 6 drugs (agomelatine, baclofen, duloxetine, exenatide, strontium ranelate, and tetrazepam) had been detected by this algorithm. A manual review revealed that among 5149 posts, 1284 (24.94%) were validated as pharmacovigilance cases [ 12 ]. The fundamental metrics used to assess the performance of the annotation module were precision (P), recall (R), and their harmonic mean F 1 -score. To calculate these metrics, it is necessary to evaluate false negatives for nonrecognition of relevant terms, false positives for irrelevant recognitions, and true positives for correct recognitions. Precision, recall, and F 1 -score are defined as follows:

Precision = (true positive)/(true positive + false positive); recall = (true positive)/(true positive + false negative); F 1 -score = (2 × precision × recall)/(precision + recall) (1)

In the “Results” section, we present a comparison of the performance of the annotation module with the performance of state-of-the-art methods [ 8 , 22 , 25 , 26 ].

Forum namePost IDDateTimeADE verbatimADE normalizedConcept unique identifierDrug verbatimDrug normalizedActive ingredientMedDRA codeATC code
Atoute7354October 8, 201821:37:00Maux de têteCéphaléeC0018681LévothyroxLEVOTHYROXLevothyroxine sodiqueH03AA01
Atoute7354October 8, 201821:37:00Maux de têteCéphaléeC0018681Calcium
Atoute7354October 8, 201821:37:00Nodules cancereuxLévothyroxLEVOTHYROXLevothyroxine sodiqueH03AA01
Atoute7354October 8, 201821:37:00Nodules cancereuxCalcium
Atoute7354October 8, 201821:37:00FatigueFatigueC0015672LévothyroxLEVOTHYROXLevothyroxine sodique10016256H03AA01
Atoute7354October 8, 201821:37:00fatigueFatigueC0015672Calcium10016256
Atoute7354October 8, 201821:37:00Perte de poidsPoids diminuéC0043096LévothyroxLEVOTHYROXLevothyroxine sodique10048061H03AA01
Atoute7354October 8, 201821:37:00Perte de poidsPoids diminuéC0043096Calcium10048061

a ADE: adverse event.

b MedDRA: Medical Dictionary for Regulatory Activities Terminology.

c ATC: Anatomical Therapeutic Classification.

d No data are available for this slot.

Statistical Module

This module generates general statistics and diagrams for web forums or Twitter. It provides data such as the number of annotated posts (related to the drug, the ADE, or both), the count of drug-ADE pairs identified, and the distribution of ADEs’ MedDRA-PTs. In addition, a change-point analysis method was used to detect significant changes over time in the mean number of posts mentioning the drug and ADE [ 27 ].

Besides, several statistical signal detection methods were implemented to generate potential signals. Safety signals, which provide information on adverse events that may potentially be caused by a medicine, were further evaluated by pharmacovigilance experts to determine the causal relationship between the medicine and the reported adverse event.

The statistical module implements 3 signal detection methods, including 2 well-known and frequently used disproportionality signal detection methods: the PRR [ 28 ] and the reporting odds ratio (ROR) [ 29 ]. In addition, a complementary method, a logistic regression–based signal detection method known as the class imbalanced subsampling lasso [ 30 ], was used.

PRR and ROR are akin to a relative risk and an odds ratio, respectively. However, they differ in their denominators: as the number of exposed patients is typically unknown in pharmacovigilance databases, the denominator in PRR and ROR calculations is the number of cases reported in the pharmacovigilance database.

PRR and ROR are specific to each drug-ADE pair and can be directly computed from the contingency table ( Table 2 ).

Adverse drug event of interestOther adverse drug events
Drug of interest
Other drugs

The PRR compares the proportion of an ADE among all the ADEs reported for a specific drug with the same proportion for all other drugs in the database (Equation 2). A PRR significantly greater than 1 suggests that the ADE is more frequently reported for patients taking the drug of interest, while a PRR equal to 1 suggests independence between the 2 variables.

PRR = [a/(a + b)]/[c/(c + d)] (2)

The ROR quantifies the strength of the association between drug administration and the occurrence of the ADE. It represents the ratio of the odds of drug administration when the ADE is present to the odds of drug administration when the ADE is absent (Equation 3). When the 2 events are independent, the ROR equals 1. An ROR significantly greater than 1 suggests that drug administration is associated with the presence of the ADE.

