how to lead a case study discussion

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Case Study At-A-Glance

A case study is a way to let students interact with material in an open-ended manner. the goal is not to find solutions, but to explore possibilities and options of a real-life scenario..

Want examples of a Case-Study?  Check out the ABLConnect Activity Database Want to read research supporting the Case-Study method? Click here

Why should you facilitate a Case Study?

Want to facilitate a case-study in your class .

How-To Run a Case-Study

• Before class pick the case study topic/scenario. You can either generate a fictional situation or can use a real-world example.
• Clearly let students know how they should prepare. Will the information be given to them in class or do they need to do readings/research before coming to class?
• Have a list of questions prepared to help guide discussion (see below)
• Sessions work best when the group size is between 5-20 people so that everyone has an opportunity to participate. You may choose to have one large whole-class discussion or break into sub-groups and have smaller discussions. If you break into groups, make sure to leave extra time at the end to bring the whole class back together to discuss the key points from each group and to highlight any differences.
• What is the problem?
• What is the cause of the problem?
• Who are the key players in the situation? What is their position?
• What are the relevant data?
• What are possible solutions – both short-term and long-term?
• What are alternate solutions? – Play (or have the students play) Devil’s Advocate and consider alternate view points
• What are potential outcomes of each solution?
• What other information do you want to see?
• What can we learn from the scenario?
• Be flexible. While you may have a set of questions prepared, don’t be afraid to go where the discussion naturally takes you. However, be conscious of time and re-focus the group if key points are being missed
• Role-playing can be an effective strategy to showcase alternate viewpoints and resolve any conflicts
• Involve as many students as possible. Teamwork and communication are key aspects of this exercise. If needed, call on students who haven’t spoken yet or instigate another rule to encourage participation.
• Write out key facts on the board for reference. It is also helpful to write out possible solutions and list the pros/cons discussed.
• Having the information written out makes it easier for students to reference during the discussion and helps maintain everyone on the same page.
• Keep an eye on the clock and make sure students are moving through the scenario at a reasonable pace. If needed, prompt students with guided questions to help them move faster.  
• Either give or have the students give a concluding statement that highlights the goals and key points from the discussion. Make sure to compare and contrast alternate viewpoints that came up during the discussion and emphasize the take-home messages that can be applied to future situations.
• Inform students (either individually or the group) how they did during the case study. What worked? What didn’t work? Did everyone participate equally?
• Taking time to reflect on the process is just as important to emphasize and help students learn the importance of teamwork and communication.

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Harvard Business School: Teaching By the Case-Study Method

Written by Catherine Weiner

Tips for Discussion Group Leaders

Once the program begins, each discussion group is assigned a leader who serves as the facilitator for each case study. Here are some tips for leading an insightful and productive exchange.

• Before you begin, make sure that all members understand the value of the discussion group process. You may find it helpful to have a brief conversation about the Discussion Group Best Practices listed above.
• Think of yourself as a discussion facilitator. Your goal is to keep the group focused on moving through the case questions. Don't feel that you need to master all the content more thoroughly than the other group members do.
• Guide the group through the study questions for each assignment. Keep track of time so that your group can discuss all the cases and readings, instead of being bogged down in the first case of the morning or afternoon.
• The study questions are designed to keep the group focused on the key issues that will contribute to an effective discussion in the larger classroom meeting. Don’t let your peers stray too far into anecdotes or issues that aren't relevant.
• If a subset of your living group appears to be dominating the discussion, encourage the less vocal members to participate. They'll be more apt to speak up if you ask them to share their unique perspectives on the topic at hand.
• If you have questions about how to handle a specific situation that may arise in your group, please reach out to the faculty or staff for assistance. We’re here to help you get the most out of your group discussions.

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.

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.

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Organizing Your Social Sciences Research Assignments

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

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

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

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

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

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

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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A Step-by-Step Guide To Case Discussion

By ashi jain.

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Are you comfortable in Decision Making in a given situation How aptly you analyze the situation with a logical approach How much time do you take in arriving at a decision How good are you in taking the rightful course of action

Solved Example:

Hari, the only working member of the family has been working an organization for 25 years. His job required long standing hours. One day, while working, he lost his leg in an accident. The company paid for his medical reimbursement.

Since he was a hardworking employee; the company offered him another compensatory job. He refused by saying, ‘Once a Lion, always a Lion’. As an HR, what solution would you suggest?

Identification of the Problem:

Obvious: accident, refusal of job, only earning member, his attitude, and inability to do his current job Hidden: the reputation of the company at stake, the course of action might influence other employees

Action Plan:

As an HR, you are first expected to check the company records and find out how a similar case has been dealt with in the past. Second, you need to take cognizance of the track record of the employee highlighted by the keyword ‘hardworking’.

Given the situation at hand, he is deemed unfit for his current role. However, the problem arises because of his attitude towards the compensatory job. Hence, in such a case, counselling is required.

Here, three levels of Counselling is required: 1.   Ist level is with Hari 2.   IInd level of counselling is required with the Union Leader (if any) to keep the collective interest and the reputation of the company in mind 3.   IIIrd level of counselling is required with his family members as they constitute of the afflicted party

If the counselling does not work, one should also identify a contingency plan or Plan B. In this case, the Contingency Plan would be – hire someone from his family for a compensatory role.

Note that the following options are out of scope and should be avoided: 1.   Increase Hari’s salary so that he gives in and agrees to do the compensatory job 2.   Status Quo – do not bother as long as the Company is making a profit 3.   Replace Hari with someone else

1. Pinpoint the key issues to be solved and identify their cause and effects

2. Start broad and try to work through a range of issues methodically

3. Connect the facts and evidence and focus on the big picture

4. Discuss any trade-offs or implications of your proposed solution

5. Relate your conclusion back to the problem statement and make sure you have answered all the questions

1. Do not be anxious if you are not able to understand the situation well or unable to justify the problem. Read again, a little slowly, it will help you understand better.

2. Do not jump to conclusions; try to move systematically and gradually.

3. Do not panic if you are unable to analyze the situation. Listen carefully to others as the discussion starts, it will help you gauge the problem at hand.

All the best! Ace the GDPI season.

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Structuring the Case Discussion

Well-designed cases are intentionally complex. Therefore, presenting an entire case to students all at once has the potential to overwhelm student groups and lead them to overlook key details or analytic steps. Accordingly, Barbara Cockrill asks students to review key case concepts the night before, and then presents the case in digestible “chunks” during a CBCL session. Structuring the case discussion around key in-depth questions, Cockrill creates a thoughtful interplay between small group work and whole group discussion that makes for more systematic forays into the case at hand.

Barbara Cockrill , Harold Amos Academy Associate Professor of Medicine

Student Group

Harvard Medical School

Homeostasis I

40 students

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First-year requisite

• Classroom Considerations
• Relevant Research
• Related Resources
• CBCL provides students the opportunity to apply course material in new ways. For this reason, you might consider not sharing the case with students beforehand and having them experience it in class with fresh eyes.
• Chunk cases so students can focus on case specifics and gradually build-up to greater complexity and understanding. 
• Introduce variety into case-based discussions. Integrate a mix of independent work, small group discussion, and whole group share outs to keep students engaged and provide multiple junctures for students to get feedback on their understanding.
• Instructor scaffolding is critical for effective case-based learning ( Ramaekers et al., 2011 )
• This resource from the Harvard Business School provides suggestions for questioning, listening, and responding during a case discussion .
• This comprehensive resource on “The ABCs of Case Teaching” provides helpful tips for planning and “running” your case .

Related Moves

Experiencing the Case as a Student Team

Regulating the Flow of Energy in the Classroom

Designing Focused Discussions for Relevance and Transfer of Knowledge

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Blog Business How to Present a Case Study like a Pro (With Examples)

How to Present a Case Study like a Pro (With Examples)

Written by: Danesh Ramuthi Sep 07, 2023

Okay, let’s get real: case studies can be kinda snooze-worthy. But guess what? They don’t have to be!

In this article, I will cover every element that transforms a mere report into a compelling case study, from selecting the right metrics to using persuasive narrative techniques.

And if you’re feeling a little lost, don’t worry! There are cool tools like Venngage’s Case Study Creator to help you whip up something awesome, even if you’re short on time. Plus, the pre-designed case study templates are like instant polish because let’s be honest, everyone loves a shortcut.

Click to jump ahead: 

What is a case study presentation?

What is the purpose of presenting a case study, how to structure a case study presentation, how long should a case study presentation be, 5 case study presentation examples with templates, 6 tips for delivering an effective case study presentation, 5 common mistakes to avoid in a case study presentation, how to present a case study faqs.

A case study presentation involves a comprehensive examination of a specific subject, which could range from an individual, group, location, event, organization or phenomenon.

They’re like puzzles you get to solve with the audience, all while making you think outside the box.

Unlike a basic report or whitepaper, the purpose of a case study presentation is to stimulate critical thinking among the viewers. 

The primary objective of a case study is to provide an extensive and profound comprehension of the chosen topic. You don’t just throw numbers at your audience. You use examples and real-life cases to make you think and see things from different angles.

The primary purpose of presenting a case study is to offer a comprehensive, evidence-based argument that informs, persuades and engages your audience.

Here’s the juicy part: presenting that case study can be your secret weapon. Whether you’re pitching a groundbreaking idea to a room full of suits or trying to impress your professor with your A-game, a well-crafted case study can be the magic dust that sprinkles brilliance over your words.

Think of it like digging into a puzzle you can’t quite crack . A case study lets you explore every piece, turn it over and see how it fits together. This close-up look helps you understand the whole picture, not just a blurry snapshot.

It’s also your chance to showcase how you analyze things, step by step, until you reach a conclusion. It’s all about being open and honest about how you got there.

Besides, presenting a case study gives you an opportunity to connect data and real-world scenarios in a compelling narrative. It helps to make your argument more relatable and accessible, increasing its impact on your audience.

One of the contexts where case studies can be very helpful is during the job interview. In some job interviews, you as candidates may be asked to present a case study as part of the selection process.

Having a case study presentation prepared allows the candidate to demonstrate their ability to understand complex issues, formulate strategies and communicate their ideas effectively.

The way you present a case study can make all the difference in how it’s received. A well-structured presentation not only holds the attention of your audience but also ensures that your key points are communicated clearly and effectively.

In this section, let’s go through the key steps that’ll help you structure your case study presentation for maximum impact.

Let’s get into it. 

Open with an introductory overview 

Start by introducing the subject of your case study and its relevance. Explain why this case study is important and who would benefit from the insights gained. This is your opportunity to grab your audience’s attention.

Explain the problem in question

Dive into the problem or challenge that the case study focuses on. Provide enough background information for the audience to understand the issue. If possible, quantify the problem using data or metrics to show the magnitude or severity.

Detail the solutions to solve the problem

After outlining the problem, describe the steps taken to find a solution. This could include the methodology, any experiments or tests performed and the options that were considered. Make sure to elaborate on why the final solution was chosen over the others.

Key stakeholders Involved

Talk about the individuals, groups or organizations that were directly impacted by or involved in the problem and its solution. 

Stakeholders may experience a range of outcomes—some may benefit, while others could face setbacks.

For example, in a business transformation case study, employees could face job relocations or changes in work culture, while shareholders might be looking at potential gains or losses.

Discuss the key results & outcomes

Discuss the results of implementing the solution. Use data and metrics to back up your statements. Did the solution meet its objectives? What impact did it have on the stakeholders? Be honest about any setbacks or areas for improvement as well.

Include visuals to support your analysis

Visual aids can be incredibly effective in helping your audience grasp complex issues. Utilize charts, graphs, images or video clips to supplement your points. Make sure to explain each visual and how it contributes to your overall argument.

Pie charts illustrate the proportion of different components within a whole, useful for visualizing market share, budget allocation or user demographics.

This is particularly useful especially if you’re displaying survey results in your case study presentation.

Stacked charts on the other hand are perfect for visualizing composition and trends. This is great for analyzing things like customer demographics, product breakdowns or budget allocation in your case study.

Consider this example of a stacked bar chart template. It provides a straightforward summary of the top-selling cake flavors across various locations, offering a quick and comprehensive view of the data.

Not the chart you’re looking for? Browse Venngage’s gallery of chart templates to find the perfect one that’ll captivate your audience and level up your data storytelling.

Recommendations and next steps

Wrap up by providing recommendations based on the case study findings. Outline the next steps that stakeholders should take to either expand on the success of the project or address any remaining challenges.

Acknowledgments and references

Thank the people who contributed to the case study and helped in the problem-solving process. Cite any external resources, reports or data sets that contributed to your analysis.

Feedback & Q&A session

Open the floor for questions and feedback from your audience. This allows for further discussion and can provide additional insights that may not have been considered previously.

Closing remarks

Conclude the presentation by summarizing the key points and emphasizing the takeaways. Thank your audience for their time and participation and express your willingness to engage in further discussions or collaborations on the subject.

Well, the length of a case study presentation can vary depending on the complexity of the topic and the needs of your audience. However, a typical business or academic presentation often lasts between 15 to 30 minutes. 

This time frame usually allows for a thorough explanation of the case while maintaining audience engagement. However, always consider leaving a few minutes at the end for a Q&A session to address any questions or clarify points made during the presentation.

When it comes to presenting a compelling case study, having a well-structured template can be a game-changer. 

It helps you organize your thoughts, data and findings in a coherent and visually pleasing manner. 

Not all case studies are created equal and different scenarios require distinct approaches for maximum impact. 

To save you time and effort, I have curated a list of 5 versatile case study presentation templates, each designed for specific needs and audiences. 

Here are some best case study presentation examples that showcase effective strategies for engaging your audience and conveying complex information clearly.

1 . Lab report case study template

Ever feel like your research gets lost in a world of endless numbers and jargon? Lab case studies are your way out!

Think of it as building a bridge between your cool experiment and everyone else. It’s more than just reporting results – it’s explaining the “why” and “how” in a way that grabs attention and makes sense.

This lap report template acts as a blueprint for your report, guiding you through each essential section (introduction, methods, results, etc.) in a logical order.

Want to present your research like a pro? Browse our research presentation template gallery for creative inspiration!

2. Product case study template

It’s time you ditch those boring slideshows and bullet points because I’ve got a better way to win over clients: product case study templates.

Instead of just listing features and benefits, you get to create a clear and concise story that shows potential clients exactly what your product can do for them. It’s like painting a picture they can easily visualize, helping them understand the value your product brings to the table.

Grab the template below, fill in the details, and watch as your product’s impact comes to life!

3. Content marketing case study template

In digital marketing, showcasing your accomplishments is as vital as achieving them. 

A well-crafted case study not only acts as a testament to your successes but can also serve as an instructional tool for others. 

With this coral content marketing case study template—a perfect blend of vibrant design and structured documentation, you can narrate your marketing triumphs effectively.

4. Case study psychology template

Understanding how people tick is one of psychology’s biggest quests and case studies are like magnifying glasses for the mind. They offer in-depth looks at real-life behaviors, emotions and thought processes, revealing fascinating insights into what makes us human.

Writing a top-notch case study, though, can be a challenge. It requires careful organization, clear presentation and meticulous attention to detail. That’s where a good case study psychology template comes in handy.

Think of it as a helpful guide, taking care of formatting and structure while you focus on the juicy content. No more wrestling with layouts or margins – just pour your research magic into crafting a compelling narrative.

5. Lead generation case study template

Lead generation can be a real head-scratcher. But here’s a little help: a lead generation case study.

Think of it like a friendly handshake and a confident resume all rolled into one. It’s your chance to showcase your expertise, share real-world successes and offer valuable insights. Potential clients get to see your track record, understand your approach and decide if you’re the right fit.

No need to start from scratch, though. This lead generation case study template guides you step-by-step through crafting a clear, compelling narrative that highlights your wins and offers actionable tips for others. Fill in the gaps with your specific data and strategies, and voilà! You’ve got a powerful tool to attract new customers.

Related: 15+ Professional Case Study Examples [Design Tips + Templates]

So, you’ve spent hours crafting the perfect case study and are now tasked with presenting it. Crafting the case study is only half the battle; delivering it effectively is equally important. 

Whether you’re facing a room of executives, academics or potential clients, how you present your findings can make a significant difference in how your work is received. 

Forget boring reports and snooze-inducing presentations! Let’s make your case study sing. Here are some key pointers to turn information into an engaging and persuasive performance:

• Know your audience : Tailor your presentation to the knowledge level and interests of your audience. Remember to use language and examples that resonate with them.
• Rehearse : Rehearsing your case study presentation is the key to a smooth delivery and for ensuring that you stay within the allotted time. Practice helps you fine-tune your pacing, hone your speaking skills with good word pronunciations and become comfortable with the material, leading to a more confident, conversational and effective presentation.
• Start strong : Open with a compelling introduction that grabs your audience’s attention. You might want to use an interesting statistic, a provocative question or a brief story that sets the stage for your case study.
• Be clear and concise : Avoid jargon and overly complex sentences. Get to the point quickly and stay focused on your objectives.
• Use visual aids : Incorporate slides with graphics, charts or videos to supplement your verbal presentation. Make sure they are easy to read and understand.
• Tell a story : Use storytelling techniques to make the case study more engaging. A well-told narrative can help you make complex data more relatable and easier to digest.

Ditching the dry reports and slide decks? Venngage’s case study templates let you wow customers with your solutions and gain insights to improve your business plan. Pre-built templates, visual magic and customer captivation – all just a click away. Go tell your story and watch them say “wow!”

Nailed your case study, but want to make your presentation even stronger? Avoid these common mistakes to ensure your audience gets the most out of it:

Overloading with information

A case study is not an encyclopedia. Overloading your presentation with excessive data, text or jargon can make it cumbersome and difficult for the audience to digest the key points. Stick to what’s essential and impactful. Need help making your data clear and impactful? Our data presentation templates can help! Find clear and engaging visuals to showcase your findings.

Lack of structure

Jumping haphazardly between points or topics can confuse your audience. A well-structured presentation, with a logical flow from introduction to conclusion, is crucial for effective communication.

Ignoring the audience

Different audiences have different needs and levels of understanding. Failing to adapt your presentation to your audience can result in a disconnect and a less impactful presentation.

Poor visual elements

While content is king, poor design or lack of visual elements can make your case study dull or hard to follow. Make sure you use high-quality images, graphs and other visual aids to support your narrative.

Not focusing on results

A case study aims to showcase a problem and its solution, but what most people care about are the results. Failing to highlight or adequately explain the outcomes can make your presentation fall flat.

How to start a case study presentation?

Starting a case study presentation effectively involves a few key steps:

• Grab attention : Open with a hook—an intriguing statistic, a provocative question or a compelling visual—to engage your audience from the get-go.
• Set the stage : Briefly introduce the subject, context and relevance of the case study to give your audience an idea of what to expect.
• Outline objectives : Clearly state what the case study aims to achieve. Are you solving a problem, proving a point or showcasing a success?
• Agenda : Give a quick outline of the key sections or topics you’ll cover to help the audience follow along.
• Set expectations : Let your audience know what you want them to take away from the presentation, whether it’s knowledge, inspiration or a call to action.

How to present a case study on PowerPoint and on Google Slides?

Presenting a case study on PowerPoint and Google Slides involves a structured approach for clarity and impact using presentation slides :

• Title slide : Start with a title slide that includes the name of the case study, your name and any relevant institutional affiliations.
• Introduction : Follow with a slide that outlines the problem or situation your case study addresses. Include a hook to engage the audience.
• Objectives : Clearly state the goals of the case study in a dedicated slide.
• Findings : Use charts, graphs and bullet points to present your findings succinctly.
• Analysis : Discuss what the findings mean, drawing on supporting data or secondary research as necessary.
• Conclusion : Summarize key takeaways and results.
• Q&A : End with a slide inviting questions from the audience.

What’s the role of analysis in a case study presentation?

The role of analysis in a case study presentation is to interpret the data and findings, providing context and meaning to them. 

It helps your audience understand the implications of the case study, connects the dots between the problem and the solution and may offer recommendations for future action.

Is it important to include real data and results in the presentation?

Yes, including real data and results in a case study presentation is crucial to show experience,  credibility and impact. Authentic data lends weight to your findings and conclusions, enabling the audience to trust your analysis and take your recommendations more seriously

How do I conclude a case study presentation effectively?

To conclude a case study presentation effectively, summarize the key findings, insights and recommendations in a clear and concise manner. 

End with a strong call-to-action or a thought-provoking question to leave a lasting impression on your audience.

What’s the best way to showcase data in a case study presentation ?

The best way to showcase data in a case study presentation is through visual aids like charts, graphs and infographics which make complex information easily digestible, engaging and creative. 

Don’t just report results, visualize them! This template for example lets you transform your social media case study into a captivating infographic that sparks conversation.

Choose the type of visual that best represents the data you’re showing; for example, use bar charts for comparisons or pie charts for parts of a whole. 

Ensure that the visuals are high-quality and clearly labeled, so the audience can quickly grasp the key points. 

Keep the design consistent and simple, avoiding clutter or overly complex visuals that could distract from the message.

Choose a template that perfectly suits your case study where you can utilize different visual aids for maximum impact. 

Need more inspiration on how to turn numbers into impact with the help of infographics? Our ready-to-use infographic templates take the guesswork out of creating visual impact for your case studies with just a few clicks.

Related: 10+ Case Study Infographic Templates That Convert

Congrats on mastering the art of compelling case study presentations! This guide has equipped you with all the essentials, from structure and nuances to avoiding common pitfalls. You’re ready to impress any audience, whether in the boardroom, the classroom or beyond.

And remember, you’re not alone in this journey. Venngage’s Case Study Creator is your trusty companion, ready to elevate your presentations from ordinary to extraordinary. So, let your confidence shine, leverage your newly acquired skills and prepare to deliver presentations that truly resonate.

Go forth and make a lasting impact!

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• Section 4. Techniques for Leading Group Discussions

Chapter 16 Sections

• Section 1. Conducting Effective Meetings
• Section 2. Developing Facilitation Skills
• Section 3. Capturing What People Say: Tips for Recording a Meeting
• Main Section

A local coalition forms a task force to address the rising HIV rate among teens in the community.  A group of parents meets to wrestle with their feeling that their school district is shortchanging its students.  A college class in human services approaches the topic of dealing with reluctant participants.  Members of an environmental group attend a workshop on the effects of global warming.  A politician convenes a “town hall meeting” of constituents to brainstorm ideas for the economic development of the region.  A community health educator facilitates a smoking cessation support group.

All of these might be examples of group discussions, although they have different purposes, take place in different locations, and probably run in different ways.  Group discussions are common in a democratic society, and, as a community builder, it’s more than likely that you have been and will continue to be involved in many of them.  You also may be in a position to lead one, and that’s what this section is about.  In this last section of a chapter on group facilitation, we’ll examine what it takes to lead a discussion group well, and how you can go about doing it.

What is an effective group discussion?

The literal definition of a group discussion is obvious: a critical conversation about a particular topic, or perhaps a range of topics, conducted in a group of a size that allows participation by all members.  A group of two or three generally doesn’t need a leader to have a good discussion, but once the number reaches five or six, a leader or facilitator can often be helpful.  When the group numbers eight or more, a leader or facilitator, whether formal or informal, is almost always helpful in ensuring an effective discussion.

A group discussion is a type of meeting, but it differs from the formal meetings in a number of ways: It may not have a specific goal – many group discussions are just that: a group kicking around ideas on a particular topic.  That may lead to a goal ultimately...but it may not. It’s less formal, and may have no time constraints, or structured order, or agenda. Its leadership is usually less directive than that of a meeting. It emphasizes process (the consideration of ideas) over product (specific tasks to be accomplished within the confines of the meeting itself. Leading a discussion group is not the same as running a meeting.  It’s much closer to acting as a facilitator, but not exactly the same as that either.

An effective group discussion generally has a number of elements:

• All members of the group have a chance to speak, expressing their own ideas and feelings freely, and to pursue and finish out their thoughts
• All members of the group can hear others’ ideas and feelings stated openly
• Group members can safely test out ideas that are not yet fully formed
• Group members can receive and respond to respectful but honest and constructive feedback.  Feedback could be positive, negative, or merely clarifying or correcting factual questions or errors, but is in all cases delivered respectfully.
• A variety of points of view are put forward and discussed
• The discussion is not dominated by any one person
• Arguments, while they may be spirited, are based on the content of ideas and opinions, not on personalities
• Even in disagreement, there’s an understanding that the group is working together to resolve a dispute, solve a problem, create a plan, make a decision, find principles all can agree on, or come to a conclusion from which it can move on to further discussion

Many group discussions have no specific purpose except the exchange of ideas and opinions.  Ultimately, an effective group discussion is one in which many different ideas and viewpoints are heard and considered.  This allows the group to accomplish its purpose if it has one, or to establish a basis either for ongoing discussion or for further contact and collaboration among its members.

