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Case Study – Methods, Examples and Guide

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Case Study Research

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

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

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

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

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

Multiple-Case Study

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

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

Exploratory Case Study

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

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

Descriptive Case Study

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

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

Instrumental Case Study

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

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

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

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

Observations

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

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

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

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

How to conduct Case Study Research

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

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

Examples of Case Study

Here are some examples of case study research:

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

Application of Case Study

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

Business and Management

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

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

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

Social Sciences

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

Law and Ethics

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

Purpose of Case Study

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

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

Case studies can also serve other purposes, including:

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

Advantages of Case Study Research

There are several advantages of case study research, including:

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

Limitations of Case Study Research

There are several limitations of case study research, including:

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

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What is case study research?

Last updated

8 February 2023

Reviewed by

Cathy Heath

Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

Analyze case study research

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  • What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

  • When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

  • What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

  • What are some case study examples?

What are the best approaches for introducing our product into the Kenyan market?

How does the change in marketing strategy aid in increasing the sales volumes of product Y?

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

Case study of the effects of a marketing strategy change on product Y sales volumes

Case study of X school teachers that encourage active student participation in the classroom

Case study of the effects of poverty on literacy levels in children

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Case Study | Definition, Examples & Methods

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

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

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

Table of contents

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

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

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

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

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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

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

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

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

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

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

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

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

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

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

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

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

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

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case studies new research

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

case studies new research

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

Research question

  • Conceptual framework
  • Conceptual vs. theoretical framework

Data collection

  • Qualitative research methods
  • Focus groups
  • Observational research

What is a case study?

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

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

Case studies

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

case studies new research

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

Definition of a case study

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

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

Characteristics of case studies

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

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

The role of case studies in research

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

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

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

What is the purpose of a case study?

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

Why use case studies in qualitative research?

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

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

The explanatory, exploratory, and descriptive roles of case studies

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

The impact of case studies on knowledge development

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

case studies new research

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

Types of case studies

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

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

Exploratory case studies

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

Descriptive case studies

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

Explanatory case studies

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

case studies new research

Intrinsic, instrumental, and collective case studies

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

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

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

Critical information systems research

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

Health research

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

case studies new research

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

Asthma research studies

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

Other fields

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

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

case studies new research

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

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

Propositions

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

Units of analysis

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

Argumentation

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

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

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

Defining the research question

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

Selecting and defining the case

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

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

Developing a detailed case study protocol

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

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

Collecting data

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

Analyzing and interpreting data

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

Writing the case study report

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

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

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

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

Observations

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

Documents and artifacts

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

case studies new research

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

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

Ensuring the quality of data collection

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

Data analysis

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

Organizing the data

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

Categorizing and coding the data

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

Identifying patterns and themes

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

Interpreting the data

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

Verification of the data

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

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

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

Benefits include the following:

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

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

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

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

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Writing a Case Study

Hands holding a world globe

What is a case study?

A Map of the world with hands holding a pen.

A Case study is: 

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

What are the different types of case studies?

Man and woman looking at a laptop

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

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

Who are your case study participants?

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What is triangulation ? 

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

Triangulation image with examples

How to write a Case Study?

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

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Definition and Introduction

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

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

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

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

How to Approach Writing a Case Analysis Paper

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

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

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

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

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

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

Structure and Writing Style

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

Introduction

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

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

Background Analysis

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

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

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

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

Identification of Problems

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

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

Alternative Solutions

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

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

Recommended Courses of Action

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

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

Ca se Study and Case Analysis Are Not the Same!

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

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

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

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

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a research strategy whose characteristics include

  • a focus on the interrelationships that constitute the context of a specific entity (such as an organization, event, phenomenon, or person),
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  • the explicit purpose of using those insights (of the interactions between contextual relationships and the entity in question) to generate theory and/or contribute to extant theory. 

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What is the value of working with case studies.

Professor Todd Landman explains how case studies can be used in research. He discusses the importance of choosing a case study correctly and warns about limitations of case study research.

This is just one segment in a series about case studies. You can find the rest of the series in our SAGE database, Research Methods:

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Case study research and causal inference

Judith green.

1 Wellcome Centre for Cultures & Environments of Health, University of Exeter, Exeter, UK

Benjamin Hanckel

2 Institute for Culture and Society, Western Sydney University, Sydney, Australia

Mark Petticrew

3 Department of Public Health, Environments & Society, London School of Hygiene & Tropical Medicine, London, UK

Sara Paparini

4 Wolfson Institute of Population Health, Queen Mary University of London, London, UK

5 Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK

Associated Data

Not applicable; no new data generated in this study.