ROR = ad / bc (3)

We considered events over posts for the calculation of disproportionality statistics. If the same drug-ADE pair was identified multiple times within a post, the pair was counted as many times as it occurred in the calculation.

Disproportionality analysis has certain limitations, including the confounding effect resulting from coreported drugs and the masking effect, where the background relative reporting rate of an ADE is distorted by extensive reporting on the ADE with a specific drug or drug group. Caster et al [ 31 ] demonstrated through 2 real case examples how multivariate regression–based approaches can address these issues. Harpaz et al also suggested that logistic regression could be used for safety surveillance [ 32 ]. Initially designed for pharmacovigilance case reports, we hypothesize that they may also be applicable to posts.

The logistic regression model specifically focuses on a particular ADE or a group of ADEs. It involves creating a vector that represents the presence (1) or absence (0) of the ADE of interest in the pharmacovigilance case (in our case, in the post). Additionally, a matrix is generated to represent the administration or nonadministration of all drugs in the database by the patient (1 for administration and 0 for nonadministration). Figure S3 in Multimedia Appendix 1 illustrates an example of using logistic regression. In our case, we assumed that if a drug was annotated in the post, it was taken by the patient. The logistic regression aims to predict the probability of the presence of the ADE (ADE=1) of interest based on the presence of all ( N m ) drugs in the database (Equation 4), where X represents the distribution of the presence/absence of the drugs. The adjusted factors included only concomitant medications, as patient-related factors are often missing in web forums’ posts. Therefore, we did not need to address the impact of missing data, which should be evaluated when necessary.

ln([P(X|ADE=1)]/[P(X|ADE=0)]) = a + b1 × Drug1 + ... + bi × Drug i + .. . + bNm × Drug Nm (4)

The selection of the drugs depends on the parameter b i . If b i <0, the drug i decreases the risk of the ADE, and if b i >0, the drug i increases the risk of the ADE.

Then, 2 sets are defined:

  • S 1 : set of n 1 posts with an annotation of the ADEs of interest.
  • S 0 : set of n 0 posts without an annotation of the ADEs of interest.

In our case n 0 >> n 1 , indicating a significant imbalance toward posts lacking annotations of the ADEs of interest. To address this issue, we took a subsample with a more favorable ratio of posts with annotated ADEs versus those without. Additionally, to enhance result stability, we conducted multiple draws instead of just one.

In practice, we generated B subsamples. Each subsample was constructed by randomly drawing, with replacement, n 1 posts from S 1 and R posts from S 0 , where R=max(4 n 1 , 4 N m ). The choice of 4 n 1 was inspired by case-control studies, while 4 N m was included to ensure an adequate number of observations considering the multitude of predictors.

analysis method case study

We implemented a change-point analysis method described in [ 27 ] to detect whether there was a change in the evolution over time of a chosen statistic, such as the number of a specific drug-ADE pair, the number of ADEs associated with a specific drug, or the number of drugs associated with a specific ADE. The method uses the Cumulative Sum (CUSUM) algorithm to analyze the evolution of statistics over time, comparing current values with the period mean. It identifies breakpoints by calculating the highest difference in statistical values and comparing it with random samples. The process repeats for periods before and after detected breakpoints until no more are found.

User Interface Module

The user interface module facilitates user interaction with the pipeline in a user-friendly manner. The interface comprises a dashboard divided into 2 main parts. The left dark column ( Figure 2 ) serves as a control sidebar, where users can select parameters to filter the data, including the forum, period, drug(s) according to the ATC classification, and ADE(s) according to a level in the MedDRA hierarchy. On the right side of the interface, various visualizations are available, organized into several tabs such as “Forum Statistics” and “Consultation of Posts,” with additional tabs for statistics that become active upon querying.

Before applying a specific query, the interface provides general information about the currently available data ( Figure 2 ), including the total annotated posts since 2017 (n=2,081,296) and total annotations since 2017 (n=2,454,310). In addition, a “Consultation of Tweets” tab (not visible in the figure) displays the total annotated tweets since March 2020 (n=46,153).

