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Making Learning Relevant With Case Studies

The open-ended problems presented in case studies give students work that feels connected to their lives.

Students working on projects in a classroom

To prepare students for jobs that haven’t been created yet, we need to teach them how to be great problem solvers so that they’ll be ready for anything. One way to do this is by teaching content and skills using real-world case studies, a learning model that’s focused on reflection during the problem-solving process. It’s similar to project-based learning, but PBL is more focused on students creating a product.

Case studies have been used for years by businesses, law and medical schools, physicians on rounds, and artists critiquing work. Like other forms of problem-based learning, case studies can be accessible for every age group, both in one subject and in interdisciplinary work.

You can get started with case studies by tackling relatable questions like these with your students:

  • How can we limit food waste in the cafeteria?
  • How can we get our school to recycle and compost waste? (Or, if you want to be more complex, how can our school reduce its carbon footprint?)
  • How can we improve school attendance?
  • How can we reduce the number of people who get sick at school during cold and flu season?

Addressing questions like these leads students to identify topics they need to learn more about. In researching the first question, for example, students may see that they need to research food chains and nutrition. Students often ask, reasonably, why they need to learn something, or when they’ll use their knowledge in the future. Learning is most successful for students when the content and skills they’re studying are relevant, and case studies offer one way to create that sense of relevance.

Teaching With Case Studies

Ultimately, a case study is simply an interesting problem with many correct answers. What does case study work look like in classrooms? Teachers generally start by having students read the case or watch a video that summarizes the case. Students then work in small groups or individually to solve the case study. Teachers set milestones defining what students should accomplish to help them manage their time.

During the case study learning process, student assessment of learning should be focused on reflection. Arthur L. Costa and Bena Kallick’s Learning and Leading With Habits of Mind gives several examples of what this reflection can look like in a classroom: 

Journaling: At the end of each work period, have students write an entry summarizing what they worked on, what worked well, what didn’t, and why. Sentence starters and clear rubrics or guidelines will help students be successful. At the end of a case study project, as Costa and Kallick write, it’s helpful to have students “select significant learnings, envision how they could apply these learnings to future situations, and commit to an action plan to consciously modify their behaviors.”

Interviews: While working on a case study, students can interview each other about their progress and learning. Teachers can interview students individually or in small groups to assess their learning process and their progress.

Student discussion: Discussions can be unstructured—students can talk about what they worked on that day in a think-pair-share or as a full class—or structured, using Socratic seminars or fishbowl discussions. If your class is tackling a case study in small groups, create a second set of small groups with a representative from each of the case study groups so that the groups can share their learning.

4 Tips for Setting Up a Case Study

1. Identify a problem to investigate: This should be something accessible and relevant to students’ lives. The problem should also be challenging and complex enough to yield multiple solutions with many layers.

2. Give context: Think of this step as a movie preview or book summary. Hook the learners to help them understand just enough about the problem to want to learn more.

3. Have a clear rubric: Giving structure to your definition of quality group work and products will lead to stronger end products. You may be able to have your learners help build these definitions.

4. Provide structures for presenting solutions: The amount of scaffolding you build in depends on your students’ skill level and development. A case study product can be something like several pieces of evidence of students collaborating to solve the case study, and ultimately presenting their solution with a detailed slide deck or an essay—you can scaffold this by providing specified headings for the sections of the essay.

Problem-Based Teaching Resources

There are many high-quality, peer-reviewed resources that are open source and easily accessible online.

  • The National Center for Case Study Teaching in Science at the University at Buffalo built an online collection of more than 800 cases that cover topics ranging from biochemistry to economics. There are resources for middle and high school students.
  • Models of Excellence , a project maintained by EL Education and the Harvard Graduate School of Education, has examples of great problem- and project-based tasks—and corresponding exemplary student work—for grades pre-K to 12.
  • The Interdisciplinary Journal of Problem-Based Learning at Purdue University is an open-source journal that publishes examples of problem-based learning in K–12 and post-secondary classrooms.
  • The Tech Edvocate has a list of websites and tools related to problem-based learning.

In their book Problems as Possibilities , Linda Torp and Sara Sage write that at the elementary school level, students particularly appreciate how they feel that they are taken seriously when solving case studies. At the middle school level, “researchers stress the importance of relating middle school curriculum to issues of student concern and interest.” And high schoolers, they write, find the case study method “beneficial in preparing them for their future.”

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Case studies

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Case studies usually involve real-life situations and often take the form of a problem-based inquiry approach; in other words students are presented with a complex real life situation that they are asked to find a solution to. “The benefits of utilizing case studies in instruction include the way that cases model how to think professionally about real problems and situations, helping candidates to think productively about concrete experiences” (Kleinfeld, 1990 in Ulanoff, Fingon and Beltran, 2009). The case study method involves placing students in the role of decision-makers and asking them to address a challenge that may confront a company, non-profit organisation or government department. In the absence of a single straightforward answer students are expected to exchange ideas, consider possible theoretical explanations and data, and weigh up possible solutions. Based on this exchange and evaluation of mixed data they are expected to come up with a decision, and choose a solution to the particular challenge. Though case study learning and assessment may take many forms the common thread is that the case study involves a real-life situation and finding solutions is the focus of the assessment.

Advantages of case studies

  • Enables students to apply their knowledge and skills to real life situations.
  • Can be undertaken individually or as a group assessment.
  • Generally designed to assess the higher levels of Bloom’s taxonomy of educational objectives (application, analysis and evaluation).
  • Well adapted to multi- or inter-disciplinary learning.
  • Calls on students to demonstrate a range of different skills such as the selection on information, analysis, decision-making problem-solving and presentation.
  • In the case of a group-based approach students are given the opportunity to demonstrate their ability to collaborate and communicate effectively.
  • Supports the development of a range of valuable employability skills which are likely to be attractive to employers and students alike.

Challenges of case studies

  • Case studies can be used in time-constrained examinations but this method of assessment really lends itself better to a coursework approach.
  • Can be a complex activity that involves negotiating a range of media that may be hard to contain in a controlled environment.
  • It is important to have realistic expectations of what actually can be achieved.
  • Planning and preparing for case study work can be time-consuming for teachers.

How students might experience case studies

There is some evidence to suggest that case studies increase students’ motivation. Students are often very interested in working on real life situations. It brings their learning alive and enables them not only to develop solutions to actual situations/problems but also to understand in new ways the valuable role that theory and relevant concepts can play as part of this process. In addition as part of their work on the case study they are clearly developing valuable transferable skills that they can take forward into the workplace and society at large. Students may not be used to this form of assessment so they will need clear guidance as to what is expected (length, format, main elements), a clear explanation of marking criteria as well as development in the different skills they will need to acquire in order to successfully complete the case study. These will in part depend on the nature of the case study - is data analysis involved?; where and how will students find relevant qualitative and quantitative data?; what is the appropriate way of citing and referencing?

Reliability, validity, fairness and inclusivity of case studies

Teaching and learning activities should be carefully designed to support the work on the case study or the development of the relevant skills and knowledge bases. From an inclusive design perspective case studies are an attractive form of learning and assessment.  Depending on the nature of the inquiry students may be given a degree of choice over their case study and thus be in a position to bring their different backgrounds and experience to bear. In any case, it is important to ensure that the chosen case studies are accessible to all students taking the course. In the case of first year students the teacher may want to provide all the relevant materials to the students. For more advanced students, they may be expected to do some research and to identify relevant supporting materials for the case study inquiry. Where group work is involved a number of options may be considered to ensure fairness. The students may complete some elements of both formative and summative work as a group as well as others individually. For example, students may complete various tasks or give a presentation on the case study as a group but write up part of the final case study individually. In addition, it is relatively common practice to ask students engaged in groupwork to write a short reflective piece discussing their experience of group work. Students can also be asked to rate their contribution and the contribution of other members of the group using one of a number of online group assessment tools such as WebPA and Teammates.

How to maintain and ensure rigour in case studies

Critical to ensuring rigour is having clarity about the different parts of the case study or, in the case of a single assessment task, the criteria against which the assessment will be marked; the weight that will be attached to different parts of the assignment, and the marking scheme.  Marking and moderation should follow departmental practice.

How to limit possible misconduct in case studies

Whether the students are working in groups or individually teachers can check that the work is the work of particular students by designing in opportunities to assess (formatively or summatively) work at several points in the assessment process. This can be done by asking students to present work in written or oral form – either by submitting assignment tasks via Moodle or making short presentations in class. In addition to serving as a check for misconduct this also provides an opportunity for teachers and peers to give constructive feedback on the development of the case study and as such constitutes good practice.

LSE examples

Daniel Ferreira discussed his use of case studies in teaching Master’s level Finance students for many years, and, starting in 2016/17 undergraduates with the introduction of the Finance department’s new BSc programme

http://lti.lse.ac.uk/lse-innovators/irene-papanicolas-healthy-collaboration/

Further resources

University of New South Wales, Sydney: Assessment by Case Studies and Scenarios https://teaching.unsw.edu.au/assessment-case-studies-and-scenarios

Assessment Resources at Hong Kong University: Types of Assessment Methods: Case Study http://ar.cetl.hku.hk/am_case_study.htm

Bonney, K.M. (2015) Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains.  Journal of Microbiological Education , 16(1): 21–28

Ulanoff, S.H., Fingon, J.C. and Beltrán, D. (2009) Using Case Studies To Assess Candidates’ Knowledge and Skills in a Graduate Reading Program,  Teacher Education Quarterly,  6(2): 125-142

Fry, H., Ketteridge, S. and Marshall, S. (1999)  A Handbook for Teaching and Learning in Higher Education,  Routledge, UK

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  • Knowledge Base

Methodology

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

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

Research bias

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

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Do Your Students Know How to Analyze a Case—Really?

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  • Case Teaching
  • Student Engagement

J ust as actors, athletes, and musicians spend thousands of hours practicing their craft, business students benefit from practicing their critical-thinking and decision-making skills. Students, however, often have limited exposure to real-world problem-solving scenarios; they need more opportunities to practice tackling tough business problems and deciding on—and executing—the best solutions.

To ensure students have ample opportunity to develop these critical-thinking and decision-making skills, we believe business faculty should shift from teaching mostly principles and ideas to mostly applications and practices. And in doing so, they should emphasize the case method, which simulates real-world management challenges and opportunities for students.

To help educators facilitate this shift and help students get the most out of case-based learning, we have developed a framework for analyzing cases. We call it PACADI (Problem, Alternatives, Criteria, Analysis, Decision, Implementation); it can improve learning outcomes by helping students better solve and analyze business problems, make decisions, and develop and implement strategy. Here, we’ll explain why we developed this framework, how it works, and what makes it an effective learning tool.

The Case for Cases: Helping Students Think Critically

Business students must develop critical-thinking and analytical skills, which are essential to their ability to make good decisions in functional areas such as marketing, finance, operations, and information technology, as well as to understand the relationships among these functions. For example, the decisions a marketing manager must make include strategic planning (segments, products, and channels); execution (digital messaging, media, branding, budgets, and pricing); and operations (integrated communications and technologies), as well as how to implement decisions across functional areas.

Faculty can use many types of cases to help students develop these skills. These include the prototypical “paper cases”; live cases , which feature guest lecturers such as entrepreneurs or corporate leaders and on-site visits; and multimedia cases , which immerse students into real situations. Most cases feature an explicit or implicit decision that a protagonist—whether it is an individual, a group, or an organization—must make.

For students new to learning by the case method—and even for those with case experience—some common issues can emerge; these issues can sometimes be a barrier for educators looking to ensure the best possible outcomes in their case classrooms. Unsure of how to dig into case analysis on their own, students may turn to the internet or rely on former students for “answers” to assigned cases. Or, when assigned to provide answers to assignment questions in teams, students might take a divide-and-conquer approach but not take the time to regroup and provide answers that are consistent with one other.

To help address these issues, which we commonly experienced in our classes, we wanted to provide our students with a more structured approach for how they analyze cases—and to really think about making decisions from the protagonists’ point of view. We developed the PACADI framework to address this need.

PACADI: A Six-Step Decision-Making Approach

The PACADI framework is a six-step decision-making approach that can be used in lieu of traditional end-of-case questions. It offers a structured, integrated, and iterative process that requires students to analyze case information, apply business concepts to derive valuable insights, and develop recommendations based on these insights.

Prior to beginning a PACADI assessment, which we’ll outline here, students should first prepare a two-paragraph summary—a situation analysis—that highlights the key case facts. Then, we task students with providing a five-page PACADI case analysis (excluding appendices) based on the following six steps.

Step 1: Problem definition. What is the major challenge, problem, opportunity, or decision that has to be made? If there is more than one problem, choose the most important one. Often when solving the key problem, other issues will surface and be addressed. The problem statement may be framed as a question; for example, How can brand X improve market share among millennials in Canada? Usually the problem statement has to be re-written several times during the analysis of a case as students peel back the layers of symptoms or causation.

Step 2: Alternatives. Identify in detail the strategic alternatives to address the problem; three to five options generally work best. Alternatives should be mutually exclusive, realistic, creative, and feasible given the constraints of the situation. Doing nothing or delaying the decision to a later date are not considered acceptable alternatives.

Step 3: Criteria. What are the key decision criteria that will guide decision-making? In a marketing course, for example, these may include relevant marketing criteria such as segmentation, positioning, advertising and sales, distribution, and pricing. Financial criteria useful in evaluating the alternatives should be included—for example, income statement variables, customer lifetime value, payback, etc. Students must discuss their rationale for selecting the decision criteria and the weights and importance for each factor.

Step 4: Analysis. Provide an in-depth analysis of each alternative based on the criteria chosen in step three. Decision tables using criteria as columns and alternatives as rows can be helpful. The pros and cons of the various choices as well as the short- and long-term implications of each may be evaluated. Best, worst, and most likely scenarios can also be insightful.

Step 5: Decision. Students propose their solution to the problem. This decision is justified based on an in-depth analysis. Explain why the recommendation made is the best fit for the criteria.

Step 6: Implementation plan. Sound business decisions may fail due to poor execution. To enhance the likeliness of a successful project outcome, students describe the key steps (activities) to implement the recommendation, timetable, projected costs, expected competitive reaction, success metrics, and risks in the plan.

“Students note that using the PACADI framework yields ‘aha moments’—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.”

PACADI’s Benefits: Meaningfully and Thoughtfully Applying Business Concepts

The PACADI framework covers all of the major elements of business decision-making, including implementation, which is often overlooked. By stepping through the whole framework, students apply relevant business concepts and solve management problems via a systematic, comprehensive approach; they’re far less likely to surface piecemeal responses.

As students explore each part of the framework, they may realize that they need to make changes to a previous step. For instance, when working on implementation, students may realize that the alternative they selected cannot be executed or will not be profitable, and thus need to rethink their decision. Or, they may discover that the criteria need to be revised since the list of decision factors they identified is incomplete (for example, the factors may explain key marketing concerns but fail to address relevant financial considerations) or is unrealistic (for example, they suggest a 25 percent increase in revenues without proposing an increased promotional budget).

In addition, the PACADI framework can be used alongside quantitative assignments, in-class exercises, and business and management simulations. The structured, multi-step decision framework encourages careful and sequential analysis to solve business problems. Incorporating PACADI as an overarching decision-making method across different projects will ultimately help students achieve desired learning outcomes. As a practical “beyond-the-classroom” tool, the PACADI framework is not a contrived course assignment; it reflects the decision-making approach that managers, executives, and entrepreneurs exercise daily. Case analysis introduces students to the real-world process of making business decisions quickly and correctly, often with limited information. This framework supplies an organized and disciplined process that students can readily defend in writing and in class discussions.

PACADI in Action: An Example

Here’s an example of how students used the PACADI framework for a recent case analysis on CVS, a large North American drugstore chain.

The CVS Prescription for Customer Value*

PACADI Stage

Summary Response

How should CVS Health evolve from the “drugstore of your neighborhood” to the “drugstore of your future”?

Alternatives

A1. Kaizen (continuous improvement)

A2. Product development

A3. Market development

A4. Personalization (micro-targeting)

Criteria (include weights)

C1. Customer value: service, quality, image, and price (40%)

C2. Customer obsession (20%)

C3. Growth through related businesses (20%)

C4. Customer retention and customer lifetime value (20%)

Each alternative was analyzed by each criterion using a Customer Value Assessment Tool

Alternative 4 (A4): Personalization was selected. This is operationalized via: segmentation—move toward segment-of-1 marketing; geodemographics and lifestyle emphasis; predictive data analysis; relationship marketing; people, principles, and supply chain management; and exceptional customer service.

Implementation

Partner with leading medical school

Curbside pick-up

Pet pharmacy

E-newsletter for customers and employees

Employee incentive program

CVS beauty days

Expand to Latin America and Caribbean

Healthier/happier corner

Holiday toy drives/community outreach

*Source: A. Weinstein, Y. Rodriguez, K. Sims, R. Vergara, “The CVS Prescription for Superior Customer Value—A Case Study,” Back to the Future: Revisiting the Foundations of Marketing from Society for Marketing Advances, West Palm Beach, FL (November 2, 2018).

Results of Using the PACADI Framework

When faculty members at our respective institutions at Nova Southeastern University (NSU) and the University of North Carolina Wilmington have used the PACADI framework, our classes have been more structured and engaging. Students vigorously debate each element of their decision and note that this framework yields an “aha moment”—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.

These lively discussions enhance individual and collective learning. As one external metric of this improvement, we have observed a 2.5 percent increase in student case grade performance at NSU since this framework was introduced.

Tips to Get Started

The PACADI approach works well in in-person, online, and hybrid courses. This is particularly important as more universities have moved to remote learning options. Because students have varied educational and cultural backgrounds, work experience, and familiarity with case analysis, we recommend that faculty members have students work on their first case using this new framework in small teams (two or three students). Additional analyses should then be solo efforts.

To use PACADI effectively in your classroom, we suggest the following:

Advise your students that your course will stress critical thinking and decision-making skills, not just course concepts and theory.

Use a varied mix of case studies. As marketing professors, we often address consumer and business markets; goods, services, and digital commerce; domestic and global business; and small and large companies in a single MBA course.

As a starting point, provide a short explanation (about 20 to 30 minutes) of the PACADI framework with a focus on the conceptual elements. You can deliver this face to face or through videoconferencing.

Give students an opportunity to practice the case analysis methodology via an ungraded sample case study. Designate groups of five to seven students to discuss the case and the six steps in breakout sessions (in class or via Zoom).

Ensure case analyses are weighted heavily as a grading component. We suggest 30–50 percent of the overall course grade.

Once cases are graded, debrief with the class on what they did right and areas needing improvement (30- to 40-minute in-person or Zoom session).

Encourage faculty teams that teach common courses to build appropriate instructional materials, grading rubrics, videos, sample cases, and teaching notes.

When selecting case studies, we have found that the best ones for PACADI analyses are about 15 pages long and revolve around a focal management decision. This length provides adequate depth yet is not protracted. Some of our tested and favorite marketing cases include Brand W , Hubspot , Kraft Foods Canada , TRSB(A) , and Whiskey & Cheddar .

Art Weinstein

Art Weinstein , Ph.D., is a professor of marketing at Nova Southeastern University, Fort Lauderdale, Florida. He has published more than 80 scholarly articles and papers and eight books on customer-focused marketing strategy. His latest book is Superior Customer Value—Finding and Keeping Customers in the Now Economy . Dr. Weinstein has consulted for many leading technology and service companies.

Herbert V. Brotspies

Herbert V. Brotspies , D.B.A., is an adjunct professor of marketing at Nova Southeastern University. He has over 30 years’ experience as a vice president in marketing, strategic planning, and acquisitions for Fortune 50 consumer products companies working in the United States and internationally. His research interests include return on marketing investment, consumer behavior, business-to-business strategy, and strategic planning.