For the purpose of open access, the author has applied a ‘Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising.

Case study methodology is widely used in health research, but has had a marginal role in evaluative studies, given it is often assumed that case studies offer little for making causal inferences. We undertook a narrative review of examples of case study research from public health and health services evaluations, with a focus on interventions addressing health inequalities. We identified five types of contribution these case studies made to evidence for causal relationships. These contributions relate to: (1) evidence about system actors’ own theories of causality; (2) demonstrative examples of causal relationships; (3) evidence about causal mechanisms; (4) evidence about the conditions under which causal mechanisms operate; and (5) inference about causality in complex systems. Case studies can and do contribute to understanding causal relationships. More transparency in the reporting of case studies would enhance their discoverability, and aid the development of a robust and pluralistic evidence base for public health and health services interventions. To strengthen the contribution that case studies make to that evidence base, researchers could: draw on wider methods from the political and social sciences, in particular on methods for robust analysis; carefully consider what population their case is a case ‘of’; and explicate the rationale used for making causal inferences.

Case study research is widely used in studies of context in public health and health services research to make sense of implementation and service delivery as enacted across complex systems. A recent meta-narrative review identified four broad, overlapping traditions in this body of work: developing and testing complex interventions; analysing change in organisations; undertaking realist evaluations; and studying complex change naturalistically [ 1 ]. Case studies can provide essential thick description of interventions, context and systems; qualitative understanding of the mechanisms of interventions; and evidence of how interventions are adapted in the ‘real’ world [ 2 , 3 ].

However, in evaluative health research, case study designs remain relegated to a minor, supporting role [ 4 , 5 ], typically at the bottom of evidence hierarchies. This relegation is largely due to assumptions that they offer little for making the kinds of causal claims that are essential to evaluating the effects of interventions. The strengths of deep, thick studies of specific cases are conventionally set against the benefits of ‘variable-based’ designs, with the former positioned as descriptive, exploratory or illustrative, and the latter as providing the strongest evidence for making causal claims about the links between interventions and outcomes. In conventional hierarchies of evidence, the primary evidence for making causal claims comes from randomised controlled trials (RCTs), in which the linear relationship between a change in one phenomenon and a later change in another can be delineated from other causal factors. The classic account of causality drawn on in epidemiology requires identifying that the relationship between two phenomena is characterised by co-variation; time order; a plausible relationship; and a lack of competing explanations [ 6 ]. The theoretical and pragmatic limitations of RCT designs for robust and generalizable evaluation of interventions in complex systems are now well-rehearsed [ 2 , 7 – 10 ]. In theory, though, random selection from a population to intervention exposure maximises ability to make causal claims: randomisation minimises risks of confounding, and enables both an unbiased estimate of the effect size of the intervention and extrapolation to the larger population [ 6 ]. Guidance for evaluations in which the intervention cannot be manipulated, such as in natural experiments, therefore typically focuses on methods for addressing threats to validity from non-random allocation in order to strengthen the credibility of probabilistic causal effect estimates [ 4 , 11 ].

This is, however, not the only kind of causal logic. Case study research typically draws on other logics for understanding causation and making causal inferences. We illustrate some of the contributions made by case studies, drawing on a narrative review of research relating to one particularly enduring and complex problem: inequalities in health. The causal chains linking interventions to equity outcomes are long and complex, with recognised limitations in the evidence base for ‘what works’ [ 12 ]. Case study research, we argue, has a critical role to play in making claims about whether, how and why interventions reduce, mitigate, or exacerbate inequalities. Our examples are drawn from a broader review of case study research [ 1 ] and supporting literature reviews [ 5 ], from which we focused on cases which had an explanatory aim, and which shed light on how interventions in public health or health services might reduce, create or sustain inequality. In this paper, we: i) outline some different kinds of evidence relevant to causal relationships that can be  derived from case study research; ii) outline what is needed for case study research to contribute to explanatory, as well as exploratory claims; and iii) advocate for greater clarity in reporting case study research to foster discoverability.