There are many possible purposes for a group discussion, such as:

• Create a new situation – form a coalition, start an initiative, etc.
• Explore cooperative or collaborative arrangements among groups or organizations
• Discuss and/or analyze an issue, with no specific goal in mind but understanding
• Create a strategic plan – for an initiative, an advocacy campaign, an intervention, etc.
• Discuss policy and policy change
• Air concerns and differences among individuals or groups
• Hold public hearings on proposed laws or regulations, development, etc.
• Decide on an action
• Provide mutual support
• Solve a problem
• Resolve a conflict
• Plan your work or an event

Possible leadership styles of a group discussion also vary.  A group leader or facilitator might be directive or non-directive; that is, she might try to control what goes on to a large extent; or she might assume that the group should be in control, and that her job is to facilitate the process.  In most group discussions, leaders who are relatively non-directive make for a more broad-ranging outlay of ideas, and a more satisfying experience for participants.

Directive leaders can be necessary in some situations. If a goal must be reached in a short time period, a directive leader might help to keep the group focused. If the situation is particularly difficult, a directive leader might be needed to keep control of the discussion and make

Why would you lead a group discussion?

There are two ways to look at this question: “What’s the point of group discussion?” and “Why would you, as opposed to someone else, lead a group discussion?”  Let’s examine both.

What’s the point of group discussion?

As explained in the opening paragraphs of this section, group discussions are common in a democratic society.  There are a number of reasons for this, some practical and some philosophical.

A group discussion:

• G ives everyone involved a voice .  Whether the discussion is meant to form a basis for action, or just to play with ideas, it gives all members of the group a chance to speak their opinions, to agree or disagree with others, and to have their thoughts heard.  In many community-building situations, the members of the group might be chosen specifically because they represent a cross-section of the community, or a diversity of points of view.
• Allows for a variety of ideas to be expressed and discussed .  A group is much more likely to come to a good conclusion if a mix of ideas is on the table, and if all members have the opportunity to think about and respond to them.
• Is generally a democratic, egalitarian process .  It reflects the ideals of most grassroots and community groups, and encourages a diversity of views.
• Leads to group ownership of whatever conclusions, plans, or action the group decides upon .  Because everyone has a chance to contribute to the discussion and to be heard, the final result feels like it was arrived at by and belongs to everyone.
• Encourages those who might normally be reluctant to speak their minds .  Often, quiet people have important things to contribute, but aren’t assertive enough to make themselves heard.  A good group discussion will bring them out and support them.
• Can often open communication channels among people who might not communicate in any other way .  People from very different backgrounds, from opposite ends of the political spectrum, from different cultures, who may, under most circumstances, either never make contact or never trust one another enough to try to communicate, might, in a group discussion, find more common ground than they expected.
• Is sometimes simply the obvious, or even the only, way to proceed.  Several of the examples given at the beginning of the section – the group of parents concerned about their school system, for instance, or the college class – fall into this category, as do public hearings and similar gatherings.

Why would you specifically lead a group discussion?

You might choose to lead a group discussion, or you might find yourself drafted for the task.  Some of the most common reasons that you might be in that situation:

• It’s part of your job .  As a mental health counselor, a youth worker, a coalition coordinator, a teacher, the president of a board of directors, etc. you might be expected to lead group discussions regularly.
• You’ve been asked to .  Because of your reputation for objectivity or integrity, because of your position in the community, or because of your skill at leading group discussions, you might be the obvious choice to lead a particular discussion.
• A discussion is necessary, and you’re the logical choice to lead it .  If you’re the chair of a task force to address substance use in the community, for instance, it’s likely that you’ll be expected to conduct that task force’s meetings, and to lead discussion of the issue.
• It was your idea in the first place .  The group discussion, or its purpose, was your idea, and the organization of the process falls to you.

You might find yourself in one of these situations if you fall into one of the categories of people who are often tapped to lead group discussions.  These categories include (but aren’t limited to):

• Directors of organizations
• Public officials
• Coalition coordinators
• Professionals with group-leading skills – counselors, social workers, therapists, etc.
• Health professionals and health educators
• Respected community members.  These folks may be respected for their leadership – president of the Rotary Club, spokesperson for an environmental movement – for their positions in the community – bank president, clergyman – or simply for their personal qualities – integrity, fairness, ability to communicate with all sectors of the community.
• Community activists.  This category could include anyone from “professional” community organizers to average citizens who care about an issue or have an idea they want to pursue.

When might you lead a group discussion?

The need or desire for a group discussion might of course arise anytime, but there are some times when it’s particularly necessary.

• At the start of something new . Whether you’re designing an intervention, starting an initiative, creating a new program, building a coalition, or embarking on an advocacy or other campaign, inclusive discussion is likely to be crucial in generating the best possible plan, and creating community support for and ownership of it.
• When an issue can no longer be ignored . When youth violence reaches a critical point, when the community’s drinking water is declared unsafe, when the HIV infection rate climbs – these are times when groups need to convene to discuss the issue and develop action plans to swing the pendulum in the other direction.
• When groups need to be brought together . One way to deal with racial or ethnic hostility, for instance, is to convene groups made up of representatives of all the factions involved.  The resulting discussions – and the opportunity for people from different backgrounds to make personal connections with one another – can go far to address everyone’s concerns, and to reduce tensions.
• When an existing group is considering its next step or seeking to address an issue of importance to it . The staff of a community service organization, for instance, may want to plan its work for the next few months, or to work out how to deal with people with particular quirks or problems.

How do you lead a group discussion?

In some cases, the opportunity to lead a group discussion can arise on the spur of the moment; in others, it’s a more formal arrangement, planned and expected.  In the latter case, you may have the chance to choose a space and otherwise structure the situation.  In less formal circumstances, you’ll have to make the best of existing conditions.

We’ll begin by looking at what you might consider if you have time to prepare.  Then we’ll examine what it takes to make an effective discussion leader or facilitator, regardless of external circumstances.

Set the stage

If you have time to prepare beforehand, there are a number of things you may be able to do to make the participants more comfortable, and thus to make discussion easier.

Choose the space

If you have the luxury of choosing your space, you might look for someplace that’s comfortable and informal.  Usually, that means comfortable furniture that can be moved around (so that, for instance, the group can form a circle, allowing everyone to see and hear everyone else easily).  It may also mean a space away from the ordinary.

One organization often held discussions on the terrace of an old mill that had been turned into a bookstore and café.  The sound of water from the mill stream rushing by put everyone at ease, and encouraged creative thought.

Provide food and drink

The ultimate comfort, and one that breaks down barriers among people, is that of eating and drinking.

Bring materials to help the discussion along

Most discussions are aided by the use of newsprint and markers to record ideas, for example.

Become familiar with the purpose and content of the discussion

If you have the opportunity, learn as much as possible about the topic under discussion.  This is not meant to make you the expert, but rather to allow you to ask good questions that will help the group generate ideas.

Make sure everyone gets any necessary information, readings, or other material beforehand

If participants are asked to read something, consider questions, complete a task, or otherwise prepare for the discussion, make sure that the assignment is attended to and used.  Don’t ask people to do something, and then ignore it.

Lead the discussion

Think about leadership style

The first thing you need to think about is leadership style, which we mentioned briefly earlier in the section.  Are you a directive or non-directive leader?  The chances are that, like most of us, you fall somewhere in between the extremes of the leader who sets the agenda and dominates the group completely, and the leader who essentially leads not at all. The point is made that many good group or meeting leaders are, in fact, facilitators, whose main concern is supporting and maintaining the process of the group’s work.  This is particularly true when it comes to group discussion, where the process is, in fact, the purpose of the group’s coming together.

A good facilitator helps the group set rules for itself, makes sure that everyone participates and that no one dominates, encourages the development and expression of all ideas, including “odd” ones, and safeguards an open process, where there are no foregone conclusions and everyone’s ideas are respected.  Facilitators are non-directive, and try to keep themselves out of the discussion, except to ask questions or make statements that advance it.  For most group discussions, the facilitator role is probably a good ideal to strive for.

It’s important to think about what you’re most comfortable with philosophically, and how that fits what you’re comfortable with personally.  If you’re committed to a non-directive style, but you tend to want to control everything in a situation, you may have to learn some new behaviors in order to act on your beliefs.

Put people at ease

Especially if most people in the group don’t know one another, it’s your job as leader to establish a comfortable atmosphere and set the tone for the discussion.

Help the group establish ground rules

The ground rules of a group discussion are the guidelines that help to keep the discussion on track, and prevent it from deteriorating into namecalling or simply argument.  Some you might suggest, if the group has trouble coming up with the first one or two:

• Everyone should treat everyone else with respect : no name-calling, no emotional outbursts, no accusations.
• No arguments directed at people – only at ideas and opinions .  Disagreement should be respectful – no ridicule.
• Don’t interrupt .  Listen to the whole of others’ thoughts – actually listen, rather than just running over your own response in your head.
• Respect the group’s time .  Try to keep your comments reasonably short and to the point, so that others have a chance to respond.
• Consider all comments seriously, and try to evaluate them fairly .  Others’ ideas and comments may change your mind, or vice versa: it’s important to be open to that.
• Don’t be defensive if someone disagrees with you .  Evaluate both positions, and only continue to argue for yours if you continue to believe it’s right.
• Everyone is responsible for following and upholding the ground rules .

Ground rules may also be a place to discuss recording the session.  Who will take notes, record important points, questions for further discussion, areas of agreement or disagreement?  If the recorder is a group member, the group and/or leader should come up with a strategy that allows her to participate fully in the discussion.

Generate an agenda or goals for the session

You might present an agenda for approval, and change it as the group requires, or you and the group can create one together.  There may actually be no need for one, in that the goal may simply be to discuss an issue or idea.  If that’s the case, it should be agreed upon at the outset.

How active you are might depend on your leadership style, but you definitely have some responsibilities here.  They include setting, or helping the group to set the discussion topic; fostering the open process; involving all participants; asking questions or offering ideas to advance the discussion; summarizing or clarifying important points, arguments, and ideas; and wrapping up the session.  Let’s look at these, as well as some do’s and don’t’s for discussion group leaders.

• Setting the topic . If the group is meeting to discuss a specific issue or to plan something, the discussion topic is already set.  If the topic is unclear, then someone needs to help the group define it.  The leader – through asking the right questions, defining the problem, and encouraging ideas from the group – can play that role.
• Fostering the open process . Nurturing the open process means paying attention to the process, content, and interpersonal dynamics of the discussion all at the same time – not a simple matter. As leader, your task is not to tell the group what to do, or to force particular conclusions, but rather to make sure that the group chooses an appropriate topic that meets its needs, that there are no “right” answers to start with (no foregone conclusions), that no one person or small group dominates the discussion, that everyone follows the ground rules, that discussion is civil and organized, and that all ideas are subjected to careful critical analysis.  You might comment on the process of the discussion or on interpersonal issues when it seems helpful (“We all seem to be picking on John here – what’s going on?”), or make reference to the open process itself (“We seem to be assuming that we’re supposed to believe X – is that true?”). Most of your actions as leader should be in the service of modeling or furthering the open process.

Part of your job here is to protect “minority rights,” i.e., unpopular or unusual ideas.  That doesn’t mean you have to agree with them, but that you have to make sure that they can be expressed, and that discussion of them is respectful, even in disagreement. (The exceptions are opinions or ideas that are discriminatory or downright false.)  Odd ideas often turn out to be correct, and shouldn’t be stifled.

• Involving all participants . This is part of fostering the open process, but is important enough to deserve its own mention. To involve those who are less assertive or shy, or who simply can’t speak up quickly enough, you might ask directly for their opinion, encourage them with body language (smile when they say anything, lean and look toward them often), and be aware of when they want to speak and can’t break in.  It’s important both for process and for the exchange of ideas that everyone have plenty of opportunity to communicate their thoughts.
• Asking questions or offering ideas to advance the discussion . The leader should be aware of the progress of the discussion, and should be able to ask questions or provide information or arguments that stimulate thinking or take the discussion to the next step when necessary. If participants are having trouble grappling with the topic, getting sidetracked by trivial issues, or simply running out of steam, it’s the leader’s job to carry the discussion forward.

This is especially true when the group is stuck, either because two opposing ideas or factions are at an impasse, or because no one is able or willing to say anything.  In these circumstances, the leader’s ability to identify points of agreement, or to ask the question that will get discussion moving again is crucial to the group’s effectiveness.

• Summarizing or clarifying important points, arguments, or ideas . This task entails making sure that everyone understands a point that was just made, or the two sides of an argument.  It can include restating a conclusion the group has reached, or clarifying a particular idea or point made by an individual (“What I think I heard you say was…”).  The point is to make sure that everyone understands what the individual or group actually meant.
• Wrapping up the session .  As the session ends, the leader should help the group review the discussion and make plans for next steps (more discussion sessions, action, involving other people or groups, etc.). He should also go over any assignments or tasks that were agreed to, make sure that every member knows what her responsibilities are, and review the deadlines for those responsibilities.  Other wrap-up steps include getting feedback on the session – including suggestions for making it better – pointing out the group’s accomplishments, and thanking it for its work.

Even after you’ve wrapped up the discussion, you’re not necessarily through. If you’ve been the recorder, you might want to put the notes from the session in order, type them up, and send them to participants. The notes might also include a summary of conclusions that were reached, as well as any assignments or follow-up activities that were agreed on.

If the session was one-time, or was the last of a series, your job may now be done. If it was the beginning, however, or part of an ongoing discussion, you may have a lot to do before the next session, including contacting people to make sure they’ve done what they promised, and preparing the newsprint notes to be posted at the next session so everyone can remember the discussion.

Leading an effective group discussion takes preparation (if you have the opportunity for it), an understanding of and commitment to an open process, and a willingness to let go of your ego and biases. If you can do these things, the chances are you can become a discussion leader that can help groups achieve the results they want.

Do’s and don’ts for discussion leaders

• Model the behavior and attitudes you want group members to employ . That includes respecting all group members equally; advancing the open process; demonstrating what it means to be a learner (admitting when you’re wrong, or don’t know a fact or an answer, and suggesting ways to find out); asking questions based on others’ statements; focusing on positions rather than on the speaker; listening carefully; restating others’ points; supporting your arguments with fact or logic; acceding when someone else has a good point; accepting criticism; thinking critically; giving up the floor when appropriate; being inclusive and culturally sensitive, etc.
• Use encouraging body language and tone of voice, as well as words .  Lean forward when people are talking, for example, keep your body position open and approachable, smile when appropriate, and attend carefully to everyone, not just to those who are most articulate.
• Give positive feedback for joining the discussion .  Smile, repeat group members’ points, and otherwise show that you value participation.
• Be aware of people’s reactions and feelings, and try to respond appropriately . If a group member is hurt by others’ comments, seems puzzled or confused, is becoming angry or defensive, it’s up to you as discussion leader to use the ground rules or your own sensitivity to deal with the situation. If someone’s hurt, for instance, it may be important to point that out and discuss how to make arguments without getting personal.  If group members are confused, revisiting the comments or points that caused the confusion, or restating them more clearly, may be helpful.  Being aware of the reactions of individuals and of the group as a whole can make it possible to expose and use conflict, or to head off unnecessary emotional situations and misunderstandings.
• Ask open-ended questions .  In advancing the discussion, use questions that can’t be answered with a simple yes or no.  Instead, questions should require some thought from group members, and should ask for answers that include reasons or analysis.  The difference between “Do you think the President’s decision was right?” and “Why do you think the President’s decision was or wasn’t right?” is huge.  Where the first question can be answered with a yes or no, the second requires an analysis supporting the speaker’s opinion, as well as discussion of the context and reasons for the decision.
• Control your own biases .  While you should point out factual errors or ideas that are inaccurate and disrespectful of others, an open process demands that you not impose your views on the group, and that you keep others from doing the same.  Group members should be asked to make rational decisions about the positions or views they want to agree with, and ultimately the ideas that the group agrees on should be those that make the most sense to them – whether they coincide with yours or not.  Pointing out bias – including your own – and discussing it helps both you and group members try to be objective.

A constant question that leaders – and members – of any group have is what to do about racist, sexist, or homophobic remarks, especially in a homogeneous group where most or all of the members except the leader may agree with them.  There is no clear-cut answer, although if they pass unchallenged, it may appear you condone the attitude expressed. How you challenge prejudice is the real question.  The ideal here is that other members of the group do the challenging, and it may be worth waiting long enough before you jump in to see if that’s going to happen.  If it doesn’t, you can essentially say, “That’s wrong, and I won’t allow that kind of talk here,” which may well put an end to the remarks, but isn’t likely to change anyone’s mind.  You can express your strong disagreement or discomfort with such remarks and leave it at that, or follow up with “Let’s talk about it after the group,” which could generate some real discussion about prejudice and stereotypes, and actually change some thinking over time. Your ground rules – the issue of respecting everyone – should address this issue, and it probably won’t come up…but there are no guarantees.  It won’t hurt to think beforehand about how you want to handle it.

• Encourage disagreement, and help the group use it creatively .  Disagreement is not to be smoothed over, but rather to be analyzed and used.  When there are conflicting opinions – especially when both can be backed up by reasonable arguments – the real discussion starts.  If everyone agrees on every point, there’s really no discussion at all.  Disagreement makes people think.  It may not be resolved in one session, or at all, but it’s the key to discussion that means something.

All too often, conflict – whether conflicting opinions, conflicting world views, or conflicting personalities – is so frightening to people that they do their best to ignore it or gloss it over.  That reaction not only leaves the conflict unresolved – and therefore growing, so that it will be much stronger when it surfaces later– but fails to examine the issues that it raises.  If those are brought out in the open and discussed reasonably, the two sides often find that they have as much agreement as disagreement, and can resolve their differences by putting their ideas together.  Even where that’s not the case, facing the conflict reasonably, and looking at the roots of the ideas on each side, can help to focus on the issue at hand and provide solutions far better than if one side or the other simply operated alone.

• Keep your mouth shut as much as possible .  By and large, discussion groups are for the group members.  You may be a member of the group and have been asked by the others to act as leader, in which case you certainly have a right to be part of the discussion (although not to dominate).  If you’re an outside facilitator, or leader by position, it’s best to confine your contributions to observations on process, statements of fact, questions to help propel the discussion, and clarification and summarization.  The simple fact that you’re identified as leader or facilitator gives your comments more force than those of other group members.  If you’re in a position of authority or seen as an expert, that force becomes even greater.  The more active you are in the discussion, the more the group will take your positions and ideas as “right,” and the less it will come to its own conclusions.
• Don’t let one or a small group of individuals dominate the discussion .  People who are particularly articulate or assertive, who have strong feelings that they urgently want to express, or who simply feel the need – and have the ability – to dominate can take up far more than their fair share of a discussion.  This often means that quieter people have little or no chance to speak, and that those who disagree with the dominant individual(s) are shouted down and cease trying to make points.  It’s up to the leader to cut off individuals who take far more than their share of time, or who try to limit discussion.  This can be done in a relatively non-threatening way (“This is an interesting point, and it’s certainly worth the time we’ve spent on it, but there are other points of view that need to be heard as well.  I think Alice has been waiting to speak…”), but it’s crucial to the open process and to the comfort and effectiveness of the group.
• Don’t let one point of view override others , unless it’s based on facts and logic, and is actually convincing group members to change their minds.  If a point of view dominates because of its merits, its appeal to participants’ intellectual and ethical sensibilities, that’s fine.  It’s in fact what you hope will happen in a good group discussion.  If a point of view dominates because of the aggressiveness of its supporters, or because it’s presented as something it’s wrong to oppose (“People who disagree with the President are unpatriotic and hate their country”), that’s intellectual bullying or blackmail, and is the opposite of an open discussion.  As leader, you should point it out when that’s happening, and make sure other points of view are aired and examined.

Sometimes individuals or factions that are trying to dominate can disrupt the process of the group. Both Sections 1 and 2 of this chapter contain some guidelines for dealing with this type of situation.

• Don’t assume that anyone holds particular opinions or positions because of his culture, background, race, personal style, etc .  People are individuals, and can’t be judged by their exteriors.  You can find out what someone thinks by asking, or by listening when he speaks.
• Don’t assume that someone from a particular culture, race, or background speaks for everyone else from that situation .  She may or may not represent the general opinion of people from situations similar to hers…or there may not be a general opinion among them.  In a group discussion, no one should be asked or assumed to represent anything more than herself.

The exception here is when someone has been chosen by her community or group to represent its point of view in a multi-sector discussion.  Even in that situation, the individual may find herself swayed by others’ arguments, or may have ideas of her own.  She may have agreed to sponsor particular ideas that are important to her group, but she may still have her own opinions as well, especially in other areas.

• Don’t be the font of all wisdom .  Even if you know more about the discussion topic than most others in the group (if you’re the teacher of a class, for instance), presenting yourself as the intellectual authority denies group members the chance to discuss the topic freely and without pressure.  Furthermore, some of them may have ideas you haven’t considered, or experiences that give them insights into the topic that you’re never likely to have.  Model learning behavior, not teaching behavior.

If you’re asked your opinion directly, you should answer honestly.  You have some choices about how you do that, however.  One is to state your opinion, but make very clear that it’s an opinion, not a fact, and that other people believe differently.  Another is to ask to hold your opinion until the end of the discussion, so as not to influence anyone’s thinking while it’s going on.  Yet another is to give your opinion after all other members of the group have stated theirs, and then discuss the similarities and differences among all the opinions and people’s reasons for holding them. If you’re asked a direct question, you might want to answer it if it’s a question of fact and you know the answer, and if it’s relevant to the discussion.  If the question is less clear-cut, you might want to throw it back to the group, and use it as a spur to discussion.

Group discussions are common in our society, and have a variety of purposes, from planning an intervention or initiative to mutual support to problem-solving to addressing an issue of local concern.  An effective discussion group depends on a leader or facilitator who can guide it through an open process – the group chooses what it’s discussing, if not already determined, discusses it with no expectation of particular conclusions, encourages civil disagreement and argument, and makes sure that every member is included and no one dominates.  It helps greatly if the leader comes to the task with a democratic or, especially, a collaborative style, and with an understanding of how a group functions.

A good group discussion leader has to pay attention to the process and content of the discussion as well as to the people who make up the group.  She has to prepare the space and the setting to the extent possible; help the group establish ground rules that will keep it moving civilly and comfortably; provide whatever materials are necessary; familiarize herself with the topic; and make sure that any pre-discussion readings or assignments get to participants in plenty of time.  Then she has to guide the discussion, being careful to promote an open process; involve everyone and let no one dominate; attend to the personal issues and needs of individual group members when they affect the group; summarize or clarify when appropriate; ask questions to keep the discussion moving, and put aside her own agenda, ego, and biases.

It’s not an easy task, but it can be extremely rewarding.  An effective group discussion can lay the groundwork for action and real community change.

Online resources

Everyday-Democracy . Study Circles Resource Center. Information and publications related to study circles, participatory discussion groups meant to address community issues.

Facilitating Political Discussions from the Institute for Democracy and Higher Education at Tufts University is designed to assist experienced facilitators in training others to facilitate politically charged conversations. The materials are broken down into "modules" and facilitation trainers can use some or all of them to suit their needs.

Project on Civic Reflection provides information about leading study circles on civic reflection.

“ Suggestions for Leading Small-Group Discussions ,” prepared by Lee Haugen, Center for Teaching Excellence, Iowa State University, 1998. Tips on university teaching, but much of the information is useful in other circumstances as well.

“ Tips for Leading Discussions ,” by Felisa Tibbits, Human Rights Education Associates.

Print resources

Forsyth, D . Group Dynamics . (2006). (4th edition).  Belmont, CA: Thomson Wadsworth. 

Johnson, D., & Frank P. (2002). Joining Together: Group theory and group skills . (8th edition).  Boston: Allyn & Bacon.

How to Write a Case Study: Bookmarkable Guide & Template

Published: November 30, 2023

Earning the trust of prospective customers can be a struggle. Before you can even begin to expect to earn their business, you need to demonstrate your ability to deliver on what your product or service promises.

Sure, you could say that you're great at X or that you're way ahead of the competition when it comes to Y. But at the end of the day, what you really need to win new business is cold, hard proof.

One of the best ways to prove your worth is through a compelling case study. In fact, HubSpot’s 2020 State of Marketing report found that case studies are so compelling that they are the fifth most commonly used type of content used by marketers.

Below, I'll walk you through what a case study is, how to prepare for writing one, what you need to include in it, and how it can be an effective tactic. To jump to different areas of this post, click on the links below to automatically scroll.

Case Study Definition

Case study templates, how to write a case study.

• How to Format a Case Study

Business Case Study Examples

A case study is a specific challenge a business has faced, and the solution they've chosen to solve it. Case studies can vary greatly in length and focus on several details related to the initial challenge and applied solution, and can be presented in various forms like a video, white paper, blog post, etc.

In professional settings, it's common for a case study to tell the story of a successful business partnership between a vendor and a client. Perhaps the success you're highlighting is in the number of leads your client generated, customers closed, or revenue gained. Any one of these key performance indicators (KPIs) are examples of your company's services in action.

When done correctly, these examples of your work can chronicle the positive impact your business has on existing or previous customers and help you attract new clients.

Free Case Study Templates

Showcase your company's success using these three free case study templates.

• Data-Driven Case Study Template
• Product-Specific Case Study Template
• General Case Study Template

You're all set!

Click this link to access this resource at any time.

Why write a case study? 

I know, you’re thinking “ Okay, but why do I need to write one of these? ” The truth is that while case studies are a huge undertaking, they are powerful marketing tools that allow you to demonstrate the value of your product to potential customers using real-world examples. Here are a few reasons why you should write case studies. 