John T. Gironda

John T. Gironda , Ph.D., is an assistant professor of marketing at the University of North Carolina Wilmington. His research has been published in Industrial Marketing Management, Psychology & Marketing , and Journal of Marketing Management . He has also presented at major marketing conferences including the American Marketing Association, Academy of Marketing Science, and Society for Marketing Advances.

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using case studies for assessment

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Case Study-Based Learning

Enhancing learning through immediate application.

By the Mind Tools Content Team

using case studies for assessment

If you've ever tried to learn a new concept, you probably appreciate that "knowing" is different from "doing." When you have an opportunity to apply your knowledge, the lesson typically becomes much more real.

Adults often learn differently from children, and we have different motivations for learning. Typically, we learn new skills because we want to. We recognize the need to learn and grow, and we usually need – or want – to apply our newfound knowledge soon after we've learned it.

A popular theory of adult learning is andragogy (the art and science of leading man, or adults), as opposed to the better-known pedagogy (the art and science of leading children). Malcolm Knowles , a professor of adult education, was considered the father of andragogy, which is based on four key observations of adult learners:

  • Adults learn best if they know why they're learning something.
  • Adults often learn best through experience.
  • Adults tend to view learning as an opportunity to solve problems.
  • Adults learn best when the topic is relevant to them and immediately applicable.

This means that you'll get the best results with adults when they're fully involved in the learning experience. Give an adult an opportunity to practice and work with a new skill, and you have a solid foundation for high-quality learning that the person will likely retain over time.

So, how can you best use these adult learning principles in your training and development efforts? Case studies provide an excellent way of practicing and applying new concepts. As such, they're very useful tools in adult learning, and it's important to understand how to get the maximum value from them.

What Is a Case Study?

Case studies are a form of problem-based learning, where you present a situation that needs a resolution. A typical business case study is a detailed account, or story, of what happened in a particular company, industry, or project over a set period of time.

The learner is given details about the situation, often in a historical context. The key players are introduced. Objectives and challenges are outlined. This is followed by specific examples and data, which the learner then uses to analyze the situation, determine what happened, and make recommendations.

The depth of a case depends on the lesson being taught. A case study can be two pages, 20 pages, or more. A good case study makes the reader think critically about the information presented, and then develop a thorough assessment of the situation, leading to a well-thought-out solution or recommendation.

Why Use a Case Study?

Case studies are a great way to improve a learning experience, because they get the learner involved, and encourage immediate use of newly acquired skills.

They differ from lectures or assigned readings because they require participation and deliberate application of a broad range of skills. For example, if you study financial analysis through straightforward learning methods, you may have to calculate and understand a long list of financial ratios (don't worry if you don't know what these are). Likewise, you may be given a set of financial statements to complete a ratio analysis. But until you put the exercise into context, you may not really know why you're doing the analysis.

With a case study, however, you might explore whether a bank should provide financing to a borrower, or whether a company is about to make a good acquisition. Suddenly, the act of calculating ratios becomes secondary – it's more important to understand what the ratios tell you. This is how case studies can make the difference between knowing what to do, and knowing how, when, and why to do it.

Then, what really separates case studies from other practical forms of learning – like scenarios and simulations – is the ability to compare the learner's recommendations with what actually happened. When you know what really happened, it's much easier to evaluate the "correctness" of the answers given.

When to Use a Case Study

As you can see, case studies are powerful and effective training tools. They also work best with practical, applied training, so make sure you use them appropriately.

Remember these tips:

  • Case studies tend to focus on why and how to apply a skill or concept, not on remembering facts and details. Use case studies when understanding the concept is more important than memorizing correct responses.
  • Case studies are great team-building opportunities. When a team gets together to solve a case, they'll have to work through different opinions, methods, and perspectives.
  • Use case studies to build problem-solving skills, particularly those that are valuable when applied, but are likely to be used infrequently. This helps people get practice with these skills that they might not otherwise get.
  • Case studies can be used to evaluate past problem solving. People can be asked what they'd do in that situation, and think about what could have been done differently.

Ensuring Maximum Value From Case Studies

The first thing to remember is that you already need to have enough theoretical knowledge to handle the questions and challenges in the case study. Otherwise, it can be like trying to solve a puzzle with some of the pieces missing.

Here are some additional tips for how to approach a case study. Depending on the exact nature of the case, some tips will be more relevant than others.

  • Read the case at least three times before you start any analysis. Case studies usually have lots of details, and it's easy to miss something in your first, or even second, reading.
  • Once you're thoroughly familiar with the case, note the facts. Identify which are relevant to the tasks you've been assigned. In a good case study, there are often many more facts than you need for your analysis.
  • If the case contains large amounts of data, analyze this data for relevant trends. For example, have sales dropped steadily, or was there an unexpected high or low point?
  • If the case involves a description of a company's history, find the key events, and consider how they may have impacted the current situation.
  • Consider using techniques like SWOT analysis and Porter's Five Forces Analysis to understand the organization's strategic position.
  • Stay with the facts when you draw conclusions. These include facts given in the case as well as established facts about the environmental context. Don't rely on personal opinions when you put together your answers.

Writing a Case Study

You may have to write a case study yourself. These are complex documents that take a while to research and compile. The quality of the case study influences the quality of the analysis. Here are some tips if you want to write your own:

  • Write your case study as a structured story. The goal is to capture an interesting situation or challenge and then bring it to life with words and information. You want the reader to feel a part of what's happening.
  • Present information so that a "right" answer isn't obvious. The goal is to develop the learner's ability to analyze and assess, not necessarily to make the same decision as the people in the actual case.
  • Do background research to fully understand what happened and why. You may need to talk to key stakeholders to get their perspectives as well.
  • Determine the key challenge. What needs to be resolved? The case study should focus on one main question or issue.
  • Define the context. Talk about significant events leading up to the situation. What organizational factors are important for understanding the problem and assessing what should be done? Include cultural factors where possible.
  • Identify key decision makers and stakeholders. Describe their roles and perspectives, as well as their motivations and interests.
  • Make sure that you provide the right data to allow people to reach appropriate conclusions.
  • Make sure that you have permission to use any information you include.

A typical case study structure includes these elements:

  • Executive summary. Define the objective, and state the key challenge.
  • Opening paragraph. Capture the reader's interest.
  • Scope. Describe the background, context, approach, and issues involved.
  • Presentation of facts. Develop an objective picture of what's happening.
  • Description of key issues. Present viewpoints, decisions, and interests of key parties.

Because case studies have proved to be such effective teaching tools, many are already written. Some excellent sources of free cases are The Times 100 , CasePlace.org , and Schroeder & Schroeder Inc . You can often search for cases by topic or industry. These cases are expertly prepared, based mostly on real situations, and used extensively in business schools to teach management concepts.

Case studies are a great way to improve learning and training. They provide learners with an opportunity to solve a problem by applying what they know.

There are no unpleasant consequences for getting it "wrong," and cases give learners a much better understanding of what they really know and what they need to practice.

Case studies can be used in many ways, as team-building tools, and for skill development. You can write your own case study, but a large number are already prepared. Given the enormous benefits of practical learning applications like this, case studies are definitely something to consider adding to your next training session.

Knowles, M. (1973). 'The Adult Learner: A Neglected Species [online].' Available here .

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What the Case Study Method Really Teaches

  • Nitin Nohria

using case studies for assessment

Seven meta-skills that stick even if the cases fade from memory.

It’s been 100 years since Harvard Business School began using the case study method. Beyond teaching specific subject matter, the case study method excels in instilling meta-skills in students. This article explains the importance of seven such skills: preparation, discernment, bias recognition, judgement, collaboration, curiosity, and self-confidence.

During my decade as dean of Harvard Business School, I spent hundreds of hours talking with our alumni. To enliven these conversations, I relied on a favorite question: “What was the most important thing you learned from your time in our MBA program?”

  • Nitin Nohria is the George F. Baker Jr. Professor at Harvard Business School and the former dean of HBS.

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Engaging Students with Case Studies

The case study method is a pedagogical approach which asks students to investigate real-world problems presented as a descriptive case about which decisions must be made. The case is a narrative, often presented without a conclusion. Case studies are distinctly problem-centered assignments, often completed in a group format – requiring students to work together with others as a team, analyze a problem, synthesize knowledge, and apply their learning to communicate a resolution to the case’s central challenge. All well-designed case studies clearly indicate student learning objectives and include assignments, enabling authentic assessment of student work. Case studies can be used at many levels and in many settings; they are widely used in undergraduate general education classes, as well as in courses for the major. 

Although faculty sometimes create their own case studies for use in the classroom, many organizations provide peer-reviewed case studies for classroom use, free of charge or for a modest subscription fee. Below are two case study banks in science education, available to WSU faculty.

STIRS. In 2012, the American Association of Colleges and Universities (AAC&U) launched its Scientific Thinking and Integrative Reasoning Skills (STIRS) initiative. The STIRS Framework encompasses four elements based on the central concept of evidence : what it is, how it’s collected, and its use in solving problems and in making decisions.  An example from the STIRS collection is physicist Vandana Singh’s case study, ‘” To Drill or Not to Drill? A Dilemma in the context of Climate Change in the Arctic ,” in which students are required to consider the scientific basis of climate change as they develop recommendations for local communities – to “drill or not” for oil and gas.  STIRS peer-reviewed cases offer compelling narratives and topics for general education and for the major, including cases about bird flu, cell phones and cancer, organic foods, and congressional redistricting.

NCCSTS. Likewise, with support from the National Science Foundation, among others, the National Center for Case Study Teaching in Science  (NCCSTS) at Buffalo University has curated nearly 700 individual peer-reviewed case studies in science and technology – from aerospace engineering to zoology. This repository features brief “plug-and-play” modules for use in a single class session to more complex inquiry-driven projects in which elements of the case are progressively revealed, requiring a full term to complete successfully. The NCCSTS case studies focus on helping students make science more relevant to their lives while learning and applying critical thinking, information literacy, and scientific and quantitative reasoning skills. This award-winning collection of science-based case studies allow for active learning in many instructional formats, and makes them ideal for embedding assessment of student learning within the case study course module.

Use in many disciplines.  Case studies benefit student learning in science. Students report greater motivation to learn and more engagement with the subject matter. Assessments of student learning demonstrate other advantages to case studies, with significant gains in students’ ability to synthesize complex scientific concepts as they considered difficult analytical questions, as science educator Kevin Bonney has written in the Journal of Microbiology and Biology Education .

Case studies have been used in other fields, as well: WSU Vancouver’s Public Affairs program has utilized case studies from the Electronic Hallway collection to help their students develop professional communication skills.  Guides to collections of peer-reviewed case studies in these and many other disciplines are available through the STIRS resources page.

Using case studies effectively . Most peer-reviewed case studies provide the case, supplementary documents, teaching notes, and assessment tools. While case studies engage students in active learning experiences that most find meaningful, using the method requires that faculty assume a different role – that of facilitator who must guide students to take control over their own learning, provide assistance in wading through piles of sometimes contradictory evidence, and help students manage emotions that aspects of a case may trigger. If you are interested in adopting the case study method in your classes, the NCCSTS Teaching Resources page offers many publications helpful to faculty preparing to adopt this method.

For an example of how a WSU program has utilized case students in a course in the major, please see the  Public Affairs assessment spotlight.  For additional information,  contact ATL .

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What Is a Case Study?

Weighing the pros and cons of this method of research

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

using case studies for assessment

Cara Lustik is a fact-checker and copywriter.

using case studies for assessment

Verywell / Colleen Tighe

  • Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

  • Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
  • Gives researchers the chance to collect information on why one strategy might be chosen over another
  • Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

  • It cannot necessarily be generalized to the larger population
  • Cannot demonstrate cause and effect
  • It may not be scientifically rigorous
  • It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

  • Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
  • Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
  • Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

  • Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
  • Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
  • Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
  • Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
  • Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
  • Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

  • Archival records : Census records, survey records, and name lists are examples of archival records.
  • Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
  • Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
  • Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
  • Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
  • Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

  • Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
  • Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
  • Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
  • Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

  • Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
  • Read examples of case studies to gain an idea about the style and format.
  • Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

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

Effective Use of Student-Created Case Studies as Assessment in an Undergraduate Neuroscience Course

Affiliations.

  • 1 Neuroscience Department, Carthage College, Kenosha, WI 53140.
  • 2 Department of Physiology, Medical College of Wisconsin, Milwaukee WI 53226.
  • PMID: 34552434
  • PMCID: PMC8437362

Case studies and student-led learning activities are both effective active learning methods for increasing student engagement, promoting student learning, and improving student performance. Here, we describe combining these instructional methods to use student-created case studies as assessment for an online neurovirology module in a neuroanatomy and physiology course. First, students learned about neurovirology in a flipped classroom format using free, open-access virology resources. Then, students used iterative writing practices to write an interrupted case study incorporating a patient narrative and primary literature data on the neurovirulent virus of their choice, which was graded as a writing assessment. Finally, students exchanged case studies with their peers, and both taught and completed the case studies as low-stakes assessment. Student performance and evaluations support the efficacy of case studies as assessment, where iterative writing improved student performance, and students reported increased knowledge and confidence in the corresponding learning objectives. Overall, we believe that using student-created case studies as assessment is a valuable, student-led extension of effective case study pedagogy, and has wide applicability to a variety of undergraduate courses.

Keywords: active learning; case study; collaborative learning; cooperative learning; neurovirology; primary literature.

Copyright © 2021 Faculty for Undergraduate Neuroscience.

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The “case” for case studies: why we need high-quality examples of global implementation research

Blythe beecroft.

1 Fogarty International Center, US National Institutes of Health, Bethesda, USA

Rachel Sturke

2 National Cancer Institute, US National Institutes of Health, Bethesda, USA

Rohit Ramaswamy

3 Cincinnati Children’s Hospital Medical Center, Cincinnati, USA

Associated Data

Not applicable.

Rigorous and systematic documented examples of implementation research in global contexts can be a valuable resource and help build research capacity. In the context of low- and middle-income countries (LMICs), there is a need for practical examples of how to conduct implementation studies. To address this gap, Fogarty’s Center for Global Health Studies in collaboration with the Cincinnati Children's Hospital Medical Center and the National Cancer Institute is commissioning a collection of implementation science case studies in LMICs that describe key components of conducting implementation research, including how to select, adapt, and apply implementation science models, theories, and frameworks to these settings; develop and test implementation strategies; and evaluate implementation processes and outcomes. The case studies describe implementation research in various disease areas in LMICs around the world. This commentary highlights the value of case study methods commonly used in law and business schools as a source of “thick” (i.e., context-rich) description and a teaching tool for global implementation researchers. It addresses the independent merit of case studies as an evaluation approach for disseminating high-quality research in a format that is useful to a broad range of stakeholders. This commentary finally describes an approach for developing high-quality case studies of global implementation research, in order to be of value to a broad audience of researchers and practitioners.

Contributions to the literature

  • Reinforcing the need for “thick” (i.e., context-rich) descriptions of implementation studies
  • Highlighting the utility of case studies as a dissemination strategy for researchers, practitioners, and policymakers
  • Articulating the value of detailed case studies as a teaching tool for global implementation researchers
  • Describing a method for developing high-quality case studies of global implementation research

Research capacity for implementation science remains limited in low- and middle-income countries (LMICs). Various stakeholders, including NIH-funded implementation researchers and practitioners, often inquire about how to apply implementation science methods and have requested additional resources and training to support implementation capacity building. This is in part due to a dearth of practical examples for both researchers and practitioners of how to select, adapt, and apply implementation science models, theories, and frameworks to these settings; how to evaluate implementation processes and outcomes; and how to develop and test implementation strategies. The need for detailed documentation of implementation research in all settings has been well established, and guidelines for documentation of implementation research studies have been created [ 1 , 2 ]. But the mere availability of checklists and guidelines in and of themselves does not result in comprehensive documentation that is useful for learning, as has been pointed out by many systematic reviews of implementation science and quality improvement studies ([ 3 , 4 ]). It has also been observed that documentation alone is not enough, and there is a need for mentors to translate abstract theories into context-appropriate research designs and practice approaches [ 5 ]. Because of the especially acute shortage of mentors and coaches in LMIC settings, we propose that documentation with “thick” descriptions that go beyond checklists and guidelines are needed to make the field more useful to emerging professionals [ 6 ]. We suggest that the case study method intended to “explore the space between the world of theory and the experience of practice” [ 7 ] that has been used successfully for over a century by law and business schools as a teaching aid can be of value to develop detailed narratives of implementation research projects. In this definition, we are not referring to the case study as a qualitative research method [ 8 ], but as a rich and detailed method of retrospective documentation to aid teaching, practice, and research. In this context, our case studies are akin to “single-institution or single-patient descriptions” [ 9 ] called “case reports” or “case examples” in other fields. As these terms are rarely used in global health, we have used the words “case studies” in this paper but reiterate that they do not refer to case study research designs.

Fogarty’s Center for Global Health Studies (CGHS) in collaboration with the Cincinnati Children's Hospital Medical Center and the National Cancer Institute (NCI) is commissioning a collection of implementation science case studies that describe implementation research focusing on various disease areas in different (LMIC) contexts around the world. These case study descriptions will provide guidance on the process of conducting implementation science studies and will highlight the impact these studies have had on practice and policy in global health contexts. This brief note makes a case for using case studies to document and disseminate implementation research, describes the CGHS approach to case study development and poses evaluation questions that need to be answered to better understand the utility of case studies. This effort is intended to develop a set of useful examples for LMIC researchers, practitioners, and policymakers, but also to assess and improve the use of case studies as a tested documentation methodology in implementation research.

The “case” for case studies

A preliminary landscape analysis of the field conducted by CGHS found that there are not many descriptions of global implementation science projects in a case study format in the peer-reviewed or gray literature, and those that exist are embedded in the content of academic teaching materials. There is not a cohesive collection, especially relating to health, that illustrates how implementation research has been conducted in varied organizations, countries, or disease areas. This new collection will add value in three different ways: as a dissemination strategy, as a tool for capacity building, and as a vehicle for stimulating better research.

Case studies as a dissemination strategy

Case studies have independent merit as an evaluation approach for disseminating high-quality research in a format that is useful to a broad range of stakeholders. The Medical Research Council (MRC) has recommended process evaluation as a useful approach to examine complex implementation, mechanisms of impact, and context [ 10 ]. Guidelines on documentation of implementation recommend that researchers should provide “detailed descriptions of interventions (and implementation strategies) in published papers, clarify assumed change processes and design principles, provide access to manuals and protocols that provide information about the clinical interventions or implementation strategies, and give detailed descriptions of active control conditions” [ 1 ]. Case studies can be thought of as a form of post hoc process evaluation, to disseminate how the delivery of an intervention is achieved, the mechanisms by which implementation strategies produce change, or how context impacts implementation and related outcomes.

Case studies as a capacity building tool

In addition, case studies can address the universal recognition of the need for more capacity building in Implementation Science , especially in LMIC settings. Case studies have been shown to address common pedagogical challenges in helping students learn by allowing students to dissect and explore limitations, adaptations, and utilization of theories, thereby creating a bridge between theories presented in a classroom and their application in the field [ 11 ]. A recent learning needs assessment for implementation researchers, practitioners, and policymakers in LMICs conducted by Turner et al. [ 12 ] reflected a universal consensus on the need for context-specific knowledge about how to apply implementation science in practice, delivered in an interactive format supported by mentorship. A collection of case studies is a valuable and scalable resource to meet this need.

Using case studies to strengthen implementation research

Descriptions of research using studies can illustrate not just whether implementation research had an impact on practice and policy, but how, why, under what circumstances, and to whom, which is the ultimate goal of generating generalizable knowledge about how to implement. Using diverse cases to demonstrate how a variety of research designs have been used to answer complex implementation questions provides researchers with a palette of design options and examples of their use. A framework developed by Minary et al. [ 13 ] illustrates the wide variety of research designs that are useful for complex interventions, depending on whether the emphasis is on internal and external validity or whether knowledge about content and process or about outcomes is more important. A collection of case studies would be invaluable to researchers seeking to develop appropriate designs for their work. In addition, the detailed documentation provided through these case descriptions will hopefully motivate researchers to document their own studies better using the guidelines described earlier.