Cases and causes

There are considerable challenges in defining case study designs or approaches in ways that adequately delineate them from other research designs. Yin [ 13 ], for instance, one of the most highly cited source texts on case studies in health research [ 1 ], resists providing a definition, instead suggesting case study research is more a strategy for doing empirical research. Gerring [ 14 ] defines case study research as: “ an intensive study of a single unit for the purpose of understanding a larger class of (similar) units ” (p342, emphasis in original). This definition is useful in suggesting the basis for the inferences drawn from cases, and the need to consider the relationships between the ‘case’ (and phenomena observed within it) and the population from which it is drawn. Gerring notes that studies of single cases may have a greater “affinity” for descriptive aims, but that they can furnish “evidence for causal propositions” ( [ 14 ], p347). Case studies are, he suggests, more likely to be useful in elucidating deterministic causes: those conditions that are necessary and/or sufficient for an outcome, whereas variable based designs have advantages for demonstrating probabilistic causation, where the aim is to estimate the likelihood of two phenomena being causally related. Case studies provide evidence for the mechanisms of causal relationships (e.g. through process tracing, through observing two variables interacting in the real world) and corroboration of causal relationships (for instance, through pattern matching).

Gerring’s argument, drawing on political science examples, is that there is nothing epistemologically distinct about research using the case study: rather, it has particular affinities with certain styles of causal modelling. We take this as a point of departure to consider not whether case studies can furnish evidence to help with causal inference in health research, but rather how they have done this. From our examples on case study research on inequalities in health, we identify the kinds of claims that relate to causality that were made. We note that some relate to (1) Actors’ accounts of causality : that is, the theories of those studied about if, how and why interventions work. Other types of claim use various kinds of comparative analytic logic to elucidate evidence of causal relationships between phenomena. These claims include: (2) Demonstrations of causal relationships – in which evidence from one case is sufficient for identifying a plausible causal relationship; (3) Mechanisms – evidence of the mechanisms through which causal relationships work; (4) Conditions —evidence of the conditions under which such mechanisms operate; and (5) Complex causality —evidence for outcomes that arise from complex causality within a system. This list is neither mutually exclusive, nor exhaustive: many case studies aim to do several of these (and some more). It is also a pragmatic rather than theoretical list, focusing on the kinds of evidence claimed by researchers rather than the formal methodological underpinnings of causal claims (for a discussion of the latter, see Rohlfing [ 15 ]).

What kinds of causal evidence do case studies provide?

Actors’ accounts of causality.

This is perhaps the most common kind of evidence provided by case study research. Case studies, through in-depth research on the actors within systems, can generate evidence about how those actors themselves account for causal relationships between interventions and outcomes. This is an overt aim of many realist evaluation studies, which focus on real forces or processes that exist in the world that can provide insight into causal mechanisms for change.

Ford and colleagues [ 16 ], for example, used a series of five case studies of local health systems to explore socio-economic inequalities in unplanned hospital admission. Cases were selected on the basis of either narrowing or widening inequalities in admission, with a realist evaluation focused on delineating the context-mechanisms-outcome (CMO) configurations in each setting, to develop a broader theory of change for addressing inequalities. The case study approach used a mix of methods, including drawing on documentary data to assess the credibility of mechanisms proposed by health providers. The authors identified 17 distinct CMO configurations; and five factors that were related to trends for inequalities in emergency admissions, including health service factors (primary care workforce challenges, case finding and proactive case management) and those external to the health service (e.g., financial constraints on public services, residential gentrification). Ford and colleagues noted that none of the CMO configurations were clearly associated with improved or worsening trends in inequalities in admission.

Clearly, actors’ accounts of causality are not in themselves evidence of causality. Ford and colleagues noted that they interrogated accounts for plausibility (e.g. that interventions mentioned were prior to effects claimed) and triangulated these accounts with other sources of data, but that inability to empirically corroborate the hypothesized CMO links limited their ability to make claims about causal inference. This is crucial: actors in a system may be aware of the forces and processes shaping change but unaware of counterfactuals, and they are unlikely to have any privileged insight into whether factors are causal or simply co-occurring (see, for instance, Milton et. al. [ 17 ] on how commonly cited ‘barriers’ in accounts of not doing evaluations are also evident in actors’ accounts of doing successful evaluations). Over-interpretation of qualitative accounts of insiders’ claims about causal relationships as if they provide conclusive evidence of causal relationships is poor methodology.