1. Explain Complex Topics or Concepts

Case studies give you the space to break down complex concepts, ideas, and strategies and show how they can be applied in a practical way. You can use real-world examples, like an existing client, and use their story to create a compelling narrative that shows how your product solved their issue and how those strategies can be repeated to help other customers get similar successful results.  

2. Show Expertise

Case studies are a great way to demonstrate your knowledge and expertise on a given topic or industry. This is where you get the opportunity to show off your problem-solving skills and how you’ve generated successful outcomes for clients you’ve worked with. 

3. Build Trust and Credibility

In addition to showing off the attributes above, case studies are an excellent way to build credibility. They’re often filled with data and thoroughly researched, which shows readers you’ve done your homework. They can have confidence in the solutions you’ve presented because they’ve read through as you’ve explained the problem and outlined step-by-step what it took to solve it. All of these elements working together enable you to build trust with potential customers.

4. Create Social Proof

Using existing clients that have seen success working with your brand builds social proof . People are more likely to choose your brand if they know that others have found success working with you. Case studies do just that — putting your success on display for potential customers to see. 

All of these attributes work together to help you gain more clients. Plus you can even use quotes from customers featured in these studies and repurpose them in other marketing content. Now that you know more about the benefits of producing a case study, let’s check out how long these documents should be. 

How long should a case study be?

The length of a case study will vary depending on the complexity of the project or topic discussed. However, as a general guideline, case studies typically range from 500 to 1,500 words. 

Whatever length you choose, it should provide a clear understanding of the challenge, the solution you implemented, and the results achieved. This may be easier said than done, but it's important to strike a balance between providing enough detail to make the case study informative and concise enough to keep the reader's interest.

The primary goal here is to effectively communicate the key points and takeaways of the case study. It’s worth noting that this shouldn’t be a wall of text. Use headings, subheadings, bullet points, charts, and other graphics to break up the content and make it more scannable for readers. We’ve also seen brands incorporate video elements into case studies listed on their site for a more engaging experience. 

Ultimately, the length of your case study should be determined by the amount of information necessary to convey the story and its impact without becoming too long. Next, let’s look at some templates to take the guesswork out of creating one. 

To help you arm your prospects with information they can trust, we've put together a step-by-step guide on how to create effective case studies for your business with free case study templates for creating your own.

Tell us a little about yourself below to gain access today:

And to give you more options, we’ll highlight some useful templates that serve different needs. But remember, there are endless possibilities when it comes to demonstrating the work your business has done.

1. General Case Study Template

Do you have a specific product or service that you’re trying to sell, but not enough reviews or success stories? This Product Specific case study template will help.

This template relies less on metrics, and more on highlighting the customer’s experience and satisfaction. As you follow the template instructions, you’ll be prompted to speak more about the benefits of the specific product, rather than your team’s process for working with the customer.

4. Bold Social Media Business Case Study Template

You can find templates that represent different niches, industries, or strategies that your business has found success in — like a bold social media business case study template.

In this template, you can tell the story of how your social media marketing strategy has helped you or your client through collaboration or sale of your service. Customize it to reflect the different marketing channels used in your business and show off how well your business has been able to boost traffic, engagement, follows, and more.

5. Lead Generation Business Case Study Template

It’s important to note that not every case study has to be the product of a sale or customer story, sometimes they can be informative lessons that your own business has experienced. A great example of this is the Lead Generation Business case study template.

If you’re looking to share operational successes regarding how your team has improved processes or content, you should include the stories of different team members involved, how the solution was found, and how it has made a difference in the work your business does.

Now that we’ve discussed different templates and ideas for how to use them, let’s break down how to create your own case study with one.

• Get started with case study templates.
• Determine the case study's objective.
• Establish a case study medium.
• Find the right case study candidate.
• Contact your candidate for permission to write about them.
• Ensure you have all the resources you need to proceed once you get a response.
• Download a case study email template.
• Define the process you want to follow with the client.
• Ensure you're asking the right questions.
• Layout your case study format.
• Publish and promote your case study.

1. Get started with case study templates.

Telling your customer's story is a delicate process — you need to highlight their success while naturally incorporating your business into their story.

If you're just getting started with case studies, we recommend you download HubSpot's Case Study Templates we mentioned before to kickstart the process.

2. Determine the case study's objective.

All business case studies are designed to demonstrate the value of your services, but they can focus on several different client objectives.

Your first step when writing a case study is to determine the objective or goal of the subject you're featuring. In other words, what will the client have succeeded in doing by the end of the piece?

The client objective you focus on will depend on what you want to prove to your future customers as a result of publishing this case study.

Your case study can focus on one of the following client objectives:

• Complying with government regulation
• Lowering business costs
• Becoming profitable
• Generating more leads
• Closing on more customers
• Generating more revenue
• Expanding into a new market
• Becoming more sustainable or energy-efficient

3. Establish a case study medium.

Next, you'll determine the medium in which you'll create the case study. In other words, how will you tell this story?

Case studies don't have to be simple, written one-pagers. Using different media in your case study can allow you to promote your final piece on different channels. For example, while a written case study might just live on your website and get featured in a Facebook post, you can post an infographic case study on Pinterest and a video case study on your YouTube channel.

Here are some different case study mediums to consider:

Written Case Study

Consider writing this case study in the form of an ebook and converting it to a downloadable PDF. Then, gate the PDF behind a landing page and form for readers to fill out before downloading the piece, allowing this case study to generate leads for your business.

Video Case Study

Plan on meeting with the client and shooting an interview. Seeing the subject, in person, talk about the service you provided them can go a long way in the eyes of your potential customers.

Infographic Case Study

Use the long, vertical format of an infographic to tell your success story from top to bottom. As you progress down the infographic, emphasize major KPIs using bigger text and charts that show the successes your client has had since working with you.

Podcast Case Study

Podcasts are a platform for you to have a candid conversation with your client. This type of case study can sound more real and human to your audience — they'll know the partnership between you and your client was a genuine success.

4. Find the right case study candidate.

Writing about your previous projects requires more than picking a client and telling a story. You need permission, quotes, and a plan. To start, here are a few things to look for in potential candidates.

Product Knowledge

It helps to select a customer who's well-versed in the logistics of your product or service. That way, he or she can better speak to the value of what you offer in a way that makes sense for future customers.

Remarkable Results

Clients that have seen the best results are going to make the strongest case studies. If their own businesses have seen an exemplary ROI from your product or service, they're more likely to convey the enthusiasm that you want prospects to feel, too.

One part of this step is to choose clients who have experienced unexpected success from your product or service. When you've provided non-traditional customers — in industries that you don't usually work with, for example — with positive results, it can help to remove doubts from prospects.

Recognizable Names

While small companies can have powerful stories, bigger or more notable brands tend to lend credibility to your own. In fact, 89% of consumers say they'll buy from a brand they already recognize over a competitor, especially if they already follow them on social media.

Customers that came to you after working with a competitor help highlight your competitive advantage and might even sway decisions in your favor.

5. Contact your candidate for permission to write about them.

To get the case study candidate involved, you have to set the stage for clear and open communication. That means outlining expectations and a timeline right away — not having those is one of the biggest culprits in delayed case study creation.

Most importantly at this point, however, is getting your subject's approval. When first reaching out to your case study candidate, provide them with the case study's objective and format — both of which you will have come up with in the first two steps above.

To get this initial permission from your subject, put yourself in their shoes — what would they want out of this case study? Although you're writing this for your own company's benefit, your subject is far more interested in the benefit it has for them.

Benefits to Offer Your Case Study Candidate

Here are four potential benefits you can promise your case study candidate to gain their approval.

Brand Exposure

Explain to your subject to whom this case study will be exposed, and how this exposure can help increase their brand awareness both in and beyond their own industry. In the B2B sector, brand awareness can be hard to collect outside one's own market, making case studies particularly useful to a client looking to expand their name's reach.

Employee Exposure

Allow your subject to provide quotes with credits back to specific employees. When this is an option for them, their brand isn't the only thing expanding its reach — their employees can get their name out there, too. This presents your subject with networking and career development opportunities they might not have otherwise.

Product Discount

This is a more tangible incentive you can offer your case study candidate, especially if they're a current customer of yours. If they agree to be your subject, offer them a product discount — or a free trial of another product — as a thank-you for their help creating your case study.

Backlinks and Website Traffic

Here's a benefit that is sure to resonate with your subject's marketing team: If you publish your case study on your website, and your study links back to your subject's website — known as a "backlink" — this small gesture can give them website traffic from visitors who click through to your subject's website.

Additionally, a backlink from you increases your subject's page authority in the eyes of Google. This helps them rank more highly in search engine results and collect traffic from readers who are already looking for information about their industry.

6. Ensure you have all the resources you need to proceed once you get a response.

So you know what you’re going to offer your candidate, it’s time that you prepare the resources needed for if and when they agree to participate, like a case study release form and success story letter.

Let's break those two down.

Case Study Release Form

This document can vary, depending on factors like the size of your business, the nature of your work, and what you intend to do with the case studies once they are completed. That said, you should typically aim to include the following in the Case Study Release Form:

• A clear explanation of why you are creating this case study and how it will be used.
• A statement defining the information and potentially trademarked information you expect to include about the company — things like names, logos, job titles, and pictures.
• An explanation of what you expect from the participant, beyond the completion of the case study. For example, is this customer willing to act as a reference or share feedback, and do you have permission to pass contact information along for these purposes?
• A note about compensation.

Success Story Letter

As noted in the sample email, this document serves as an outline for the entire case study process. Other than a brief explanation of how the customer will benefit from case study participation, you'll want to be sure to define the following steps in the Success Story Letter.

7. Download a case study email template.

While you gathered your resources, your candidate has gotten time to read over the proposal. When your candidate approves of your case study, it's time to send them a release form.

A case study release form tells you what you'll need from your chosen subject, like permission to use any brand names and share the project information publicly. Kick-off this process with an email that runs through exactly what they can expect from you, as well as what you need from them. To give you an idea of what that might look like, check out this sample email:

8. Define the process you want to follow with the client.

Before you can begin the case study, you have to have a clear outline of the case study process with your client. An example of an effective outline would include the following information.

The Acceptance

First, you'll need to receive internal approval from the company's marketing team. Once approved, the Release Form should be signed and returned to you. It's also a good time to determine a timeline that meets the needs and capabilities of both teams.

The Questionnaire

To ensure that you have a productive interview — which is one of the best ways to collect information for the case study — you'll want to ask the participant to complete a questionnaire before this conversation. That will provide your team with the necessary foundation to organize the interview, and get the most out of it.

The Interview

Once the questionnaire is completed, someone on your team should reach out to the participant to schedule a 30- to 60-minute interview, which should include a series of custom questions related to the customer's experience with your product or service.

The Draft Review

After the case study is composed, you'll want to send a draft to the customer, allowing an opportunity to give you feedback and edits.

The Final Approval

Once any necessary edits are completed, send a revised copy of the case study to the customer for final approval.

Once the case study goes live — on your website or elsewhere — it's best to contact the customer with a link to the page where the case study lives. Don't be afraid to ask your participants to share these links with their own networks, as it not only demonstrates your ability to deliver positive results and impressive growth, as well.

9. Ensure you're asking the right questions.

Before you execute the questionnaire and actual interview, make sure you're setting yourself up for success. A strong case study results from being prepared to ask the right questions. What do those look like? Here are a few examples to get you started:

• What are your goals?
• What challenges were you experiencing before purchasing our product or service?
• What made our product or service stand out against our competitors?
• What did your decision-making process look like?
• How have you benefited from using our product or service? (Where applicable, always ask for data.)

Keep in mind that the questionnaire is designed to help you gain insights into what sort of strong, success-focused questions to ask during the actual interview. And once you get to that stage, we recommend that you follow the "Golden Rule of Interviewing." Sounds fancy, right? It's actually quite simple — ask open-ended questions.

If you're looking to craft a compelling story, "yes" or "no" answers won't provide the details you need. Focus on questions that invite elaboration, such as, "Can you describe ...?" or, "Tell me about ..."

In terms of the interview structure, we recommend categorizing the questions and flowing them into six specific sections that will mirror a successful case study format. Combined, they'll allow you to gather enough information to put together a rich, comprehensive study.

Open with the customer's business.

The goal of this section is to generate a better understanding of the company's current challenges and goals, and how they fit into the landscape of their industry. Sample questions might include:

• How long have you been in business?
• How many employees do you have?
• What are some of the objectives of your department at this time?

Cite a problem or pain point.

To tell a compelling story, you need context. That helps match the customer's need with your solution. Sample questions might include:

• What challenges and objectives led you to look for a solution?
• What might have happened if you did not identify a solution?
• Did you explore other solutions before this that did not work out? If so, what happened?

Discuss the decision process.

Exploring how the customer decided to work with you helps to guide potential customers through their own decision-making processes. Sample questions might include:

• How did you hear about our product or service?
• Who was involved in the selection process?
• What was most important to you when evaluating your options?

Explain how a solution was implemented.

The focus here should be placed on the customer's experience during the onboarding process. Sample questions might include:

• How long did it take to get up and running?
• Did that meet your expectations?
• Who was involved in the process?

Explain how the solution works.

The goal of this section is to better understand how the customer is using your product or service. Sample questions might include:

• Is there a particular aspect of the product or service that you rely on most?
• Who is using the product or service?

End with the results.

In this section, you want to uncover impressive measurable outcomes — the more numbers, the better. Sample questions might include:

• How is the product or service helping you save time and increase productivity?
• In what ways does that enhance your competitive advantage?
• How much have you increased metrics X, Y, and Z?

10. Lay out your case study format.

When it comes time to take all of the information you've collected and actually turn it into something, it's easy to feel overwhelmed. Where should you start? What should you include? What's the best way to structure it?

To help you get a handle on this step, it's important to first understand that there is no one-size-fits-all when it comes to the ways you can present a case study. They can be very visual, which you'll see in some of the examples we've included below, and can sometimes be communicated mostly through video or photos, with a bit of accompanying text.

Here are the sections we suggest, which we'll cover in more detail down below:

• Title: Keep it short. Develop a succinct but interesting project name you can give the work you did with your subject.
• Subtitle: Use this copy to briefly elaborate on the accomplishment. What was done? The case study itself will explain how you got there.
• Executive Summary : A 2-4 sentence summary of the entire story. You'll want to follow it with 2-3 bullet points that display metrics showcasing success.
• About the Subject: An introduction to the person or company you served, which can be pulled from a LinkedIn Business profile or client website.
• Challenges and Objectives: A 2-3 paragraph description of the customer's challenges, before using your product or service. This section should also include the goals or objectives the customer set out to achieve.
• How Product/Service Helped: A 2-3 paragraph section that describes how your product or service provided a solution to their problem.
• Results: A 2-3 paragraph testimonial that proves how your product or service specifically benefited the person or company and helped achieve its goals. Include numbers to quantify your contributions.
• Supporting Visuals or Quotes: Pick one or two powerful quotes that you would feature at the bottom of the sections above, as well as a visual that supports the story you are telling.
• Future Plans: Everyone likes an epilogue. Comment on what's ahead for your case study subject, whether or not those plans involve you.
• Call to Action (CTA): Not every case study needs a CTA, but putting a passive one at the end of your case study can encourage your readers to take an action on your website after learning about the work you've done.

When laying out your case study, focus on conveying the information you've gathered in the most clear and concise way possible. Make it easy to scan and comprehend, and be sure to provide an attractive call-to-action at the bottom — that should provide readers an opportunity to learn more about your product or service.

11. Publish and promote your case study.

Once you've completed your case study, it's time to publish and promote it. Some case study formats have pretty obvious promotional outlets — a video case study can go on YouTube, just as an infographic case study can go on Pinterest.

But there are still other ways to publish and promote your case study. Here are a couple of ideas:

Lead Gen in a Blog Post

As stated earlier in this article, written case studies make terrific lead-generators if you convert them into a downloadable format, like a PDF. To generate leads from your case study, consider writing a blog post that tells an abbreviated story of your client's success and asking readers to fill out a form with their name and email address if they'd like to read the rest in your PDF.

Then, promote this blog post on social media, through a Facebook post or a tweet.

Published as a Page on Your Website

As a growing business, you might need to display your case study out in the open to gain the trust of your target audience.

Rather than gating it behind a landing page, publish your case study to its own page on your website, and direct people here from your homepage with a "Case Studies" or "Testimonials" button along your homepage's top navigation bar.

Format for a Case Study

The traditional case study format includes the following parts: a title and subtitle, a client profile, a summary of the customer’s challenges and objectives, an account of how your solution helped, and a description of the results. You might also want to include supporting visuals and quotes, future plans, and calls-to-action.

Image Source

The title is one of the most important parts of your case study. It should draw readers in while succinctly describing the potential benefits of working with your company. To that end, your title should:

• State the name of your custome r. Right away, the reader must learn which company used your products and services. This is especially important if your customer has a recognizable brand. If you work with individuals and not companies, you may omit the name and go with professional titles: “A Marketer…”, “A CFO…”, and so forth.
• State which product your customer used . Even if you only offer one product or service, or if your company name is the same as your product name, you should still include the name of your solution. That way, readers who are not familiar with your business can become aware of what you sell.
• Allude to the results achieved . You don’t necessarily need to provide hard numbers, but the title needs to represent the benefits, quickly. That way, if a reader doesn’t stay to read, they can walk away with the most essential information: Your product works.

The example above, “Crunch Fitness Increases Leads and Signups With HubSpot,” achieves all three — without being wordy. Keeping your title short and sweet is also essential.

2. Subtitle

Your subtitle is another essential part of your case study — don’t skip it, even if you think you’ve done the work with the title. In this section, include a brief summary of the challenges your customer was facing before they began to use your products and services. Then, drive the point home by reiterating the benefits your customer experienced by working with you.

The above example reads:

“Crunch Fitness was franchising rapidly when COVID-19 forced fitness clubs around the world to close their doors. But the company stayed agile by using HubSpot to increase leads and free trial signups.”

We like that the case study team expressed the urgency of the problem — opening more locations in the midst of a pandemic — and placed the focus on the customer’s ability to stay agile.

3. Executive Summary

The executive summary should provide a snapshot of your customer, their challenges, and the benefits they enjoyed from working with you. Think it’s too much? Think again — the purpose of the case study is to emphasize, again and again, how well your product works.

The good news is that depending on your design, the executive summary can be mixed with the subtitle or with the “About the Company” section. Many times, this section doesn’t need an explicit “Executive Summary” subheading. You do need, however, to provide a convenient snapshot for readers to scan.

In the above example, ADP included information about its customer in a scannable bullet-point format, then provided two sections: “Business Challenge” and “How ADP Helped.” We love how simple and easy the format is to follow for those who are unfamiliar with ADP or its typical customer.

4. About the Company

Readers need to know and understand who your customer is. This is important for several reasons: It helps your reader potentially relate to your customer, it defines your ideal client profile (which is essential to deter poor-fit prospects who might have reached out without knowing they were a poor fit), and it gives your customer an indirect boon by subtly promoting their products and services.

Feel free to keep this section as simple as possible. You can simply copy and paste information from the company’s LinkedIn, use a quote directly from your customer, or take a more creative storytelling approach.

In the above example, HubSpot included one paragraph of description for Crunch Fitness and a few bullet points. Below, ADP tells the story of its customer using an engaging, personable technique that effectively draws readers in.

5. Challenges and Objectives

The challenges and objectives section of your case study is the place to lay out, in detail, the difficulties your customer faced prior to working with you — and what they hoped to achieve when they enlisted your help.

In this section, you can be as brief or as descriptive as you’d like, but remember: Stress the urgency of the situation. Don’t understate how much your customer needed your solution (but don’t exaggerate and lie, either). Provide contextual information as necessary. For instance, the pandemic and societal factors may have contributed to the urgency of the need.

Take the above example from design consultancy IDEO:

“Educational opportunities for adults have become difficult to access in the United States, just when they’re needed most. To counter this trend, IDEO helped the city of South Bend and the Drucker Institute launch Bendable, a community-powered platform that connects people with opportunities to learn with and from each other.”

We love how IDEO mentions the difficulties the United States faces at large, the efforts its customer is taking to address these issues, and the steps IDEO took to help.

6. How Product/Service Helped

This is where you get your product or service to shine. Cover the specific benefits that your customer enjoyed and the features they gleaned the most use out of. You can also go into detail about how you worked with and for your customer. Maybe you met several times before choosing the right solution, or you consulted with external agencies to create the best package for them.

Whatever the case may be, try to illustrate how easy and pain-free it is to work with the representatives at your company. After all, potential customers aren’t looking to just purchase a product. They’re looking for a dependable provider that will strive to exceed their expectations.

In the above example, IDEO describes how it partnered with research institutes and spoke with learners to create Bendable, a free educational platform. We love how it shows its proactivity and thoroughness. It makes potential customers feel that IDEO might do something similar for them.

The results are essential, and the best part is that you don’t need to write the entirety of the case study before sharing them. Like HubSpot, IDEO, and ADP, you can include the results right below the subtitle or executive summary. Use data and numbers to substantiate the success of your efforts, but if you don’t have numbers, you can provide quotes from your customers.

We can’t overstate the importance of the results. In fact, if you wanted to create a short case study, you could include your title, challenge, solution (how your product helped), and result.

8. Supporting Visuals or Quotes

Let your customer speak for themselves by including quotes from the representatives who directly interfaced with your company.

Visuals can also help, even if they’re stock images. On one side, they can help you convey your customer’s industry, and on the other, they can indirectly convey your successes. For instance, a picture of a happy professional — even if they’re not your customer — will communicate that your product can lead to a happy client.

In this example from IDEO, we see a man standing in a boat. IDEO’s customer is neither the man pictured nor the manufacturer of the boat, but rather Conservation International, an environmental organization. This imagery provides a visually pleasing pattern interrupt to the page, while still conveying what the case study is about.

9. Future Plans

This is optional, but including future plans can help you close on a more positive, personable note than if you were to simply include a quote or the results. In this space, you can show that your product will remain in your customer’s tech stack for years to come, or that your services will continue to be instrumental to your customer’s success.

Alternatively, if you work only on time-bound projects, you can allude to the positive impact your customer will continue to see, even after years of the end of the contract.

10. Call to Action (CTA)

Not every case study needs a CTA, but we’d still encourage it. Putting one at the end of your case study will encourage your readers to take an action on your website after learning about the work you've done.

It will also make it easier for them to reach out, if they’re ready to start immediately. You don’t want to lose business just because they have to scroll all the way back up to reach out to your team.

To help you visualize this case study outline, check out the case study template below, which can also be downloaded here .

You drove the results, made the connection, set the expectations, used the questionnaire to conduct a successful interview, and boiled down your findings into a compelling story. And after all of that, you're left with a little piece of sales enabling gold — a case study.

To show you what a well-executed final product looks like, have a look at some of these marketing case study examples.

1. "Shopify Uses HubSpot CRM to Transform High Volume Sales Organization," by HubSpot

What's interesting about this case study is the way it leads with the customer. This reflects a major HubSpot value, which is to always solve for the customer first. The copy leads with a brief description of why Shopify uses HubSpot and is accompanied by a short video and some basic statistics on the company.

Notice that this case study uses mixed media. Yes, there is a short video, but it's elaborated upon in the additional text on the page. So, while case studies can use one or the other, don't be afraid to combine written copy with visuals to emphasize the project's success.

2. "New England Journal of Medicine," by Corey McPherson Nash

When branding and design studio Corey McPherson Nash showcases its work, it makes sense for it to be visual — after all, that's what they do. So in building the case study for the studio's work on the New England Journal of Medicine's integrated advertising campaign — a project that included the goal of promoting the client's digital presence — Corey McPherson Nash showed its audience what it did, rather than purely telling it.

Notice that the case study does include some light written copy — which includes the major points we've suggested — but lets the visuals do the talking, allowing users to really absorb the studio's services.

3. "Designing the Future of Urban Farming," by IDEO

Here's a design company that knows how to lead with simplicity in its case studies. As soon as the visitor arrives at the page, he or she is greeted with a big, bold photo, and two very simple columns of text — "The Challenge" and "The Outcome."

Immediately, IDEO has communicated two of the case study's major pillars. And while that's great — the company created a solution for vertical farming startup INFARM's challenge — it doesn't stop there. As the user scrolls down, those pillars are elaborated upon with comprehensive (but not overwhelming) copy that outlines what that process looked like, replete with quotes and additional visuals.

4. "Secure Wi-Fi Wins Big for Tournament," by WatchGuard

Then, there are the cases when visuals can tell almost the entire story — when executed correctly. Network security provider WatchGuard can do that through this video, which tells the story of how its services enhanced the attendee and vendor experience at the Windmill Ultimate Frisbee tournament.

5. Rock and Roll Hall of Fame Boosts Social Media Engagement and Brand Awareness with HubSpot

In the case study above , HubSpot uses photos, videos, screenshots, and helpful stats to tell the story of how the Rock and Roll Hall of Fame used the bot, CRM, and social media tools to gain brand awareness.