Developing and testing the case study creation process: the CGHS approach

Writing case studies that satisfy the objectives described above is an implementation science undertaking in itself that requires the engagement of a variety of stakeholders and planned implementation strategies. The CGHS team responsible for commissioning the case studies began this process in 2017 and followed the approach detailed below to test the process of case study development.

  • Conducted 25+ consultations with various implementation science experts on gaps in the field and the relevance of global case studies
  • Convened a 15-member Steering Committee 1 of implementation scientists with diverse expertise, from various academic institutions and NIH institutes to serve as technical experts and to help guide the development and execution of the project
  • Developed a case study protocol in partnership with the Steering Committee to guide the inclusion of key elements in the case studies
  • Commissioned two pilot cases 2 to assess the feasibility and utility of the case study protocol and elicited feedback on the writing experience and how it could be improved as the collection expands
  • Led an iterative pilot writing process where each case study writing team developed several drafts, which were reviewed by CGHS staff and a designated member of the Steering Committee
  • Truncated and adjusted the protocol in response to input from the pilot case study authors teams
  • Developed a comprehensive grid with the Steering Committee, outlining the key dimensions of implementation science that are significant and would be important areas of focus for future case studies. The grid will be used to evaluate potential case applicants and is intended to help foster diversity of focus and content, in addition to geography

Implementing the process: the call for case studies

In March of 2021, CGHS issued a closed call for case studies to solicit applications from a pool of researchers. Potential applicants completed the comprehensive grid in addition to a case study proposal. Applicants will go through a three-tier screening and review process. CGHS will initially screen the applications for completeness to ensure all required elements are present. Each case study application will then be reviewed by two Steering Committee members for content and scientific rigor and given a numerical score based on the selection criteria. Finally, the CGHS team will screen the applications to ensure diversity of implementation elements, geography, and disease area. Approximately 10 case studies will be selected for development in an iterative process. Each case team will present their case drafts to the Steering Committee, which will collectively workshop the drafts in multiple sittings, drawing on the committee’s implementation science expertise. Once case study manuscripts are accepted by the Steering Committee, they will be submitted to Implementation Science Communications for independent review by the journal. CGHS intends for the case studies to be published collectively, but on a rolling basis as they are accepted for publication.

Future research: evaluating the effectiveness of the case study approach

This commentary has put forth arguments for the potential value of case studies for documenting implementation research for researchers, practitioners, and policymakers. Case studies not only provide a way to underscore how implementation science can advance practice and policy in LMICs, but also offer guidance on how to conduct implementation research tailored to global contexts. However, there is little empirical evidence about the validity of these arguments. The creation of this body of case studies will allow us to study why, how, how often, and by whom these case studies are used. This is a valuable opportunity to learn and use that information to better inform future use of this approach as a capacity-building or dissemination strategy.

Conclusions

Similar to their use in law and business, case study descriptions of implementation research could be an important mechanism to counteract the paucity of training programs and mentors to meet the demands of global health researchers. If the evaluation results indicate that the case study creation process produces useful products that enhance learning to improve future implementation research, a mechanism needs to be put in place to create more case studies than the small set that can be generated through this initiative. There will be a need to create a set of documentation guidelines that complement those that currently exist and a mechanism to solicit, review, publish, and disseminate case studies from a wide variety of researchers and practitioners. Journals such as Implementation Science or Implementation Science Communications can facilitate this effort by either creating a new article type or by considering a new journal with a focus on rigorous and systematic case study descriptions of implementation research and practice. An example that could serve as a guide is BMJ Open Quality , which is a peer-reviewed, open-access journal focused on healthcare improvement. In addition to original research and systematic reviews, the journal publishes two article types: Quality Improvement Report and Quality Education Report to document healthcare quality improvement programs and training. The journal offers resources for authors to document their work rigorously. Recently, a new journal titled BMJ Open Quality South Asia has been released to disseminate regional research. We hope that our efforts in sponsoring and publishing these cases, and in setting up a process to support their creation, will make an important contribution to the field and become a mechanism for sharing knowledge that accelerates the growth of implementation science in LMIC settings.

Acknowledgements

The findings and conclusions in this manuscript are those of the authors and do not necessarily represent any official position or policy of the US National Institutes of Health or the US Department of Health and Human Services or any other institutions with which authors are affiliated.

Abbreviations

Authors’ contributions.

BB, RS, and GN contributed to the conceptualization of the manuscript with leadership from RR. BB and RS drafted the main text. RR and GN reviewed and contributed additional content to further develop the text. All authors have read and agreed to the contents of the final draft of the manuscript.

Availability of data and materials

Declarations.

The authors declare that they have no competing interests.

1 Rohit Ramaswamy, CCHMC, Gila Neta, NCI NIH, Theresa Betancourt, BC, Ross Brownson, WASU, David Chambers, NCI NIH, Sharon Straus, University of Toronto, Greg Aarons, UCSD, Bryan Weiner, UW, Sonia Lee, NICHD NIH, Andrea Horvath Marques, NIMH NIH, Susannah Allison, NIMH NIH, Suzy Pollard, NIMH NIH, Chris Gordon, NIMH NIH, Kenny Sherr, UW, Usman Hamdani, HDR Foundation Pakistan, Linda Kupfer, FIC NIH

2 The first pilot case was led by the Human Development Research Foundation (HDRF) in Pakistan and examines scaling up evidenced-based care for children with developmental disorders in rural Pakistan. The second pilot was led by Boston College and investigates alternate delivery platforms and implementation models for bringing evidence-based behavioral Interventions to scale for youth facing adversity in Sierra Leone to close the mental health treatment gap.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Case Study Exercises at Assessment Centers ({YEAR} Guide)

Why Do Employers Use Case Studies at Assessment Centers?

What to expect from a case study exercise, how to prepare for the case study exercise in 2024, how to approach a group exercise, how to approach a presentation, case study exercises at assessment centers (2024 guide).

Updated November 21, 2023

Fi Phillips

Should you be invited to be tested at an assessment center as part of an employer's recruitment process, one of the exercises you may face is a case study .

A case study exercise presents you with a scenario similar to what you would experience in the job you have applied for.

It will generally be accompanied by documents, emails or other forms of information.

You are asked to make business decisions based on the data you have been provided with, either alone or as part of a group of candidates.

A case study enables employers to assess your skill-base and likely performance in the job, providing them with a more rounded view of the type of employee you would be and the value you would bring to the company.

Commonly used in the finance, banking, legal and business management industries, the main advantage to employers of using case study exercises is to see candidates in action, demonstrating the skills they would be expected to use at work.

The skills assessed when participating in a case study exercise will vary depending on the employer, the industry and the job applied for, but may include:

  • Analytical skills
  • Strategic thinking
  • Decision making
  • Problem-solving
  • Communication
  • Stress tolerance
  • The ability to assimilate information quickly and effectively
  • Organisational skills
  • Situational judgment
  • Commercial awareness
  • Time management
  • Team working
  • Knowledge pertinent to the industry or job, for example, marketing skills

Despite the skills that the employer is actively assessing, such as those mentioned above, success in a case study exercise relies on your ability to:

  • Interpret and analyze the information provided
  • Reach a decision
  • Use commercial awareness
  • Manage your time
  • Communicate well

Practice Case Study Exercises with JobTestPrep

There are generally two types of case study exercise that you may face as part of a selection process:

  • Subject-related case studies pertinent to the job you are applying for and the related industry
  • General case studies that assess your overall aptitude and skills

The actual scenario of the case study exercise you face will vary, but examples of typical case studies include:

  • Expanding a team or department
  • Deciding whether an acquisition or merger is advisable
  • Investigating whether to begin a new product line
  • Re-organisation of management structure
  • The creation of an advertising campaign
  • Responding to negative publicity
  • Choosing from three business proposals
  • Developing a social media presence

Prepare for Case Study Exercises with JobTestPrep

For example: You are presented with the scenario of an IT company that went through an expensive re-brand one year ago. At that time, the company moved to bigger premises in a better area, and two new teams of developers were recruited to work with two new clients. The IT company has recently lost one of those clients and is facing increasing costs as the rent is raised for their premises. The company's directors have concluded that they must make one of the following changes: Make staff redundancies and offer the chance to several employees to change to part-time hours Move to less expensive premises in a less desirable area Combine a move to a flexible working business model where employees work part of the week from home and desk-share in the office along with a physical move to smaller premises in the same area where the IT company is currently based

You are asked to advise the directors on which change would provide the greatest benefit.

Here is another example:

A multi-national environmental testing organization buys out an oil-testing laboratory. A gap test is carried out on whether: The oil-testing lab should be brought in line with the rest of the organization concerning its processes, customer interface, and testing procedures The oil-testing lab should be closed down and its clients absorbed into the rest of the organization The oil-testing lab should be allowed to continue as it is, but new processes put in place between it and the larger organization

You are asked to consider the findings of the gap test and suggest the best course of action.

Just as you would prepare before a job interview, it is always in your best interests to prepare before facing a case study exercise at an assessment center.

Step 1 . Do the Research

There is a whole range of research you can look into to prepare yourself for the case study exercise:

  • The job description and any other literature or documents forwarded to you
  • The employer's website and social media
  • Industry related news stories and developments

Any of the above should provide you with a better understanding of the job you have applied for, the industry you will work within, and the culture and values of the employer.

Step 2 . Use Practice Case Studies

Practicing case study exercises in the run-up to the assessment day is one of the best ways you can prepare for the real thing.

Unless the employer provides sample case studies on their website or as part of their recruitment pack, you will not know the exact format that the exercise will take; however, you can build familiarity with the overall process of a case study through practice.

You can find plenty of practice case study exercises online. Most of these come at a cost, but you may also be able to find free sample case studies too.

For case study resources at a cost, have a look at JobTestPrep .

For two free sample case study exercises, you might like to visit Bain & Company's website .

Scroll down to the Associate Consultant Case Library. Europa also offers an extensive and detailed sample case study .

Step 3 . Timed Practice

Once you have sourced one or more practice case studies, take the opportunity to practice to a time limit.

The case study may come with a time limit, or the employer may have already told you how long you will have to complete the real case study exercise on the day.

Alternatively, set your reasonable time limit.

Timed practice will improve your response time and explain exactly how much time you should allocate to each stage of the case study process.

Step 4 . Improve Your Reading Comprehension

One skill that is key to handle a case study exercise successfully is your reading comprehension, that is, your ability to understand written information, interpret it and describe it in your own words.

In the context of a case study, this skill will help you to assimilate the information provided to you quickly, analyze it and ultimately reach a decision.

In the run-up to your assessment day, put aside time to improve your reading comprehension by reading a wide variety of material and picking out the key points of each passage.

You might find it especially helpful to read professional journals and news articles related to the job you have applied for and the related industry.

Try to improve the speed at which you can read but still retain information too. This will prove helpful during the real case study exercise.

Step 5 . Practice Mental Math

The case study exercise may include prices, area measurements, staff numbers, salaries and other numeric values.

It is important that you can complete basic mental math calculations, such as multiplication and percentages.

Practice your mental math using puzzle books, online math resources and math problems that you create yourself.

You can find plenty of online business math resources, for example:

  • The University of Alabama at Birmingham Math and Business Guide
  • Money Instructor
  • Open Textbook Library
If you need to prepare for a number of different employment tests and want to outsmart the competition, choose a Premium Membership from JobTestPrep . You will get access to three PrepPacks of your choice, from a database that covers all the major test providers and employers and tailored profession packs.

Get a Premium Package Now

How To Prepare for Case Study Exercises at Assessment Centers

Top Tips for Approaching Case Study Exercises

Now that you have prepared yourself, you can further improve your chances of a successful outcome by following our top tips on approaching case study exercises on the day.

Read the Information Carefully

Read all of the information provided as part of your case study exercise to understand what is being asked of you fully.

Quickly identify the key points in the task and the overall decision you have been asked to make, for example:

  • Has the exercise provided you with a choice of outcomes you must decide between, or must you create the outcome yourself?
  • What information do you need to make your decision?
  • Are there calculations involved in the task?
  • What character are you playing in the task (for example, HR manager or business consultant) and what are that character's motivations?
  • Who is your character presenting their response to? Company directors, client or HR department?

Prioritize the Information

Prioritize the information by importance.

Which pieces of information are most pertinent to the task, and what key data do they provide?

Can any of the information be dismissed? Does any of the information contradict or sit in conflict with others?

Divide Up the Tasks and Allocate Time

You will generally be asked to come to a conclusion or advise a course of action regarding your case study exercise; however, you may have to carry out several tasks to arrive at this result.

Once you have read through the information, plan out what tasks the exercise will entail and allocate time for each one.

Do Not Be Distracted by Finding the Only 'Right' Answer

Where you are provided with several outcomes, and you must decide on one, do not assume that anyone's outcome is the only right answer to give.

It may be that any of the outcomes could be correct if you can sufficiently support your decision from the information provided.

Keep the Objective in Focus

  • What does the task ask you to do?
  • Must you choose between three business acquisitions?
  • Are you providing advice on whether or not to invest?
  • Are you putting together a plan for a staff redundancy situation?

Keep the objective of the case study exercise in mind at all times.

Support Your Decision With Evidence

The conclusion you come to may seem obvious to you, but you must be able to support your decision with evidence.

Why would it be better for the company to invest in property overstock? What is the benefit to the company of entering a new market?

It is not sufficient to know which outcome would be the best. As in the real-life business world, you must be able to support your claims.

If you are assessed as part of a group, you must arrive at a conclusion as a team and bear in mind your strengths.

For example, do you have a good eye for detail and would therefore be suited to the analytical part of the task?

Arrive at a list of tasks together and then assign the tasks to different members of the group.

Please make sure you contribute to the group discussions but do not dominate them.

Group assessments are generally used by employers who place value on leadership, teamwork and communication skills.

If you are asked to present your findings or conclusion as part of a case study exercise, bear in mind to whom the task has asked you to make that presentation.

For example, a business client or a marketing manager.

Make sure that you can fully support the reasons that you came to your conclusion.

If you are presenting as a group, make sure that each group member has their role to play in the presentation and that everyone knows why the group came to that conclusion.

Act professionally to suit the job you have applied for. Be polite, confident and well-spoken.

Case study exercises are just one of the many methods that employers use to assess job applicants, and as with any other aspect of the selection process, they require a degree of consideration and preparation.

The best way to improve your chances of a successful outcome and reduce exam tension is to research the job and the industry, practice case study exercises and improve your skills.

You might also be interested in these other Psychometric Success articles:

Assessment Centres – A Guide for 2024

Or explore the Aptitude Tests / Test Types sections.

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10 Case Study Advantages and Disadvantages

case study advantages and disadvantages, explained below

A case study in academic research is a detailed and in-depth examination of a specific instance or event, generally conducted through a qualitative approach to data.

The most common case study definition that I come across is is Robert K. Yin’s (2003, p. 13) quote provided below:

“An empirical inquiry that investigates a contemporary phenomenon within its real-life context, especially when the boundaries between phenomenon and context are not clearly evident.”

Researchers conduct case studies for a number of reasons, such as to explore complex phenomena within their real-life context, to look at a particularly interesting instance of a situation, or to dig deeper into something of interest identified in a wider-scale project.

While case studies render extremely interesting data, they have many limitations and are not suitable for all studies. One key limitation is that a case study’s findings are not usually generalizable to broader populations because one instance cannot be used to infer trends across populations.

Case Study Advantages and Disadvantages

1. in-depth analysis of complex phenomena.

Case study design allows researchers to delve deeply into intricate issues and situations.

By focusing on a specific instance or event, researchers can uncover nuanced details and layers of understanding that might be missed with other research methods, especially large-scale survey studies.

As Lee and Saunders (2017) argue,

“It allows that particular event to be studies in detail so that its unique qualities may be identified.”

This depth of analysis can provide rich insights into the underlying factors and dynamics of the studied phenomenon.

2. Holistic Understanding

Building on the above point, case studies can help us to understand a topic holistically and from multiple angles.

This means the researcher isn’t restricted to just examining a topic by using a pre-determined set of questions, as with questionnaires. Instead, researchers can use qualitative methods to delve into the many different angles, perspectives, and contextual factors related to the case study.

We can turn to Lee and Saunders (2017) again, who notes that case study researchers “develop a deep, holistic understanding of a particular phenomenon” with the intent of deeply understanding the phenomenon.

3. Examination of rare and Unusual Phenomena

We need to use case study methods when we stumble upon “rare and unusual” (Lee & Saunders, 2017) phenomena that would tend to be seen as mere outliers in population studies.

Take, for example, a child genius. A population study of all children of that child’s age would merely see this child as an outlier in the dataset, and this child may even be removed in order to predict overall trends.

So, to truly come to an understanding of this child and get insights into the environmental conditions that led to this child’s remarkable cognitive development, we need to do an in-depth study of this child specifically – so, we’d use a case study.

4. Helps Reveal the Experiences of Marginalzied Groups

Just as rare and unsual cases can be overlooked in population studies, so too can the experiences, beliefs, and perspectives of marginalized groups.

As Lee and Saunders (2017) argue, “case studies are also extremely useful in helping the expression of the voices of people whose interests are often ignored.”

Take, for example, the experiences of minority populations as they navigate healthcare systems. This was for many years a “hidden” phenomenon, not examined by researchers. It took case study designs to truly reveal this phenomenon, which helped to raise practitioners’ awareness of the importance of cultural sensitivity in medicine.

5. Ideal in Situations where Researchers cannot Control the Variables

Experimental designs – where a study takes place in a lab or controlled environment – are excellent for determining cause and effect . But not all studies can take place in controlled environments (Tetnowski, 2015).

When we’re out in the field doing observational studies or similar fieldwork, we don’t have the freedom to isolate dependent and independent variables. We need to use alternate methods.

Case studies are ideal in such situations.

A case study design will allow researchers to deeply immerse themselves in a setting (potentially combining it with methods such as ethnography or researcher observation) in order to see how phenomena take place in real-life settings.

6. Supports the generation of new theories or hypotheses

While large-scale quantitative studies such as cross-sectional designs and population surveys are excellent at testing theories and hypotheses on a large scale, they need a hypothesis to start off with!

This is where case studies – in the form of grounded research – come in. Often, a case study doesn’t start with a hypothesis. Instead, it ends with a hypothesis based upon the findings within a singular setting.

The deep analysis allows for hypotheses to emerge, which can then be taken to larger-scale studies in order to conduct further, more generalizable, testing of the hypothesis or theory.

7. Reveals the Unexpected

When a largescale quantitative research project has a clear hypothesis that it will test, it often becomes very rigid and has tunnel-vision on just exploring the hypothesis.

Of course, a structured scientific examination of the effects of specific interventions targeted at specific variables is extermely valuable.

But narrowly-focused studies often fail to shine a spotlight on unexpected and emergent data. Here, case studies come in very useful. Oftentimes, researchers set their eyes on a phenomenon and, when examining it closely with case studies, identify data and come to conclusions that are unprecedented, unforeseen, and outright surprising.

As Lars Meier (2009, p. 975) marvels, “where else can we become a part of foreign social worlds and have the chance to become aware of the unexpected?”

Disadvantages

1. not usually generalizable.

Case studies are not generalizable because they tend not to look at a broad enough corpus of data to be able to infer that there is a trend across a population.

As Yang (2022) argues, “by definition, case studies can make no claims to be typical.”