Furthermore, several tabs corresponding to different types of statistics, including “Forums Statistics” and “Twitter Statistics,” provide general statistics and diagrams for web forums and Twitter. Examples of these are pie charts showing forum distribution, line charts depicting the evolution of drug and ADE mentions, histograms displaying ADE distribution by system organ class, and line charts illustrating the temporal trend of posts containing the drug and an ADE, as shown in Figures 3 and 4 . The “Annotations Plot” tab displays annotations of drugs and adverse effects selected by the user, along with forum information, PTs, high-level terms, high-level group terms, dates, and hours. The “Logistic Regression” tab allows users to choose parameters for applying logistic regression. In the “Disproportionality” tab, users can choose between the PRR and ROR methods, with the time evolution of the chosen method displayed. The “Change-Point” tab enables analysis of temporal evolution, with identified breakpoints indicated. The “Consultation of Posts” and “Consultation of Tweets” tabs provide details on annotated posts/tweets, including downloadable tables. The statistical module performs calculations based on user queries, updating the interface accordingly. If multiple drugs or adverse events are selected, they are treated as new entities for analysis.

The interface was implemented using the R language and environment (R Foundation) for statistical computing and graphics [ 33 ], leveraging the Shiny package [ 34 ] for development.

analysis method case study

Ethical Considerations

A statement by an Institutional Review Board was not required because we used only publicly available data that do not necessitate Institutional Review Board review.

This study complied with the European General Data Protection Regulation (GDPR), which has been in force since 2018 in Europe [ 35 ]. The GDPR enhances the protection of individuals by introducing the right to be informed about the processing of personal data. However, informing each user individually may be impractical. Therefore, the GDPR introduces 2 legal conditions where informed consent is not mandatory, which can be interpreted as supporting the processing of web forum posts for pharmacovigilance (Article 9): “(e) processing relates to personal data which are manifestly made public by the data subject; [. . .] (i) processing is necessary for reasons of public interest in the area of public health, such as [. . .] ensuring high standards of quality and safety of health care and of medicinal products . . ..” The GDPR also requires data processing to “not permit or no longer permits the identification of data subjects” (Article 89). Deidentification was conducted during the extraction of posts from web forums to ensure privacy [ 9 ]. User identifiers in the main RDF file were encrypted using the SHA1 algorithm [ 36 ]. The correspondence between these encrypted identifiers and the original keys is presented in RDF triplets in a separate file, referred to as the “keys file.” Therefore, the only way to retrieve the original authors’ identities is by concatenating the main RDF containing the encrypted data with the keys file, which is kept in a secured location. Moreover, all our data processing was carried out on a secured server with restricted access.

General Results About the Pipeline

The primary outcome of this study is the operational PHARES pipeline itself. Daily extraction and annotation of posts are initiated and imported into the database linked to the user interface. In this paper, the platform’s use will be demonstrated through a specific use case on the analysis of Levothyrox ADE mentions in forums (discussed later). In addition, we conducted a comparative analysis of the PHARES pipeline with the existing platforms mentioned in the “Introduction” section, based on the criteria listed in the “Methods” section.

Of the 10 identified pipelines, half were public and half were private. While 8 out of 10 focused on ADEs, only 4 were designed for routine usage. Five scrapers were open source, and all posts from considered websites were extracted by only 6 of the scrapers (with others extracting posts under certain conditions). Six scraped web forum posts, but only 3 performed deidentification. Additionally, 4 pipelines focused on the French language. A total of 6 pipelines displayed the temporal evolution of the number of posts, but only 1 conducted a change-point analysis. Signal detection methods were performed by only 4 of them, with none displaying the temporal evolution of the PRR nor a logistic regression–based method. Finally, 6 of them had an interface ( Table 3 ).

PipelineGeneralScraperAnnotationStatisticsSignal detection

Focus on ADEs Routine usagePublic/privateAll postsDeidentificationWeb forumsOpen sourceFrench languageTemporal evolutionChange-point analysisSignal detectionPRR temporal evolutionLogistic regressionInterface
PREDOSE XPublicXXXXXX
Insight ExplorerXPrivateXXXXXXXXX
MedWatcher SocialPublicXXXXXX
Yeleswarapu et al [ ]XPrivateXXXXXXXXXX
DominoXPublicXXXXX
Nikfarjam et al [ ]XPublic and PrivateXXXXXXXXXXX
Magge et al [ ]XPublicXXXXXXXX
ADR-PRISM XPublic and PrivateXXXX
Kappa SantéPrivateXXX
Expert SystemXPrivateXXXXXX

a PHARES: Pharmacovigilance in Social Networks.

b The X symbol means that the characteristic is missing and the symbol ✓ means the characteristic is fulfilled.

c ADE: adverse drug event.

d PRR: proportional reporting ratio.

e PREDOSE: Prescription Drug Abuse Online Surveillance and Epidemiology.

f ADR-PRISM: Adverse Drug Reaction from Patient Reports in Social Media.