6. Small Desk Plant Business Ups Sales by 30% With Trello

This case study from Trello is straightforward and easy to understand. It begins by explaining the background of the company that decided to use it, what its goals were, and how it planned to use Trello to help them.

It then goes on to discuss how the software was implemented and what tasks and teams benefited from it. Towards the end, it explains the sales results that came from implementing the software and includes quotes from decision-makers at the company that implemented it.

7. Facebook's Mercedes Benz Success Story

Facebook's Success Stories page hosts a number of well-designed and easy-to-understand case studies that visually and editorially get to the bottom line quickly.

Each study begins with key stats that draw the reader in. Then it's organized by highlighting a problem or goal in the introduction, the process the company took to reach its goals, and the results. Then, in the end, Facebook notes the tools used in the case study.

Showcasing Your Work

You work hard at what you do. Now, it's time to show it to the world — and, perhaps more important, to potential customers. Before you show off the projects that make you the proudest, we hope you follow these important steps that will help you effectively communicate that work and leave all parties feeling good about it.

Editor's Note: This blog post was originally published in February 2017 but was updated for comprehensiveness and freshness in July 2021.

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Discussion Tools: Case Studies

Instructional tools that promote active, participatory learning are widely recognized as the most effective way to engage trainees, convey knowledge, develop skills, and change attitudes.

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Case Studies

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Information about the history and authors of the Resources for Research Ethics Collection

Case studies are a tool for discussing scientific integrity. Although one of the most frequently used tools for encouraging discussion, cases are only one of many possible tools. Many of the principles discussed below for discussing case studies can be generalized to other approaches to encouraging discussion about research ethics. Cases are designed to confront readers with specific real-life problems that do not lend themselves to easy answers. Case discussion demands critical and analytical skills and, when implemented in small groups, also fosters collaboration (Pimple, 2002). By providing a focus for discussion, cases help trainees to define or refine their own standards, to appreciate alternative approaches to identifying and resolving ethical problems, and to develop skills for analyzing and dealing with hard problems on their own. The effective use of case studies is comprised of many factors, including:

• appropriate selection of case(s) (topic, relevance, length, complexity)
• method of case presentation (verbal, printed, before or during discussion)
• format for case discussion (Email or Internet-based, small group, large group)
• leadership of case discussion (choice of discussion leader, roles and responsibilities for discussion leader)
• outcomes for case discussion (answers to specific questions, answers to general questions, written or verbal summaries)

It should be noted that ethical decision-making is a process rather than a specific correct answer. In this sense, unethical behavior is defined by a failure to engage in the process of ethical decision-making. It is always unacceptable to have made no reasonable attempt to define a consistent and defensible basis for conduct.  

Leading Case Discussions

For the sake of time and clarity of purpose, it is essential that one individual have responsibility for leading the group discussion. As a minimum, this responsibility should include:

• Reading the case aloud.
• Defining, and re-defining as needed, the questions to be answered.
• Encouraging discussion that is "on topic".
• Discouraging discussion that is "off topic".
• Keeping the pace of discussion appropriate to the time available.
• Eliciting contributions from all members of the discussion group.
• Summarizing both majority and minority opinions at the end of the discussion.

How should cases be analyzed?

Many of the skills necessary to analyze case studies can become tools for responding to real world problems. Cases, like the real world, contain uncertainties and ambiguities. Readers are encouraged to identify key issues, make assumptions as needed, and articulate options for resolution. In addition to the specific questions accompanying each case, readers might consider the following questions:

• Who are the affected parties (individuals, institutions, a field, society) in this situation?
• What interest(s) (material, financial, ethical, other) does each party have in the situation? Which interests are in conflict?
• Were the actions taken by each of the affected parties acceptable (ethical, legal, moral, or common sense)? If not, are there circumstances under which those actions would have been acceptable? Who should impose what sanction(s)?
• What other courses of action are open to each of the affected parties? What is the likely outcome of each course of action?
• For each party involved, what course of action would you take, and why?
• What actions could have been taken to avoid the conflict?

If consensus is not possible, then written or oral summaries should reflect majority and minority opinions.  

Is there a right answer?

ACCEPTABLE SOLUTIONS: Most problems will have several acceptable solutions or answers, but it will not always be the case that a perfect solution can be found. At times, even the best solution will still have some unsatisfactory consequences. UNACCEPTABLE SOLUTIONS: While more than one acceptable solution may be possible, not all solutions are acceptable. For example, obvious violations of specific rules and regulations or of generally accepted standards of conduct would typically be unacceptable. However, it is also plausible that blind adherence to accepted rules or standards would sometimes be an unacceptable course of action.

• Bebeau MJ with Pimple KD, Muskavitch KMT, Borden SL, Smith DH (1995): Moral Reasoning in Scientific Research: Cases for Teaching and Assessment . Indiana University.
• Elliott D, Stern JE (1997): Research Ethics - A Reader. University Press of New England, Hanover, NH.
• OEC Resources: Cases
• Ellison, Karin and Karin Wellner. (2013) Research, Ethics, and Society Cases: Discussion Guide , Online Ethics Center.
• The Case Method , Center for Innovation in Teaching & Learning, University of Illinois at Urbana-Champaign
• Herreid CF: National Center for Case Study Teaching in Science, State University of New York at Buffalo. This comprehensive site offers methodology, a case study collection, case study teachers, workshops, and links to additional resources. https://web.archive.org/web/20071006070923/http://ublib.buffalo.edu/libraries/projects/cases/case.html  
• Korenman SG, Shipp AC (1994): Teaching the Responsible Conduct of Research through a Case Study Approach: A Handbook for Instructors. Association of American Medical Colleges, Washington, DC.
• Macrina FL (2005): Scientific Integrity: An Introductory Text with Cases. 3rd edition, American Society for Microbiology Press, Washington, DC.
• National Academy of Sciences (2009): On Being a Scientist: Responsible Conduct in Research . 3rd Edition. Publication from the Committee on Science, Engineering, and Public Policy, National Academy of Sciences, National Academy of Engineering, and Institute of Medicine. National Academy Press, Washington DC.
• Penslar RL, ed. (1995): Research Ethics: Cases and Materials. Indiana University Press, Bloomington, IN.
• Pimple, KD (2002): Using Case Studies in Teaching Research Ethics
• Pimple KD (2002): Using Small Group Assignments in Teaching Research Ethics
• Schrag B, ed. (1996-2007): Graduate Research Ethics: Cases and Commentaries , Volumes 1-7, Association for Practical and Professional Ethics, Bloomington, Indiana.  

The Resources for Research Ethics Education site was originally developed and maintained by Dr. Michael Kalichman, Director of the Research Ethics Program at the University of California San Diego. The site was transferred to the Online Ethics Center in 2021 with the permission of the author.

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This material is based upon work supported by the National Science Foundation under Award No. 2055332. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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• How to Write Discussions and Conclusions

The discussion section contains the results and outcomes of a study. An effective discussion informs readers what can be learned from your experiment and provides context for the results.

What makes an effective discussion?

When you’re ready to write your discussion, you’ve already introduced the purpose of your study and provided an in-depth description of the methodology. The discussion informs readers about the larger implications of your study based on the results. Highlighting these implications while not overstating the findings can be challenging, especially when you’re submitting to a journal that selects articles based on novelty or potential impact. Regardless of what journal you are submitting to, the discussion section always serves the same purpose: concluding what your study results actually mean.

A successful discussion section puts your findings in context. It should include:

• the results of your research,
• a discussion of related research, and
• a comparison between your results and initial hypothesis.

Tip: Not all journals share the same naming conventions.

You can apply the advice in this article to the conclusion, results or discussion sections of your manuscript.

Our Early Career Researcher community tells us that the conclusion is often considered the most difficult aspect of a manuscript to write. To help, this guide provides questions to ask yourself, a basic structure to model your discussion off of and examples from published manuscripts. 

Questions to ask yourself:

• Was my hypothesis correct?
• If my hypothesis is partially correct or entirely different, what can be learned from the results? 
• How do the conclusions reshape or add onto the existing knowledge in the field? What does previous research say about the topic? 
• Why are the results important or relevant to your audience? Do they add further evidence to a scientific consensus or disprove prior studies? 
• How can future research build on these observations? What are the key experiments that must be done? 
• What is the “take-home” message you want your reader to leave with?

How to structure a discussion

Trying to fit a complete discussion into a single paragraph can add unnecessary stress to the writing process. If possible, you’ll want to give yourself two or three paragraphs to give the reader a comprehensive understanding of your study as a whole. Here’s one way to structure an effective discussion:

Writing Tips

While the above sections can help you brainstorm and structure your discussion, there are many common mistakes that writers revert to when having difficulties with their paper. Writing a discussion can be a delicate balance between summarizing your results, providing proper context for your research and avoiding introducing new information. Remember that your paper should be both confident and honest about the results! 

• Read the journal’s guidelines on the discussion and conclusion sections. If possible, learn about the guidelines before writing the discussion to ensure you’re writing to meet their expectations. 
• Begin with a clear statement of the principal findings. This will reinforce the main take-away for the reader and set up the rest of the discussion. 
• Explain why the outcomes of your study are important to the reader. Discuss the implications of your findings realistically based on previous literature, highlighting both the strengths and limitations of the research. 
• State whether the results prove or disprove your hypothesis. If your hypothesis was disproved, what might be the reasons? 
• Introduce new or expanded ways to think about the research question. Indicate what next steps can be taken to further pursue any unresolved questions. 
• If dealing with a contemporary or ongoing problem, such as climate change, discuss possible consequences if the problem is avoided. 
• Be concise. Adding unnecessary detail can distract from the main findings. 

Don’t

• Rewrite your abstract. Statements with “we investigated” or “we studied” generally do not belong in the discussion. 
• Include new arguments or evidence not previously discussed. Necessary information and evidence should be introduced in the main body of the paper. 
• Apologize. Even if your research contains significant limitations, don’t undermine your authority by including statements that doubt your methodology or execution. 
• Shy away from speaking on limitations or negative results. Including limitations and negative results will give readers a complete understanding of the presented research. Potential limitations include sources of potential bias, threats to internal or external validity, barriers to implementing an intervention and other issues inherent to the study design. 
• Overstate the importance of your findings. Making grand statements about how a study will fully resolve large questions can lead readers to doubt the success of the research. 

Snippets of Effective Discussions:

Consumer-based actions to reduce plastic pollution in rivers: A multi-criteria decision analysis approach

Identifying reliable indicators of fitness in polar bears

• How to Write a Great Title
• How to Write an Abstract
• How to Write Your Methods
• How to Report Statistics
• How to Edit Your Work

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How To Facilitate A Case Study Workshop Session

A case study can be used as part of a training workshop to facilitate a learning point or as part of an assessment programme to gauge candidate’s response and analysis of situations. Case studies can be great for sharing experiences and reaffirming knowledge and understanding.

Here are some reasons to give a case study a try:

• increases awareness of a problem and helps teams formulate possible solutions.
• exchanges ideas and helps team members share past experiences.
• helps to analyse a problem and reach a decision as a team.
• facilitates and reaffirms key learning points.

Pre-printed scenario cards (optional)

Space Required:

Small. Classroom or training room

Group Size:

6 to 16 people

Total Time:

• 5 minutes to introduction and setup
• 10 minutes per case study for analysis and discussion (based on 4 case studies)
• 5 minutes for final review and case study debrief

Case Study Setup

Select the topic or theme that you were like to focus on during the training exercise. Prepare some possible scenarios or research articles related to the subject.

Case studies should be descriptions of events that really happened or fictional but based on reality. When leading the exercise, you can present the case study yourself, provide it in written form or even use videos or audio clips.

When I lead case studies sessions, I normally print the question on a piece of A4 paper and laminate them ready for workshop.

Case Study Instructions

From experience, I have found that a case studies session can be delivered two different ways.

The first way is to simply provide the group with a scenario and let them discuss it together as one big group.

The alternative is to split the group into smaller sub-groups and provide each group with the scenario. Once all groups have an opportunity to analyse and discuss the scenario, ask each group to present their findings back. This is a good way to get participants that are less likely to open up in bigger groups involved.

Look at your group and think about what will work best and give you the results you need.

When leading the case studies session, actively listen to discussion and provide necessary assistance to facilitate (guide) the analysis and discussion in the proper direction. Make sure you lead the discussion towards the learning objectives of the training workshop.

If you have people that conflicting views, then let them argue their points. If the discussion becomes too heated, stop them and summarise the discussion points and move on.

If everyone in the group agrees on something, or the discussion becomes stagnant then try playing devil’s advocate to get participants to look at the scenario from a different point of view.

When introducing the scenario, ask the group to think about the following 5 questions:

• What’s the problem?
• What’s the cause of the problem?
• How could the problem have been avoided?
• What are the solutions to the problem?
• What can you learn from this scenario?

Try to be flexible with your timings. If you need to stop a scenario early because the group become too heated or the group have explored the subject completely, stop them and summarise before moving on. If the scenario leads to valuable learning and you’re running out of time, allow an extra five minutes and skip another scenario.

Tips and Guidance

A good way to lead up to a case study is to present the scenario to the group at the end of the day and ask them to read up on the material and prepare in the evening. The first part of the following days’ workshop should then be the case study.

I like to lead a case study session by simply handed over the question cards and letting the group begin the discussion on their own. At the end of the discussion, I’ll summarise the key points – help them identify why the case study was important to the learning and move on to the next one.

If you’re discussing any sensitive subjects such as child protection etc then it is important to tell the group at the beginning of the case study. Explain that anything discussed exercise must not be mentioned again and if anyone needs to leave for a couple of minutes then they are more than welcome to.

Further Reading

10 Tips for Better Facilitation 

How To Facilitate Group Discussions: The “Gallery” Exercise

Questions? Comments?  Let us know in the comments below!

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Gigi, I am glad this helped.

Can you elaborate on what you mean about the case studies not being based on a problem?

A big part of the value of this type of exercise is that you can ideally take emotions out of play and analyze an undesired situation or problem neutrally helping your team to better deal with these types of scenarios in real life when emotions could potentially flare up. If the person can realize the bigger picture and be equipped with productive ways to handle the situation then hopefully the outcome with be better in real life.

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The Perfect Opening Question

Explore more.

• Case Teaching
• Classroom Management

I n a successful case discussion, ideas and arguments fly around the room like a puck rocketing around the rink at a hockey game. “Ideally, we want students to discuss the case with each other. That means the opening question may be the professor’s only opportunity to speak before the discussion takes on a life of its own,” says Bill Schiano, Professor of Computer Information Systems at Bentley University, who regularly facilitates faculty seminars on case method teaching.

The Stakes Are High

The opening question is the key to a productive, valuable case discussion. It sets the first impression, establishes a tone, and determines the direction for the entire conversation that follows.

On the flip side, if the opening question falls flat, silence may reign. “Professors can panic when they don’t get immediate feedback from the class,” says Schiano. “There’s a deep vulnerability involved in case teaching. It can be scary even for experienced faculty to lead case discussions.”

Given its importance, professors should aim high when crafting an opening question designed to spark vigorous debate. Also, how the professor delivers the opening question can be just as important as the content of the question itself. “The opening question gives the professor an important opportunity to demonstrate energy and encourage engagement,” says William Ellet, a lecturer at University of Miami Business School who has served as a writing consultant and coach for the Harvard Business School MBA program for over 20 years. “If the professor shows he or she is interested in what the class has to say, students are more likely to respond with enthusiasm.”

"There’s a deep vulnerability involved in case teaching. It can be scary even for experienced faculty to lead case discussions.” Bill Schiano

There’s one more reason the opening question carries disproportionate weight—professors are most likely to have students’ undivided attention at the beginning of class. “People start to drift away no matter how good a performer the teacher may be,” notes Ellet. “So the opening question is the professor’s best chance to stimulate discussion while he or she still has the students’ full attention.”

Three Key Elements

The ideal opening case discussion question should have at least the following three characteristics. It should be:

Case method teaching demonstrates to business students how and when the concepts and theories they learn can be applied in the real world. “Case method teaching for business students is almost like laboratory work for science students,” explains Schiano. “It gives students a chance to test the theories they’ve learned and see how they apply in the real world. I want students to get caught up in the discussion and role playing. If they are assigned the role of CEO, board member, or outside consultant, I want the opening question to draw them into the story and help them embrace their role.”

A business classroom is likely to include students from various countries and backgrounds. For many of these students, English may not be their first language. Schiano suggests that professors therefore craft a precise, concise opening question. To ward off confusion, he advises teachers to avoid compound sentences that ask students to answer multiple questions. Instead, propose a focused question so that students understand what you are asking. Also, omit any idioms (like “ballpark figure,” “Monday morning quarterback,” or “pass the buck” in U.S. classrooms) that might confuse a non-native speaker.

Delivered as planned.

Many professors spend a long time crafting a sharp, precise question before class only to undermine their own hard work by offering a lengthy preamble, asking the question, and then quickly rephrasing it if they don’t immediately see dozens of students raising their hands. This can be a counterproductive move that drains energy from the room and leaves students unsure which question to answer—the original one or the rephrased version. Instead, Schiano advises professors to take a deep breath and wait. “Trust yourself and the class,” he says. “Ask your question as scripted, adhere to it exactly, and then wait at least 15 or 30 seconds. Students often need that time to come up with a good response to a thoughtful question. This is especially true for international students who may need extra time to translate and process the question before they can offer a response.”

Hitting the Jackpot

Let’s say a professor has posed a sharp opening question, resisted the urge to reframe the question, and set the stage for an immersive discussion. How can a teacher know whether the opening question has truly hit its mark and maximized the learning potential in the classroom?

SAMPLE OPENING QUESTIONS

Here are some road-tested structures for opening questions that can help you kick off a lively case discussion:

“You are [the protagonist] on [the date of the case] . What will you do today?”

“What is it like to work in [relevant business unit] at [company in the case] ?”

“How did [the protagonist] end up in this situation?”

“You are a consultant hired by [company in the case] . How would you decide what your client should do?”

For Schiano, a great opening question is one that results in the class dividing itself along several points of view. “Let’s say I pose an opening question that gives students three choices or viewpoints to pick,” he says. “Ideally, a cohort of students forms around each viewpoint, with all the groups holding strongly to their beliefs. This lets the professor play the role of a facilitator who guides the class through an enthusiastic discussion.”

Ellet agrees that great opening questions can produce spirited class discussions, but he notes that even the best questions can take time to generate that response. “I don’t measure the success of the opening question by how many students immediately raise their hands,” he says. “Cases are like puzzles. Sometimes they require slow and steady progress to fill in a picture and find a solution. Often, it doesn’t take more than a few student contributions at a time to build that picture. It’s always exciting when a case resonates so deeply with students and they have so much to say that they forget to raise their hands entirely and start speaking over one another so that the professor must restore order. But it’s important for teachers to have realistic expectations. Even the greatest case teachers won’t necessarily achieve that sort of vibrant discussion every single time.”

The Big Flop

Inevitably, every case teacher is likely to face that dreaded moment when an opening question is met with complete silence and a sea of befuddled faces.

It’s possible, of course, that students simply did not properly study the case or take the time to prepare for the discussion. “Any question can fail if students are not prepared,” admits Ellet. “If no hands go up, professors can probe preparedness by cold calling on students. If the students have not done the groundwork to prepare for the discussion, the professor could simply cancel the class. But when I’ve encountered this situation, I prefer to give the students 20 minutes to study the case individually or in groups and then resume the case discussion. I warn them that this is a one-time indulgence and that I will not do it again. But some teachers will build time into the start of each class for students to discuss cases among themselves in small groups; they feel that this produces better results.”

In other cases, students may be well-prepared, but the opening question  still  lands like a lead balloon. Sometimes the problem is that the opening question was too broad. “Let’s say you’re trying to get students to recognize a pattern of facts,” says Ellet. “Instead of asking students to make judgments, you can get the conversation started by leading the class through a series of objective, factual questions. Once the students have agreed on the facts of the case, then you can move on to the meatier and more meaningful questions:  How do you make sense of these facts? What are your judgments of the main issues?”

“Cases are like puzzles. Sometimes they require slow and steady progress to fill in a picture and find a solution.” William Ellet

Sometimes students  do  respond to the opening question, but they misinterpret the question or focus on a peripheral issue. “If the discussion starts heading down an unproductive path that I had not intended, that means I did not frame the question clearly enough,” says Schiano. “I never say ‘That’s not what I meant,’ because that sounds like I’m blaming the students. Instead, I ask a follow-up question to redirect the discussion and get it back onto the track that I wanted to take in the first place.”

Schiano has a few other tricks up his sleeve when it comes to keeping students engaged and increasing the odds that an opening question will lead to a productive discussion:

Vary the format of the opening question. Schiano sometimes launches case discussions with a poll or a writing exercise.

Experiment with alternatives when questions fall flat. If an opening question misses the mark, Schiano might try a radically different approach the next time he teaches that case. For instance, he might rearrange the discussion by taking a point from the middle or end of his lesson plan and repurposing that as his new opener.

Discuss cases with colleagues. Schiano finds it helpful to talk about cases with other professors to see if someone else has hit upon a particularly effective opening question that sparks robust classroom discussion.

Above all, says Ellet, case method teachers should have a fervor for experimentation. They should continuously look for ways to improve their opening questions, whether by making a disappointing opening question work better or boosting a good opening question to the next level. Ellet applies that philosophy in his own classroom. “I co-authored a three-page case four years ago,” he notes. “I’ve taught that case for years and I’m  still  finding new ways to work through it with students.”

Ellet also returns to the theme of reasonable expectations. “Professors need to be kinder to themselves,” he advises. “Teachers accustomed to the lecture hall approach may think that students have not learned anything unless they walk out of the classroom with full notebooks. But that’s not how you measure the success of a case discussion. If the students are asking themselves meaningful questions, exploring how certain facts relate to other elements of the case, and practicing how to think about real-world scenarios using knowledge from the case, then you have done your job as a professor.”

Bill Schiano is a professor of computer information systems at Bentley University. He teaches both managerial and technical courses exclusively using discussion and the case method and has done so in online and hybrid formats. Bill regularly facilitates the web-based seminar Teaching with Cases Online .

William Ellet  is a lecturer in the business law department at the University of Miami Business School, where he teaches critical thinking, writing, and speaking. He has over 20 years of experience as an MBA writing coach and teaches workshops on the case method all over the globe.

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Artificial intelligence in strategy

Can machines automate strategy development? The short answer is no. However, there are numerous aspects of strategists’ work where AI and advanced analytics tools can already bring enormous value. Yuval Atsmon is a senior partner who leads the new McKinsey Center for Strategy Innovation, which studies ways new technologies can augment the timeless principles of strategy. In this episode of the Inside the Strategy Room podcast, he explains how artificial intelligence is already transforming strategy and what’s on the horizon. This is an edited transcript of the discussion. For more conversations on the strategy issues that matter, follow the series on your preferred podcast platform .

Joanna Pachner: What does artificial intelligence mean in the context of strategy?

Yuval Atsmon: When people talk about artificial intelligence, they include everything to do with analytics, automation, and data analysis. Marvin Minsky, the pioneer of artificial intelligence research in the 1960s, talked about AI as a “suitcase word”—a term into which you can stuff whatever you want—and that still seems to be the case. We are comfortable with that because we think companies should use all the capabilities of more traditional analysis while increasing automation in strategy that can free up management or analyst time and, gradually, introducing tools that can augment human thinking.

Joanna Pachner: AI has been embraced by many business functions, but strategy seems to be largely immune to its charms. Why do you think that is?

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Yuval Atsmon: You’re right about the limited adoption. Only 7 percent of respondents to our survey about the use of AI say they use it in strategy or even financial planning, whereas in areas like marketing, supply chain, and service operations, it’s 25 or 30 percent. One reason adoption is lagging is that strategy is one of the most integrative conceptual practices. When executives think about strategy automation, many are looking too far ahead—at AI capabilities that would decide, in place of the business leader, what the right strategy is. They are missing opportunities to use AI in the building blocks of strategy that could significantly improve outcomes.

I like to use the analogy to virtual assistants. Many of us use Alexa or Siri but very few people use these tools to do more than dictate a text message or shut off the lights. We don’t feel comfortable with the technology’s ability to understand the context in more sophisticated applications. AI in strategy is similar: it’s hard for AI to know everything an executive knows, but it can help executives with certain tasks.

When executives think about strategy automation, many are looking too far ahead—at AI deciding the right strategy. They are missing opportunities to use AI in the building blocks of strategy.

Joanna Pachner: What kind of tasks can AI help strategists execute today?

Yuval Atsmon: We talk about six stages of AI development. The earliest is simple analytics, which we refer to as descriptive intelligence. Companies use dashboards for competitive analysis or to study performance in different parts of the business that are automatically updated. Some have interactive capabilities for refinement and testing.

The second level is diagnostic intelligence, which is the ability to look backward at the business and understand root causes and drivers of performance. The level after that is predictive intelligence: being able to anticipate certain scenarios or options and the value of things in the future based on momentum from the past as well as signals picked in the market. Both diagnostics and prediction are areas that AI can greatly improve today. The tools can augment executives’ analysis and become areas where you develop capabilities. For example, on diagnostic intelligence, you can organize your portfolio into segments to understand granularly where performance is coming from and do it in a much more continuous way than analysts could. You can try 20 different ways in an hour versus deploying one hundred analysts to tackle the problem.