Case studies focus on one specific instance of a phenomenon. They explore the context, nuances, and situational factors that have come to bear on the case study. This is really useful for bringing to light important, new, and surprising information, as I’ve already covered.

But , it’s not often useful for generating data that has validity beyond the specific case study being examined.

2. Subjectivity in interpretation

Case studies usually (but not always) use qualitative data which helps to get deep into a topic and explain it in human terms, finding insights unattainable by quantitative data.

But qualitative data in case studies relies heavily on researcher interpretation. While researchers can be trained and work hard to focus on minimizing subjectivity (through methods like triangulation), it often emerges – some might argue it’s innevitable in qualitative studies.

So, a criticism of case studies could be that they’re more prone to subjectivity – and researchers need to take strides to address this in their studies.

3. Difficulty in replicating results

Case study research is often non-replicable because the study takes place in complex real-world settings where variables are not controlled.

So, when returning to a setting to re-do or attempt to replicate a study, we often find that the variables have changed to such an extent that replication is difficult. Furthermore, new researchers (with new subjective eyes) may catch things that the other readers overlooked.

Replication is even harder when researchers attempt to replicate a case study design in a new setting or with different participants.

Comprehension Quiz for Students

Question 1: What benefit do case studies offer when exploring the experiences of marginalized groups?

a) They provide generalizable data. b) They help express the voices of often-ignored individuals. c) They control all variables for the study. d) They always start with a clear hypothesis.

Question 2: Why might case studies be considered ideal for situations where researchers cannot control all variables?

a) They provide a structured scientific examination. b) They allow for generalizability across populations. c) They focus on one specific instance of a phenomenon. d) They allow for deep immersion in real-life settings.

Question 3: What is a primary disadvantage of case studies in terms of data applicability?

a) They always focus on the unexpected. b) They are not usually generalizable. c) They support the generation of new theories. d) They provide a holistic understanding.

Question 4: Why might case studies be considered more prone to subjectivity?

a) They always use quantitative data. b) They heavily rely on researcher interpretation, especially with qualitative data. c) They are always replicable. d) They look at a broad corpus of data.

Question 5: In what situations are experimental designs, such as those conducted in labs, most valuable?

a) When there’s a need to study rare and unusual phenomena. b) When a holistic understanding is required. c) When determining cause-and-effect relationships. d) When the study focuses on marginalized groups.

Question 6: Why is replication challenging in case study research?

a) Because they always use qualitative data. b) Because they tend to focus on a broad corpus of data. c) Due to the changing variables in complex real-world settings. d) Because they always start with a hypothesis.

Lee, B., & Saunders, M. N. K. (2017). Conducting Case Study Research for Business and Management Students. SAGE Publications.

Meir, L. (2009). Feasting on the Benefits of Case Study Research. In Mills, A. J., Wiebe, E., & Durepos, G. (Eds.). Encyclopedia of Case Study Research (Vol. 2). London: SAGE Publications.

Tetnowski, J. (2015). Qualitative case study research design.  Perspectives on fluency and fluency disorders ,  25 (1), 39-45. ( Source )

Yang, S. L. (2022). The War on Corruption in China: Local Reform and Innovation . Taylor & Francis.

Yin, R. (2003). Case Study research. Thousand Oaks, CA: Sage.

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Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

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Case Studies

What are case studies.

Case studies are stories or scenarios, often in narrative form, created and used as a tool for analysis and discussion. They have long been used in higher education, particularly in business and law. Hatcher et al. (2018, pp. 274-5) write:

Case studies, at their core, are metaphors for larger, more general classes of administrative problems. When presented to a class, they are narratives allow students to envision themselves in the role of the protagonist and experience the application of theory to practice by struggling with and attempting to solve the problem or issue that the protagonist faces.... Out of the metaphor students can derive a series of “lessons learned” that they can apply or transfer to other, more general issues that may arise in their professional careers.

They further note (p. 276) that "[a] good case is one that achieves its learning objectives by means of a story and a critical analysis of the situation".

Cases are often based on actual events, which adds a sense of urgency or reality. Case studies have elements of simulations , although for case studies the students tend to be observers rather than participants.

Why use case studies?

Case studies are effective ways to get students to practically apply their skills and their understanding of learned facts to a real-world situation. They are particularly useful where situations are complex and solutions are uncertain.

They can serve as the launching pad for a class discussion, or as a project for individuals or small groups. A single case may be presented to several groups, with each group offering its solutions.

Used as a teaching tool, a case study:

  • engages students in research and reflective discussion
  • encourages higher-order thinking
  • facilitates creative problem solving
  • allows students to develop realistic solutions to complex problems
  • develops students' ability to identify and distinguish between critical and extraneous factors
  • enables students to apply previously acquired skills
  • creates an opportunity for students to learn from one another.

Case studies bridge the gap between a more teacher-centred lecture method and pure problem-based learning. They leave room for teachers to give direct guidance, and the scenarios themselves provide hints and parameters within which the students operate.

Common issues using case studies

The challenges with case studies are similar to those with discussions :

  • getting students to talk and keeping the class moving
  • pointless arguments, which can throw a case analysis off track.

Since case-study analysis is student-led, it can be difficult to get the class to move through various stages of analysis and arrive at a reasonable conclusion.

How to write or choose case studies

Hatcher et al. (2018, p. 276) categorise case studies as either issue-driven (focusing on a particular problem or aspects of the course material) or organisationally based (focusing on the various issues faced by a particular type of organisation). They can be based on general knowledge or adopt the viewpoint of a single protagonist, an organisation as a whole or information gathered from governent, company or other public documents.

"Like any good story" (Hatcher et al., 2018, p. 279), a case study begins with an exposition that introduces the problem and the protagonist and launches the action. Next, the narrative escalates, with complications exacerbating the problem and constraining the protagonist's choices. These complications are revealed as the protagonist discovers them, rather than as part of the background information, to increase the verisimilitude of the case study. Eventually the situation comes to a head, and the protagonist must decide on a solution. Finally, the case study relates the consequences of that solution.

A case study should be engaging, relevant and clearly written. In particular it needs to be economical: every aspect must be directly relevant to the problem the case study is examining, with no extraneous details or digressions.

How to teach effectively with case studies

Case content should reflect the purposes of the course, and should align with the course learning outcomes, other teaching strategies and assessment in your course or program.

1) Use complex cases requiring multiple perspectives

A good case has sufficient detail to:

  • necessitate research and
  • stimulate analysis from a variety of viewpoints or perspectives.

It places the learner in the position of problem-solver. Students actively engage with the materials, discovering underlying issues, dilemmas and conflict issues.

2) Assess the process of analysis, not only the outcome

The resolution of a case is only the last stage of a process. You can observe or evaluate:

  • the quality of research
  • structural issues in written material
  • organisation of arguments
  • the feasibility of solutions presented
  • intra-group dynamics
  • evidence of consideration of all case factors.

Case studies may be resolved in more than one manner.

3) Use a variety of questions in case analysis

Various ways to use questions in teaching are discussed in detail on the Questioning page. If you are using the Harvard Business School Case Method , when analysing case studies, use a range of question types to enable the class to move through the stages of analysis:

  • clarification / information seeking ( what? )
  • analysis / diagnosis ( why? )
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What do you think it means? Using cognitive interviewing to improve measurement in implementation science: description and case example

  • Zabin Patel-Syed   ORCID: orcid.org/0000-0002-0250-0848 1 ,
  • Sara Becker 1 ,
  • Miranda Olson 1 ,
  • Hailey Rinella 1 &
  • Kelli Scott 1  

Implementation Science Communications volume  5 , Article number:  14 ( 2024 ) Cite this article

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Pragmatic measures are essential to evaluate the implementation of evidence-based interventions. Cognitive interviewing, a qualitative method that collects partner feedback throughout measure development, is particularly useful for developing pragmatic implementation measures. Measure developers can use cognitive interviewing to increase a measure’s fit within a particular implementation context. However, cognitive interviewing is underused in implementation research, where most measures remain “homegrown” and used for single studies. We provide a rationale for using cognitive interviewing in implementation science studies and illustrate its use through a case example employing cognitive interviewing to inform development of a measurement-based care protocol for implementation in opioid treatment programs. Applications of cognitive interviewing, including developing a common language with partners and collecting multi-level feedback on assessment procedures, to improve measurement in implementation science are discussed.

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Contributions to the literature

Measurement concerns in implementation science are among the most significant barriers to advancing the field.

Previous studies suggest that implementation measures are often used in single studies, high burden, and developed without partner input.

There remains limited guidance on methods to develop pragmatic measures.

To address this gap, we provide a brief overview of cognitive interviewing, a qualitative method that uses partner feedback throughout the measure development process.

Measurement issues in implementation science are among the most critical barriers to advancing the field [ 7 , 9 , 21 , 22 , 23 , 30 ]. Measures developed and tested in efficacy trials may not be feasible in service systems, and the widespread use of “homegrown” implementation measures limits generalizability of study findings [ 12 , 25 ]. Implementation science is especially vulnerable to measurement issues given the rapid growth of the field and the need for multi-level measurement in diverse health contexts (e.g., community mental health treatment, medicine, etc.) [ 31 ].

Measure development involves conceptualization (identifying measurement gaps and relevant constructs for a target population); development (generating measure content and administration procedures); and testing (assessing psychometric properties) [ 5 ]. Psychometric testing has received the most attention in the implementation science literature [ 20 , 26 ]. However, implementation partners—treatment developers, implementation researchers, community leaders—are unlikely to select measures based on psychometric evidence alone [ 13 , 14 , 29 ]. Emphasis must also be placed on a measure’s pragmatic qualities, goals for use, and translatability to clinical practice [ 34 ].

Glasgow and colleagues [ 13 ] recommended guidelines for pragmatic implementation measures. Based on a review of the literature, the authors noted that pragmatic measures have four key characteristics: importance to partners; low burden for respondents; actionable; and sensitivity to change. Extending this work, Stanick and colleagues [ 34 ] interviewed implementation science experts and identified the following three characteristics as priorities: integration with an electronic/health record, facilitation of guided action (e.g., selection of an intervention), and low-cost. This work contributed to the development of the Psychometric and Pragmatic Evidence Rating Scale (PAPERS) for evaluating implementation measures [ 21 , 22 ]. However, there remains limited guidance on methods for developing pragmatic implementation measures to be used across different contexts.

Implementation measures must balance both psychometric and pragmatic quality. To attain this balance, we advocate that implementation scientists routinely use cognitive interviewing, a qualitative method that collects partner feedback throughout measure development [ 40 ]. Cognitive interviewing is uniquely suited to address measurement concerns in implementation science for four key reasons. First, implementation measures often evaluate efforts that engage diverse partners across multiple levels (patient, provider, organization) [ 1 , 35 ]. Cognitive interviewing can reveal whether measure content is relevant across partner groups and inform tailoring as needed. Second, cognitive interviews can help assess psychometric and pragmatic characteristics, including a measure’s construct validity, training burden, relevance, and usefulness across different contexts. Third, unique to implementation research, in which context is paramount [ 4 , 11 , 28 ], cognitive interviews can be used to collect partner feedback on measure administration procedures. Cognitive interviews can assess partner preferences for a measure delivery platform (e.g., electronic or paper), measure format (e.g., time, length, multiple choice versus free response), and strategies to integrate the measure with a clinical setting’s workflow (e.g., when, and how often to administer a measure), all of which can enhance a measure’s utility and scalability. Finally, collaborative research techniques like cognitive interviewing can be used to center partner perspectives, which can promote equitable partnership-building and increase buy-in [ 36 ].

To advance the development of psychometrically and pragmatically valid tools, we advocate for the widespread use of cognitive interviewing in implementation science studies. We first provide a detailed overview of cognitive interviewing theory and the stages of cognitive interviewing. We then provide a case example from an ongoing implementation trial to demonstrate how cognitive interviewing can be used to develop a pragmatic measure and to design a measure administration protocol [ 32 ]. We conclude with reflections on how cognitive interviewing can be used to improve measurement in implementation science.

Cognitive interviewing: overview of theory and techniques for use in implementation science

During a cognitive interview, implementation partners verbalize their thoughts as they evaluate measure questions and provide responses [ 2 , 40 ]. As the partner reads a measure aloud, an interviewer uses intermittent verbal probes to elicit their response process (concurrent interviewing) or has the partner verbalize their thoughts after completion (retrospective interviewing). Interviews may be used to identify constructs that partners value and consider important to assess (concept elicitation) or to revise an existing measure (debriefing). This method is used widely in other areas such as survey methodology and health outcome measurement (e.g., patient-reported outcomes in clinical trials), and by organizations like the United States Census Bureau [ 6 , 16 , 27 ] for measure development.

Cognitive interviews can be tailored to the goals of an implementation study. Given implementation research often includes a broad range of academic and community partners, interviews can be tailored for specific partner groups, to assess specific parts of a measure (e.g., instructions, terms, response options), to examine the relevance of the measure, or to evaluate administration procedures. In addition to its flexibility, cognitive interviewing can produce informative data even with small sample sizes (e.g., 5–10 interviews and a 15–30-min interview period) [ 40 ], which is particularly useful for resource-constrained implementation efforts.

Cognitive interviewing theory

Drawing on cognitive psychology, cognitive interviewing frameworks propose that a partner follows a four-stage mental model: (1) comprehension; (2) memory retrieval; (3) judgement; and (4) response [ 10 , 17 , 37 ]. At the comprehension stage, the goal is for the partner to interpret measure content (e.g., instructions, items, response options) as intended by the developer [ 39 ]. Misunderstandings may result from confusing or complex wording, missing information, inattention, and unfamiliarity with terminology. Measurement error due to comprehension issues [ 40 ] is especially likely in implementation science where it is well documented that users are often unfamiliar with key constructs [ 3 , 8 ]. For example, the question, “Recently, how many days have you participated in a training on evidence-based practice?” presumes the partner comprehends key terms about time reference (“recently”), implementation strategy (“training”), and a construct (“evidence-based practice”). If the partner is unfamiliar with these terms, they may not understand what types of training activities and intervention to include when responding to the question, which contributes to measurement error.

Next, to recall an answer, the partner must draw on information in memory. Several factors influence the memory retrieval process including a partner’s past experiences and the number and quality of memory cues provided, such as the time anchor (e.g., “recently”) and examples (e.g., participation in a workshop versus ongoing training) [ 10 ]. Third, the partner must integrate the information presented and form a judgement [ 40 ]. Previous studies indicate that decreasing item complexity (e.g., length, vocabulary) may facilitate decision-making, leading to more accurate self-reports [ 18 ]. In the example provided, researchers could consider changing the time anchor, replacing the general term “evidence-based practice” with a specific intervention, and simplifying the question (“Over the past month, did you attend a workshop on cognitive behavioral therapy?”).

In the final stage, the partner selects an answer and communicates it to the interviewer [ 17 , 40 ]. It is important to consider how response options are provided, specifically the type of scale used (e.g., Likert scale, rank order, multiple choice, open-ended), the direction of response options (e.g., “Strongly Disagree to Strongly Agree” versus “Strongly Agree to Strongly Disagree”), and whether the partner can meaningfully differentiate among the response options. In sum, cognitive processes involved in recall and recognition are affected by how measure content is presented, and these factors warrant consideration in measure development.

Cognitive interviewing techniques

Several cognitive interviewing techniques, generally categorized as think aloud and verbal probing [ 10 , 40 ], may be used. In think aloud, the interviewer takes an observer role and asks a partner to spontaneously verbalize their thoughts as they respond to questions. In verbal probing, the interviewer takes a more active role by asking a partner pointed follow-up questions after each response. Probes may be general (Does this question makes sense?) or item-specific (What do you think the term “evidence-based practice” means?). Probe selection can be standardized/pre-planned or applied flexibly in response to the partner (You hesitated to answer, can you tell me why?). The goals of the implementation study will guide probe selection. Table 1 presents key goals of cognitive interviewing and probes to elicit implementation relevant feedback.

Cognitive interviewing experts recommend using a structured or semi-structured protocol to guide data collection (see [ 40 ]). The protocol typically includes study-specific interview techniques (e.g., standardized probes) and administration information (e.g., use of technical equipment). For implementation studies, the cognitive interview protocol may also include several key additions: (1) probes to elicit multi-level partner perspectives (e.g., asking a clinical provider: What factors may affect how a patient would answer this question?,asking a clinical supervisor: Do you think clinicians would need additional training to administer this question?); (2) definitions of terms to facilitate shared understanding between partners (e.g., Can you describe what evidence-based practice means in your own words?); and (3) instructions on how to tailor probes for specific partner groups (e.g., clinic supervisors versus front-line providers). Given the multi-level nature of implementation studies, analyzing data at the item- and partner-level may reveal important patterns in terms of conceptual themes, informant discrepancies, targeted revision areas, and measurement feasibility barriers. These patterns can inform subsequent refinements to the measure and measure administration protocol to enhance the usability and scalability in real-world contexts.

Cognitive interviewing case example in ongoing implementation science project

Our team is currently employing cognitive interviewing to develop a pragmatic measurement-based care (MBC) tool. MBC is an evidence-based practice that involves the systematic administration, review, and discussion of patient assessment data to inform treatment decisions [ 19 , 33 ]. Few measures to assess patient progress in opioid use disorder treatment exist [ 24 ]. To address this need, the Director of the National Institute on Drug Abuse (NIDA) put forth a call to develop pragmatic measures of opioid use disorder symptoms and overdose risk. In response to this call, the NIDA-funded Measurement-Based Care to Opioid Treatment Programs (MBC2OTP) Project (K23DA050729) aims to develop a pragmatic overdose risk measure and measure administration protocol [ 32 ]. A preliminary 22-item measure was drafted by members of our study team based on published recommendations from the NIDA Director and colleagues and the DSM-5 diagnostic criteria for opioid use disorder [ 24 ]. Cognitive interviews are being used to collect partner feedback on measure content (symptoms, impairment, frequency of opioid use), format (open-ended questions versus multiple choice, preferred length, scoring), and administration procedures to inform implementation in community opioid treatment programs (OTP).

Multi-level partners are being recruited via email for cognitive interviews in two rounds. In the first round, relevant partners include program leaders who would decide whether to introduce the measure at an opioid treatment program, clinical supervisors who would oversee the training and supervision of counselors in measure administration, and front-line counselors who would deliver the measure to a patient. The second round of interviews focus on patients who would complete the measure in treatment. Eligibility requirements include English fluency and staff employment at the opioid treatment program for at least 3 months. No other exclusion criteria are used. Exclusion criteria are purposefully minimal to capture a range of diverse partner perspectives.

During the interview, three female researchers trained in cognitive interviewing present partners with the measure draft and ask them to answer each question aloud. We then apply the four-stage cognitive model to assess participant comprehension, memory retrieval, judgement, and response. First, in the comprehension phase, we assess whether partners comprehend the question and all the embedded constructs. For instance, our draft tool contains the item, “What typical dose of opioids do you take?” Ensuring comprehension requires us to assess whether a patient understands what opioids are and if they are aware of their average levels of opioid use.

Next, we assess the partner’s ability to recall an answer by drawing on information in memory. For example, we assess whether a patient’s response to the question about typical opioid use may differ based on whether they are experiencing withdrawal symptoms and if they would value examples of opioids in the item wording.

Third, we ask the partner to think aloud and describe how they are answering the question, so that we can assess how they form a judgment [ 40 ]. We also assess whether item complexity (e.g., length, vocabulary) seems appropriate or whether the item can be simplified to facilitate more accurate self-reports [ 18 ]. In the example provided, we ask whether participants might prefer a different time anchor or simpler wording of the question (“Over the past month, did you use more opioids than usual?”).