Annotation Module’s Comparison With Up-to-Date State-of-the-Art Methods

We also compared the performance of our annotation process with those of up-to-date state-of-the-art methods ( Table 4 ).

While the annotation module demonstrated good performance for named entity recognition ( F 1 -score=0.886), it remains slightly below the state of the art. Presently, in medical texts, the best performances are achieved by Hussain et al [ 25 ] and Ding et al [ 26 ] for the named entity recognition task, and by Xia [ 22 ] for the relationship extraction task. On Twitter, known for its notably more complex data, Hussain et al [ 25 ] achieved slightly better results than our annotator, while Ding et al [ 26 ] achieved slightly worse results.

AnnotatorLanguageDataNatural language processing methodNamed entity recognition (precision; recall; -score)Relationship extraction (precision; recall; -score)
PHARES FrenchPatient’s web drug reviewConditional random fields and support vector machines0.926; 0.845; 0.8860.683; 0.956; 0.797
Magge et al [ ]EnglishTwitterBERT neural networks0.82; 0.76; 0.78
Xia [ ]EnglishMedical textsHAMLE model0.929; 0.914; 0.921
Hussain et al [ ]EnglishMedical texts (PubMed) and TwitterBERT0.982; 0.964; 0.976 (PubMed) and 0.840; 0.861; 0.896 (X/Twitter)
Ding et al [ ]EnglishMedical texts (PubMed) and TwitterBGRU + char LSTM attention + auxiliary classifier0.867; 0.948; 0.906 (PubMed) and 0.785; 0.914; 0.844 (Twitter)

a The 2 categories are entity recognition, which is the detection of a drug or ADE mention, and relationship extraction, which is the detection of a relation between a drug and an ADE.

b PHARES: Pharmacovigilance in Social Networks.

c BERT: Bidirectional Encoder Representations from Transformer.

d Not available.

e HAMLE: Historical Awareness Multi-Level Embedding.

f BGRU: Bidirectional Gated Recurrent Unit.

g LSTM: Long-Short-Term-Memory.

Summary of the Result

From January 1, 2017, to February 28, 2021, a total of 2,081,296 posts were extracted from 23 French web forums ( Table 5 ). We obtained 713,057 normalized annotations of drugs, 1,527,004 normalized annotations of ADEs, and 437,192 annotations of normalized drug-ADE couples. The number of posts annotated with at least one normalized drug-ADE couple was equal to 125,279 (6.02%). Table 4 summarizes the number of posts extracted per forum, the publication dates, and the description of the web forum. For 1 forum, the publication dates were not available. A total of 9 were generalist health forums, 3 were specialized for parents of a young baby, 2 for families, 3 for mothers, 2 specialized in thyroid issues, 1 for pregnant women, 1 for women, 1 for parents of a teenager or for teenagers, 1 for sports persons, and 1 specialized in rare diseases.