Predictive AI is both more difficult and more risky. Executives shouldn’t fully rely on predictive AI, but it provides another systematic viewpoint in the room. Because strategic decisions have significant consequences, a key consideration is to use AI transparently in the sense of understanding why it is making a certain prediction and what extrapolations it is making from which information. You can then assess if you trust the prediction or not. You can even use AI to track the evolution of the assumptions for that prediction.

Those are the levels available today. The next three levels will take time to develop. There are some early examples of AI advising actions for executives’ consideration that would be value-creating based on the analysis. From there, you go to delegating certain decision authority to AI, with constraints and supervision. Eventually, there is the point where fully autonomous AI analyzes and decides with no human interaction.

Because strategic decisions have significant consequences, you need to understand why AI is making a certain prediction and what extrapolations it’s making from which information.

Joanna Pachner: What kind of businesses or industries could gain the greatest benefits from embracing AI at its current level of sophistication?

Yuval Atsmon: Every business probably has some opportunity to use AI more than it does today. The first thing to look at is the availability of data. Do you have performance data that can be organized in a systematic way? Companies that have deep data on their portfolios down to business line, SKU, inventory, and raw ingredients have the biggest opportunities to use machines to gain granular insights that humans could not.

Companies whose strategies rely on a few big decisions with limited data would get less from AI. Likewise, those facing a lot of volatility and vulnerability to external events would benefit less than companies with controlled and systematic portfolios, although they could deploy AI to better predict those external events and identify what they can and cannot control.

Third, the velocity of decisions matters. Most companies develop strategies every three to five years, which then become annual budgets. If you think about strategy in that way, the role of AI is relatively limited other than potentially accelerating analyses that are inputs into the strategy. However, some companies regularly revisit big decisions they made based on assumptions about the world that may have since changed, affecting the projected ROI of initiatives. Such shifts would affect how you deploy talent and executive time, how you spend money and focus sales efforts, and AI can be valuable in guiding that. The value of AI is even bigger when you can make decisions close to the time of deploying resources, because AI can signal that your previous assumptions have changed from when you made your plan.

Joanna Pachner: Can you provide any examples of companies employing AI to address specific strategic challenges?

Yuval Atsmon: Some of the most innovative users of AI, not coincidentally, are AI- and digital-native companies. Some of these companies have seen massive benefits from AI and have increased its usage in other areas of the business. One mobility player adjusts its financial planning based on pricing patterns it observes in the market. Its business has relatively high flexibility to demand but less so to supply, so the company uses AI to continuously signal back when pricing dynamics are trending in a way that would affect profitability or where demand is rising. This allows the company to quickly react to create more capacity because its profitability is highly sensitive to keeping demand and supply in equilibrium.

Joanna Pachner: Given how quickly things change today, doesn’t AI seem to be more a tactical than a strategic tool, providing time-sensitive input on isolated elements of strategy?

Yuval Atsmon: It’s interesting that you make the distinction between strategic and tactical. Of course, every decision can be broken down into smaller ones, and where AI can be affordably used in strategy today is for building blocks of the strategy. It might feel tactical, but it can make a massive difference. One of the world’s leading investment firms, for example, has started to use AI to scan for certain patterns rather than scanning individual companies directly. AI looks for consumer mobile usage that suggests a company’s technology is catching on quickly, giving the firm an opportunity to invest in that company before others do. That created a significant strategic edge for them, even though the tool itself may be relatively tactical.

Joanna Pachner: McKinsey has written a lot about cognitive biases  and social dynamics that can skew decision making. Can AI help with these challenges?

Yuval Atsmon: When we talk to executives about using AI in strategy development, the first reaction we get is, “Those are really big decisions; what if AI gets them wrong?” The first answer is that humans also get them wrong—a lot. [Amos] Tversky, [Daniel] Kahneman, and others have proven that some of those errors are systemic, observable, and predictable. The first thing AI can do is spot situations likely to give rise to biases. For example, imagine that AI is listening in on a strategy session where the CEO proposes something and everyone says “Aye” without debate and discussion. AI could inform the room, “We might have a sunflower bias here,” which could trigger more conversation and remind the CEO that it’s in their own interest to encourage some devil’s advocacy.

We also often see confirmation bias, where people focus their analysis on proving the wisdom of what they already want to do, as opposed to looking for a fact-based reality. Just having AI perform a default analysis that doesn’t aim to satisfy the boss is useful, and the team can then try to understand why that is different than the management hypothesis, triggering a much richer debate.

In terms of social dynamics, agency problems can create conflicts of interest. Every business unit [BU] leader thinks that their BU should get the most resources and will deliver the most value, or at least they feel they should advocate for their business. AI provides a neutral way based on systematic data to manage those debates. It’s also useful for executives with decision authority, since we all know that short-term pressures and the need to make the quarterly and annual numbers lead people to make different decisions on the 31st of December than they do on January 1st or October 1st. Like the story of Ulysses and the sirens, you can use AI to remind you that you wanted something different three months earlier. The CEO still decides; AI can just provide that extra nudge.

Joanna Pachner: It’s like you have Spock next to you, who is dispassionate and purely analytical.

Yuval Atsmon: That is not a bad analogy—for Star Trek fans anyway.

Joanna Pachner: Do you have a favorite application of AI in strategy?

Yuval Atsmon: I have worked a lot on resource allocation, and one of the challenges, which we call the hockey stick phenomenon, is that executives are always overly optimistic about what will happen. They know that resource allocation will inevitably be defined by what you believe about the future, not necessarily by past performance. AI can provide an objective prediction of performance starting from a default momentum case: based on everything that happened in the past and some indicators about the future, what is the forecast of performance if we do nothing? This is before we say, “But I will hire these people and develop this new product and improve my marketing”— things that every executive thinks will help them overdeliver relative to the past. The neutral momentum case, which AI can calculate in a cold, Spock-like manner, can change the dynamics of the resource allocation discussion. It’s a form of predictive intelligence accessible today and while it’s not meant to be definitive, it provides a basis for better decisions.

Joanna Pachner: Do you see access to technology talent as one of the obstacles to the adoption of AI in strategy, especially at large companies?

Yuval Atsmon: I would make a distinction. If you mean machine-learning and data science talent or software engineers who build the digital tools, they are definitely not easy to get. However, companies can increasingly use platforms that provide access to AI tools and require less from individual companies. Also, this domain of strategy is exciting—it’s cutting-edge, so it’s probably easier to get technology talent for that than it might be for manufacturing work.

The bigger challenge, ironically, is finding strategists or people with business expertise to contribute to the effort. You will not solve strategy problems with AI without the involvement of people who understand the customer experience and what you are trying to achieve. Those who know best, like senior executives, don’t have time to be product managers for the AI team. An even bigger constraint is that, in some cases, you are asking people to get involved in an initiative that may make their jobs less important. There could be plenty of opportunities for incorpo­rating AI into existing jobs, but it’s something companies need to reflect on. The best approach may be to create a digital factory where a different team tests and builds AI applications, with oversight from senior stakeholders.

The big challenge is finding strategists to contribute to the AI effort. You are asking people to get involved in an initiative that may make their jobs less important.

Joanna Pachner: Do you think this worry about job security and the potential that AI will automate strategy is realistic?

Yuval Atsmon: The question of whether AI will replace human judgment and put humanity out of its job is a big one that I would leave for other experts.

The pertinent question is shorter-term automation. Because of its complexity, strategy would be one of the later domains to be affected by automation, but we are seeing it in many other domains. However, the trend for more than two hundred years has been that automation creates new jobs, although ones requiring different skills. That doesn’t take away the fear some people have of a machine exposing their mistakes or doing their job better than they do it.

Joanna Pachner: We recently published an article about strategic courage in an age of volatility  that talked about three types of edge business leaders need to develop. One of them is an edge in insights. Do you think AI has a role to play in furnishing a proprietary insight edge?

Yuval Atsmon: One of the challenges most strategists face is the overwhelming complexity of the world we operate in—the number of unknowns, the information overload. At one level, it may seem that AI will provide another layer of complexity. In reality, it can be a sharp knife that cuts through some of the clutter. The question to ask is, Can AI simplify my life by giving me sharper, more timely insights more easily?

Joanna Pachner: You have been working in strategy for a long time. What sparked your interest in exploring this intersection of strategy and new technology?

Yuval Atsmon: I have always been intrigued by things at the boundaries of what seems possible. Science fiction writer Arthur C. Clarke’s second law is that to discover the limits of the possible, you have to venture a little past them into the impossible, and I find that particularly alluring in this arena.

AI in strategy is in very nascent stages but could be very consequential for companies and for the profession. For a top executive, strategic decisions are the biggest way to influence the business, other than maybe building the top team, and it is amazing how little technology is leveraged in that process today. It’s conceivable that competitive advantage will increasingly rest in having executives who know how to apply AI well. In some domains, like investment, that is already happening, and the difference in returns can be staggering. I find helping companies be part of that evolution very exciting.

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Research: Negotiating Is Unlikely to Jeopardize Your Job Offer

• Einav Hart,
• Julia Bear,
• Zhiying (Bella) Ren

A series of seven studies found that candidates have more power than they assume.

Job seekers worry about negotiating an offer for many reasons, including the worst-case scenario that the offer will be rescinded. Across a series of seven studies, researchers found that these fears are consistently exaggerated: Candidates think they are much more likely to jeopardize a deal than managers report they are. This fear can lead candidates to avoid negotiating altogether. The authors explore two reasons driving this fear and offer research-backed advice on how anxious candidates can approach job negotiations.

Imagine that you just received a job offer for a position you are excited about. Now what? You might consider negotiating for a higher salary, job flexibility, or other benefits , but you’re apprehensive. You can’t help thinking: What if I don’t get what I ask for? Or, in the worst-case scenario, what if the hiring manager decides to withdraw the offer?

• Einav Hart is an assistant professor of management at George Mason University’s Costello College of Business, and a visiting scholar at the Wharton School. Her research interests include conflict management, negotiations, and organizational behavior.
• Julia Bear is a professor of organizational behavior at the College of Business at Stony Brook University (SUNY). Her research interests include the influence of gender on negotiation, as well as understanding gender gaps in organizations more broadly.
• Zhiying (Bella) Ren is a doctoral student at the Wharton School of the University of Pennsylvania. Her research focuses on conversational dynamics in organizations and negotiations.

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New CAS Class Teaches the History of Empires Through Fashion and Beauty

Students design and construct custom outfits based on historical case studies.

Jilene Chua’s Fashion and Beauty Under War and Empire is a course on how clothing and makeup provided insights into war and empire in the 20th century.

Sam Thomas (COM’24)

Jackie ricciardi.

A skirt made of newspaper. A blonde wig with brown roots. A headband made of crocheted “plarn” (yarn made of repurposed plastic bags). A pair of army green pants with extra pockets sewn around the ankles.

In lieu of a traditional exam, Jilene Chua , a College of Arts & Sciences assistant professor of history, assigned her students a different kind of final for their Fashion and Beauty Under War and Empire class: designing and constructing an entire outfit. The course, which wrapped earlier this month, spans the time periods from settler colonialism in the 1800s to the modern day and sets out to examine how clothing and makeup can provide insights into war and empire in the 20th century.

During the final two meetings of the class, groups presented their creations, accompanied by historical case studies they wrote reflecting on the symbolism of each piece. While some students had sewing experience, others were crafting outfits for the first time.

Chua, who came to BU this year, says she designed the Fashion and Beauty Under War and Empire class as a way to unite her research interests of history, fashion, and empire. “I wanted to figure out a way to have students learn about [this history], but in a way that wasn’t just constant violence,” she says. “Sometimes, histories of empires can be really dark and involve a lot of brutal things, so I wanted the students to think about how unexpected things like clothing, fashion, and beauty can be ways of analyzing this form of power.”

Sometimes, histories of empires can be really dark and involve a lot of brutal things, so I wanted the students to think about how unexpected things like clothing, fashion, and beauty can be ways of analyzing this form of power. Jilene Chua

Chua says the students in the class—which attracted different majors and class years—made connections she hadn’t even considered. For example, one class discussion on the prevalence of camouflage in fashion turned into an analysis of military recruitment—specifically, how it affected students during their high school experience.

In a presentation titled “Sustainability & Empire Through Time,” students investigated how different populations utilized resources readily available around them for clothing. For example, one student created a crocheted wrap to reflect how some Native American tribes used the fur of Churro sheep for clothing since it was a by-product of a food source. Another student made a shirt and attached a Kirkland jasmine rice bag, representing how people repurposed food sacks during the Great Depression.

In another presentation, titled “Combat Couture: The American Culture of War,” students examined how fashion in the United States is based on a military aesthetic. They discussed the Bikini Atoll , a coral reef in the Pacific Ocean that the US government used as a nuclear testing site and how it displaced and harmed its inhabitants. The bikini swimsuit was introduced and named just four days after the testing. Now, when someone says “bikini,” it conjures images of summer days and swimming rather than nuclear waste. 

“It started to make me think about how I didn’t have that on my syllabus, so I changed it to adapt,” Chua said. “It made sense to add because they have all these experiences with militarism in their own lives that they’re bringing in.” 

During the presentation, one student displayed a fuzzy green jacket with a camo pattern with “Are you registered for the draft?” and only a “Yes” checkbox, painted on the back. This, the student explained, was meant to represent how the draft was not optional, as well as how “fashion can reframe ugly parts of an empire into something soft and fuzzy.”

Reflecting on the course, Kal Hawley (CAS’27) says they were excited to create outfits with the added historical context from the course. Their outfit included a blazer with sewn lace hanging from about waist level, a commentary on softness—that is, not being afraid of being vulnerable or perceived as weak.

Among other topics in the course are the commodification of human products such as hair, skincare during chemical warfare, and profit as a connection between war and beauty. 

Throughout the semester, Chua encouraged students to engage in sustainable practices. The class went together to Goodwill to pick out raw materials and clothing items and they discussed the environmental impacts of the fashion industry—for example, 87 percent of garments made each year end up in a landfill. The material they thrifted or recycled was then used to construct their final outfits.

Students were able to use BU’s Engineering Product Innovation Center (EPIC), right on the Charles River Campus, when crafting their clothes. EPIC spans 15,000 square feet and offers students access to a variety of engineering and manufacturing tools, such as laser cutters, welding equipment, drill presses, sewing machines, and more. 

Ivan Perez (CAS’24) had no experience making clothes and had no background in fashion before enrolling. He says he took the class as a creative outlet and because he wanted “to see how and what a class like this could offer.” His enrollment in the course was a “happy accident,” he says.

“Aside, of course, from the material covered throughout the semester, the class really helped me express myself creatively through an unfamiliar yet incredibly cool medium,” Perez says. “It certainly was a unique experience, and an obscure class that made the semester very memorable. It is something quite niche that BU offers. I was just fortunate enough to stumble upon a new diamond in the rough.”

Although the class focuses specifically on fashion and beauty, Chua says she hopes this kind of critical societal analysis carries over to other parts of her students’ lives.

“I think they’re already starting to make connections to how this is a culture of militarism all around us even today,” she says. “But with these big topics like war and empire, students can see how they also appear in everyday life, not just through clothing and beauty. We are still living this culture out, right now.”

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Jackie Ricciardi is a staff photojournalist at BU Today and Bostonia  magazine. She has worked as a staff photographer at newspapers that include the Augusta Chronicle  in Augusta, Ga., and at Seacoast Media Group in Portsmouth, N.H., where she was twice named New Hampshire Press Photographer of the Year. Profile

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• Open access
• Published: 11 May 2024

Does a perceptual gap lead to actions against digital misinformation? A third-person effect study among medical students

• Zongya Li   ORCID: orcid.org/0000-0002-4479-5971 1 &
• Jun Yan   ORCID: orcid.org/0000-0002-9539-8466 1  

BMC Public Health volume  24 , Article number:  1291 ( 2024 ) Cite this article

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We are making progress in the fight against health-related misinformation, but mass participation and active engagement are far from adequate. Focusing on pre-professional medical students with above-average medical knowledge, our study examined whether and how third-person perceptions (TPP), which hypothesize that people tend to perceive media messages as having a greater effect on others than on themselves, would motivate their actions against misinformation.

We collected the cross-sectional data through a self-administered paper-and-pencil survey of 1,500 medical students in China during April 2022.

Structural equation modeling (SEM) analysis, showed that TPP was negatively associated with medical students’ actions against digital misinformation, including rebuttal of misinformation and promotion of corrective information. However, self-efficacy and collectivism served as positive predictors of both actions. Additionally, we found professional identification failed to play a significant role in influencing TPP, while digital misinformation self-efficacy was found to broaden the third-person perceptual gap and collectivism tended to reduce the perceptual bias significantly.

Conclusions

Our study contributes both to theory and practice. It extends the third-person effect theory by moving beyond the examination of restrictive actions and toward the exploration of corrective and promotional actions in the context of misinformation., It also lends a new perspective to the current efforts to counter digital misinformation; involving pre-professionals (in this case, medical students) in the fight.

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Introduction

The widespread persistence of misinformation in the social media environment calls for effective strategies to mitigate the threat to our society [ 1 ]. Misinformation has received substantial scholarly attention in recent years [ 2 ], and solution-oriented explorations have long been a focus but the subject remains underexplored [ 3 ].

Health professionals, particularly physicians and nurses, are highly expected to play a role in the fight against misinformation as they serve as the most trusted information sources regarding medical topics [ 4 ]. However, some barriers, such as limitations regarding time and digital skills, greatly hinder their efforts to tackle misinformation on social media [ 5 ].

Medical students (i.e., college students majoring in health/medical science), in contrast to medical faculty, have a greater potential to become the major force in dealing with digital misinformation as they are not only equipped with basic medical knowledge but generally possess greater social media skills than the former generation [ 6 ]. Few studies, to our knowledge, have tried to explore the potential of these pre-professionals in tackling misinformation. Our research thus fills the gap by specifically exploring how these pre-professionals can be motivated to fight against digital health-related misinformation.

The third-person perception (TPP), which states that people tend to perceive media messages as having a greater effect on others than on themselves [ 7 ], has been found to play an important role in influencing individuals’ coping strategies related to misinformation. But empirical exploration from this line of studies has yielded contradictory results. Some studies revealed that individuals who perceived a greater negative influence of misinformation on others than on themselves were more likely to take corrective actions to debunk misinformation [ 8 ]. In contrast, some research found that stronger TPP reduced individuals’ willingness to engage in misinformation correction [ 9 , 10 ]. Such conflicting findings impel us to examine the association between the third-person perception and medical students’ corrective actions in response to misinformation, thus attempting to unveil the underlying mechanisms that promote or inhibit these pre-professionals’ engagement with misinformation.

Researchers have also identified several perceptual factors that motivate individuals’ actions against misinformation, especially efficacy-related concepts (e.g., self-efficacy and health literacy) and normative variables (e.g., subjective norms and perceived responsibility) [ 3 , 8 , 9 ]. However, most studies devote attention to the general population; little is known about whether and how these factors affect medical students’ intentions to deal with misinformation. We recruited Chinese medical students in order to study a social group that is mutually influenced by cultural norms (collectivism in Chinese society) and professional norms. Meanwhile, systematic education and training equip medical students with abundant clinical knowledge and good levels of eHealth literacy [ 5 ], which enable them to have potential efficacy in tackling misinformation. Our study thus aims to examine how medical students’ self-efficacy, cultural norms (i.e., collectivism) and professional norms (i.e., professional identification) impact their actions against misinformation.

Previous research has found self-efficacy to be a reliable moderator of optimistic bias, the tendency for individuals to consider themselves as less likely to experience negative events but more likely to experience positive events as compared to others [ 11 , 12 , 13 ]. As TPP is thought to be a product of optimistic bias, accordingly, self-efficacy should have the potential to influence the magnitude of third-person perception [ 14 , 15 ]. Meanwhile, scholars also suggest that the magnitude of TPP is influenced by social distance corollary [ 16 , 17 ]. Simply put, individuals tend to perceive those who are more socially distant from them to be more susceptible to the influence of undesirable media than those who are socially proximal [ 18 , 19 , 20 ]. From a social identity perspective, collectivism and professional identification might moderate the relative distance between oneself and others while the directions of such effects differ [ 21 , 22 ]. For example, collectivists tend to perceive a smaller social distance between self and others as “they are less likely to view themselves as distinct or unique from others” [ 23 ]. In contrast, individuals who are highly identified with their professional community (i.e., medical community) are more likely to perceive a larger social distance between in-group members (including themselves) and out-group members [ 24 ]. In this way, collectivism and professional identification might exert different effects on TPP. On this basis, this study aims to examine whether and how medical students’ perceptions of professional identity, self-efficacy and collectivism influence the magnitude of TPP and in turn influence their actions against misinformation.

Our study builds a model that reflects the theoretical linkages among self-efficacy, collectivism, professional identity, TPP, and actions against misinformation. The model, which clarifies the key antecedents of TPP and examines the mediating role of TPP, contribute to the third-person effect literature and offer practical contributions to countering digital misinformation.

Context of the study

As pre-professionals equipped with specialized knowledge and skills, medical students have been involved in efforts in health communication and promotion during the pandemic. For instance, thousands of medical students have participated in various volunteering activities in the fight against COVID-19, such as case data visualization [ 25 ], psychological counseling [ 26 ], and providing online consultations [ 27 ]. Due to the shortage of medical personnel and the burden of work, some medical schools also encouraged their students to participate in health care assistance in hospitals during the pandemic [ 28 , 29 ].

The flood of COVID-19 related misinformation has posed an additional threat to and burden on public health. We have an opportunity to address this issue and respond to the general public’s call for guidance from the medical community about COVID-19 by engaging medical students as a main force in the fight against coronavirus related misinformation.

Literature review

The third-person effect in the misinformation context.

Originally proposed by Davison [ 7 ], the third-person effect hypothesizes that people tend to perceive a greater effect of mass media on others than on themselves. Specifically, the TPE consists of two key components: the perceptual and the behavioral [ 16 ]. The perceptual component centers on the perceptual gap where individuals tend to perceive that others are more influenced by media messages than themselves. The behavioral component refers to the behavioral outcomes of the self-other perceptual gap in which people act in accordance with such perceptual asymmetry.

According to Perloff [ 30 ], the TPE is contingent upon situations. For instance, one general finding suggests that when media messages are considered socially undesirable, nonbeneficial, or involving risks, the TPE will get amplified [ 16 ]. Misinformation characterized as inaccurate, misleading, and even false, is regarded as undesirable in nature [ 31 ]. Based on this line of reasoning, we anticipate that people will tend to perceive that others would be more influenced by misinformation than themselves.

Recent studies also provide empirical evidence of the TPE in the context of misinformation [ 32 ]. For instance, an online survey of 511 Chinese respondents conducted by Liu and Huang [ 33 ] revealed that individuals would perceive others to be more vulnerable to the negative influence of COVID-19 digital disinformation. An examination of the TPE within a pre-professional group – the medical students–will allow our study to examine the TPE scholarship in a particular population in the context of tackling misinformation.

Why TPE occurs among medical students: a social identity perspective

Of the works that have provided explanations for the TPE, the well-known ones include self-enhancement [ 34 ], attributional bias [ 35 ], self-categorization theory [ 36 ], and the exposure hypothesis [ 19 ]. In this study, we argue for a social identity perspective as being an important explanation for third-person effects of misinformation among medical students [ 36 , 37 ].

The social identity explanation suggests that people define themselves in terms of their group memberships and seek to maintain a positive self-image through favoring the members of their own groups over members of an outgroup, which is also known as downward comparison [ 38 , 39 ]. In intergroup settings, the tendency to evaluate their ingroups more positively than the outgroups will lead to an ingroup bias [ 40 ]. Such an ingroup bias is typically described as a trigger for the third-person effect as individuals consider themselves and their group members superior and less vulnerable to undesirable media messages than are others and outgroup members [ 20 ].

In the context of our study, medical students highly identified with the medical community tend to maintain a positive social identity through an intergroup comparison that favors the ingroup and derogates the outgroup (i.e., the general public). It is likely that medical students consider themselves belonging to the medical community and thus are more knowledgeable and smarter than the general public in health-related topics, leading them to perceive the general public as more vulnerable to health-related misinformation than themselves. Accordingly, we propose the following hypothesis:

H1: As medical students’ identification with the medical community increases, the TPP concerning digital misinformation will become larger.

What influences the magnitude of TPP

Previous studies have demonstrated that the magnitude of the third-person perception is influenced by a host of factors including efficacy beliefs [ 3 ] and cultural differences in self-construal [ 22 , 23 ]. Self-construal is defined as “a constellation of thoughts, feelings, and actions concerning the relationship of the self to others, and the self as distinct from others” [ 41 ]. Markus and Kitayama (1991) identified two dimensions of self-construal: Independent and interdependent. Generally, collectivists hold an interdependent view of the self that emphasizes harmony, relatedness, and places importance on belonging, whereas individualists tend to have an independent view of the self and thus view themselves as distinct and unique from others [ 42 ]. Accordingly, cultural values such as collectivism-individualism should also play a role in shaping third-person perception due to the adjustment that people make of the self-other social identity distance [ 22 ].