In the final stage, we ask the partner to communicate their final response to the question to the interviewer [ 17 , 40 ]. In our cognitive interviews, after a partner provides a response to one of the MBC items, we elicit their feedback on how the question is presented using verbal probes, which are outlined in a semi-structured protocol [ 10 , 40 ]. We use both general probes (Does this question makes sense?) and item-specific probes (What do you think the term “dose” means?) that are applied flexibly in response to the partner (You hesitated to answer, can you tell me why?). Importantly, our cognitive interview protocol uses supplemental open-ended questions to collect feedback on the ideal measure administration procedures to facilitate implementation of the protocol into the organizational workflow. Specifically, we elicit feedback on assessment frequency (how often the measure should be administered), administration context (group vs. individual counseling; in-person vs. telehealth sessions), and preferred administration method (electronic health record vs. tablet vs. pen and paper). Additionally, as an extension of typical cognitive interviewing, partners are asked to reflect on the types of implementation supports likely needed. Table 2 presents the four steps of cognitive interviewing currently being applied in the MBC2OTP study. Additional file 1 presents the full cognitive interview script used in the MBC2OTP study.

One-on-one partner interviews are currently being conducted via videoconference, are audio-recorded, and transcribed. Transcripts are being analyzed by three independent coders (ZPS, HR, and KS) to thematically identify areas for revision using NVivo. Using a reflexive team analysis approach [ 15 ], the study team meets weekly to establish consensus and resolve coding discrepancies. Reflexivity in qualitative analysis refers to the process by which the researcher identifies and reflects on the impact they may have (i.e., their own assumptions and biases) on the data being collected and analyzed in a study. The reflexive team analysis approach was selected to enable the coding team to iteratively reflect on their roles as researchers who are unfamiliar with the OTP context, as well as how this outside role may have impacted data collection, analysis, and interpretation.

Suggested revisions are being analyzed by item and partner background. Cognitive interviews will be continued until a representative sample is obtained from each participating OTP, defined as interview completion with all eligible partners who consent at each site. Data from these initial interviews will inform iterative development of the pragmatic MBC measure and measure administration protocol. Discrepancies and conflicting views across different partner groups (e.g., leaders and patients) will be resolved via collaborative co-design meetings with representatives from each OTP and the research team following interview completion. Results from the qualitative data analysis will be presented to OTP representatives, and consensus discussions will be held to make final decisions about conflicting feedback on each measure item.

To date, we have conducted 13 first-round 30 to 60-min cognitive interviews with participants from three opioid treatment programs ( n  = 6 opioid program leaders; n  = 3 clinical supervisors; n  = 4 front-line counselors). Data collection is ongoing and an additional five opioid treatment programs will be recruited to participate in the MBC2OTP study. Table 3 presents illustrative data gathered from the multi-level partners thus far to highlight how cognitive interviewing can be used to elucidate feedback on potential measure refinements as well as workflow administration.

The interviews have identified specific items, instructions, and response options that may require modification to enhance clarity. Specifically, partners have suggested shortening items due to confusing clinical wording to enhance literacy, rephrasing instructions using simpler language, and including a mix of open-ended and multiple-choice response options. Additionally, interviews have identified questions that can likely be removed due to limited perceived utility, conceptual overlap with other items, and fit with counseling procedures at opioid treatment programs. Perhaps most valuably, the interviews conducted thus far have elucidated partner preferences regarding ideal measure administration procedures. Specific administration advice elicited by the interviews has included: administration of the measure prior to individual or group counseling sessions, review of the measure at the start of a clinical encounter to guide service provision, and use of paper and pencil to facilitate administration off-line or in group contexts. The interviews have also provided encouraging preliminary data that the measure is viewed as low burden to be pragmatic within the standard opioid treatment program workflow. Final decisions about which items to eliminate, add, or modify, as well as how to administer the measure in the usual opioid treatment program workflow, will be made once data collection is complete to ensure responsiveness to the elucidated feedback.

Reflections on use of cognitive interviewing

Methods to develop pragmatic measures are critical to advance implementation science [ 23 ]. As the field evolves, ensuring that partners share a common understanding of implementation constructs is essential to further the study of implementation strategies and outcomes [ 38 ]. Although cognitive interviews can be time and labor intensive, involving partners in measure development incorporates the perspectives of the end-users, which can increase measure relevancy, increase the buy-in of front-line staff and administrators, and optimize a measure’s fit within a specific organizational context. Additionally, while interviews elicit discrepant data on measure quality and fit, cognitive interviews allow researchers to qualitatively capture discrepant partner viewpoints. This increased buy-in may result in measures that are more pragmatic, easily implemented, and sustained in community-based settings.

Cognitive interviewing can facilitate a shared understanding between partners and measure developers of implementation constructs, which with time, can reduce the field’s reliance on home grown implementation measures developed for single use. We assert that using cognitive interviewing to engage partners is complementary to psychometric testing because it increases measure utility and, thus, urge implementation researchers to routinely adopt this method. We believe that cognitive interviewing has potential to improve the rigor of implementation measures and facilitate a greater common language for the field.

Measurement concerns in implementation science are among the most significant barriers to advancing the field. There is an immense need for pragmatic and psychometrically sound measures but there remains limited guidance on methods to develop these measures. We hope that the overview of the four-stage approach to cognitive interviewing provided in this manuscript, along with a case example of how these stages are actively being applied in an ongoing implementation study, can help to advance the development of pragmatic measures and address measurement issues in the field.

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Acknowledgements

This study protocol was supported by a grant award from the National Institute on Drug Abuse (K23DA050729; PI: Scott).

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ZPS conceptualized this manuscript and wrote the first draft of the manuscript. SB also contributed to the conceptualization, writing, and review of the full manuscript. MO, HR, KS contributed to the writing and review of the full manuscript. SB and KS provided mentorship on the development of the manuscript. All authors read and approved the final manuscript.

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Additional file 1..

Measurement-Based Care Cognitive Interview Script. This file includes the Measurement-Based Care Cognitive Interview Script, Interview Table, and Suggested Follow-up Questions used in the MBC2OTP case example.

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Patel-Syed, Z., Becker, S., Olson, M. et al. What do you think it means? Using cognitive interviewing to improve measurement in implementation science: description and case example. Implement Sci Commun 5 , 14 (2024). https://doi.org/10.1186/s43058-024-00549-0

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A systematic review and meta-analysis of the effects of long-term antibiotic use on cognitive outcomes

  • Yongqin Ye 1   na1 ,
  • Hor Yee Kimberley Tong 2   na1 ,
  • Wai Hong Chong 1   na2 ,
  • Zhiqian Li 1   na2 ,
  • Paul Kwong Hang Tam 1 ,
  • Daniel T. Baptista-Hon 1 , 3   na3 &
  • Olivia Monteiro 1   na3  

Scientific Reports volume  14 , Article number:  4026 ( 2024 ) Cite this article

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  • Medical research
  • Neuroscience

Antibiotics are indispensable to infection management. However, use of antibiotics can cause gut microbiota dysbiosis, which has been linked to cognitive impairment by disrupting communication between the gut microbiota and the brain. We conducted a systematic review and meta-analysis on the effects of long-term antibiotic use on cognitive outcomes. We have searched PubMed, Web of Science, Embase, Cochrane Library and Scopus for English publications before March 2023 following the PRISMA guidelines. Screening, data extraction, and quality assessment were performed in duplicate. 960 articles were screened and 16 studies which evaluated the effect of any antibiotic compared to no antibiotics or placebo were included. Case-reports, in vitro and animal studies were excluded. We found that antibiotic use was associated with worse cognitive outcomes with a pooled effect estimate of − 0.11 (95% CI − 0.15, − 0.07, Z = 5.45; P < 0.00001). Subgroup analyses performed on adult vs pediatric patients showed a similar association of antibiotic on cognition in both subgroups. Antibiotic treatment was not associated with worse cognition on subjects with existing cognitive impairment. On the other hand, antibiotic treatment on subjects with no prior cognitive impairment was associated with worse cognitive performance later in life. This calls for future well-designed and well-powered studies to investigate the impact of antibiotics on cognitive performance.

Introduction

Dementia can occur in people of all ages and is a leading cause of death and disability worldwide accounting for > 1.6 million total deaths in 2019 ( WHO Global Health Estimates ). It is a chronic and progressive deterioration in cognitive function beyond that to be expected from normal biological aging. Whilst dementia occurs mainly at older ages, it is not an inevitable consequence of ageing 1 . Dementia is usually a result of neurodegenerative and neurological diseases such as Alzheimer’s disease (AD), Parkinson’s disease or stroke. Death or degeneration of neurons in brain areas important for memory and cognition is the main cause for loss of cognitive function. AD accounts for around 70% of all cases of dementia worldwide. Although extensive research and progress has been made regarding the pathophysiology of AD, its cause is not fully understood. There is currently no cure for AD or dementia and treatment focuses on the alleviation of symptoms and risk reduction.

There is growing interest on the regulation of the gut-brain axis and how dysbiosis in the intestines can affect brain function. This raises the possibility that the microbiota–gut–brain-axis has a role to play in neurodegenerative diseases 2 . In addition to the important role of the gut microbiota on metabolic functions 3 , the gut microbiota is capable of synthesizing and releasing neurotransmitters (e.g. GABA and tryptophan) and neuromodulators such as short-chain fatty acids and biogenic amines (e.g. serotonin, histamine, and dopamine) 4 . Moreover, the gut microbiota produces proinflammatory cytokines that can activate neuroinflammation which may affect cognitive function 5 . The relative composition of the gut microbiota is affected by our genetic makeup, lifestyle, diet, and drugs we take such as antibiotics 6 . There is also evidence that the composition of gut microbiota changes with aging 7 , and the microbiota composition in children may be less stable and diverse compared to adults 8 . It is therefore possible that perturbations in microbiota compositions and their effects may be age dependent. There are profound changes in the gut microbial profiles in AD patients compared to healthy controls with less richness in operational taxonomic units in AD and less α- and β-diversity (mean diversity of species and ratio between regional and local species) 9 . There is increasing evidence that cognitive impairments caused by antibiotics are effects of disruption of the gut microbiota. Germ-free mice with no intestinal microbiome displayed disrupted brain development 10 , suggesting a direct link between the microbiome and the brain. There is strong evidence that long-term treatment with broad spectrum antibiotics disrupted the microbial composition in the gut 11 . The loss of diversity in gut microbiota and the altered microbial composition after long-term antibiotic treatment may be long lasting, where bacterial populations do not recover after cessation of antibiotics 12 . A 2-week treatment of rheumatoid arthritis patients with vancomycin showed an inability of some patients to fully recover their baseline microbiota structure up to 22 weeks after antibiotic cessation 13 . Importantly, development of AD seems to be directly linked to the gut microbiome. Transplantation of healthy fecal microbiota to AD mice reduced brain deposition of amyloid-beta, decreased tau phosphorylation, increased synaptic plasticity and improved cognitive performance 14 . In a clinical case report, an AD patient with mild cognitive impairment who received a single fecal microbiota transplantation (FMT) had an increased mental acuity and improved affection 2 months after FMT 15 . Furthermore, memory and mood were improved at 4 and 6 months after FMT with improvements in MMSE scores compared to scores prior to FMT. Another recent case report of the use of FMT in a patient with AD dementia confirmed this finding 16 . As rapidly as 1 month after FMT, the patient benefited from improved cognitive functions including improvements in short-term memory, semantic skills, attention, non-verbal learning, and expressive affection.

Antibiotics play a crucial role in modern medicine to prevent serious complications and fatality from infections. The average total antibacterial consumption in the European Union (EU) for 2019 was 19.4 daily doses per 1000 inhabitants per day (Ecdc. Antimicrobial consumption in the EU and EEA). In the United States, 270.2 million antibiotic prescriptions were written in 2016, a rate which was equivalent to enough antibiotic courses for 5 out of every 6 Americans (U.S. Department of Health and Human Services, 2018). More than 10% of children in the EU use antibiotics each year and antibiotics account for 25% of all pediatric prescriptions in the United States 17 . Although antibiotics are indispensable to control infections, its use can cause gut microbiota dysbiosis and the potential downstream cognitive impairments 18 . This may be especially true for broad-spectrum antibiotics 19 . Animal studies found that antibiotic treatment impaired cognition by disrupting communication between the gut microbiota and the brain 20 . Recently, several human studies also found that antibiotic use reduced cognitive function later in life 18 , 21 , 22 , 23 . On the other hand, there are clinical trials investigating the efficacy of antibiotics in the treatment of dementia (NCT03413384, NCT04408625, NCT04629495, NCT04200911). Broad spectrum antibiotics such as doxycycline, rifampin and minocycline have been tested for their ability to reduce cognitive decline in patients with neurodegenerative diseases 24 , 25 , 26 , 27 , 28 . In vitro studies suggest rifampin and its derivative prevented the aggregation of amyloid beta peptide, prevented beta-amyloid fibrils formation and reduced neurotoxic effects of amyloid beta by acting as a free radical scavenger 29 . In vivo animal studies also supported the role of rifampin and its derivative in clearing amyloid-beta and tau oligomers and improved spatial memory in AD mouse models 30 . Doxycycline disrupts the formation of amyloid-beta plaques in AD models by destabilising the structure of amyloid fibrils and reducing neuroinflammation leading to rescue of memory impairments in AD mice 31 . Minocycline, another tetracycline antibiotic, prevented neurotoxicity in AD mouse models by reducing deposition and fibrillisation of amyloid-beta, reducing tau aggregation and reducing inflammatory markers in AD brains leading to rescue of memory impairments 32 .

Antibiotic stewardship for better antibiotic prescription is an important component of infection management, primarily to mitigate the emerging problem of antibiotic resistance. However, the possibility of cognitive impairment with long-term and recurrent antibiotic use, if present, will also be an important consideration in antibiotic stewardship. We therefore initiate this systematic review with the aim of evaluating the current clinical evidence on antibiotic usage and cognitive outcomes in patients who have received long-term or recurrent antibiotic treatment.

We identified a total of 960 articles (220 from Pubmed, 288 from Web of Science, 125 from Embase, 151 from Scopus and 176 from the Cochrane Library) from electronic sources for this systematic review (flowchart is shown in Fig.  1 ).

figure 1

PRISMA flowchart for study selection according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020.

We found two peer reviewed publications from two additional articles identified from records on http://www.clinicaltrials.gov . After removal of duplicates and removal of non-English articles, title and abstract screening was performed for 625 articles. A preliminary screen was carried out to assess for eligibility. 55 articles were selected for full text screening, after 399 articles were removed due to wrong intervention, no assessment outcome or no control. Finally, after removal of articles with the wrong intervention (including articles that did not specify the type of antibiotics used or the duration or frequency of antibiotic use, or the intervention was not an antibiotic), outcome assessment (including articles where we could not identify the treatment group from the outcome assessment), and articles with no control group, 16 articles were included in the systematic review and meta-analysis 18 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 33 , 34 , 35 , 36 , 37 , 38 , 39 . Descriptive summaries of the 16 included studies are listed in Table 1 . For all randomised controlled trials, one or two specific antibiotic was tested. Minocycline, doxycycline and rifampin were the most common antibiotics tested 24 , 25 , 26 , 27 , 28 , 39 . Five retrospective cohort studies investigated long-term antibiotic use (< 7 to 28 days 38 , 30 to ≥ 91 days 33 , < 7 to ≥ 15 days 36 , and < 30 to ≥ 365 days 37 ) and the risk of developing dementia later in life. Our primary objective is in understanding the long-term effects of antibiotic treatment on cognitive performance. Hence, where studies reported more than one duration of antibiotic treatment, the longest duration was analysed (Table 1 ). By extracting data on the longest treatment duration, we aim to capture the potential cumulative and sustained impact of antibiotics on cognitive function. Where studies reported more than one specified antibiotic treatment, the effects of each antibiotic was analysed. Two additional cohort studies 18 , 23 investigated long-term or recurrent antibiotic use for > 2 months or 3 regimens in 1 year with no specification of the types of antibiotics used. Three studies investigated the effects of paediatric long-term or recurrent antibiotic use 21 , 22 , 23 . The included studies also showed differences in their interval to testing, which represents the time between the commencement of antibiotic treatment and cognitive tests carried out. The timing of the cognitive tests can be divided into acute (cognitive performance was measured at the end of long-term antibiotic treatment) or chronic (cognitive tests performed at least 6 months after treatment).

Supplementary Fig.  1 A summarises the risk of bias for 8 randomised controlled studies. Amongst the 8 RCT, one study Molloy et al . 26 has a high risk of bias due to missing outcome data in the study. In addition, there are some concerns regarding selection of reported results Sacktor et al . 28 and Howard et al . 24 . There were also some concerns regarding deviations from intended intervention and bias due to missing outcome data in Kraig et al . 34 . Among the seven cohort studies, five studies, Chao et al . 38 , Kim et al . 33 , Ou et al . 36 , Slykerman et al . 22 and Yang et al . had low risk of bias. Liu et al . 23 and Mehta et al . 18 and, had a low to moderate risk of bias with scores of 6 and 7 respectively. Slykerman et al . 21 , a case control study, had a moderate risk of bias score of 5/9. Supplementary Fig.  1 B summarises the risk of bias for all included studies.

We included 16 studies in our meta-analysis, of which 8 were randomized controlled trials, 8 were cohort studies. We evaluated the standardized mean difference (SMD) of antibiotic exposure on cognitive test scores from 12 studies where the SMD can be calculated (Fig.  2 A). One study, Molloy et al . , evaluated the effects of doxycycline and rifampin on cognition on separate cohorts and hence, data on the two antibiotics were analysed separately. The pooled effect estimate was − 0.11 [95% CI − 0.15, − 0.07, total number of control subjects = 35,611, antibiotic subjects = 6831]. A Z -test showed that antibiotic use was associated with worse cognitive outcomes (Z = 5.45; P < 0.00001; Fig.  2 A). We found no heterogeneity in the included studies (τ 2  = 0, χ 2  = 1.77, P = 1, I 2  = 0%). We did not perform publication bias analyses due to the small number of studies included. Visual inspection of the forest plot indicates that one large study carries most of the weight in the calculation of the pooled estimate. We therefore performed a sensitivity analysis (Fig.  2 B), by sequentially removing individual studies to evaluate their overall contribution to the pooled estimate or heterogeneity. When we removed the study with the heaviest weighting, Mehta et al . 18 , the data revealed a smaller but nevertheless statistically significant overall effect (pooled effect estimate − 0.10, 95% CI − 0.19, 0.00; Z = 1.96; P = 0.05). We found minor effects of sequentially removing other studies on either the pooled SMD (from − 0.11 to − 0.12 when Liu et al . 23 was removed), or extent of heterogeneity (I 2  = 0% in all cases).

figure 2

( A ) Forest plot of adjusted SMDs showing overall effect of antibiotic on cognitive performance. One study (Molloy et al. 26 ) tested two antibiotics on different populations and hence, the results were extracted separately. There is an overall effect favouring no antibiotic in the SMD of cognitive performance (pooled effect estimate − 0.11, 95% CI − 0.15, − 0.07; Z = 5.47; P < 0.00001). ( B ) Sensitivity analysis showing the change in SMD after the individual removal of each study from the overall analysis. Individual study was sequentially removed to evaluate their overall contribution to the pooled estimate or heterogeneity. Removing the study with the heaviest weighting (Mehta et al. 18 ) revealed a smaller but nevertheless statistically significant overall effect (Z = 1.99; P = 0.05) of antibiotics on cognitive impairment. Removing the second largest study (Liu et al . 23 ) altered the SMD in favour of no antibiotics (− 0.12, 95% CI − 0.16, − 0.07) with a similar overall effect (Z = 5.21; P < 0.00001). Removing other studies sequentially did not result in a change in the pooled SMD.