ForumExtracted posts, nPublication date of the first extracted postPublication date of the last extracted postDescription
thyroideNEW451,253February 15, 2001February 25, 2021Specialized in thyroid issues
doctissimoSante248,691March 19, 2003January 16, 2021Generalist health forum
doctissimoNutrition183,730December 30, 2002January 16, 2021Specialized in nutrition
infoBebe127,341November 30, 2000March 08, 2019Specialized for parents of a young baby
atoute118,415February 05, 2005February 28, 2021Generalist health forum
notreFamille97,098March 16, 2000October 26, 2017Specialized for families
magicMaman96,713June 14, 1999February 22, 2021Specialized for mothers
doctissimoMed95,531August 05, 2002January 15, 2021Generalist health forum
doctissimoGrossesse93,449November 09, 2006January 15, 2021Specialized for pregnant women
thyroide73,376September 25, 2001January 07, 2019Specialized in thyroid issues
aufeminin72,732April 05, 2001January 09, 2020Specialized for women
mamanVie69,167June 07, 2006April 10, 2019Specialized for mothers
onmeda61,428July 25, 2001February 24, 2021Generalist health forum
ados58,181June 20, 2006March 08, 2019Specialized for parents of a teenager or for teenagers
carenity52,659May 16, 2011August 29, 2020Generalist health forum
famili51,844November 06, 2000November 17, 2019Specialized for families
babyFrance43,806January 20, 2003April 30, 2018Specialized for parents of young baby
bebeMaman38,450Specialized for mothers of young baby
alloDocteurs15,833June 15, 2009February 09, 2021Generalist health forum
reboot9383May 04, 2016February 25, 2021Generalist health forum
futura6765May 12, 2003February 22, 2021Generalist health forum
sportSante6350May 10, 2011January 14, 2020Specialized for sportsperson
maladieRares4827October 09, 2012May 14, 2020Specialized in rare diseases
queChoisir4250June 16, 2003February 11, 2021Generalist health forum

a Not available.

Use Case: Analysis of Levothyrox ADE Mentions in Forums

To demonstrate the usage of the pipeline, we chose to focus on Levothyrox as a case study. Levothyrox is a drug prescribed in France since 1980 for hypothyroidism and circumstances where it is necessary to limit the thyroid-stimulating hormone. In 2017, a new formula of Levothyrox, differing from the 30-year-old drug at the excipient level (with lactose being replaced by mannitol and citric acid in the new formula), was marketed with widespread media coverage. In parallel, an unexpected increase in notifications of ADEs for this drug was detected. Viard et al [ 37 ] were unable to find any pharmacological rationale to explain that signal. Approximately 32,000 adverse effects were reported by patients in France in 2017, representing 42% of all the ADEs collected yearly [ 38 ]. Most of these notifications concerned the new formulation of Levothyrox and led to the “French Levothyrox crisis.” In 2017, 1664 notifications of ADEs were spontaneously reported by patients to the Pharmacovigilance Center of Nice. Among the 1544 reviewed notifications, 1372 concerned Levothyrox while only 172 concerned other drugs [ 37 ].

In this use case, the study period was from January 1, 2017, to February 28, 2021, and the drugs included were 2 drugs from the “H03AA Thyroid hormones” ATC class: “Levothyroxine sodium” and “associations of levothyroxine and liothyronine.” A total of 17 forums were selected as they included at least one post with information about these drugs. Posts were extracted, annotated, and analyzed through the pipeline from several forums ( Table 6 ). Signal detection methods were applied to an ADE chosen as it frequently appeared with Levothyrox in our data: “tiredness.” A signal can be detected when the lower bound of the 95% CI of the logarithm of the PRR is greater than 0. For logistic regression, we applied the tenth quantile. A total of 11,340 posts contained an annotation concerning the drugs of interest. Figure S4 in Multimedia Appendix 1 illustrates the source and evolution over time of these posts. Out of a total of 50,127 annotations of Levothyrox, they principally originated from the Vivre sans thyroïde forum and were mostly posted in mid-2017 ( Figure 4 , Table 6 ). The results of the statistical analysis were displayed by the user interface.

ADEs annotated with Levothyrox were mainly from system organ classes: general disorders and administration site conditions (29.6%), metabolism and nutrition disorders (11.6%), and endocrine disorders (11.4%). The PTs mostly found in association with Levothyrox are listed in Table 7 . All this information is accessible in the interface module (Figure S5 in Multimedia Appendix 1 ).

We chose the PT “tiredness” for the signal detection analysis. A total of 85,976 posts were annotated with either one of the drugs of interest or the ADE tiredness. Among them, 1841 Levothyrox-tiredness couples were found, mostly in 2017 ( Table 7 ).