Set in a Chinese context aiming to explore the potential of individual-level approaches to deal with misinformation, this study examines whether collectivism (the prevailing cultural value in China) and self-efficacy (an important determinant of ones’ behavioral intentions) would affect the magnitude of TPP concerning misinformation and how such impact in turn would influence their actions against misinformation.

The impact of self-efficacy on TPP

Bandura [ 43 ] refers to self-efficacy as one’s perceived capability to perform a desired action required to overcome barriers or manage challenging situations. He also suggests understanding self-efficacy as “a differentiated set of self-beliefs linked to distinct realms of functioning” [ 44 ]. That is to say, self-efficacy should be specifically conceptualized and operationalized in accordance with specific contexts, activities, and tasks [ 45 ]. In the context of digital misinformation, this study defines self-efficacy as one’s belief in his/her abilities to identify and verify misinformation within an affordance-bounded social media environment [ 3 ].

Previous studies have found self-efficacy to be a reliable moderator of biased optimism, which indicates that the more efficacious individuals consider themselves, the greater biased optimism will be invoked [ 12 , 23 , 46 ]. Even if self-efficacy deals only with one’s assessment of self in performing a task, it can still create the other-self perceptual gap; individuals who perceive a higher self-efficacy tend to believe that they are more capable of controlling a stressful or challenging situation [ 12 , 14 ]. As such, they are likely to consider themselves less vulnerable to negative events than are others [ 23 ]. That is, individuals with higher levels of self-efficacy tend to underestimate the impact of harmful messages on themselves, thereby widening the other-self perceptual gap.

In the context of fake news, which is closely related to misinformation, scholars have confirmed that fake news efficacy (i.e., a belief in one’s capability to evaluate fake news [ 3 ]) may lead to a larger third-person perception. Based upon previous research evidence, we thus propose the following hypothesis:

H2: As medical students’ digital misinformation self-efficacy increases, the TPP concerning digital misinformation will become larger.

The influence of collectivism on TPP

Originally conceptualized as a societal-level construct [ 47 ], collectivism reflects a culture that highlights the importance of collective goals over individual goals, defines the self in relation to the group, and places great emphasis on conformity, harmony and interdependence [ 48 ]. Some scholars propose to also examine cultural values at the individual level as culture is embedded within every individual and could vary significantly among individuals, further exerting effects on their perceptions, attitudes, and behaviors [ 49 ]. Corresponding to the construct at the macro-cultural level, micro-psychometric collectivism which reflects personality tendencies is characterized by an interdependent view of the self, a strong sense of other-orientation, and a great concern for the public good [ 50 ].

A few prior studies have indicated that collectivism might influence the magnitude of TPP. For instance, Lee and Tamborini [ 23 ] found that collectivism had a significant negative effect on the magnitude of TPP concerning Internet pornography. Such an impact can be understood in terms of biased optimism and social distance. Collectivists tend to view themselves as an integral part of a greater social whole and consider themselves less differentiated from others [ 51 ]. Collectivism thus would mitigate the third-person perception due to a smaller perceived social distance between individuals and other social members and a lower level of comparative optimism [ 22 , 23 ]. Based on this line of reasoning, we thus propose the following hypothesis:

H3: As medical students’ collectivism increases, the TPP concerning digital misinformation will become smaller.

Behavioral consequences of TPE in the misinformation context

The behavioral consequences trigged by TPE have been classified into three categories: restrictive actions refer to support for censorship or regulation of socially undesirable content such as pornography or violence on television [ 52 ]; corrective action is a specific type of behavior where people seek to voice their own opinions and correct the perceived harmful or ambiguous messages [ 53 ]; promotional actions target at media content with desirable influence, such as advocating for public service announcements [ 24 ]. In a word, restriction, correction and promotion are potential behavioral outcomes of TPE concerning messages with varying valence of social desirability [ 16 ].

Restrictive action as an outcome of third-person perceptual bias (i.e., the perceptual component of TPE positing that people tend to perceive media messages to have a greater impact on others than on themselves) has received substantial scholarly attention in past decades; scholars thus suggest that TPE scholarship to go beyond this tradition and move toward the exploration of corrective and promotional behaviors [ 16 , 24 ]. Moreover, individual-level corrective and promotional actions deserve more investigation specifically in the context of countering misinformation, as efforts from networked citizens have been documented as an important supplement beyond institutional regulations (e.g., drafting policy initiatives to counter misinformation) and platform-based measures (e.g., improving platform algorithms for detecting misinformation) [ 8 ].

In this study, corrective action specifically refers to individuals’ reactive behaviors that seek to rectify misinformation; these include such actions as debunking online misinformation by commenting, flagging, or reporting it [ 3 , 54 ]. Promotional action involves advancing correct information online, including in response to misinformation that has already been disseminated to the public [ 55 ].

The impact of TPP on corrective and promotional actions

Either paternalism theory [ 56 ] or the protective motivation theory [ 57 ] can act as an explanatory framework for behavioral outcomes triggered by third-person perception. According to these theories, people act upon TPP as they think themselves to know better and feel obligated to protect those who are more vulnerable to negative media influence [ 58 ]. That is, corrective and promotional actions as behavioral consequences of TPP might be driven by a protective concern for others and a positive sense of themselves.

To date, several empirical studies across contexts have examined the link between TPP and corrective actions. Koo et al. [ 8 ], for instance, found TPP was not only positively related to respondents’ willingness to correct misinformation propagated by others, but also was positively associated with their self-correction. Other studies suggest that TPP motivates individuals to engage in both online and offline corrective political participation [ 59 ], give a thumbs down to a biased story [ 60 ], and implement corrective behaviors concerning “problematic” TV reality shows [ 16 ]. Based on previous research evidence, we thus propose the following hypothesis:

H4: Medical students with higher degrees of TPP will report greater intentions to correct digital misinformation.

Compared to correction, promotional behavior has received less attention in the TPE research. Promotion commonly occurs in a situation where harmful messages have already been disseminated to the public and others appear to have been influenced by these messages, and it serves as a remedial action to amplify messages with positive influence which may in turn mitigate the detrimental effects of harmful messages [ 16 ].

Within this line of studies, however, empirical studies provide mixed findings. Wei and Golan [ 24 ] found a positive association between TPP of desirable political ads and promotional social media activism such as posting or linking the ad on their social media accounts. Sun et al. [ 16 ] found a negative association between TPP regarding clarity and community-connection public service announcements (PSAs) and promotion behaviors such as advocating for airing more PSAs in TV shows.

As promotional action is still underexplored in the TPE research, and existing evidence for the link between TPP and promotion is indeed mixed, we thus propose an exploratory research question:

RQ1: What is the relationship between TPP and medical students’ intentions to promote corrective information?

The impact of self-efficacy and collectivism on actions against misinformation

According to social cognitive theory, people with higher levels of self-efficacy tend to believe they are competent and capable and are more likely to execute specific actions [ 43 ]. Within the context of digital misinformation, individuals might become more willing to engage in misinformation correction if they have enough knowledge and confidence to evaluate information, and possess sufficient skills to verify information through digital tools and services [ 61 ].

Accordingly, we assumed medical students with higher levels of digital misinformation self-efficacy would be likely to become more active in the fight against misinformation.

H5: Medical students with higher levels of digital misinformation self-efficacy will report greater intentions to (a) correct misinformation and (b) promote corrective information on social media.

Social actions of collectivists are strongly guided by prevailing social norms, collective responsibilities, and common interest, goals, and obligations [ 48 ]. Hence, highly collectivistic individuals are more likely to self-sacrifice for group interests and are more oriented toward pro-social behaviors, such as adopting pro-environmental behaviors [ 62 ], sharing knowledge [ 23 ], and providing help for people in need [ 63 ].

Fighting against misinformation is also considered to comprise altruism, especially self-engaged corrective and promotional actions, as such actions are costly to the actor (i.e., taking up time and energy) but could benefit the general public [ 61 ]. Accordingly, we assume collectivism might play a role in prompting people to engage in reactive behaviors against misinformation.

It is also noted that collectivist values are deeply rooted in Chinese society and were especially strongly advocated during the outbreak of COVID-19 with an attempt to motivate prosocial behaviors [ 63 ]. Accordingly, we expected that the more the medical students were oriented toward collectivist values, the more likely they would feel personally obliged and normatively motivated to engage in misinformation correction. However, as empirical evidence was quite limited, we proposed exploratory research questions:

RQ2: Will medical students with higher levels of collectivism report greater intentions to (a) correct misinformation and (b) promote corrective information on social media?

The theoretical model

To integrate both the antecedents and consequences of TPP, we proposed a theoretical model (as shown in Fig. 1 ) to examine how professional identification, self-efficacy and collectivism would influence the magnitude of TPP, and how such impact would in turn influence medical students’ intentions to correct digital misinformation and promote corrective information. Thus, RQ3 was proposed:

RQ3: Will the TPP mediate the impact of self-efficacy and collectivism on medical students’ intentions to (a) correct misinformation, and (b) promote corrective information on social media? Fig. 1 The proposed theoretical model. DMSE = Digital Misinformation Self-efficacy; PIMC = Professional Identification with Medical Community; ICDM = Intention to Correct Digital Misinformation; IPCI = Intention to Promote Corrective Information Full size image

To examine the proposed hypotheses, this study utilized cross-sectional survey data from medical students in Tongji Medical College (TJMC) of China. TJMC is one of the birthplaces of Chinese modern medical education and among the first universities and colleges that offer eight-year curricula on clinical medicine. Further, TJMC is located in Wuhan, the epicenter of the initial COVID-19 outbreaks, thus its students might find the pandemic especially relevant – and threatening – to them.

The survey instrument was pilot tested using a convenience sample of 58 respondents, leading to minor refinements to a few items. Upon approval from the university’s Institutional Research Board (IRB), the formal investigation was launched in TJMC during April 2022. Given the challenges of reaching the whole target population and acquiring an appropriate sampling frame, this study employed purposive and convenience sampling.

We first contacted four school counselors as survey administrators through email with a letter explaining the objective of the study and requesting cooperation. All survey administrators were trained by the principal investigator to help with the data collection in four majors (i.e., basic medicine, clinical medicine, nursing, and public health). Paper-and-pencil questionnaires were distributed to students on regular weekly departmental meetings of each major as students in all grades (including undergraduates, master students, and doctoral students) were required to attend the meeting. The projected time of completion of the survey was approximately 10–15 min. The survey administrators indicated to students that participation was voluntary, their responses would remain confidential and secure, and the data would be used only for academic purposes. Though a total of 1,500 participants took the survey, 17 responses were excluded from the analysis as they failed the attention filters. Ultimately, a total of 1,483 surveys were deemed valid for analysis.

Of the 1,483 respondents, 624 (42.10%) were men and 855 (57.70%) were women, and four did not identify gender. The average age of the sample was 22.00 ( SD  = 2.54, ranging from 17 to 40). Regarding the distribution of respondents’ majors, 387 (26.10%) were in basic medicine, 390 (26.30%) in clinical medicine, 307 (20.70%) in nursing, and 399 (26.90%) in public health. In terms of university class, 1,041 (70.40%) were undergraduates, 291 (19.70%) were working on their master degrees, 146 (9.90%) were doctoral students, and five did not identify their class data.

Measurement of key variables

Perceived effects of digital misinformation on oneself and on others.

Three modified items adapted from previous research [ 33 , 64 ] were employed to measure perceived effects of digital misinformation on oneself. Respondents were asked to indicate to what extent they agreed with the following: (1) I am frequently concerned that the information about COVID-19 I read on social media might be false; (2) Misinformation on social media might misguide my understanding of the coronavirus; (3) Misinformation on social media might influence my decisions regarding COVID-19. The response categories used a 7-point scale, where 1 meant “strongly disagree” and 7 meant “strongly agree.” The measure of perceived effects of digital misinformation on others consisted of four parallel items with the same statement except replacing “I” and “my” with “the general others” and “their”. The three “self” items were averaged to create a measure of “perceived effects on oneself” ( M  = 3.98, SD  = 1.49, α  = 0.87). The three “others” items were also added and averaged to form an index of “perceived effects on others” ( M  = 4.62, SD  = 1.32, α  = 0.87).

The perceived self-other disparity (TPP)

TPP was derived by subtracting perceived effects on oneself from perceived effects on others.

Professional identification with medical community

Professional identification was measured using a three item, 7-point Likert-type scale (1 =  strongly disagree , 7 =  strongly agree ) adapted from previous studies [ 65 , 66 ] by asking respondents to indicate to what extent they agreed with the following statements: (1) I would be proud to be a medical staff member in the future; (2) I am committed to my major; and (3) I will be in an occupation that matches my current major. The three items were thus averaged to create a composite measure of professional identification ( M  = 5.34, SD  = 1.37, α  = 0.88).

Digital misinformation self-efficacy

Modified from previous studies [ 3 ], self-efficacy was measured with three items. Respondents were asked to indicate on a 7-point Linkert scale from 1 (strongly disagree) to 7 (strongly agree) their agreement with the following: (1) I think I can identify misinformation relating to COVID-19 on social media by myself; (2) I know how to verify misinformation regarding COVID-19 by using digital tools such as Tencent Jiaozhen Footnote 1 and Piyao.org.cn Footnote 2 ; (3) I am confident in my ability to identify digital misinformation relating to COVID-19. A composite measure of self-efficacy was constructed by averaging the three items ( M  = 4.38, SD  = 1.14, α  = 0.77).

• Collectivism

Collectivism was measured using four items adapted from previous research [ 67 ], in which respondents were asked to indicate their agreement with the following statements on a 7-point scale, from 1 (strongly disagree) to 7 (strongly agree): (1) Individuals should sacrifice self-interest for the group; (2) Group welfare is more important than individual rewards; (3) Group success is more important than individual success; and (4) Group loyalty should be encouraged even if individual goals suffer. Therefore, the average of the four items was used to create a composite index of collectivism ( M  = 4.47, SD  = 1.30, α  = 0.89).

Intention to correct digital misinformation

We used three items adapted from past research [ 68 ] to measure respondents’ intention to correct misinformation on social media. All items were scored on a 7-point scale from 1 (very unlikely) to 7 (very likely): (1) I will post a comment saying that the information is wrong; (2) I will message the person who posts the misinformation to tell him/her the post is wrong; (3) I will track the progress of social media platforms in dealing with the wrong post (i.e., whether it’s deleted or corrected). A composite measure of “intention to correct digital misinformation” was constructed by adding the three items and dividing by three ( M  = 3.39, SD  = 1.43, α  = 0.81).

Intention to promote corrective information

On a 7-point scale ranging from 1 (very unlikely) to 7 (very likely), respondents were asked to indicate their intentions to (1) Retweet the corrective information about coronavirus on my social media account; (2) Share the corrective information about coronavirus with others through Social Networking Services. The two items were averaged to create a composite measure of “intention to promote corrective information” ( M  = 4.60, SD  = 1.68, r  = 0.77).

Control variables

We included gender, age, class (1 = undergraduate degree; 2 = master degree; 3 = doctoral degree), and clinical internship (0 = none; 1 = less than 0.5 year; 2 = 0.5 to 1.5 years; 3 = 1.5 to 3 years; 4 = more than 3 years) as control variables in the analyses. Additionally, coronavirus-related information exposure (i.e., how frequently they were exposed to information about COVID-19 on Weibo, WeChat, and QQ) and misinformation exposure on social media (i.e., how frequently they were exposed to misinformation about COVID-19 on Weibo, WeChat, and QQ) were also assessed as control variables because previous studies [ 69 , 70 ] had found them relevant to misinformation-related behaviors. Descriptive statistics and bivariate correlations between main variables were shown in Table 1 .

Statistical analysis

We ran confirmatory factor analysis (CFA) in Mplus (version 7.4, Muthén & Muthén, 1998) to ensure the construct validity of the scales. To examine the associations between variables and tested our hypotheses, we performed structural equation modeling (SEM). Mplus was chosen over other SEM statistical package mainly because the current data set included some missing data, and the Mplus has its strength in handling missing data using full-information maximum likelihood imputation, which enabled us to include all available data [ 71 , 72 ]. Meanwhile, Mplus also shows great flexibility in modelling when simultaneously handling continuous, categorical, observed, and latent variables in a variety of models. Further, Mplus provides a variety of useful information in a concise manner [ 73 ].

Table 2 shows the model fit information for the measurement and structural models. Five latent variables were specified in the measurement model. To test the measurement model, we examined the values of Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) (Table 1 ). Cronbach’s alpha values ranged from 0.77 to 0.89. The CRs, which ranged from 0.78 to 0.91, exceeded the level of 0.70 recommended by Fornell (1982) and thus confirmed the internal consistency. The AVE estimates, which ranged from 0.54 to 0.78, exceeded the 0.50 lower limit recommended by Fornell and Larcker (1981), and thus supported convergent validity. All the square roots of AVE were greater than the off-diagonal correlations in the corresponding rows and columns [ 74 ]. Therefore, discriminant validity was assured. In a word, our measurement model showed sufficient convergence and discriminant validity.

Five model fit indices–the relative chi-square ratio (χ 2 / df ), the comparative fit index (CFI), the Tucker–Lewis index (TLI), the root mean square error of approximation (RMSEA), and the standardized root-mean-square residual (SRMR) were used to assess the model. Specifically, the normed chi-square between 1 and 5 is acceptable [ 75 ]. TLI and CFI over 0.95 are considered acceptable, SRMR value less than 0.08 and RMSEA value less than 0.06 indicate good fit [ 76 ]. Based on these criteria, the model was found to have an acceptable fit to the data.

Figure 2 presents the results of our hypothesized model. H1 was rejected as professional identification failed to predict TPP ( β  = 0.06, p  > 0.05). Self-efficacy was positively associated with TPP ( β  = 0.14, p  < 0.001) while collectivism was negatively related to TPP ( β  = -0.10, p  < 0.01), lending support to H2 and H3.

Note. N  = 1,483. The coefficients of relationships between latent variables are standardized beta coefficients. Significant paths are indicated by solid line; non-significant paths are indicated by dotted lines. * p  < .05, ** p  < .01; *** p  < .001. DMSE = Digital Misinformation Self-efficacy; PIMC = Professional Identification with Medical Community; ICDM = Intention to Correct Digital Misinformation; IPCI = Intention to Promote Corrective Information

H4 posited that medical students with higher degrees of TPP would report greater intentions to correct digital misinformation. However, we found a negative association between TPP and intentions to correct misinformation ( β  = -0.12, p  < 0.001). H4 was thus rejected. Regarding RQ1, results revealed that TPP was negatively associated with intentions to promote corrective information ( β  = -0.08, p  < 0.05).

Further, our results supported H5 as we found that self-efficacy had a significant positive relationship with corrective intentions ( β  = 0.18, p  < 0.001) and promotional intentions ( β  = 0.32, p  < 0.001). Collectivism was also positively associated with intentions to correct misinformation ( β  = 0.14, p  < 0.001) and promote corrective information ( β  = 0.20, p  < 0.001), which answered RQ2.

Regarding RQ3 (see Table 3 ), TPP significantly mediated the relationship between self-efficacy and intentions to correct misinformation ( β  = -0.016), as well as the relationship between self-efficacy and intentions to promote corrective information ( β  = -0.011). However, TPP failed to mediate either the association between collectivism and corrective intentions ( β  = 0.011, ns ) or the association between collectivism and promotional intentions ( β  = 0.007, ns ).

Recent research has highlighted the role of health professionals and scientists in the fight against misinformation as they are considered knowledgeable, ethical, and reliable [ 5 , 77 ]. This study moved a step further by exploring the great potential of pre-professional medical students to tackle digital misinformation. Drawing on TPE theory, we investigated how medical students perceived the impact of digital misinformation, the influence of professional identification, self-efficacy and collectivism on these perceptions, and how these perceptions would in turn affect their actions against digital misinformation.

In line with prior studies [ 3 , 63 ], this research revealed that self-efficacy and collectivism played a significant role in influencing the magnitude of third-person perception, while professional identification had no significant impact on TPP. As shown in Table 1 , professional identification was positively associated with perceived effects of misinformation on oneself ( r  = 0.14, p  < 0.001) and on others ( r  = 0.20, p  < 0.001) simultaneously, which might result in a diminished TPP. What explains a shared or joint influence of professional identification on self and others? A potential explanation is that even medical staff had poor knowledge about the novel coronavirus during the initial outbreak [ 78 ]. Accordingly, identification with the medical community was insufficient to create an optimistic bias concerning identifying misinformation about COVID-19.

Our findings indicated that TPP was negatively associated with medical students’ intentions to correct misinformation and promote corrective information, which contradicted our hypotheses but was consistent with some previous TPP research conducted in the context of perceived risk [ 10 , 79 , 80 , 81 ]. For instance, Stavrositu and Kim (2014) found that increased TPP regarding cancer risk was negatively associated with behavioral intentions to engage in further cancer information search/exchange, as well as to adopt preventive lifestyle changes. Similarly, Wei et al. (2008) found concerning avian flu news that TPP negatively predicted the likelihood of engaging in actions such as seeking relevant information and getting vaccinated. In contrast, the perceived effects of avian flu news on oneself emerged as a positive predictor of intentions to take protective behavior.

Our study shows a similar pattern as perceived effects of misinformation on oneself were positively associated with intentions to correct misinformation ( r  = 0.06, p  < 0.05) and promote corrective information ( r  = 0.10, p  < 0.001, See Table 1 ). While the reasons for the behavioral patterns are rather elusive, such findings are indicative of human nature. When people perceive misinformation-related risk to be highly personally relevant, they do not take chances. However, when they perceive others to be more vulnerable than themselves, a set of sociopsychological dynamics such as self-defense mechanism, positive illusion, optimistic bias, and social comparison provide a restraint on people’s intention to engage in corrective and promotional actions against misinformation [ 81 ].

In addition to the indirect effects via TPP, our study also revealed that self-efficacy and collectivism serve as direct and powerful drivers of corrective and promotive actions. Consistent with previous literature [ 61 , 68 ], individuals will be more willing to engage in social corrections of misinformation if they possess enough knowledge, skills, abilities, and resources to identify misinformation, as correcting misinformation is difficult and their effort would not necessarily yield positive outcomes. Collectivists are also more likely to engage in misinformation correction as they are concerned for the public good and social benefits, aiming to protect vulnerable people from being misguided by misinformation [ 82 ].

This study offers some theoretical advancements. First, our study extends the TPE theory by moving beyond the examination of restrictive actions and toward the exploration of corrective and promotional actions in the context of misinformation. This exploratory investigation suggests that self-other asymmetry biased perception concerning misinformation did influence individuals’ actions against misinformation, but in an unexpected direction. The results also suggest that using TPP alone to predict behavioral outcomes was deficient as it only “focuses on differences between ‘self’ and ‘other’ while ignoring situations in which the ‘self’ and ‘other’ are jointly influenced” [ 83 ]. Future research, therefore, could provide a more sophisticated understanding of third-person effects on behavior by comparing the difference of perceived effects on oneself, perceived effects on others, and the third-person perception in the pattern and strength of the effects on behavioral outcomes.

Moreover, institutionalized corrective solutions such as government and platform regulation are non-exhaustive [ 84 , 85 ]; it thus becomes critical to tap the great potential of the crowd to engage in the fight against misinformation [ 8 ] while so far, research on the motivations underlying users’ active countering of misinformation has been scarce. The current paper helps bridge this gap by exploring the role of self-efficacy and collectivism in predicting medical students’ intentions to correct misinformation and promote corrective information. We found a parallel impact of the self-ability-related factor and the collective-responsibility-related factor on intentions to correct misinformation and promote corrective information. That is, in a collectivist society like China, cultivating a sense of collective responsibility and obligation in tackling misinformation (i.e., a persuasive story told with an emphasis on collective interests of social corrections of misinformation), in parallel with systematic medical education and digital literacy training (particularly, handling various fact-checking tools, acquiring Internet skills for information seeking and verification) would be effective methods to encourage medical students to engage in active countering behaviors against misinformation. Moreover, such an effective means of encouraging social corrections of misinformation might also be applied to the general public.

In practical terms, this study lends new perspectives to the current efforts in dealing with digital misinformation by involving pre-professionals (in this case, medical students) into the fight against misinformation. As digital natives, medical students usually spend more time online, have developed sophisticated digital competencies and are equipped with basic medical knowledge, thus possessing great potential in tackling digital misinformation. This study further sheds light on how to motivate medical students to become active in thwarting digital misinformation, which can help guide strategies to enlist pre-professionals to reduce the spread and threat of misinformation. For example, collectivism education in parallel with digital literacy training would help increase medical students’ sense of responsibility for and confidence in tackling misinformation, thus encouraging them to engage in active countering behaviors.

This study also has its limitations. First, the cross-sectional survey study did not allow us to justify causal claims. Granted, the proposed direction of causality in this study is in line with extant theorizing, but there is still a possibility of reverse causal relationships. To establish causality, experimental research or longitudinal studies would be more appropriate. Our second limitation lies in the generalizability of our findings. With the focus set on medical students in Chinese society, one should be cautious in generalizing the findings to other populations and cultures. For example, the effects of collectivism on actions against misinformation might differ in Eastern and Western cultures. Further studies would benefit from replication in diverse contexts and with diverse populations to increase the overall generalizability of our findings.