We separately analysed the effects of antibiotics on cognition for studies which reported hazard ratios for the likelihood of developing dementia after antibiotic treatment. Similarly, studies which evaluated the risk of dementia after more than one antibiotic treatment on separate cohorts were analysed separately. The log risk ratio for the four retrospective cohort studies were analysed using the generic inverse-variance method and the pooled effect estimate was 0.70 [95% CI 0.59, 0.83]. A Z -test showed that antibiotic use was again associated with worse cognitive outcomes (Z = 4.05; P < 0.0001; Supplementary Fig.  2 A). Chi 2 for heterogeneity revealed large differences in data (Chi 2  = 138.33, P < 0.00001; I 2  = 96%). This means that 96% of the variability in the effects observed is due to heterogeneity and not chance. Sensitivity analysis did not find a great deal of difference when studies were removed sequentially (risk ratios from 0.65 to 0.77; Supplementary Fig.  2 B). When the study with the heaviest weight (Yang et al . 37 ) was removed, the effect estimate was 0.65 [95% CI 0.58, 0.73] and the overall effect was Z = 7.36; P < 0.00001. Heterogeneity decreased slightly (Chi 2  = 6.7, P < 0.00001; I 2  = 25%). Yang et al . reported the risk of dementia is 0.932 and 0.664 [95% CI 0.901, 0.986; 0.602, 0.692] in patients who took sulfadiazine and those who took clindamycin for ≥ 365 days respectively. Unsurprisingly, removing this study resulted in a much lower I 2 statistic.

The microbiota composition shows dynamic changes through life 22 , 23 . Children have less diverse gut microbial population which makes them more vulnerable to antibiotic dysbiosis 40 . Children may therefore be more vulnerable to the effects of antibiotics on cognitive abilities later in life. We carried out subgroup analysis for SMD in cognitive abilities for pediatric (under 19 years; 3 studies) and adults (10 studies). Studies reporting hazard ratios were not included in this subgroup analysis since there is no accurate way to convert hazard ratios to SMD. Antibiotic use had an overall effect on the adult subgroup (pooled effect estimate = − 0.12; 95% CI − 0.16, − 0.07; total number for control subjects = 3896, antibiotic subjects = 1673; Z = 5.19; P < 0.00001;) and the pediatric subgroup (pooled effect estimate = − 0.11; 95% CI − 0.14, − 0.07; total number for control subjects = 31,715, antibiotic subjects = 5158, Z = 3.09; P = 0.002) (Fig.  3 A). There was no heterogeneity of data in both subgroups (I 2  = 0%). The subgroup analysis indicated that long-term or recurrent antibiotic use had a negative influence on cognitive performance in children and adults.

figure 3

Forest plots of adjusted SMDs showing analysis ( A ) on antibiotic treatment in the pediatric and the adult subgroups. There is an overall effect favouring no antibiotic for the “Young” (Z = 3.09; P = 0.002) and the “Old” (Z = 5.20; P < 0.00001) subgroups. ( B ) Analysis on the acute and chronic effects of antibiotic treatment on cognitive performance. Cognitive performance was not affected (Z = 1.03; P = 0.31) when assessed immediately after antibiotic treatment. Cognitive performance was significantly impaired (Z = 5.93; P < 0.00001) when assessed > 6 months after antibiotic treatment. ( C ) Analysis on subgroups with and without prior cognitive deficits. Cognitive performance was not affected (Z = 0.94; P = 0.35) in the subgroup with prior cognitive deficits. Cognitive performance was significantly impaired (Z = 5.93; P < 0.00001) in the subgroup with no prior cognitive deficits.

The included studies contained cognitive performance measured soon after antibiotic treatment (7 studies), and also longer term (> 6 months) effects (6 studies). We therefore attempted to dissect acute and chronic effects of antibiotic treatment on cognitive performance. Studies reporting hazard ratios were not included in this subgroup analysis since there is no accurate way to compare hazard ratios to SMD. The acute effects group included studies in which cognitive tests were performed < 6 months after the end of antibiotic use. Table 1 details the interval between the first administration of antibiotics and testing of cognitive outcomes. The chronic effects group included studies in which cognitive tests were performed ≥ 6 months after the end of antibiotic use. The pooled SMD estimate for studies evaluating acute cognitive performance was − 0.12 [95% CI − 0.36, 0.12; total number for control subjects = 445, antibiotic subjects = 422], and was not statistically significant (Z = 0.96; P = 0.34; I 2  = 0%; Fig.  3 B). By contrast, the pooled SMD estimate for the studies evaluating chronic cognitive performance was − 0.11 [95% CI − 0.14, − 0.07; total number for control subjects = 35,166, antibiotic subjects = 6409], which was statistically significant (Z = 5.93; P < 0.00001; I 2  = 0%; Fig.  3 B).

Seven studies investigated the effect of antibiotic treatment on cognitive performance on subjects with cognitive impairments whereas five studies investigated the effect of antibiotic on subjects with no prior cognitive impairments (Fig.  3 C). Antibiotic treatment on subjects with existing cognitive impairment did not improve cognitive performance with a pooled effect estimate of − 0.11 (95% CI − 0.35, − 0.13; total number for control subjects = 485, antibiotic subjects = 468; Z = 0.87; P = 0.39). On the other hand, antibiotic treatment on subjects with no prior cognitive impairment worsen cognitive performance later in life with a pooled effect estimate of − 0.11 (95% CI − 0.14, − 0.07; total number for control subjects = 35,611, antibiotic subjects = 6831; Z = 5.93; P < 0.00001).

Our systematic review and meta-analysis is the first to analyse the effects of long-term or recurrent antibiotic use on cognitive performance. Our meta-analysis showed that long-term (≥ 15 days) or recurrent antibiotic treatment had a negative effect on cognition. In addition, our subgroup analysis of adult and pediatric patients revealed similar cognitive impairments, suggesting that long-term antibiotic use induced cognitive deficits irrespective of age. Our subgroup analysis revealed that when the studies were stratified according to the measurement of acute or chronic cognitive performance, long-term or recurrent antibiotic use only affected chronic cognitive performance. While this is interesting, and may suggest that the resulting cognitive deficit may take a while to manifest, it is important to point out that this subgroup analysis is not appropriately powered. Furthermore, the weighting is overwhelming towards the chronic subgroup. Nevertheless, our finding warrants further investigation in well-designed trials evaluating the time course of cognitive deficits following antibiotic treatments. Interestingly, all the pediatric studies evaluated cognitive performance several years after long-term or recurrent antibiotic use suggesting a chronic effect of antibiotic at an important age for development. Our meta-analysis included study populations that had prior cognitive deficits and those without. This can potentially confound the effects of antibiotics on cognitive performance. Nevertheless, the lack of heterogeneity in our meta-analysis supports the overall finding that there is a positive association of antibiotics use and cognitive impairments.

The clinical trials included in our meta-analysis investigated the cognitive enhancing effects of broad spectrum antibiotics doxycycline, minocycline, rifampin, d -cycloserine and rapamycin on patients with neurodegenerative diseases 22 , 24 , 26 , 27 , 28 . The dosages of antibiotics used in the included studies (Table 1 ) all fall within the recommended range for clinical use (National Institute for Health and Care Excellence UK guidelines). The recommended dosages for doxycycline, including minocycline, is 200 mg on day 1 and then 100 mg daily for most infections up to 500 mg twice a day for skin and soft tissue infections. Rifampin is used at 600 mg per dose for treatment of Haemophilus influenzae type b disease, meningococcal meningitis, leprosy and once daily for 6 months for the treatment of tuberculosis. d -cycloserine is also used to treat tuberculosis at 250 mg every 12 h for 2 weeks, up to 500 mg every 12 h. Sirolimus, another name for rapamycin, is indicated for 2 mg daily for 8 weeks for the prophylaxis of organ rejection in kidney allograft recipients.

Of all the clinical studies, only Loeb et al . 25 concluded that doxycycline and rifampin treatment improved cognitive outcomes in patients with mild to moderate AD. However, a larger study testing the same antibiotics found no beneficial effects of doxycycline and rifampin on cognitive function in AD patients 26 . In fact, the trial found significant deterioration in cognition in doxycycline- and rifampin-treated groups compared to the placebo group. The authors suggested that the deterioration in the antibiotic-treated group was due to a loss of effect of cholinesterase inhibitors, a drug that 94% of the tested population was taking, and a known cognitive enhancer 41 . Rifampin is a potent inducer of CYP3A4 and would therefore increase the rate of elimination of cholinesterase inhibitors 42 . Kraig et al. 34 tested the effects of 8 weeks of 1 mg rapamycin per day on cognition in 25 adults aged 70–95. The authors found no clinically significant effect of rapamycin and concluded that the trial duration was too short to observe cognitive improvements. Nevertheless, the dosage of rapamycin was found to be safely tolerated with no change in participants blood glucose concentration, insulin secretion, and insulin sensitivity. Similarly, the clinical trial testing d -cycloserine 35 , an agonist of the glutamatergic N -methyl- d -aspartate (NMDA) receptor, found no significant improvement in cognitive function over placebo at any point of the trial. The authors pointed out that participants of the trial received cognitive behavioural therapy (CBT) prior to each administration of d -cycloserine or placebo and hence, they were not able to measure further cognitive improvement in addition to that as a result of CBT. The other four randomised clinical trials (RCT) included in this meta-analysis investigated the effects of minocycline on cognitive improvement with none showing any beneficial effects of minocycline 24 , 27 , 28 , 39 . These studies concluded that the doses or duration of treatment with minocycline may have not been high enough or long enough to cause clinically relevant improvements in cognition. Howard et al . 24 studied the effects of a 400 mg dose of minocycline administered for 2 years and found that it was poorly tolerated by the test group with a high dropout rate. Since the trial was designed to detect minimal clinically important difference between minocycline and placebo groups, the authors concluded that minocycline had no clinical benefit for AD.

All the observational cohort and case-controlled studies included in the meta-analysis investigated the chronic effects of long-term or recurrent antibiotic use on cognitive outcomes. In mice, long-term and recurrent treatment with antibiotics resulted in hippocampal-dependent cognitive deficits as well as altered gut microbial profiles 20 . In humans, chronic use of antibiotic is associated with early childhood obesity 43 as well as increased risk of several types of cancer 44 . Both studies suggested a key role in antibiotic effects on the intestinal microbiome. There is a strong link between the gut dysbiosis and obesity 3 . A human study with obese and non-obese individuals found lower bacterial diversity in the gut of the obese group 45 . In rodent studies, there are reports of decreased Firmicutes and Bacteroidetes, major phyla of gut microbiota involved in lipid and bile acid metabolism, in obese mice 46 , 47 . Other studies found a regulatory role in the metabolites released by the gut microbiome on the release of metabolic hormones from enteroendocrine cells (for review see Martin et al. 48 ). There is a strong link between obesity, gut microbiome dysbiosis and cognitive function in humans and in rodents (for review see Leigh and Morris 49 ). Various mechanisms of action link the gut microbiota to brain function. Studies in antibiotic-treated mice found altered circulating metabolites, likely due to a depletion of the short-chain fatty acids (SCFAs) as a product of microbial fermentation in the gut 20 . These metabolites have been proposed to act as messengers in the communication between the gut microbiota and the brain. Interestingly, Park et al. 16 found an increase in SCFAs in the AD patient’s brain after FMT suggesting that the restoration of dementia-related functions may be associated with an increase in SCFA levels.

Antibiotic treatment can significantly change the microbiome composition in children and adults. Antibiotic exposure in children has also been associated with several diseases risks including obesity, asthma, allergies and autoimmune disease 50 , 51 , 52 , 53 . Antibiotic exposure in the first 2 years of life particularly lead to a change in α-diversity 52 . There is evidence that microbiota diversity re-establishes after antibiotic treatment in infants as the gut microbiome matures 51 . However, long-term metabolic effects such as increased risk of high-fat diet induced obesity persisted after antibiotic cessation. Microbiome α-diversity in infants has been linked to lower cognitive ability at 2 years of age 54 . There are many factors that can affect cognitive progress at this important stage of development. Disturbance in gut microbiota diversity has been linked to decreased brain-derived neurotrophic factor (BDNF) 20 . BDNF has important functions in synaptic plasticity and neurogenesis, is an important neurotrophic factor for neuronal growth and development and its expression is intricately orchestrated at stages of brain development 55 . The levels of BDNF is also reduced in neurodegenerative diseases such as AD 56 . It is then unsurprising that our analysis found that antibiotic treatment impaired cognitive performance irrespective of the age of treatment and the age of cognitive assessment.

In addition to gut microbiome dysbiosis, a lot of different factors in these studies can affect cognitive abilities. In RCTs, participants were randomly assigned to antibiotic or control groups. However, even for the two largest trials included in this study, Howard et al. 24 and Molloy et al. 26 , treatment allocation did not take into account socioeconomical status, educational attainment or any lifestyle factor such as diet that can affect cognitive assessment outcomes. In the observational studies included, one study (Mehta et al. 18 ) adjusted for body mass index, regular use of antidepressants or depression symptoms, smoking status, regular use of multivitamins, high blood pressure, high cholesterol, type 2 diabetes, emphysema, history of stroke, history of myocardial infarction, regular use of aspirin or nonsteroidal anti-inflammatory drugs, physical activity, and dietary scores. In the studies with paediatric participants, Liu et al. 23 compared the proportion of cognitive impairment by sociodemographic factors (e.g., gender, age, educational qualification, ethnicity, and income level), and clinical conditions and medical histories (e.g., Apoe4, smoking history, drinking history, BMI, history of hypertension, and diabetes) and Slykerman et al. 22 adjusted for potential confounders including treatment group assignment, mode of delivery, breastfeeding and income. However, it remains that participants taking long-term or recurrent antibiotics may be at a poorer state of health in general, contributing to increased cognitive decline compared to their control counterparts.

There are a number of limitations with our systematic review and meta-analysis. The low number of studies precluded analyses for publication bias. The total number studied in the control group was 35,611 and 6831 in the antibiotic group. However, given the fact that an improvement or any deterioration in cognitive outcome after antibiotics would be a significant finding, we do not believe that there are any studies with unpublished results. However, some authors in the included studies had had funding from or serve as advisories for pharmaceuticals. Although none of the studies were funded by these companies, this still raises the possibility that there may have been publication bias. Two large studies in the meta-analysis carried a significant weight to the analysis whereas the remaining ten studies carried little weight; this also serves as a weakness to our analyses. To ensure that the effect of antibiotics on cognition is not based on a particular study, we carried out sensitivity analysis by removing individual studies from the meta-analysis. Our finding concludes that removing the heaviest weighted study showed a smaller but nevertheless statistically significant overall effect of antibiotic on cognitive performance. Another limitation of this study is based on the difference in cognitive test scores between control and antibiotic group, however, the type of cognitive test used in each study is different. Tests used include the Standardized mini mental state examination (sMMSE), Standardized Alzheimer’s Disease Assessment Scale-Cognitive Subscale (SADAS-cog), Fluid Intelligence (FI), Global Cognition CogState, Development Index of the Merrill-Palmer Revised Scale (DI), Neuropsychological Test Composite z score (NPZ-8) and Wechsler Abbreviated Scale of Intelligence (WISC). The variety of tests used is due to the underlying cognitive state of the test population. Participants with AD were tested with the sMMSE or SADAS-cog. The sMMSE is designed to test cognitive performance of older adults. It provides a global score of cognitive ability that correlates with daily function by assessing orientation to time and place, registration, concentration, short-term recall, naming familiar items, repeating a common expression, and the ability to read and follow written instructions, write a sentence, construct a diagram, and follow a three-step verbal command 57 . SADAS-cog provides a measure of change in the cognitive and behavioral functions known to be impaired by Alzheimer’s disease and is often used to test the effect of an intervention 58 . SADAS-cog measures verbal learning/memory, expressive language, receptive language, orientation to time and place, ideational praxis, and constructional praxis (figure copying). It also measures language ability and ability to follow test instructions 59 . Studies involving children used different tests to assess cognitive development. FI assesses children’s ability to reason and their ability to solve new problems and is related to working memory, attention and executive functions 60 . The DI-MPR evaluates general cognitive, social-emotional, self-help, receptive language, and fine and gross motor development in infants and children while providing supplemental scores for memory, speed of cognition, and visual-motor ability 61 . The NPZ-8 test assessed grooved pegboard performance, trail making, choice and sequential reaction, timed gait and symbol digit. Although the NPZ-8 comprises a heavy component of psychomotor speed testing, it also tests attention, executive functioning and memory 62 . The WISC tests general intellectual ability and assesses verbal comprehension, perceptual reasoning, working memory and processing speed 63 . Although each cognitive test assesses slightly different cognitive components, they all comprise of a number of cognitive functions to measure a general cognitive score. This is reflected in our meta-analysis showing that despite the heterogeneity in the tests used, antibiotics had a robust negative effect on cognition.

This systematic review highlighted the effects of antibiotics on cognition later in life. This calls for future well-designed and well-powered studies to investigate the impact of antibiotics on cognitive performance. This systematic review, the included studies, as well as future well conducted clinical studies are also important for determining clinical guidelines for safe and responsible use of antibiotics.

Materials and methods

This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. No experiments on humans and/or human tissue samples were used. No Ethical or Institutional Review Board approval was required for the study design.

Study design

This systematic review is reported according to the Preferred Reporting Items for Systematic reviews and Meta Analyses (PRISMA) guidelines 64 . We also followed the approaches outlined in the Cochrane Handbook for Systematic Reviews of Intervention 65 . We have established a priori protocol using the PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 guidelines. This protocol has been registered on PROSPERO (protocol ID CRD42022358711) prior to study screening. With the exception of subgroup analyses and the definition of long-term antibiotic use, there were no protocol deviations in the conduct of this systematic review and meta-analysis.

Eligibility criteria

Types of studies.

We included all randomised and non-randomised controlled clinical trials, retrospective, and prospective observational studies (cohort studies, case-controlled studies, case-series) for our systematic review. We excluded case-reports, in vitro investigations or animal studies. We also restricted the language of the studies to English only and articles published until 07 Mar 2023.

Types of participants

We included studies with participants of any age. Studies with children under 2 years of age were included for any amount of antibiotics. For participants of any other ages, we included studies evaluating the effect of long-term or recurrent antibiotics. We define long-term antibiotic use as ≥ 7 days, and we define recurrent use of antibiotics as three or more separate prescriptions within a year.

Types of interventions and controls

We included any studies which evaluated the effect of any antibiotic administered via any route compared to no antibiotics or placebo. Any studies not comparing antibiotic use against the absence antibiotics or placebo were excluded.

Types of outcome measures

We included studies which recorded any type of cognitive assessment and assessment/risk of dementia (which include incidences of dementia) subsequent to antibiotic use. We excluded articles with no cognitive assessment after antibiotic treatment.

Information sources

Study search.

We searched for all English articles on PUBMED, EMBASE, ISI Web of Science, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library) until 07 Mar 2023. In addition, manual searches through the bibliographies of publications that meet the eligible criteria for a full-text screening was carried out. We also searched clinicaltrials.gov for unpublished studies with results.

Search strategy

Detailed search strategy for all electronic databases is included in the Supplementary Table 1 .

Study records

Data management.

Records from electronic databases were downloaded into Endnote and Mendeley and scanned for duplicates. The article title, author names, journal, page numbers and DOIs were manually checked before duplicated records were removed. The titles and abstracts of electronic records identified from our search were uploaded to Rayyan.ai for title and abstract screening.

Selection process

Four authors (YY, HYT, WHC and ZQL) independently screened the titles and abstracts identified by the search strategy. After the initial screen, the full text of included articles was retrieved and screened according to the eligibility criteria defined above. Three senior authors (DBH, PHKT and OM) were consulted for conflict resolutions. Resolution of any conflicts involved a unanimous agreement from all study authors.

A flowchart according to the PRISMA guidelines was produced to outline the number of studies identified from each source, number of studies screened, retrieved and assessed for eligibility, and number of studies included and excluded from the systematic review and meta-analysis.