Figure 5 illustrates the time evolution of the PRR for the Levothyrox-tiredness couple. Figure S6 in Multimedia Appendix 1 displays the source and evolution over time of French web forums’ posts for this couple. A signal is consistently generated throughout the period as the logarithm of the PRR is always greater than 0.

analysis method case study

ForumValue, nCumulative frequency, %
Vivre sans thyroïde41,21182.21
Doctissimo Santé423090.65
Doctissimo Grossesse147693.60
Doctissimo Nutrition117795.94
Carenity86397.67
Allo docteurs50298.67
Atoute17099.01
Doctissimo medicaments16699.34
Que choisir8599.51
Maladie rares7699.66
Au feminin5899.77
Sport santé5099.87
Onmeda4899.97
Famili799.98
Futura599.99
Maman vie2100.00
Magic maman1100.00
Preferred termsValues, n
Pain1882
Tiredness1841
Faintness1267
Hypothyroidism1110
Dizziness912
Insomnia627
Palpitations571
Hyperthyroidism568
Malignant tumor560
Anxiety498
Overdose490
Nervous tension484
Myalgia409
Nausea388
Stress380
Diarrhea354
Tachycardia322
Muscle spasms321
Convulsions302
Arthralgia276

analysis method case study

A total of 11 drugs were found to be associated with tiredness using logistic regression: paclitaxel, pegfilgrastim, Levothyrox, glatiramer acetate, escitalopram ferrous sulfate, the combination of Levothyrox and liothyronine, secukinumab, methotrexate, bismuth potassium, tetracycline, and metronidazole.

Change-point analysis was conducted on the monthly evolution of the number of Levothyrox-ADE couples detected in web forums. Six breakpoints were identified ( Figure 6 ), and 3 of them correlated with an increase in the number of ADEs found with Levothyrox on web forums. These increases occurred in August 2017 and in September and December 2018.

This use case demonstrates that the results obtained through the pipeline, particularly in the context of Levothyrox, align with findings in the literature derived from more traditional data sources such as case reports in pharmacovigilance (see the “Discussion” section). It underscores the potential of leveraging such a pipeline to monitor a drug, not only retrospectively but also in real time using social media. Consequently, PHARES has the capability to potentially uncover new signals in pharmacovigilance.

analysis method case study

Principal Findings

To align with our objective, we implemented and evaluated a pipeline that processes data from the extraction of web forum posts to the generation of indicators and alerts within a visual and interactive environment. Through this pipeline, we demonstrated that quantitative analysis can be conducted through the interface without requiring the user to code. We discovered the feasibility of acquiring information akin to the literature regarding a drug’s ADEs, as well as unexpected ADEs and significant event dates related to a drug. This underscores the relevance and utility of such a pipeline.

A conceptual contribution of this research was the proposal of a methodology for designing a pipeline to facilitate pharmacovigilance studies on web forums. This involved describing 4 independent modules and outlining their interactions. Additionally, another contribution was the adaptation of certain pharmacovigilance analysis methods for the examination of data extracted from web forum posts. The logistic regression–based method presented in this article was originally tailored for pharmacovigilance cases to consider co-prescriptions of drugs. We have adapted it to suit the analysis of pharmacovigilance data extracted from web forum posts.

Comparison With Prior Work

The PHARES pipeline offers added value compared with previous pipelines in terms of the criteria set, which reflects an analysis of experts’ needs for routine monitoring of ADEs in social media. Unlike previous approaches, the scrapers used in PHARES routinely perform deidentification, and the inclusion of change-point analysis, the evolution of PRRs over time, and a logistic regression–based signal detection method were previously unavailable. The temporal evolution of the number of posts and a signal detection method are also seldom supported. Designed for routine usage and focused on ADEs, all posts from selected web forums are scraped and deidentified using an open-source scraper.

The period and selected web forums differed between both studies: Audeh et al [ 38 ] covered the period from January 2015 to December 2017, while our study spanned from January 2017 to February 2021. Additionally, Audeh et al [ 38 ] included only 1 web forum specialized in thyroid issues, whereas we incorporated this specific forum along with 16 others. The main ADEs associated with Levothyrox in our study align with those found by Audeh et al [ 38 ] on similar data, albeit without using the interface. In our study, the 10 most frequent symptoms were pain, tiredness, faintness, hypothyroidism, dizziness, insomnia, palpitations, hyperthyroidism, malignant tumor, and anxiety. By contrast, Audeh et al [ 38 ] reported tiredness, weight gain, pain, ganglions, hot flush, chilly, inflammation, faintness, weight loss, and discomfort.