Drawing on TPE theory, our study revealed that TPP failed to motivate medical students to correct misinformation and promote corrective information. However, self-efficacy and collectivism were found to serve as direct and powerful drivers of corrective and promotive actions. Accordingly, in a collectivist society such as China’s, cultivating a sense of collective responsibility in tackling misinformation, in parallel with efficient personal efficacy interventions, would be effective methods to encourage medical students, even the general public, to actively engage in countering behaviors against misinformation.

Availability of data and materials

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

Tencent Jiaozhen Fact-Checking Platform which comprises the Tencent information verification tool allow users to check information authenticity through keyword searching. The tool is updated on a daily basis and adopts a human-machine collaboration approach to discovering, verifying, and refuting rumors and false information. For refuting rumors, Tencent Jiaozhen publishes verified content on the homepage of Tencent's rumor-refuting platform, and uses algorithms to accurately push this content to users exposed to the relevant rumors through the WeChat dispelling assistant.

Piyao.org.cn is hosted by the Internet Illegal Information Reporting Center under the Office of the Central Cyberspace Affairs Commission and operated by Xinhuanet.com. The platform is a website that collects statements from Twitter-like services, news portals and China's biggest search engine, Baidu, to refute online rumors and expose the scams of phishing websites. It has integrated over 40 local rumor-refuting platforms and uses artificial intelligence to identify rumors.

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We thank all participants and staff working for the project.

This work was supported by Humanities and Social Sciences Youth Foundation of the Ministry of Education of China (Grant No. 21YJC860012).

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Li, Z., Yan, J. Does a perceptual gap lead to actions against digital misinformation? A third-person effect study among medical students. BMC Public Health 24 , 1291 (2024). https://doi.org/10.1186/s12889-024-18763-9

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• Published: 14 May 2024

A burden of proof study on alcohol consumption and ischemic heart disease

• Sinclair Carr   ORCID: orcid.org/0000-0003-0421-3145 1 ,
• Dana Bryazka 1 ,
• Susan A. McLaughlin 1 ,
• Peng Zheng 1 , 2 ,
• Sarasvati Bahadursingh 3 ,
• Aleksandr Y. Aravkin 1 , 2 , 4 ,
• Simon I. Hay   ORCID: orcid.org/0000-0002-0611-7272 1 , 2 ,
• Hilary R. Lawlor 1 ,
• Erin C. Mullany 1 ,
• Christopher J. L. Murray   ORCID: orcid.org/0000-0002-4930-9450 1 , 2 ,
• Sneha I. Nicholson 1 ,
• Jürgen Rehm 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 ,
• Gregory A. Roth 1 , 2 , 13 ,
• Reed J. D. Sorensen 1 ,
• Sarah Lewington 3 &
• Emmanuela Gakidou   ORCID: orcid.org/0000-0002-8992-591X 1 , 2  

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Cohort and case-control data have suggested an association between low to moderate alcohol consumption and decreased risk of ischemic heart disease (IHD), yet results from Mendelian randomization (MR) studies designed to reduce bias have shown either no or a harmful association. Here we conducted an updated systematic review and re-evaluated existing cohort, case-control, and MR data using the burden of proof meta-analytical framework. Cohort and case-control data show low to moderate alcohol consumption is associated with decreased IHD risk – specifically, intake is inversely related to IHD and myocardial infarction morbidity in both sexes and IHD mortality in males – while pooled MR data show no association, confirming that self-reported versus genetically predicted alcohol use data yield conflicting findings about the alcohol-IHD relationship. Our results highlight the need to advance MR methodologies and emulate randomized trials using large observational databases to obtain more definitive answers to this critical public health question.

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Introduction.

It is well known that alcohol consumption increases the risk of morbidity and mortality due to many health conditions 1 , 2 , with even low levels of consumption increasing the risk for some cancers 3 , 4 . In contrast, a large body of research has suggested that low to moderate alcohol intake – compared to no consumption – is associated with a decreased risk of ischemic heart disease (IHD). This has led to substantial epidemiologic and public health interest in the alcohol-IHD relationship 5 , particularly given the high prevalence of alcohol consumption 6 and the global burden of IHD 7 .

Extensive evidence from experimental studies that vary short-term alcohol exposure suggests that average levels of alcohol intake positively affect biomarkers such as apolipoprotein A1, adiponectin, and fibrinogen levels that lower the risk of IHD 8 . In contrast, heavy episodic drinking (HED) may have an adverse effect on IHD by affecting blood lipids, promoting coagulation and thus thrombosis risk, and increasing blood pressure 9 . With effects likely to vary materially by patterns of drinking, alcohol consumption must be considered a multidimensional factor impacting IHD outcomes.

A recent meta-analysis of the alcohol-IHD relationship using individual participant data from 83 observational studies 4 found, among current drinkers, that – relative to drinking less than 50 g/week – any consumption above this level was associated with a lower risk of myocardial infarction (MI) incidence and consumption between >50 and <100 g/week was associated with lower risk of MI mortality. When evaluating other subtypes of IHD excluding MI, the researchers found that consumption between >100 and <250 g/week was associated with a decreased risk of IHD incidence, whereas consumption greater than 350 g/week was associated with an increased risk of IHD mortality. Roerecke and Rehm further observed that low to moderate drinking was not associated with reduced IHD risk when accompanied by occasional HED 10 .

The cohort studies and case-control studies (hereafter referred to as ‘conventional observational studies’) used in these meta-analyses are known to be subject to various types of bias when used to estimate causal relationships 11 . First, neglecting to separate lifetime abstainers from former drinkers, some of whom may have quit due to developing preclinical symptoms (sometimes labeled ‘sick quitters’ 12 , 13 ), and to account for drinkers who reduce their intake as a result of such symptoms may introduce reverse causation bias 13 . That is, the risk of IHD in, for example, individuals with low to moderate alcohol consumption may be lower when compared to IHD risk in sick quitters, not necessarily because intake at this level causes a reduction in risk but because sick quitters are at higher risk of IHD. Second, estimates can be biased because of measurement error in alcohol exposure resulting from inaccurate reporting, random fluctuation in consumption over time (random error), or intentional misreporting of consumption due, for example, to social desirability effects 14 (systematic error). Third, residual confounding may bias estimates if confounders of the alcohol-IHD relationship, such as diet or physical activity, have not been measured accurately (e.g., only via a self-report questionnaire) or accounted for. Fourth, because alcohol intake is a time-varying exposure, time-varying confounding affected by prior exposure must be accounted for 15 . To date, only one study that used a marginal structural model to appropriately adjust for time-varying confounding found no association between alcohol consumption and MI risk 16 . Lastly, if exposure to a risk factor, such as alcohol consumption, did not happen at random – even if all known confounders of the relationship between alcohol and IHD were perfectly measured and accounted for – the potential for unmeasured confounders persists and may bias estimates 11 .

In recent years, the analytic method of Mendelian randomization (MR) has been widely adopted to quantify the causal effects of risk factors on health outcomes 17 , 18 , 19 . MR uses single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) for the exposure of interest. A valid IV should fulfill the following three assumptions: it must be associated with the risk factor (relevance assumption); there must be no common causes of the IV and the outcome (independence assumption); and the IV must affect the outcome only through the exposure (exclusion restriction or ‘no horizontal pleiotropy’ assumption) 20 , 21 . If all three assumptions are fulfilled, estimates derived from MR are presumed to represent causal effects 22 . Several MR studies have quantified the association between alcohol consumption and cardiovascular disease 23 , including IHD, using genes known to impact alcohol metabolism (e.g., ADH1B/C and ALDH2 24 ) or SNP combinations from genome-wide association studies 25 . In contrast to the inverse associations found in conventional observational studies, MR studies have found either no association or a harmful relationship between alcohol consumption and IHD 26 , 27 , 28 , 29 , 30 , 31 .

To advance the knowledge base underlying our understanding of this major health issue – critical given the worldwide ubiquity of alcohol use and of IHD – there is a need to systematically review and critically re-evaluate all available evidence on the relationship between alcohol consumption and IHD risk from both conventional observational and MR studies.

The burden of proof approach, developed by Zheng et al. 32 , is a six-step meta-analysis framework that provides conservative estimates and interpretations of risk-outcome relationships. The approach systematically tests and adjusts for common sources of bias defined according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria: representativeness of the study population, exposure assessment, outcome ascertainment, reverse causation, control for confounding, and selection bias. The key statistical tool to implement the approach is MR-BRT (meta-regression—Bayesian, regularized, trimmed 33 ), a flexible meta-regression tool that does not impose a log-linear relationship between the risk and outcome, but instead uses a spline ensemble to model non-linear relationships. MR-BRT also algorithmically detects and trims outliers in the input data, takes into account different reference and alternative exposure intervals in the data, and incorporates unexplained between-study heterogeneity in the uncertainty surrounding the mean relative risk (RR) curve (henceforth ‘risk curve’). For those risk-outcome relationships that meet the condition of statistical significance using conventionally estimated uncertainty intervals (i.e., without incorporating unexplained between-study heterogeneity), the burden of proof risk function (BPRF) is derived by calculating the 5th (if harmful) or 95th (if protective) quantile risk curve – inclusive of between-study heterogeneity – closest to the log RR of 0. The resulting BPRF is a conservative interpretation of the risk-outcome relationship based on all available evidence. The BPRF represents the smallest level of excess risk for a harmful risk factor or reduced risk for a protective risk factor that is consistent with the data, accounting for between-study heterogeneity. To quantify the strength of the evidence for the alcohol-IHD relationship, the BPRF can be summarized in a single metric, the risk-outcome score (ROS). The ROS is defined as the signed value of the average log RR of the BPRF across the 15th to 85th percentiles of alcohol consumption levels observed across available studies. The larger a positive ROS value, the stronger the alcohol-IHD association. For ease of interpretation, the ROS is converted into a star rating from one to five. A one-star rating (ROS < 0) indicates a weak alcohol-IHD relationship, and a five-star rating (ROS > 0.62) indicates a large effect size and strong evidence. Publication and reporting bias are evaluated with Egger’s regression and by visual inspection with funnel plots 34 . Further conceptual and technical details of the burden of proof approach are described in detail elsewhere 32 .

Using the burden of proof approach, we systematically re-evaluate all available eligible evidence from cohort, case-control, and MR studies published between 1970 and 2021 to conservatively quantify the dose-response relationship between alcohol consumption and IHD risk, calculated relative to risk at zero alcohol intake (i.e., current non-drinking, including lifetime abstinence or former use). We pool the evidence from all conventional observational studies combined, as well as individually for all three study designs, to estimate mean IHD risk curves. Based on patterns of results established by previous meta-analyses 4 , 35 , we also use data from conventional observational studies to estimate risk curves by IHD endpoint (morbidity or mortality) and further by sex, in addition to estimating risk curves for MI overall and by endpoint. We follow PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines 36 through all stages of this study (Supplementary Information section  1 , Fig.  S1 and Tables  S1 and S2 ) and comply with GATHER (Guidelines on Accurate and Transparent Health Estimates Reporting) recommendations 37 (Supplementary Information section  2 , Table  S3 ). The main findings and research implications of this work are summarized in Table  1 .

We updated the systematic review on the dose-response relationship between alcohol consumption and IHD previously conducted for the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020 1 . Of 4826 records identified in our updated systematic review (4769 from databases/registers and 57 by citation search and known literature), 11 were eligible based on our inclusion criteria and were included. In total, combined with the results of the previous systematic reviews 1 , 38 , information from 95 cohort studies 26 , 27 , 29 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 27 case-control studies 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 , and five MR studies 26 , 27 , 28 , 29 , 31 was included in our meta-analysis (see Supplementary Information section  1 , Fig.  S1 , for the PRISMA diagram). Details on the extracted effect sizes, the design of each included study, underlying data sources, number of participants, duration of follow-up, number of cases and controls, and bias covariates that were evaluated and potentially adjusted for can be found in the Supplementary Information Sections  4 , 5 , and 6 .

Table  2 summarizes key metrics of each risk curve modeled, including estimates of mean RR and 95% UI (inclusive of between-study heterogeneity) at select alcohol exposure levels, the exposure level and RR and 95% UI at the nadir (i.e., lowest RR), the 85th percentile of exposure observed in the data and its corresponding RR and 95% UI, the BPRF averaged at the 15th and 85th percentile of exposure, the average excess risk or risk reduction according to the exposure-averaged BPRF, the ROS, the associated star rating, the potential presence of publication or reporting bias, and the number of studies included.

We found large variation in the association between alcohol consumption and IHD by study design. When we pooled the results of cohort and case-control studies, we observed an inverse association between alcohol at average consumption levels and IHD risk; that is, drinking average levels of alcohol was associated with a reduced IHD risk relative to drinking no alcohol. In contrast, we did not find a statistically significant association between alcohol consumption and IHD risk when pooling results from MR studies. When we subset the conventional observational studies to those reporting on IHD by endpoint, we found no association between alcohol consumption and IHD morbidity or mortality due to large unexplained heterogeneity between studies. When we further subset those studies that reported effect size estimates by sex, we found that average alcohol consumption levels were inversely associated with IHD morbidity in males and in females, and with IHD mortality in males but not in females. When we analyzed only the studies that reported on MI, we found significant inverse associations between average consumption levels and MI overall and with MI morbidity. Visualizations of the risk curves for morbidity and mortality of IHD and MI are provided in Supplementary Information Section  9 (Figs.  S2a –c, S3a –c, and S4a–c ). Among all modeled risk curves for which a BPRF was calculated, the ROS ranged from −0.40 for MI mortality to 0.20 for MI morbidity. In the Supplementary Information, we also provide details on the RR and 95% UIs with and without between-study heterogeneity associated with each 10 g/day increase in consumption for each risk curve (Table  S10 ), the parameter specifications of the model (Tables  S11 and S12 ), and each risk curve from the main analysis estimated without trimming 10% of the data (Fig.  S5a–l and Table  S13 ).

Risk curve derived from conventional observational study data

The mean risk curve and 95% UI were first estimated by combining all evidence from eligible cohort and case-control studies that quantified the association between alcohol consumption and IHD risk. In total, information from 95 cohort studies and 27 case-control studies combining data from 7,059,652 participants were included. In total, 243,357 IHD events were recorded. Thirty-seven studies quantified the association between alcohol consumption and IHD morbidity only, and 44 studies evaluated only IHD mortality. The estimated alcohol-IHD association was adjusted for sex and age in all but one study. Seventy-five studies adjusted the effect sizes for sex, age, smoking, and at least four other covariates. We adjusted our risk curve for whether the study sample was under or over 50 years of age, whether the study outcome was consistent with the definition of IHD (according to the International Classification of Diseases [ICD]−9: 410-414; and ICD-10: I20-I25) or related to specified subtypes of IHD, whether the outcome was ascertained by self-report only or by at least one other measurement method, whether the study accounted for risk for reverse causation, whether the reference group was non-drinkers (including lifetime abstainers and former drinkers), and whether effect sizes were adjusted (1) for sex, age, smoking, and at least four other variables, (2) for apolipoprotein A1, and (3) for cholesterol, as these bias covariates were identified as significant by our algorithm.

Pooling all data from cohort and case-control studies, we found that alcohol consumption was inversely associated with IHD risk (Fig.  1 ). The risk curve was J-shaped – without crossing the null RR of 1 at high exposure levels – with a nadir of 0.69 (95% UI: 0.48–1.01) at 23 g/day. This means that compared to individuals who do not drink alcohol, the risk of IHD significantly decreases with increasing consumption up to 23 g/day, followed by a risk reduction that becomes less pronounced. The average BPRF calculated between 0 and 45 g/day of alcohol intake (the 15th and 85th percentiles of the exposure range observed in the data) was 0.96. Thus, when between-study heterogeneity is accounted for, a conservative interpretation of the evidence suggests drinking alcohol across the average intake range is associated with an average decrease in the risk of IHD of at least 4% compared to drinking no alcohol. This corresponds to a ROS of 0.04 and a star rating of two, which suggests that the association – on the basis of the available evidence – is weak. Although we algorithmically identified and trimmed 10% of the data to remove outliers, Egger’s regression and visual inspection of the funnel plot still indicated potential publication or reporting bias.

The panels show the log(relative risk) function, the relative risk function, and a modified funnel plot showing the residuals (relative to 0) on the x-axis and the estimated standard error that includes the reported standard error and between-study heterogeneity on the y-axis. RR relative risk, UI uncertainty interval. Source data are provided as a Source Data file.

Risk curve derived from case-control study data

Next, we estimated the mean risk curve and 95% UI for the relationship between alcohol consumption and IHD by subsetting the data to case-control studies only. We included a total of 27 case-control studies (including one nested case-control study) with data from 60,914 participants involving 16,892 IHD cases from Europe ( n  = 15), North America ( n  = 6), Asia ( n  = 4), and Oceania ( n  = 2). Effect sizes were adjusted for sex and age in most studies ( n  = 25). Seventeen of these studies further adjusted for smoking and at least four other covariates. The majority of case-control studies accounted for the risk of reverse causation ( n  = 25). We did not adjust our risk curve for bias covariates, as our algorithm did not identify any as significant.

Evaluating only data from case-control studies, we observed a J-shaped relationship between alcohol consumption and IHD risk, with a nadir of 0.65 (0.50–0.85) at 23 g/day (Fig.  2 ). The inverse association between alcohol consumption and IHD risk reversed at an intake level of 61 g/day. In other words, alcohol consumption between >0 and 60 g/day was associated with a lower risk compared to no consumption, while consumption at higher levels was associated with increased IHD risk. However, the curve above this level is flat, implying that the association between alcohol and increased IHD risk is the same between 61 and 100 g/day, relative to not drinking any alcohol. The BPRF averaged across the exposure range between the 15th and 85th percentiles, or 0–45 g/day, was 0.87, which translates to a 13% average reduction in IHD risk across the average range of consumption. This corresponds to a ROS of 0.14 and a three-star rating. After trimming 10% of the data, no potential publication or reporting bias was found.

The panels show the log(relative risk) function, the relative risk function, and a modified funnel plot showing the residuals (relative to 0) on the x-axis and the estimated standard deviation that includes the reported standard deviation and between-study heterogeneity on the y-axis. RR relative risk, UI uncertainty interval. Source data are provided as a Source Data file.

Risk curve derived from cohort study data

We also estimated the mean risk curve and 95% UI for the relationship between alcohol consumption and IHD using only data from cohort studies. In total, 95 cohort studies – of which one was a retrospective cohort study – with data from 6,998,738 participants were included. Overall, 226,465 IHD events were recorded. Most data were from Europe ( n  = 43) and North America ( n  = 33), while a small number of studies were conducted in Asia ( n  = 14), Oceania ( n  = 3), and South America ( n  = 2). The majority of studies adjusted effect sizes for sex and age ( n  = 76). Fifty-seven of these studies also adjusted for smoking and at least four other covariates. Out of all cohort studies included, 88 accounted for the risk of reverse causation. We adjusted our risk curve for whether the study outcome was consistent with the definition of IHD or related to specified subtypes of IHD, and whether effect sizes were adjusted for apolipoprotein A1, as these bias covariates were identified as significant by our algorithm.

When only data from cohort studies were evaluated, we found a J-shaped relationship between alcohol consumption and IHD risk that did not cross the null RR of 1 at high exposure levels, with a nadir of 0.69 (0.47–1.01) at 23 g/day (Fig.  3 ). The shape of the risk curve was almost identical to the curve estimated with all conventional observational studies (i.e., cohort and case-control studies combined). When we calculated the average BPRF of 0.95 between the 15th and 85th percentiles of observed alcohol exposure (0–50 g/day), we found that alcohol consumption across the average intake range was associated with an average reduction in IHD risk of at least 5%. This corresponds to a ROS of 0.05 and a two-star rating. We identified potential publication or reporting bias after 10% of the data were trimmed.

Risk curve derived from Mendelian randomization study data

Lastly, we pooled evidence on the relationship between genetically predicted alcohol consumption and IHD risk from MR studies. Four MR studies were considered eligible for inclusion in our main analysis, with data from 559,708 participants from China ( n  = 2), the Republic of Korea ( n  = 1), and the United Kingdom ( n  = 1). Overall, 22,134 IHD events were recorded. Three studies used the rs671 ALDH2 genotype found in Asian populations, one study additionally used the rs1229984 ADH1B variant, and one study used the rs1229984 ADH1B Arg47His variant and a combination of 25 SNPs as IVs. All studies used the two-stage least squares (2SLS) method to estimate the association, and one study additionally applied the inverse-variance-weighted (IVW) method and multivariable MR (MVMR). For the study that used multiple methods to estimate effect sizes, we used the 2SLS estimates for our main analysis. Further details on the included studies are provided in Supplementary Information section  4 (Table  S6 ). Due to limited input data, we elected not to trim 10% of the observations. We adjusted our risk curve for whether the endpoint of the study outcome was mortality and whether the associations were adjusted for sex and/or age, as these bias covariates were identified as significant by our algorithm.

We did not find any significant association between genetically predicted alcohol consumption and IHD risk using data from MR studies (Fig.  4 ). No potential publication or reporting bias was detected.

As sensitivity analyses, we modeled risk curves with effect sizes estimated from data generated by Lankester et al. 28 using IVW and MVMR methods. We also used effect sizes from Biddinger et al. 31 , obtained using non-linear MR with the residual method, instead of those from Lankester et al. 28 in our main model (both were estimated with UK Biobank data) to estimate a risk curve. Again, we did not find a significant association between genetically predicted alcohol consumption and IHD risk (see Supplementary Information Section  10 , Fig.  S6a–c and Table  S14 ). To test for consistency with the risk curve we estimated using all included cohort studies, we also pooled the conventionally estimated effect sizes provided in the four MR studies. We did not observe an association between alcohol consumption and IHD risk due to large unexplained heterogeneity between studies (see Supplementary Information Section  10 , Fig.  S7, and Table  S14 ). Lastly, we pooled cohort studies that included data from China, the Republic of Korea, and the United Kingdom to account for potential geographic influences. Again, we did not find a significant association between alcohol consumption and IHD risk (see Supplementary Information Section  10 , Fig.  S8, and Table  S14 ).

Conventional observational and MR studies published to date provide conflicting estimates of the relationship between alcohol consumption and IHD. We conducted an updated systematic review and conservatively re-evaluated existing evidence on the alcohol-IHD relationship using the burden of proof approach. We synthesized evidence from cohort and case-control studies combined and separately and from MR studies to assess the dose-response relationship between alcohol consumption and IHD risk and to compare results across different study designs. It is anticipated that the present synthesis of evidence will be incorporated into upcoming iterations of GBD.

Our estimate of the association between genetically predicted alcohol consumption and IHD runs counter to our estimates from the self-report data and those of other previous meta-analyses 4 , 35 , 158 that pooled conventional observational studies. Based on the conservative burden of proof interpretation of the data, our results suggested an inverse association between alcohol and IHD when all conventional observational studies were pooled (alcohol intake was associated with a reduction in IHD risk by an average of at least 4% across average consumption levels; two-star rating). In evaluating only cohort studies, we again found an inverse association between alcohol consumption and IHD (alcohol intake was associated with a reduction in IHD risk by an average of at least 5% at average consumption levels; two-star rating). In contrast, when we pooled only case-control studies, we estimated that average levels of alcohol consumption were associated with at least a 13% average decrease in IHD risk (three-star rating), but the inverse association reversed when consumption exceeded 60 g/day, suggesting that alcohol above this level is associated with a slight increase in IHD risk. Our analysis of the available evidence from MR studies showed no association between genetically predicted alcohol consumption and IHD.

Various potential biases and differences in study designs may have contributed to the conflicting findings. In our introduction, we summarized important sources of bias in conventional observational studies of the association between alcohol consumption and IHD. Of greatest concern are residual and unmeasured confounding and reverse causation, the effects of which are difficult to eliminate in conventional observational studies. By using SNPs within an IV approach to predict exposure, MR – in theory – eliminates these sources of bias and allows for more robust estimates of causal effects. Bias may still occur, however, when using MR to estimate the association between alcohol and IHD 159 , 160 . There is always the risk of horizontal pleiotropy in MR – that is, the genetic variant may affect the outcome via pathways other than exposure 161 . The IV assumption of exclusion restriction is, for example, violated if only a single measurement of alcohol consumption is used in MR 162 ; because alcohol consumption varies over the life course, the gene directly impacts IHD through intake at time points other than that used in the MR analysis. To date, MR studies have not succeeded in separately capturing the multidimensional effects of alcohol intake on IHD risk (i.e., effects of average alcohol consumption measured through frequency-quantity, in addition to the effects of HED) 159 because the genes used to date only target average alcohol consumption that encompasses intake both at average consumption levels and HED. In other words, the instruments used are not able to separate out the individual effects of these two different dimensions of alcohol consumption on IHD risk using MR. Moreover, reverse causation may occur through cross-generational effects 160 , 163 , as the same genetic variants predispose both the individual and at least one of his or her parents to (increased) alcohol consumption. In this situation, IHD risk could be associated with the parents’ genetically predicted alcohol consumption and not with the individual’s own consumption. None of the MR studies included accounted for cross-generational effects, which possibly introduced bias in the effect estimates. It is important to note that bias by ancestry might also occur in conventional observational studies 164 . In summary, estimates of the alcohol-IHD association are prone to bias in all three study designs, limiting inferences of causation.