Data collection process

We extracted data from eligible studies using a modified data extraction form previously available from the Cochrane Library (available at https://epoc.cochrane.org/sites/epoc.cochrane.org/files/public/uploads/Resources-for-authors2017/good_practice_data_extraction_form.doc ). Data extraction was performed by YY and HYT on all eligible studies. OM, DBH and PKHT were consulted for conflict resolutions with data extraction. We extracted the generic and the trade name of the antibiotic used, the type of control used, dosage, frequency and duration of treatment, patient characteristics (age when antibiotic treatment was administered and when cognitive tests were performed, gender, type of infections leading to the use of antibiotic if available), type of cognitive outcome measured, trial design, trial size, duration between antibiotic use and subsequent cognitive testing, type and source of financial support and publication status from trial reports. Where necessary, we used information from figures in the reports to approximate dispersion from means. Data was extracted from figures using a data extraction tool available at https://apps.automeris.io/wpd/ 66 , 67 . A summary table of the type and dose of antibiotic used and how cognition was recorded was created.

Outcomes and prioritization

Primary outcome measures include cognitive abilities after antibiotic use. Outcome measures were extracted separately in studies where two different antibiotics were evaluated on separate populations. The highest dose of antibiotic or the longest duration used were extracted for analysis if more than one dose or more than one period of treatment were evaluated.

All retrospective cohort studies included reported hazard ratios for dementia diagnosis after antibiotic use. One study reported odds ratio of cognitive impairment. The odds ratio was converted to SMD using the method described below. For all other studies, a cognitive score was obtained after one of these cognitive tests were performed: sMMSE, MCCB, SLUMS, fluid intelligence, CY-BOCS, CogState, SADAS-cog, Development Index of the MP-R Scale, neuropsychological z score, and Wechsler Abbreviated Scale of Intelligence (Table 1 ). Although each test assesses a different aspect of brain function, each of these test measures components of memory, attention, and executive function. The standardised mean difference (SMD) between control and antibiotic in each study was calculated to measure the difference between the two groups and compared between studies.

Risk of bias assessment

We evaluated bias using the “Risk of Bias 2” (RoB2) tool from the Cochrane Foundation for randomised and non-randomised prospective clinical trials. The quality of RCT data for the articles included for the meta-analysis addressed the risk of bias in 5 main domains including risk of bias arising from the randomization process, risk of bias due to deviations from the intended interventions, risk of bias due to missing outcome data, risk of bias in measurement of the outcome and risk of bias in selection of the reported result. The study is judged to have a high risk of bias if there was a high risk of bias in one of the 5 domains. The risk of bias of cohort and case–control studies were graded using the Newcastle Ottawa Scale (NOS) based on the selection of participants, comparability of cohorts, and outcome assessment. A modified NOS which focuses on definition of case and control, comparability between case and control, ascertainment of exposure and response rate was used to assess risk of bias for case–control studies. A star is given to each assessment criteria on the NOS where 0–5 stars represent high risk of bias, 6–7 medium risk and 8–9 low risk of bias.

Data synthesis and statistical analyses

Scores arising from different cognitive test batteries in individual studies were converted to a SMD using the following equation:

We used baseline-adjusted scores in the evaluation of SMD. Studies which investigated cognitive outcomes after antibiotic use in populations without cognitive impairments had no baseline cognitive scores. It was therefore assumed that there was no difference in cognitive abilities between groups at baseline. For studies where higher tests scores indicate poorer cognitive performance, the SMD was multiplied by − 1. In studies reporting odds ratios (OR) for cognitive impairment, the SMD was obtained using the following formula:

The standard deviation (SD) of the cognitive scores were calculated using reported 95% confidence intervals or standard error of means. The pooled effect estimate was a weighted SMD calculated using the inverse variance method under the assumption of random effects, with Review Manager 5.4 68 . Heterogeneity among studies was evaluated using the χ 2 test, and a P-value of less than 0.05 was considered significant heterogeneity. We explored the extent of data heterogeneity with I 2 statistics using the following boundaries: < 30% low heterogeneity; 30–60% moderate heterogeneity; > 60% substantial heterogeneity. Possible reasons for heterogeneity was explored using sensitivity analyses by removing individual studies from the analysis and evaluating the effect on the pooled estimate and heterogeneity.

The generic inverse variance was used to analyse the log hazard ratio and the standard error for outcomes from population studies that reported hazard ratios. A fixed effect model was used to plot the hazard ratios with 95% confidence intervals for these studies. To avoid over transformation of this data, hazard ratios were reported separately to SMD outcomes.

Subgroup analyses

We performed subgroup analysis for cognitive deficits according to participant age (pediatric and adult), participants with or without cognitive deficits at baseline, and studies which evaluated acute or chronic cognitive deficits.

Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

This research was funded by Fundo para o Desenvolvimento das Ciências e da Tecnologia grant number FDCT 0055/2022/A1, FDCT 0106/2021/A, FDCT 0109/2020/A3 and Macau University of Science and Technology Faculty Research Grant FRG-21-037-FMD.

Author information

These authors contributed equally: Yongqin Ye and Hor Yee Kimberley Tong.

These authors contributed equally: Wai Hong Chong and Zhiqian Li.

These authors contributed equally: Daniel T. Baptista-Hon and Olivia Monteiro.

Authors and Affiliations

Faculty of Medicine, Medical Sciences Division, Macau University of Science and Technology, Avenida da Harmonia, Praia Park, Coloane, 999078, Macao SAR, China

Yongqin Ye, Wai Hong Chong, Zhiqian Li, Paul Kwong Hang Tam, Daniel T. Baptista-Hon & Olivia Monteiro

Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China

Hor Yee Kimberley Tong

Division of Systems Medicine, School of Medicine, University of Dundee, Dundee, UK

Daniel T. Baptista-Hon

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Contributions

Conceptualization: O.M.; Data curation: O.M., Y.Y. and H.Y.K.T., W.H.C. and Z.Q.L.; Formal Analysis: O.M., D.T.B.-H., Y.Y. H.Y.K.T., W.H.C. and Z.Q.L.; Funding acquisition: O.M.; Investigation: O.M., D.T.B.-H.; Methodology: O.M. and P.K.H.T.; Project Administration: O.M.; Supervision: O.M., D.T.B.-H. and P.K.H.T.; Validation: O.M.; Y.Y.; H.Y.K.T.; D.T.B.-H. and P.K.H.T.; Visualisation: O.M. and D.T.B.-H.; Writing—Original Draft Preparation: O.M.; Writing—Review and Editing: O.M., Y.Y., H.Y.K.T., W.H.C., Z.Q.L., D.T.B.-H. and P.K.H.T.

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Correspondence to Olivia Monteiro .

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Ye, Y., Tong, H.Y.K., Chong, W.H. et al. A systematic review and meta-analysis of the effects of long-term antibiotic use on cognitive outcomes. Sci Rep 14 , 4026 (2024). https://doi.org/10.1038/s41598-024-54553-4

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using case studies for assessment

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  • Published: 13 February 2024

Need assessment of medical school curriculum for MOOCs: perspectives of instructors and students of Shiraz University of Medical Sciences

  • Zahra Farhadi 1 ,
  • Eisa Rezaei 2 ,
  • Leila Bazrafkan 3 ,
  • Mitra Amini 3 ,
  • Nahid Zarif Sanaiey 4 ,
  • Reza Barati-Boldaji 5 &
  • Manoosh Mehrabi 4  

BMC Medical Education volume  24 , Article number:  141 ( 2024 ) Cite this article

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Introduction

Designing, developing, and implementing a course without assessing and prioritizing instructional needs may result in inefficiency due to the disregard for the actual needs of the target population. The present study aimed to determine and prioritize medical students’ instructional needs regarding Massive Open Online Courses (MOOCs) at Shiraz University of Medical Sciences.

This survey study was carried out in three stages (2020–2021) using the Delphi technique. Purposive and snowball sampling methods were used to select the instructors. The students were selected through simple random sampling. The first round of the Delphi technique involved a questionnaire consisting of one open-ended question, completed by 49 basic/clinical faculty members and 47 senior medical students. In the second round, a 5-point Likert scale-based questionnaire was used to prioritize the instructional needs. The reliability of the questionnaire was verified by Cronbach’s alpha coefficient. In the third round, a focus group was used. A total of six expert faculty members and one senior medical student were invited to the focus group session to prioritize the needs. Data were analyzed using Friedman’s non-parametric ranking test in SPSS version 26.

Ten instructional needs priorities were extracted, including common pharmacotherapies (antibiotics and narcotics), prescriptions, physiology, anatomy, physical examination, electrocardiography interpretation, radiography, computed tomography scans, serum electrolyte disorders, and cardiovascular and internal (endocrine and metabolic) diseases. The chi-squared calculated value (715.584) indicated a significant difference in the importance of the questionnaire’s questions ( P  < 0.001). These questions did not have equal value, and the importance, from the respondent’s point of view and the observed distribution of ranks, was not the output of a random factor.

Conclusions

The findings of this study can be used to design MOOCs, revise instructional programs, and adapt the curriculum to meet the needs of general practitioners, which will, in turn, help meet the medical needs of the general population.

Peer Review reports

Electronic learning (e-learning) is integral to medical education, especially in developed countries [ 1 ]. In basic medical sciences, complementary education by e-learning can help improve the quality of learning and clinical skills [ 2 ] and the long-term retention of information by students [ 3 ]. However, the effectiveness of e-learning depends on several factors. One important factor is the integration of technology tools into the curriculum [ 4 ]; another is how to connect the lessons learned in the theoretical phase with their applications in practice [ 5 ]. Accordingly, the content of e-learning should be designed in accordance with the instructional needs of medical students to achieve a high-quality course. One strategy for such achievement is that the students determine their instructional needs themselves, identify the problems of e-learning systems, adopt necessary strategies for the success of their courses, and properly manage and guide their e-learning courses [ 6 ].

One of the novel and recent advancements in e-learning that is attracting the attention of higher education institutions is Massive Open Online Courses (MOOCs) [ 7 ], which are presented to an unlimited number of participants via the web. The University of Manibota first offered it in 2008 for connective information, expanding to 190 countries with about 160,000 learners [ 8 ]. A smooth supply of efficient instructions in the main key to improving the performance of learners; furthermore, the success of these courses is related to the interactive atmosphere in which students, instructors, and teaching assistants can participate, facilitated by discussion forums and instructional content such as videos, texts, and problem sets. The constructivist teaching modes in MOOCs aim at knowledge construction by the student rather than knowledge transfer from teacher to student. As the latter is the usual setting for medical education, using MOOC can offer an opportunity for educational innovation [ 9 ]. The materials are usually similar to university courses, but its advantages, including the fact that they are accessible to anyone and often do not have a specific starting and ending time, have resulted in increasing interest in this method of education [ 10 ]. Considering the recent coronavirus disease 2019 (COVID-19) pandemic, the significance of online education has increased. Therefore, it is necessary to investigate the needs of learning in each field of study.

Like other fields of study, medical education is also altering with the growth of digital platforms and educational methods, and MOOCs represent an excellent instructor-independent opportunity for the education of faculty members and students [ 11 ]. Such courses have been introduced as a possible solution to the challenges of medical education and have been welcomed by the world’s medical community [ 12 ]. The lack of geographical limitations, time limits, and subscription fees are important advantages of this educational method; the student only needs an internet-based device for learning [ 13 , 14 ]. Accordingly, MOOCs are steadily increasing, and more free courses are being offered in health and medicine. Therefore, determining the role of MOOCs in medical education is vital [ 15 ]. Besides the advantages, MOOCs have some limitations, such as high dropout and low completion rates, content production expenses, and language barriers, though solutions have also been introduced to resolve these issues [ 13 ].

Despite the global attraction to MOOCs in medical education, the rate of participation is low in developing countries, and there is limited information about how medical students perceive MOOCs in these countries [ 16 ]. In our country, Iran, the high school graduate passes a national exam to enter university, and if accepted into a medical university, the students must pass a seven-year course (including internship) to graduate as a general practitioner. Most medical universities teach medicine to students via traditional methods [ 17 ], and MOOCs have been implemented in very few centers. Torbat Heydariye University of Medical Sciences launched e-learning through a learning management system (LMS) in 2014 and produced 34 MOOC items with the cooperation of Iran’s Virtual University of Medical Sciences (VUMS; established in 2017). ARMAN, the national MOOC platform, is the Persian abbreviation for new and massive national computerized education, which aims to produce MOOCs nationally and internationally. Since its establishment (2018–2019), several medical sciences universities have been cooperating with ARMAN and helped its development by holding workshops [ 18 ]. In line with these developments, more research is required to emphasize the importance of utilizing this novel technology, take effective steps toward its implementation [ 19 ], and identify challenges and related solutions [ 20 ], as presenting courses without a detailed analysis and prioritization of the needs would result in courses that fail to meet the actual needs of the target population, thereby generating expenses without causing any improvements in the knowledge, skills, and attitudes of learners. Hence, educational programs, especially in medical education, should be based on performance-related needs assessments to be motivating [ 21 ]. Therefore, the present study aimed to investigate the instructional needs of undergraduate medical students for presenting MOOCs to medical students of Shiraz University of Medical Sciences (SUMS), which can improve the quantity and quality of medical education.

This needs-assessment study was conducted using the Delphi technique in three steps at SUMS during the 2020–2021 educational semester. In this technique, questionnaires and focus groups were used, group members’ comments were collected in special forms, and the resulting opinions were ranked based on priority.

The study population included basic and clinical faculty members, as well as medical students in their internships. Purpose-based and snowball sampling was used to select experts and instructors for this study. The inclusion criteria for the instructors were having a basic or clinical specialty, having passed their fellowship period within the previous five years, and familiarity with the key concepts in healthcare education. According to the inclusion criteria, 21 out of 403 faculty members in basic sciences and 68 out of 114 faculty members in clinical sciences were finally selected. Although the existing references consider an overall sample size of 30–60 for the Delphi technique [ 22 ], a larger number was taken considering the risk of sample loss. For the students, the statistical population consisted of all undergraduate SUMS medical students who started their internships (as an appropriate time to have acquired the necessary perspective on the instructional needs) in February or October 2014. The total number of students was 107, 67 of whom were selected through random sampling with a table of random numbers.

The Delphi technique is a straightforward means of determining the instructional needs of health and medical education systems by collecting and evaluating the opinions of individuals in a certain area [ 23 ], carried out in three steps:

Round 1 : This step is the basic and most important step in the Delphi technique, in which we aimed to identify all instructional needs that can be met through MOOCs. The data collection tool in step one was a questionnaire containing demographic questions and one open-ended question designed for both instructors and students. The question asked: “What are the instructional needs that can be met through MOOCs for medical students?”. The researcher designed the question based on the study’s objectives after a thorough review of the relevant literature and confirmation by the study supervisor. After four experts in medical education and e-learning verified this questionnaire’s face validity and reliability, minor changes were made accordingly, and the final questionnaire was distributed among the faculty members and interns via Email, social networks, or instant messages. The respondents were asked to freely state their opinions about educational needs through brainstorming without prioritizing them. Considering the novelty of online education, a six-page PDF was also prepared that explained the online courses, MOOCs, and ARMAN (based on the available references) to the respondents.

The questionnaires were to be returned within seven days. The participants who had not returned their questionnaire were identified and followed through phone calls or social network messages, repeated (up to even nine times during one month) until an acceptable percentage of the questionnaires were returned. In some cases, in-person visits were made to complete paper-based questionnaires. Finally, 49 instructors and 47 students completed the questionnaires.

This stage of the Delphi technique was based on the responses to the questions in step one, aiming to identify the instructional needs. After analysis of the quantitative data collected in this step by MaxQDA software 2020, the viewpoints of some physicians and medical students were used to categorize these instructional needs and combine similar opinions based on the medical curriculum using text analysis. The results of this analysis were used to identify the educational needs related to online systems and MOOCs from the perspective of the instructors and students. This was changed to a structured questionnaire with a Likert scale, which was used as the tool for the second round. Two separate questionnaires were designed for the instructors and students. The instructors were asked to prioritize the instructional needs based on a 5-point Likert scale. Based on the instructional needs expressed by interns in step one, a separate questionnaire was designed for this group using the Likert scale.

The questionnaire designed for the instructors included 76 items, rated based on a Likert scale, while the questionnaire designed for the interns consisted of 56 items. Two open-ended questions were added: one for further suggestions, new educational topics, corrections, omissions, weaknesses, and strengths, and the other for asking about their agreement or disagreement. The respondents were also asked to state the reason for their prioritization. In step two, by providing feedback to the participants and expressing that the questionnaire is a continuance of the previous step, an effort was made to motivate the participants to continue their participation. A larger number of individuals completed the questionnaires in step two. The researcher-made questionnaire was rated based on a five-point Likert scale from 1 ( very low priority) to 5 ( very high priority). The face validity and content validity of the questionnaire were confirmed by several medical education experts; the reliability of the questionnaire was confirmed by delivering the survey questionnaire to ten members of the statistical population and calculating Cronbach’s alpha coefficient (0.964 for the instructors’ questionnaire and 0.931 for the students’ questionnaire).

The questionnaires were spread, like the previous round, and the respondents were asked to complete them within seven days; those who had not were followed for completion. Others were completed after in-person follow-ups (referring to the participant and asking them to complete a paper-based questionnaire). After one month, data from these questionnaires (49 instructors and 47 students) were collected and entered into SPSS Statistics software version 26, and the priorities were identified using descriptive and inferential statistics, as well as the nonparametric Friedman’s test.

The Delphi method classically involves four rounds, but researchers usually summarize them into three or two rounds to achieve their research objectives. The decision for the number of rounds depends on the time available to the researcher and the type of the initial question. Although validity increases with more rounds, the process often becomes tiresome after three rounds, and no new or useful results are achieved [ 24 ]. Therefore, in this stage, by utilizing a focus group methodology and inviting expert instructors, a final consensus was reached with regard to the opinions and priorities. A total of four expert faculty members at the Medical Education Development Center, two faculty members at VUMS, and one intern (graduate student in medical education) were invited to the focus group session. As the priorities of instructors and students differed, the collective wisdom of the experts in the focus group was used to achieve a consensus between the priorities. The criteria for achieving a consensus were determined first, and the common educational needs were analyzed using Friedman’s test. In the focus group meeting, first, the most common “expressed needs” of the Friedman table were selected according to the needs of instructors and interns. As the main audience of this education is students, we tried to set the students’ opinions as the first priority and the perspective of instructors and experts as the second priority. After examining the instructional needs prioritized by Friedman’s non-parametric test, the first ten priorities regarding the instructional needs presentable through MOOCs were identified. The validity of this questionnaire was reflected by Cronbach’s alpha values of 0.964 for the instructors and 0.931 for the students. The reliability of the items also showed sufficient precision of the questionnaire.

It should be noted that ethical requirements for data collection included informed consent, confidentiality, consent to participation, and the availability of researchers to answer any questions. Ethical approval for this study was obtained from the institute’s research ethics committee (IR.SUMS.REC.1398.969).

To analyze the data, descriptive and inferential statistics were applied. Among the faculty members and instructors, most respondents were males aged 35–45 years; most were married, and most had either a fellowship or postgraduate degree. Most interns were females aged 25–30 years, and most were single. In the first phase of the Delphi method, the basic instructional and clinical needs expressed by the faculty members were 266 titles; after analysis and classification, they were summarized into 36 instructional needs. The frequencies of the top 13 “expressed needs” are shown in Table  1 . Furthermore, the instructional needs expressed by the interns included 311 titles; after analyzing and classifying them, they were reduced to 40. The top 13 instructional needs are listed in Table  1 .

As shown in Table  1 , the frequency of some topics of educational needs was very close to each other, including altered level of consciousness, internal medicine, respiratory infections in children, gastroenteritis, electrolyte disorders, trauma, and acute abdomen.