Furthermore, the PHARES pipeline surpasses previous efforts, particularly regarding several criteria. These include the annotation tool, where only 4 pipelines were identified using a French annotator tool. In terms of available statistics, only 1 pipeline met both criteria we identified. Regarding signal detection, among the 3 criteria identified, 5 pipelines matched with only 1, while the remaining 5 matched with none.

In the use case, a notable increase in the number of ADEs associated with Levothyrox was detected using the change-point analysis method a few months after the introduction of the new formula in March 2017, specifically in August 2017. This surge coincided with the initial declaration to the pharmacovigilance network and a petition initiated by patients to reintroduce the former formula in June 2017. We compared these findings with results from a pharmacovigilance study based on spontaneous reporting. Out of 1554 notifications spontaneously addressed by patients to the Pharmacovigilance Center of Nice from January 1, 2017, to December 31, 2017, 1372 were related to the new formula of Levothyrox, representing 7342 ADEs. Our comparison with these data clarified our findings. The 10 most frequently reported ADEs in these notifications closely resembled our own results [ 37 ]. These were asthenia, headache, dizziness, hair loss, insomnia, cramps, weight gain, nausea, muscle pain, and irritability. Consequently, our results demonstrate coherence with the existing literature. This study illustrates the feasibility of identifying the date of significant events related to a drug. However, it is noteworthy that the detection of such events is not necessarily expedited through social media compared with the traditional pharmacovigilance system.

Limitations

The method used in our annotation process was integrated at an early stage during the pipeline’s design. Regarding the identification of drugs and symptoms, our annotation process exhibited the following performances: precision=0.926, recall=0.845, and F 1 -score=0.886 [ 20 ]. Similarly, for discerning the relationship between the drug and the ADEs, the performances were precision=0.683, recall=0.956, and F 1 -score=0.797 [ 20 ]. This study marked the inaugural publication on using NLP methods to identify ADEs in French-language web forums. The annotation process was thus developed using contemporary state-of-the-art methodologies at the time. However, it would now stand to gain from the integration of more recent NLP algorithms for named entity recognition [ 8 , 23 , 24 ]. These newer algorithms offer comparable performances while effectively handling more complex data, thereby enhancing the efficacy of NLP analysis. However, because of our emphasis on the genericity of the approach and the interoperability between the different modules rather than solely focusing on the performance of each module, we opted not to use these algorithms. Nevertheless, contemporary state-of-the-art methods for annotating ADEs from social media posts encompass convolutional neural networks trained on top of pretrained word vectors for sentence-level classification [ 24 ] and transformers using the bidirectional encoder representations from transformers (BERT) language model [ 39 ]. Hussain et al [ 25 ] introduced a multitask neural network based on BERT with hyperparameter optimization capable of sentence classification and named entity recognition. This model achieved performances of precision=0.840, recall=0.861, and F 1 -score=0.896 on the Twitter (X)-TwiMed data set. Additionally, Magge et al [ 8 ] presented a pipeline consisting of 3 BERT neural networks designed to classify sentences, extract named entities, and normalize those entities to their respective MedDRA concepts. The performances of this model were as follows: precision=0.82, recall=0.76, and F 1 -score=0.78 on the SMM4H-2020 data set (Twitter/X). Thanks to our modular design, it will be straightforward to substitute our current annotation process with an enhanced model in the future.

Several limitations should be acknowledged for future work. First, the scraper relies on the HTML structure of web forums, necessitating updates to its configuration files if a forum alters its page design. Additionally, our interface lacks the capability to incorporate alternate identifiers for drugs or ADEs. For instance, patients may commonly refer to the drug “baclofen” as “baclo” on social media platforms. Consequently, the number of posts pertaining to a drug or ADE could potentially be underestimated.

Forums must be selected before query execution to mitigate calculation time. However, selecting forums based on the presence of information related to a particular drug or ADE can introduce bias into signal detection methods, particularly in disproportionality analysis, where the drug-ADE pair may be overrepresented. Another limitation in qualitative analysis of posts is the inability of users to edit annotations or record typical pharmacovigilance qualitative data.

The assumption that all drugs mentioned in a post were consumed simultaneously by the user, as applied in the logistic regression–based method, introduces an evident bias.