The large difference in the number of available MR versus conventional observational studies, the substantially divergent results derived from the different study types, and the rapidly developing field of MR clearly argue for further investigation of MR as a means to quantify the association between alcohol consumption and IHD risk. Future studies should investigate non-linearity in the relationship using non-linear MR methods. The residual method, commonly applied in non-linear MR studies such as Biddinger et al. 31 , assumes a constant, linear relationship between the genetic IV and the exposure in the study population; a strong assumption that may result in biased estimates and inflated type I error rates if the relationship varies by population strata 165 . However, by log-transforming the exposure, the relationships between the genetic IV and the exposure as expressed on a logarithmic scale may be more homogeneous across strata, possibly reducing the bias effect of violating the assumption of a constant, linear relationship. Alternatively, or in conjunction, the recently developed doubly ranked method, which obviates the need for this assumption, could be used 166 . Since methodology for non-linear MR is an active field of study 167 , potential limitations of currently available methods should be acknowledged and latest guidelines be followed 168 . Future MR studies should further (i) employ sensitivity analyses such as the MR weighted median method 169 to relax the exclusion restriction assumption that may be violated, as well as applying other methods such as the MR-Egger intercept test; (ii) use methods such as g-estimation of structural mean models 162 to adequately account for temporal variation in alcohol consumption in MR, and (iii) attempt to disaggregate the effects of alcohol on IHD by dimension in MR, potentially through the use of MVMR 164 . General recommendations to overcome common MR limitations are described in greater detail elsewhere 159 , 163 , 170 , 171 and should be carefully considered. With respect to prospective cohort studies used to assess the alcohol-IHD relationship, they should, at a minimum: (i) adjust the association between alcohol consumption and IHD for all potential confounders identified, for example, using a causal directed acyclic graph, and (ii) account for reverse causation introduced by sick quitters and by drinkers who changed their consumption. If possible, they should also (iii) use alcohol biomarkers as objective measures of alcohol consumption instead of or in addition to self-reported consumption to reduce bias through measurement error, (iv) investigate the association between IHD and HED, in addition to average alcohol consumption, and (v) when multiple measures of alcohol consumption and potential confounders are available over time, use g-methods to reduce bias through confounding as fully as possible within the limitations of the study design. However, some bias – due, for instance, to unmeasured confounding in conventional observational and to horizontal pleiotropy in MR studies – is likely inevitable, and the interpretation of estimates should be appropriately cautious, in accordance with the methods used in the study.

With the introduction of the Moderate Alcohol and Cardiovascular Health Trial (MACH15) 172 , randomized controlled trials (RCTs) have been revisited as a way to study the long-term effects of low to moderate alcohol consumption on cardiovascular disease, including IHD. In 2018, soon after the initiation of MACH15, the National Institutes of Health terminated funding 173 , reportedly due to concerns about study design and irregularities in the development of funding opportunities 174 . Although MACH15 was terminated, its initiation represented a previously rarely considered step toward investigating the alcohol-IHD relationship using an RCT 175 . However, while the insights from an RCT are likely to be invaluable, the implementation is fraught with potential issues. Due to the growing number of studies suggesting increased disease risk, including cancer 3 , 4 , associated with alcohol use even at very low levels 176 , the use of RCTs to study alcohol consumption is ethically questionable 177 . A less charged approach could include the emulation of target trials 178 using existing observational data (e.g., from large-scale prospective cohort studies such as the UK Biobank 179 , Atherosclerosis Risk in Communities Study 180 , or the Framingham Heart Study 181 ) in lieu of real trials to gather evidence on the potential cardiovascular effects of alcohol. Trials like MACH15 can be emulated, following the proposed trial protocols as closely as the observational dataset used for the analysis allows. Safety and ethical concerns, such as those related to eligibility criteria, initiation/increase in consumption, and limited follow-up duration, will be eliminated because the data will have already been collected. This framework allows for hypothetical trials investigating ethically challenging or even untenable questions, such as the long-term effects of heavy (episodic) drinking on IHD risk, to be emulated and inferences to broader populations drawn.

There are several limitations that must be considered when interpreting our findings. First, record screening for our systematic review was not conducted in a double-blinded fashion. Second, we did not have sufficient evidence to estimate and examine potential differential associations of alcohol consumption with IHD risk by beverage type or with MI endpoints by sex. Third, despite using a flexible meta-regression tool that overcame several limitations common to meta-analyses, the results of our meta-analysis were only as good as the quality of the studies included. We were able, however, to address the issue of varying quality of input data by adjusting for bias covariates that corresponded to core study characteristics in our analyses. Fourth, because we were only able to include one-sample MR studies that captured genetically predicted alcohol consumption, statistical power may be lower than would have been possible with the inclusion of two-sample MR studies, and studies that directly estimated gene-IHD associations were not considered 23 . Finally, we were not able to account for participants’ HED status when pooling effect size estimates from conventional observational studies. Given established differences in IHD risk for drinkers with and without HED 35 and the fact that more than one in three drinkers reports HED 6 , we would expect that the decreased average risk we found at moderate levels of alcohol consumption would be attenuated (i.e., approach the IHD risk of non-drinkers) if the presence of HED was taken into account.

Using the burden of proof approach 32 , we conservatively re-evaluated the dose-response relationship between alcohol consumption and IHD risk based on existing cohort, case-control, and MR data. Consistent with previous meta-analyses, we found that alcohol at average consumption levels was inversely associated with IHD when we pooled conventional observational studies. This finding was supported when aggregating: (i) all studies, (ii) only cohort studies, (iii) only case-control studies, (iv) studies examining IHD morbidity in females and males, (v) studies examining IHD mortality in males, and (vi) studies examining MI morbidity. In contrast, we found no association between genetically predicted alcohol consumption and IHD risk based on data from MR studies. Our confirmation of the conflicting results derived from self-reported versus genetically predicted alcohol use data highlights the need to advance methodologies that will provide more definitive answers to this critical public health question. Given the limitations of randomized trials, we advocate using advanced MR techniques and emulating target trials using observational data to generate more conclusive evidence on the long-term effects of alcohol consumption on IHD risk.

This study was approved by the University of Washington IRB Committee (study #9060).

The burden of proof approach is a six-step framework for conducting meta-analysis 32 : (1) data from published studies that quantified the dose-response relationship between alcohol consumption and ischemic heart disease (IHD) risk were systematically identified and obtained; (2) the shape of the mean relative risk (RR) curve (henceforth ‘risk curve’) and associated uncertainty was estimated using a quadratic spline and algorithmic trimming of outliers; (3) the risk curve was tested and adjusted for biases due to study attributes; (4) unexplained between-study heterogeneity was quantified, adjusting for within-study correlation and number of studies included; (5) the evidence for small-study effects was evaluated to identify potential risks of publication or reporting bias; and (6) the burden of proof risk function (BPRF) – a conservative interpretation of the average risk across the exposure range found in the data – was estimated relative to IHD risk at zero alcohol intake. The BPRF was converted to a risk-outcome score (ROS) that was mapped to a star rating from one to five to provide an intuitive interpretation of the magnitude and direction of the dose-response relationship between alcohol consumption and IHD risk.

We calculated the mean RR and 95% uncertainty intervals (UIs) for IHD associated with levels of alcohol consumption separately with all evidence available from conventional observational studies and from Mendelian randomization (MR) studies. For the risk curves that met the condition of statistical significance when the conventional 95% UI that does not include unexplained between-study heterogeneity was evaluated, we calculated the BPRF, ROS, and star rating. Based on input data from conventional observational studies, we also estimated these metrics by study design (cohort studies, case-control studies), and by IHD endpoint (morbidity, mortality) for both sexes (females, males) and sex-specific. For sex-stratified analyses, we only considered studies that reported effect sizes for both females and males to allow direct comparison of IHD risk across different exposure levels; however, we did not collect information about the method each study used to determine sex. We also estimated risk curves for myocardial infarction (MI), overall and by endpoint, using data from conventional observational studies. As a comparison, we also estimated each risk curve without trimming 10% of the input data. We did not consider MI as an outcome or disaggregate findings by sex or endpoint for MR studies due to insufficient data.

With respect to MR studies, several statistical methods are typically used to estimate the associations between genetically predicted exposure and health outcomes (e.g., two-stage least squares [2SLS], inverse-variance-weighted [IVW], multivariable Mendelian randomization [MVMR]). For our main analysis synthesizing evidence from MR studies, we included the reported effect sizes estimated using 2SLS if a study applied multiple methods because this method was common to all included studies. In sensitivity analyses, we used the effect sizes obtained by other MR methods (i.e., IVW, MVMR, and non-linear MR) and estimated the mean risk curve and uncertainty. We also pooled conventionally estimated effect sizes from MR studies to allow comparison with the risk curve estimated with cohort studies. Due to limited input data from MR studies, we elected not to trim 10% of the observations. Furthermore, we estimated the risk curve from cohort studies with data from countries that corresponded to those included in MR studies (China, the Republic of Korea, and the United Kingdom). Due to a lack of data, we were unable to estimate a risk curve from case-control studies in these geographic regions.

Conducting the systematic review

In step one of the burden of proof approach, data for the dose-response relationship between alcohol consumption and IHD risk were systematically identified, reviewed, and extracted. We updated a previously published systematic review 1 in PubMed that identified all studies evaluating the dose-response relationship between alcohol consumption and risk of IHD morbidity or mortality from January 1, 1970, to December 31, 2019. In our update, we additionally considered all studies up to and including December 31, 2021, for eligibility. We searched articles in PubMed on March 21, 2022, with the following search string: (alcoholic beverage[MeSH Terms] OR drinking behavior[MeSH Terms] OR “alcohol”[Title/Abstract]) AND (Coronary Artery Disease[Mesh] OR Myocardial Ischemia[Mesh] OR atherosclerosis[Mesh] OR Coronary Artery Disease[TiAb] OR Myocardial Ischemia[TiAb] OR cardiac ischemia[TiAb] OR silent ischemia[TiAb] OR atherosclerosis Outdent [TiAb] OR Ischemic heart disease[TiAb] OR Ischemic heart disease[TiAb] OR coronary heart disease[TiAb] OR myocardial infarction[TiAb] OR heart attack[TiAb] OR heart infarction[TiAb]) AND (Risk[MeSH Terms] OR Odds Ratio[MeSH Terms] OR “risk”[Title/Abstract] OR “odds ratio”[Title/Abstract] OR “cross-product ratio”[Title/Abstract] OR “hazards ratio”[Title/Abstract] OR “hazard ratio”[Title/Abstract]) AND (“1970/01/01”[PDat]: “2021/12/31”[PDat]) AND (English[LA]) NOT (animals[MeSH Terms] NOT Humans[MeSH Terms]). Studies were eligible for inclusion if they met all of the following criteria: were published between January 1, 1970, and December 31, 2021; were a cohort study, case-control study, or MR study; described an association between alcohol consumption and IHD and reported an effect size estimate (relative risk, hazard ratio, odds ratio); and used a continuous dose as exposure of alcohol consumption. Studies were excluded if they met any of the following criteria: were an aggregate study (meta-analysis or pooled cohort); utilized a study design not designated for inclusion in this analysis: not a cohort study, case-control study, or MR study; were a duplicate study: the underlying sample of the study had also been analyzed elsewhere (we always considered the analysis with the longest follow-up for cohort studies or the most recently published analysis for MR studies); did not report on the exposure of interest: reported on combined exposure of alcohol and drug use or reported alcohol consumption in a non-continuous way; reported an outcome that was not IHD or a composite outcome that included but was not limited to IHD, or outcomes lacked specificity, such as cardiovascular disease or all-cause mortality; were not in English; and were animal studies. All screenings of titles and abstracts of identified records, as well as full texts of potentially eligible studies, and extraction of included studies, were done by a single reviewer (SC or HL) independently. If eligible, studies were extracted for study characteristics, exposure, outcome, adjusted confounders, and effect sizes and their uncertainty. While the previous systematic review only considered cohort and case-control studies, our update also included MR studies. We chose to consider only ‘one-sample’ MR studies, i.e., those in which genes, risk factors, and outcomes were measured in the same participants, and not ‘two-sample’ MR studies in which two different samples were used for the MR analysis so that we could fully capture study-specific information. We re-screened previously identified records for MR studies to consider all published MR studies in the defined time period. We also identified and included in our sensitivity analysis an MR study published in 2022 31 which used a non-linear MR method to estimate the association between genetically predicted alcohol consumption and IHD. When eligible studies reported both MR and conventionally estimated effect sizes (i.e., for the association between self-reported alcohol consumption and IHD risk), we extracted both. If studies used the same underlying sample and investigated the same outcome in the same strata, we included the study that had the longest follow-up. This did not apply when the same samples were used in conventional observational and MR studies, because they were treated separately when estimating the risk curve of alcohol consumption and IHD. Continuous exposure of alcohol consumption was defined as a frequency-quantity measure 182 and converted to g/day. IHD was defined according to the International Classification of Diseases (ICD)−9, 410-414, and ICD-10, I20-I25.

The raw data were extracted with a standardized extraction sheet (see Supplementary Information Section  3 , Table  S4 ). For conventional observational studies, when multiple effect sizes were estimated from differently adjusted regression models, we used those estimated with the model reported to be fully adjusted or the one with the most covariates. In the majority of studies, alcohol consumption was categorized based on the exposure range available in the data. If the lower end of a categorical exposure range (e.g., <10 g/day) of an effect size was not specified in the input data, we assumed that this was 0 g/day. If the upper end was not specified (e.g., >20 g/day), it was calculated by multiplying the lower end of the categorical exposure range by 1.5. When the association between alcohol and IHD risk was reported as a linear slope, the average consumption level in the sample was multiplied by the logarithm of the effect size to effectively render it categorical. From the MR study which employed non-linear MR 31 , five effect sizes and their uncertainty were extracted at equal intervals across the reported range of alcohol exposure using WebPlotDigitizer. To account for the fact that these effect sizes were derived from the same non-linear risk curve, we adjusted the extracted standard errors by multiplying them by the square root of five (i.e., the number of extracted effect sizes). Details on data sources are provided in Supplementary Information Section  4 .

Estimating the shape of the risk-outcome relationship

In step two, the shape of the dose-response relationship (i.e., ‘signal’) between alcohol consumption and IHD risk was estimated relative to risk at zero alcohol intake. The meta-regression tool MR-BRT (meta-regression—Bayesian, regularized, trimmed), developed by Zheng et al. 33 , was used for modeling. To allow for non-linearity, thus relaxing the common assumption of a log-linear relationship, a quadratic spline with two interior knots was used for estimating the risk curve 33 . We used the following three risk measures from included studies: RRs, odds ratios (ORs), and hazard ratios (HRs). ORs were treated as equivalent to RRs and HRs based on the rare outcome assumption. To counteract the potential influence of knot placement on the shape of the risk curve when using splines, an ensemble model approach was applied. Fifty component models with random knot placements across the exposure domain were computed. These were combined into an ensemble by weighting each model based on model fit and variation (i.e., smoothness of fit to the data). To prevent bias from outliers, a robust likelihood-based approach was applied to trim 10% of the observations. Technical details on estimating the risk curve, use of splines, the trimming procedure, the ensemble model approach, and uncertainty estimation are described elsewhere 32 , 33 . Details on the model specifications for each risk curve are provided in Supplementary Information section  8 . We first estimated each risk curve without trimming input data to visualize the shape of the curve, which informed knot placement and whether to set a left and/or right linear tail when data were sparse at low or high exposure levels (see Supplementary Information Section  10 , Fig.  S5a–l ).

Testing and adjusting for biases across study designs and characteristics

In step three, the risk curve was tested and adjusted for systematic biases due to study attributes. According to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) criteria 183 , the following six bias sources were quantified: representativeness of the study population, exposure assessment, outcome ascertainment, reverse causation, control for confounding, and selection bias. Representativeness was quantified by whether the study sample came from a location that was representative of the underlying geography. Exposure assessment was quantified by whether alcohol consumption was recorded once or more than once in conventional observational studies, or with only one or multiple SNPs in MR studies. Outcome ascertainment was quantified by whether IHD was ascertained by self-report only or by at least one other measurement method. Reverse causation was quantified by whether increased IHD risk among participants who reduced or stopped drinking was accounted for (e.g., by separating former drinkers from lifetime abstainers). Control for confounding factors was quantified by which and how many covariates the effect sizes were adjusted for (i.e., through stratification, matching, weighting, or standardization). Because the most adjusted effect sizes in each study were extracted in the systematic review process and thus may have been adjusted for mediators, we additionally quantified a bias covariate for each of the following potential mediators of the alcohol-IHD relationship: body mass index, blood pressure, cholesterol (excluding high-density lipoprotein cholesterol), fibrinogen, apolipoprotein A1, and adiponectin. Selection bias was quantified by whether study participants were selected and included based on pre-existing disease states. We also quantified and considered as possible bias covariates whether the reference group was non-drinkers, including lifetime abstainers and former drinkers; whether the sample was under or over 50 years of age; whether IHD morbidity, mortality, or both endpoints were used; whether the outcome mapped to IHD or referred only to subtypes of IHD; whether the outcome mapped to MI; and what study design (cohort or case-control) was used when conventional observational studies were pooled. Details on quantified bias covariates for all included studies are provided in Supplementary Information section  5 (Tables  S7 and S8 ). Using a Lasso approach 184 , the bias covariates were first ranked. They were then included sequentially, based on their ranking, as effect modifiers of the ‘signal’ obtained in step two in a linear meta-regression. Significant bias covariates were included in modeling the final risk curve. Technical details of the Lasso procedure are described elsewhere 32 .

Quantifying between-study heterogeneity, accounting for heterogeneity, uncertainty, and small number of studies

In step four, the between-study heterogeneity was quantified, accounting for heterogeneity, uncertainty, and small number of studies. In a final linear mixed-effects model, the log RRs were regressed against the ‘signal’ and selected bias covariates, with a random intercept to account for within-study correlation and a study-specific random slope with respect to the ‘signal’ to account for between-study heterogeneity. A Fisher information matrix was used to estimate the uncertainty associated with between-study heterogeneity 185 because heterogeneity is easily underestimated or may be zero when only a small number of studies are available. We estimated the mean risk curve with a 95% UI that incorporated between-study heterogeneity, and we additionally estimated a 95% UI without between-study heterogeneity as done in conventional meta-regressions (see Supplementary Information Section  7 , Table  S10 ). The 95% UI incorporating between-study heterogeneity was calculated from the posterior uncertainty of the fixed effects (i.e., the ‘signal’ and selected bias covariates) and the 95% quantile of the between-study heterogeneity. The estimate of between-study heterogeneity and the estimate of the uncertainty of the between-study heterogeneity were used to determine the 95% quantile of the between-study heterogeneity. Technical details of quantifying uncertainty of between-study heterogeneity are described elsewhere 32 .

Evaluating potential for publication or reporting bias

In step five, the potential for publication or reporting bias was evaluated. The trimming algorithm used in step two helps protect against these biases, so risk curves found to have publication or reporting bias using the following methods were derived from data that still had bias even after trimming. Publication or reporting bias was evaluated using Egger’s regression 34 and visual inspection using funnel plots. Egger’s regression tested for a significant correlation between residuals of the RR estimates and their standard errors. Funnel plots showed the residuals of the risk curve against their standard errors. We reported publication or reporting bias when identified.

Estimating the burden of proof risk function

In step six, the BPRF was calculated for risk-outcome relationships that were statistically significant when evaluating the conventional 95% UI without between-study heterogeneity. The BPRF is either the 5th (if harmful) or the 95th (if protective) quantile curve inclusive of between-study heterogeneity that is closest to the RR line at 1 (i.e., null); it indicates a conservative estimate of a harmful or protective association at each exposure level, based on the available evidence. The mean risk curve, 95% UIs (with and without between-study heterogeneity), and BPRF (where applicable) are visualized along with included effect sizes using the midpoint of each alternative exposure range (trimmed data points are marked with a red x), with alcohol consumption in g/day on the x-axis and (log)RR on the y-axis.

We calculated the ROS as the average log RR of the BPRF between the 15th and 85th percentiles of alcohol exposure observed in the study data. The ROS summarizes the association of the exposure with the health outcome in a single measure. A higher, positive ROS indicates a larger association, while a negative ROS indicates a weak association. The ROS is identical for protective and harmful risks since it is based on the magnitude of the log RR. For example, a mean log BPRF between the 15th and 85th percentiles of exposure of −0.6 (protective association) and a mean log BPRF of 0.6 (harmful association) would both correspond to a ROS of 0.6. The ROS was then translated into a star rating, representing a conservative interpretation of all available evidence. A star rating of 1 (ROS: <0) indicates weak evidence of an association, a star rating of 2 (ROS: 0–0.14) indicates a >0–15% increased or >0–13% decreased risk, a star rating of 3 (ROS: >0.14–0.41) indicates a >15–50% increased or >13–34% decreased risk, a star rating of 4 (ROS: >0.41–0.62) indicates a >50–85% increased or >34–46% decreased risk, and a star rating of 5 (ROS: >0.62) indicates a >85% increased or >46% decreased risk.

Statistics & reproducibility

The statistical analyses conducted in this study are described above in detail. No statistical method was used to predetermine the sample size. When analyzing data from cohort and case-control studies, we excluded 10% of observations using a trimming algorithm; when analyzing data from MR studies, we did not exclude any observations. As all data used in this meta-analysis were from observational studies, no experiments were conducted, and no randomization or blinding took place.

Reporting summary

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

Data availability

The findings from this study were produced using data extracted from published literature. The relevant studies were identified through a systematic literature review and can all be accessed online as referenced in the current paper 26 , 27 , 28 , 29 , 31 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 , 157 . Further details on the relevant studies can be found on the GHDx website ( https://ghdx.healthdata.org/record/ihme-data/gbd-alcohol-ihd-bop-risk-outcome-scores ). Study characteristics of all relevant studies included in the analyses are also provided in Supplementary Information Section  4 (Tables  S5 and S6 ). The template of the data collection form is provided in Supplementary Information section  3 (Table  S4 ). The source data includes processed data from these studies that underlie our estimates. Source data are provided with this paper.

Code availability

Analyses were carried out using R version 4.0.5 and Python version 3.10.9. All code used for these analyses is publicly available online ( https://github.com/ihmeuw-msca/burden-of-proof ).

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Acknowledgements

Research reported in this publication was supported by the Bill & Melinda Gates Foundation [OPP1152504]. S.L. has received grants or contracts from the UK Medical Research Council [MR/T017708/1], CDC Foundation [project number 996], World Health Organization [APW No 2021/1194512], and is affiliated with the NIHR Oxford Biomedical Research Centre. The University of Oxford’s Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) is supported by core grants from the Medical Research Council [Clinical Trial Service Unit A310] and the British Heart Foundation [CH/1996001/9454]. The CTSU receives research grants from industry that are governed by University of Oxford contracts that protect its independence and has a staff policy of not taking personal payments from industry. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. The funders of the study had no role in study design, data collection, data analysis, data interpretation, writing of the final report, or the decision to publish.

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S.C., S.A.M., S.I.H., and E.C.M. managed the estimation or publications process. S.C. wrote the first draft of the manuscript. S.C. had primary responsibility for applying analytical methods to produce estimates. S.C. and H.R.L. had primary responsibility for seeking, cataloging, extracting, or cleaning data; designing or coding figures and tables. S.C., D.B., S.B., E.C.M., S.I.N., J.R., and R.J.D.S. provided data or critical feedback on data sources. S.C., D.B., P.Z., A.Y.A., S.I.N., and R.J.D.S. developed methods or computational machinery. S.C., D.B., P.Z., S.B., S.I.H., E.C.M., C.J.L.M., S.I.N., J.R., R.J.D.S., S.L., and E.G. provided critical feedback on methods or results. S.C., D.B., S.A.M., S.B., S.I.H., C.J.L.M., J.R., G.A.R., S.L., and E.G. drafted the work or revised it critically for important intellectual content. S.C., S.I.H., E.C.M., and E.G. managed the overall research enterprise.

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G.A.R. has received support for this manuscript from the Bill and Melinda Gates Foundation [OPP1152504]. S.L. has received grants or contracts from the UK Medical Research Council [MR/T017708/1], CDC Foundation [project number 996], World Health Organization [APW No 2021/1194512], and is affiliated with the NIHR Oxford Biomedical Research Centre. The University of Oxford’s Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU) is supported by core grants from the Medical Research Council [Clinical Trial Service Unit A310] and the British Heart Foundation [CH/1996001/9454]. The CTSU receives research grants from industry that are governed by University of Oxford contracts that protect its independence and has a staff policy of not taking personal payments from industry. All other authors declare no competing interests.

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Carr, S., Bryazka, D., McLaughlin, S.A. et al. A burden of proof study on alcohol consumption and ischemic heart disease. Nat Commun 15 , 4082 (2024). https://doi.org/10.1038/s41467-024-47632-7

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