The needs expressed by interns and instructors, ordered based on frequency, are shown in Fig.  1 A, B, respectively. These figures can help better understand the differences and similarities of the viewpoints of the interns and instructors.

figure 1

( A ) Needs expressed by interns, ( B ) needs expressed by instructors

After qualitative analysis of the questions, data analysis from the second phase of the Delphi questionnaire identified the first 20 needs of the interns and instructors regarding MOOCs. Table  2 shows the list of priorities with the highest scores, reported after applying Friedman’s test.

Table  2 shows the distribution of the mean, standard deviation, and mean rank for the highest mean rank values, as expressed by the basic and clinical instructors and interns. The chi-squared value (715.584), significant at P  < 0.01, indicates a substantial difference between the questionnaire questions in terms of importance. These questions were not of equal value and importance from the respondents’ point of view, and the observed distribution of ranks was not the output of a random factor.

The final step (focus group) identified “common medications (opioids and antibiotics), prescription medications, electrocardiography (ECG) interpretation, physiology, anatomy, electrolyte abnormalities, interpretation of radiographs and computed tomography (CT) scans, physical examination, heart disease and arteries (blood pressure and chest pain), and internal diseases (related to glands and metabolism, diabetes)” as the first ten priorities of instructional needs for MOOCs.

The present study identified the needs for medical education MOOCs by the Delphi method from the perspective of instructors and students. This study was performed in line with the main challenge of educational planning, tailoring the existing curriculum to the needs of diverse individuals and groups and improving the efficiency and effectiveness of the curriculum. The results of educational needs assessments can be used to enhance the quality of curricula and improve both the quantity and quality of medical education [ 25 ]. Considering the evolution of medical teaching methods, MOOCs have gained popularity in several fields, including medical education. However, as the system of medical education is different in Iran, MOOCs and other online methods are not popular in our country. Therefore, our groundbreaking study presents several interesting points for designing an appropriate MOOC for medical students in the Iranian educational system.

In this study, the perspectives of instructors and senior students (interns) were collected to identify the priorities. The results of the three-step Delphi method showed that the viewpoints of instructors and students had some similarities and some differences; the different educational needs expressed may be possibly due to different needs and attitudes. Many faculty members believe that MOOCs cannot replace a teacher, considering the lack of interaction with the instructor, while it is welcomed by most students, who hold that MOOCs can act as an interactive global community [ 26 ]. Therefore, it is important to collect the perspectives of both students and instructors. However, few studies have considered this in the needs assessment of MOOCs in medical education, and none have focused on the needs assessment of the educational curricula. Some researchers have focused on the quality of MOOC performance [ 11 , 27 ], while others have examined the learners’ feedback from an anatomy MOOC [ 28 ]. This is while a needs assessment can help instructors prepare the health trainees to meet the needs of future patients better by including the prioritized needs in online curricula [ 29 ]. The few studies investigating the curricula have focused on providing MOOCs to health professionals in one specific area, like malnutrition [ 30 ] or substance abuse [ 31 ], rather than the general curriculum provided at a medical college. Others have focused on other aspects of medical education, like ethics, communication skills, and time management, rather than clinical courses [ 32 ].

The results of the present study showed that the similarity in the opinions of the instructors and interns included the prioritization of the interpretation of ECG, radiographs, and internal diseases among the first ten priorities of educational needs that can be met through MOOCs. As our literature review revealed no study with similar objectives to ours (need assessment of medical education MOOCs), the discussion is presented with studies that have evaluated the need assessment of medical education through other methods. In a study at Isfahan University of Medical Sciences, researchers evaluated the educational needs of third-year medical students and indicated the following courses as the major educational needs for the students: familiarity with common para-clinical examinations (ECG), major emergencies (altered level of consciousness, poisoning, fractures), resuscitation skills (such as cardiopulmonary resuscitation), familiarity with imaging interpretation (MRI, CT scan, X-ray), history-taking, physical examination, and medication prescriptions [ 33 ]. Despite differences in the educational methods, it can be claimed that these findings are quite consistent with the prior educational needs identified in the present study. In another study on third-year medical students, the results showed a clear desire for training in sonography, central line placement, paracentesis, and thoracentesis [ 34 ]. The difference between their results and that of the present study may be due to the different study populations, as they also evaluated residents’ perspectives.

Several studies evaluated the perspective of physicians rather than students. Consistent with our findings, the physicians of Ahvaz (a city in West Iran) prioritized internal and emergency medicine, imaging interpretation, and interpretation of para-clinical test results among the top ten priorities [ 21 ]. However, they outlined ear-nose-throat diseases, skin diseases, and gynecologic diseases as the top three priorities of educational needs [ 21 ], diverging from our results. This difference could be due to the varied preferences of physicians from students and instructors [ 35 ], as students’ viewpoints were considered the first priority in the present study. In North Khorasan, the top instructional priorities of general physicians included cardiovascular diseases, cardiopulmonary resuscitation, and diabetes [ 36 ], aligning with the present study’s findings. Another study evaluated the educational needs of general practitioners working in healthcare departments of the Ministry of Health and Medical Education using the Delphi technique. It concluded that diabetes, evaluation and accreditation of hospitals, communication skills for managers, principles of nutrition counseling, and neonatal resuscitation were among the top priorities, with diabetes and resuscitation also prominent in our study [ 37 ]. Family medicine workers in Iran also identified cardiovascular diseases and hypertension, diabetes prevention and management, and interpretation of ECGs among the top educational needs [ 38 ], which is consistent with the results of the present study. Other studies have also evaluated the education needs in specific fields of medicine, such as neurologic diseases [ 39 ], from the perspective of physicians or have assessed needs related to continuing medical education (post-graduate) [ 40 , 41 ], falling outside the scope of our study.

Other interesting points of the present study were revealed by comparing different subgroups participating in the study; a comparison of the results of the first and the second quantitative rounds revealed that the educational needs stated by the students in the first qualitative round were slightly different from the top twenty educational needs. However, the top twenty educational needs stated in the second round were urgent needs. Interestingly, the students of different groups had almost the same educational needs; however, some of the educational needs stated by instructors from a specific clinical group could be different from the needs stated for other clinical groups, and each group mentioned the educational needs related to their own field of specification.

Another interesting point in the present study is that instructors believed that holding online courses or MOOCs cannot be effective for the clinical training of medical students. This opinion may result from the fact that MOOCs and e-learning are new in our country and not applied frequently; therefore, the different aspects of this type of education are not clear to the instructors, which might result in a negative attitude toward e-learning. Our findings are consistent with previous ones, stating that learning assessment in clinical settings in a MOOC format could be challenging for some medical educators, especially the older ones [ 11 ]. Younger instructors, however, considered MOOCs very effective along with clinical training.

The educational needs identified by faculty members and students in the present study were also related to knowledge and skills, like achieving professional competency in cardiopulmonary resuscitation and interpreting ECG and CT scan results. Nevertheless, it is not possible to achieve these high cognitive skills through e-learning and MOOC alone, and these modalities should be complemented by learning in clinical settings. This may imply that MOOCs cannot be suitable for all types of learning in medical education. Some have suggested that MOOCs can significantly impact learning and fill the gaps in formal education when used as a complementary, non-formal education [ 42 ]. Perhaps their combination would work best for medical students [ 43 , 44 ]; however, more studies are required to determine the suitability of MOOCs and other online educational systems for medical students.

The present study had the main strength of evaluating a novel and highly applicable issue in medical education, which has not been evaluated in Iran’s educational system before. Other strengths included using the Delphi method for the survey on a large group, including both students and instructors, comparing their opinions. Despite these strengths, our study had some limitations. Firstly, the results of this study are basically based on the participants’ personal opinions, although participants with more experience were selected to get better results. Secondly, the opinions of one medical university in one city were evaluated, while differences may exist in other cities of Iran based on the medical needs of a city/province with dissimilar demographics and culture. Another limitation of the present study is related to the limited participation of instructors due to their unfamiliarity with online learning methods, including MOOCs; however, we provided them with a 6-page PDF to inform them about this educational method.

In this study, we identified the educational needs of medical education through modern electronic educational technology, MOOC, and collected the viewpoints of medical students, clinical faculty members, and medical education experts. The findings of this study can be used in designing general medicine curriculum, revising instructional programs, adapting the curriculum to meet the needs of society, and continuing medical education to improve the quality and effectiveness of medical education; when other phases of instructional design, including monitoring and evaluation, are performed appropriately. Many reputable universities are now offering their courses in the form of MOOCs. Iranian authorities must provide the necessary grounds to create and utilize MOOCs in higher education in our country and provide the students with medical content designed based on their needs. It is recommended that further studies consider the viewpoints of participants who are familiar with online training methods, especially MOOC, and consider evaluating the effectiveness of the combination of offline (clinical) and online methods in medical education at several universities from different cities of the country.

Data availability

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

Abbreviations

Coronavirus disease 2019

Computed tomography

Electrocardiography

Electronic learning

Massive open online courses

Shiraz University of Medical Sciences

Virtual University of Medical Sciences

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Acknowledgements

The researchers would like to express their appreciation and gratitude to the faculty members and students who sincerely assisted us in all stages of this research. The authors are fully grateful for the support of the university. This manuscript was revised regarding language, grammar, and writing quality by a native English-speaking language editor, Dr. Seyed Ali Hosseini (Native Editor Co., Iran).

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The concept and framework were designed by MM and ER. The questionnaires and data were collected by ZF, LB, MA, NZ, RBB and MM. Data analyzed by ZF, ER and MM. The manuscript was prepared by ZF and edited by ER AND MM. The technical editing was done by MM.

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The present study was part of a thesis submitted to the Graduate Master of Science (MSc) Degree in SUMS, entitled “Instructional needs assessment for Massive Open Online Courses (MOOCs) from the perspective of experts and medical students of Shiraz University of Medical Sciences using the Delphi technique.” The ethics code of this research was IR.SUMS.REC.1398.969. All authors confirm that all methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the Ethics Committee of Shiraz University of Medical Sciences. We confirm that informed consent was obtained from all subjects.

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Farhadi, Z., Rezaei, E., Bazrafkan, L. et al. Need assessment of medical school curriculum for MOOCs: perspectives of instructors and students of Shiraz University of Medical Sciences. BMC Med Educ 24 , 141 (2024). https://doi.org/10.1186/s12909-024-05102-0

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  • 1 Military University of Technology in Warsaw, Poland

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In this paper, we present a quantitative assessment of muscle fatigue using surface electromyography (sEMG), a widely recognized method that is conducted through various analytical approaches, including analysis of spectral and time-frequency distributions. Existing research in this field has demonstrated considerable variability in the computational methods used. Although some studies highlight the efficacy of wavelet analysis in dynamic motion, few offer a comprehensive method for determining fatigue and applying it to specific movements. Previous research has focused primarily on discerning differences based on sport type or gender, with a notable absence of studies that presented results for quantifying fatigue during exercise with rowing ergometers. Developing on our previous work, where we introduced a method for determining muscle fatigue through wavelet analysis, considering biomechanical aspects of limb position changes, this current article serves as a continuation. Our study refines the research approach for a selected group, focusing on fatigue determination using the previously established method. The results obtained confirm the effectiveness of DWT analysis in assessing muscle fatigue, as evidenced by the achievement of negative values of the regression coefficients of Median Frequency (MDF) during exercises performed to maximal fatigue. Furthermore, it has been confirmed that the homogeneity of the group and, in the case of the examined group, the results previously achieved or lower limb strength do not have an impact on the results. We investigate whether results are influenced by participants' strength and their past ergometer performance, both of which are translated into a scoring system indicating levels from the lowest to the highest results/strength. Finally, we discuss the main limitations of our study and outline the subsequent steps of our investigation, providing valuable information for future investigations in this field.

Keywords: Electromyography, EMG, Rowing Ergometer, Wavelet Transform, DWT

Received: 25 Nov 2023; Accepted: 15 Feb 2024.

Copyright: © 2024 Daniel, Malachowski, Sybilski and Siemiaszko. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Prof. Jerzy Malachowski, Military University of Technology in Warsaw, Warsaw, Masovian, Poland

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  • Proton pump inhibitors and the risk of inflammatory bowel disease: a Mendelian randomisation study
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  • Hongjin An 1 ,
  • Min Zhong 1 ,
  • http://orcid.org/0000-0002-5736-1283 Huatian Gan 2 , 3
  • 1 Department of Gastroenterology and Hepatology, West China Hospital, Sichuan University , Chengdu , China
  • 2 Department of Geriatrics and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University , Chengdu , China
  • 3 Department of Gastroenterology and Laboratory of Inflammatory Bowel Disease, the Center for Inflammatory Bowel Disease, Clinical Institute of Inflammation and Immunology, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University , Chengdu , China
  • Correspondence to Dr Huatian Gan, West China Hospital of Sichuan University, Chengdu, Sichuan, China; ganhuatian123{at}163.com

https://doi.org/10.1136/gutjnl-2024-331904

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  • INFLAMMATORY BOWEL DISEASE

We read with great interest the population-based cohort study by Abrahami D et al , 1 in which they found that the use of proton pump inhibitors (PPIs) was not associated with an increased risk of inflammatory bowel disease (IBD). However, the assessment of causality in observational studies is often challenging due to the presence of multiple confounding factors. The existence of a causal relationship between PPIs and IBD remains unclear at present. Mendelian randomisation (MR) is a method of generating more reliable evidence using exposure-related genetic variants to assess causality, limiting the bias caused by confounders. 2 Therefore, we used a two-sample MR analysis to investigate the association between the use of PPIs and IBD including Crohn’s disease (CD) and ulcerative colitis (UC).

Supplemental material

Here, we mainly used the inverse-variance weighted 8 method for MR analysis with weighted median, 9 MR-Egger 10 and MR-PRESSO 5 as complementary approaches. Furthermore, we applied a series of sensitivity analyses to ensure the robustness of our results, with Cochran’s Q test to assess heterogeneity and the intercept of an MR-Egger regression to assess horizontal pleiotropy. The genetic prediction of omeprazole, esomeprazole, lansoprazole and rabeprazole use, as depicted in figure 1 , demonstrated no significant association with an increased risk of IBD after excluding pleiotropic SNPs (omeprazole, OR, 1.05; 95% CI, 0.88 to 1.25; p=0.587; esomeprazole, OR, 0.99; 95% CI, 0.92 to 1.07; p=0.865; lansoprazole, OR, 1.06; 95% CI, 0.89 to 1.26; p=0.537; and rabeprazole, OR, 1.00; 95% CI, 0.95 to 1.04; p=0.862). The IBD subtype analyses also did not reveal any evidence of an increased risk of CD or UC associated with the use of PPIs ( figure 1 ). These findings were robustly confirmed through complementary approaches employing rigorous methodologies that consistently yielded similar point estimates ( figure 1 ). Further sensitivity analyses showed the absence of heterogeneity (All P heterogeneity >0.05) and pleiotropy (All P pleiotropy >0.05), again demonstrating the robustness of the conclusions ( figure 1 ).

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Mendelian randomisation estimates the associations between the use of different types of proton pump inhibitors and inflammatory bowel disease. IBD, inflammatory bowel disease; CD, Crohn’s disease; UC, ulcerative colitis; PPIs, proton pump inhibitors; IVW, inverse-variance weighted; MR, Mendelian randomisation.

In conclusion, the MR results corroborate Abrahami D et al ’s findings that PPIs were not associated with an increased risk of IBD. Nonetheless, further research is needed to elucidate the effects of more types, drug dosage, frequency and duration on IBD.

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  • Yin H , et al
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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

  • Data supplement 1

HA and MZ contributed equally.

Contributors All authors conceived and designed the study. HA and MZ did the statistical analyses and wrote the manuscript. HG revised the manuscript and is the guarantor. HA and MZ have contributed equally to this study.

Funding The present work was supported by the National Natural Science Foundation of China (No. 82070560) and 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan (No. ZYGD23013).

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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EU AI Act: first regulation on artificial intelligence

The use of artificial intelligence in the EU will be regulated by the AI Act, the world’s first comprehensive AI law. Find out how it will protect you.

A man faces a computer generated figure with programming language in the background

As part of its digital strategy , the EU wants to regulate artificial intelligence (AI) to ensure better conditions for the development and use of this innovative technology. AI can create many benefits , such as better healthcare; safer and cleaner transport; more efficient manufacturing; and cheaper and more sustainable energy.

In April 2021, the European Commission proposed the first EU regulatory framework for AI. It says that AI systems that can be used in different applications are analysed and classified according to the risk they pose to users. The different risk levels will mean more or less regulation. Once approved, these will be the world’s first rules on AI.

Learn more about what artificial intelligence is and how it is used

What Parliament wants in AI legislation

Parliament’s priority is to make sure that AI systems used in the EU are safe, transparent, traceable, non-discriminatory and environmentally friendly. AI systems should be overseen by people, rather than by automation, to prevent harmful outcomes.

Parliament also wants to establish a technology-neutral, uniform definition for AI that could be applied to future AI systems.

Learn more about Parliament’s work on AI and its vision for AI’s future

AI Act: different rules for different risk levels

The new rules establish obligations for providers and users depending on the level of risk from artificial intelligence. While many AI systems pose minimal risk, they need to be assessed.

Unacceptable risk

Unacceptable risk AI systems are systems considered a threat to people and will be banned. They include:

  • Cognitive behavioural manipulation of people or specific vulnerable groups: for example voice-activated toys that encourage dangerous behaviour in children
  • Social scoring: classifying people based on behaviour, socio-economic status or personal characteristics
  • Biometric identification and categorisation of people
  • Real-time and remote biometric identification systems, such as facial recognition

Some exceptions may be allowed for law enforcement purposes. “Real-time” remote biometric identification systems will be allowed in a limited number of serious cases, while “post” remote biometric identification systems, where identification occurs after a significant delay, will be allowed to prosecute serious crimes and only after court approval.

AI systems that negatively affect safety or fundamental rights will be considered high risk and will be divided into two categories:

1) AI systems that are used in products falling under the EU’s product safety legislation . This includes toys, aviation, cars, medical devices and lifts.

2) AI systems falling into specific areas that will have to be registered in an EU database:

  • Management and operation of critical infrastructure
  • Education and vocational training
  • Employment, worker management and access to self-employment
  • Access to and enjoyment of essential private services and public services and benefits
  • Law enforcement
  • Migration, asylum and border control management
  • Assistance in legal interpretation and application of the law.

All high-risk AI systems will be assessed before being put on the market and also throughout their lifecycle.

General purpose and generative AI

Generative AI, like ChatGPT, would have to comply with transparency requirements:

  • Disclosing that the content was generated by AI
  • Designing the model to prevent it from generating illegal content
  • Publishing summaries of copyrighted data used for training

High-impact general-purpose AI models that might pose systemic risk, such as the more advanced AI model GPT-4, would have to undergo thorough evaluations and any serious incidents would have to be reported to the European Commission.

Limited risk

Limited risk AI systems should comply with minimal transparency requirements that would allow users to make informed decisions. After interacting with the applications, the user can then decide whether they want to continue using it. Users should be made aware when they are interacting with AI. This includes AI systems that generate or manipulate image, audio or video content, for example deepfakes.

On December 9 2023, Parliament reached a provisional agreement with the Council on the AI act . The agreed text will now have to be formally adopted by both Parliament and Council to become EU law. Before all MEPs have their say on the agreement, Parliament’s internal market and civil liberties committees will vote on it.

More on the EU’s digital measures

  • Cryptocurrency dangers and the benefits of EU legislation
  • Fighting cybercrime: new EU cybersecurity laws explained
  • Boosting data sharing in the EU: what are the benefits?
  • EU Digital Markets Act and Digital Services Act
  • Five ways the European Parliament wants to protect online gamers
  • Artificial Intelligence Act

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