One limitation associated with the use of social media data pertains to fraudulent posts. The pseudonymity inherent in these platforms provides malevolent individuals with the opportunity to disseminate false rumors. Additionally, patients might post identical or similar messages across multiple discussion boards, or even multiple times on the same board. Thus, it is crucial to consider these factors to mitigate biases in signal detection.

Perspectives

In the short to medium term, our objectives are updating the annotation module to enhance accuracy, improving the qualitative analysis by enabling users to edit and correct annotations, and expanding the range of signal detection methods available in the statistics module.

This method could indeed be beneficial for identifying potential drug misuse and unknown ADEs [ 40 ]. By categorizing pathological terms found in web forums based on their presence in the summary of product characteristics, we can distinguish between indications, known ADEs, and potential instances of drug misuse or unexpected ADEs. However, it is important to note that considering all pathological terms found in the summary of product characteristics as indications might obscure cases of drug inefficiency. Therefore, a nuanced approach is necessary to ensure comprehensive and accurate analysis.

We next tested our pipeline from the perspective of end users. However, the hypothesis was only partially confirmed, indicating the need for further studies. These studies should include evaluations with ergonomic criteria.

In the long term, our vision is to expand this tool to encompass other languages and themes beyond pharmacovigilance. This includes areas such as drug misuse, the consumption of food supplements, and the use of illegal drugs. French web forums dedicated to recreational drug use already exist, providing a valuable source of data for such endeavors.

Conclusions

Our hypothesis focused on the challenge encountered by regulatory agencies in using social media, primarily because of the lack of appropriate decision-making tools. To tackle this challenge, we devised a pipeline consisting of 4 editable modules aimed at effectively analyzing health-related French web forums for pharmacovigilance purposes. Using this pipeline and its user-friendly interface, we successfully demonstrated the feasibility of conducting quantitative analyses without the need for coding. This approach yielded coherent results and holds the potential to reveal new insights about drugs.

A practical implication of our pipeline is its potential application in health surveillance by regulatory agencies such as the ANSM or pharmaceutical companies. It can be instrumental in detecting issues related to drug safety and efficacy in real time. Furthermore, research teams can leverage this tool to retrospectively analyze events and gain valuable insights into pharmacovigilance trends.

Acknowledgments

The annotation module was developed by François Morlane-Hondère, Cyril Grouin, Pierre Zweigenbaum, and Leonardo Campillos-Llanos from the Computer Science Laboratory for Mechanics and Engineering Sciences (LIMSI). Code review for the graphical user interface in R language was performed by Stevenn Volant under a contract with the Stat4Decision company. Stat4Decision was not involved in designing the study and writing this article. This work was funded by the Agence nationale de sécurité du médicament et des produits de santé (ANSM) through Convention No. 2016S076 and was supported by a PhD contract with Sorbonne Université.

Data Availability

Our data were extracted from web forums that do not allow data sharing. Thus, as we are not the owners of the data we cannot make the data available. The scrapper we developed to extract these data is open source and can be used to extract data from web forum posts. The tool as well as full documentation (in English and French) of the code and configuration file are available online [ 41 ].

Conflicts of Interest

None declared.

Vigi4Med Scraper structure, PHARES database structure, example of data representation, and source and evolution over time of web forum posts. PHARES: Pharmacovigilance in Social Networks.

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Abbreviations

adverse drug event
Agence nationale de sécurité du médicament et des produits de santé
Anatomical Therapeutic Classification
Bidirectional Encoder Representations from Transformer
comma-separated values
Cumulative Sum
European Medicines Agency
Food and Drug Administration
French Pharmacovigilance Database
General Data Protection Regulation
French National Health Authority
Medical Dictionary for Regulatory Activities Terminology
natural language processing
Pharmacovigilance in Social Networks
Prescription Drug Abuse Online Surveillance and Epidemiology
proportional reporting ratio
preferred term
resource description framework
reporting odds ratio
Recognizing Adverse Drug Reactions

Edited by A Mavragani; submitted 01.02.23; peer-reviewed by S Matsuda, L Shang; comments to author 06.07.23; revised version received 20.10.23; accepted 12.03.24; published 18.06.24.

©Pierre Karapetiantz, Bissan Audeh, Akram Redjdal, Théophile Tiffet, Cédric Bousquet, Marie-Christine Jaulent. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.06.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

COMMENTS

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