This does not mean that actors’ accounts are not of value. First, in realist evaluation, as in Ford and colleagues’ study [ 16 ], these accounts provide the initial theories of change for thinking about the potential causal pathways in logic models of interventions. Second, insiders’ accounts of causality are part of the system that is being explained. An example comes from Mead and colleagues [ 18 ], who used a case study drawing largely on qualitative interviews to explore “how local actors from public health, and the wider workforce, make sense of and work on social inequalities in health” ( [ 18 ] p168). This used a case study of a partnership in northwest England to address an enduring challenge in inequalities policy: the tendency for policies that address upstream health determinants to transform, in practice, to focus more on behavioural and individual level factors . Local public health actors in the partnership recognised the structural causes of unequal health outcomes, yet discourses of policy action tended to focus only on the downstream, more individualising levels of health, and on personal choice and agency as targets for intervention. Professionals conceptualised action on inequality as relating only to the health of the poorest, rather than as a problem of a gradient in health outcomes across society. There was a geographical localism in their approach, which framed particular places as constellations of health and social problems. Drawing on theory from figurational sociology, Mead and colleagues note that actors’ own accounts are the starting point of an analysis, which then puts those accounts into play with theory about how such discourses are reproduced. The researchers suggest that partnership working itself exacerbated the individualising frameworks used to orient action, as it became a hegemonic framing, reducing the possibilities for partnerships to transform health inequalities. Here, then, a case study approach is used to shed light on the causes of a common failure in policies addressing inequalities. The authors take seriously the divergence of actors’ own accounts of causality and those of other sources, and analyse these as part of the system.

Finally, insider accounts should be taken seriously as contributing to evidence about causal inference through shedding light on the complex looping effects of theoretical models of causality and public accounts. For instance, Smith and Anderson [ 19 ], drawing on a meta-ethnographic literature review of ‘lay theorising’ about health inequalities, note that, counter to common assumptions, public understanding of the structural causes of health inequalities is sophisticated: but that it may be disavowed to avoid stigma and shame and to reassert some agency. This is an important finding for informing knowledge exchange, suggesting that further ‘awareness raising’ may be unnecessary for policy change, and counter-productive in needlessly increasing stigma and shame.

Demonstrations of causal relationships

When strategically sampled, and rooted in a sound theoretical framework, studies of single cases can provide evidence for generalizable causal inferences. The strongest examples are perhaps those that operate as ‘black swans’ for deterministic claims, in that one case may be all that is needed to show that a commonly held assumption is not generalizable. That is, a case study can demonstrate unequivocally that one phenomenon is not inevitably related to another. These can come from cases sampled because they are extreme or unusual. Prior’s [ 20 ] study of a single man in a psychiatric institution in Northern Ireland, for instance, showed that, counter to Goffman’s [ 21 ] original theory of how ‘total institutions’ lead to stigmatisation and depersonalisation, the effects of institutionalisation depended on context—in this case, how the institution related to the local community and the availability of alternative sources of self-worth available to residents.

Strategically sampled typical cases can also provide demonstrative evidence of causal relationships. To take the enduring health services challenge of inequalities in self-referral to emergency care, Hudgins and Rising’s [ 22 ] case study of a single patient is used to debunk a common assumption that high use of emergency care is related to inappropriate care-seeking by low-income patients. They look in detail at the case of “a 51-year-old low-income, recently insured, African American man in Philadelphia (USA) who had two recent ED [emergency department] visits for evaluation of frequent headaches and described fear of being at risk for a stroke.” ( [ 22 ] p50). Drawing on theories of structural violence and patient subjectivity, they use this single case to shed light on why emergency department use may appear inappropriate to providers. They analyse the interplay of gender roles, employment, and insurance status in generating competing drivers of health seeking, and point to the ways in which current policies deterring self-referral do not align well with micro- and macro-level determinants of service use. The study authors also note that because their methods generate data on ‘why’ as well ‘what’ people do, they can “lay the groundwork” ( [ 22 ], p54] for developing future interventions. Here, again, a single case is sufficient. In understanding the causal pathways that led to this patient’s use of emergency care, it is clear why policies addressing inequalities through deterring low-income users would be unlikely to work.

Mechanisms: how causal relationships operate

A strength of case study approaches compared with variable-based designs is furnishing evidence of how causal relationships operate, deriving from both direct observations of causal processes and from analysis of comparisons within and between cases. All cases contain multiple observations; variations can be observed over time and space, across or within cases [ 14 ]. Observing regularities, co-variation and deviant or surprising findings, and then using processes of analytic induction [ 23 ] or abductive logic [ 24 ] to derive, develop and test causal theories using observations from the case, can build a picture of causal pathways.

Process tracing is one formal qualitative methodology for doing this. Widely used in political and policy studies, but less in health evaluations [ 25 ], process tracing links outcomes with their causes, focusing on the mechanisms that link events on causal pathways, and on the strength of evidence for making connections on that causal chain. This requires sound theoretical knowledge (such that credible hypotheses can be developed), well described cases (ideally at different time points), observed causal processes (the activities that transfer causes to effects), and careful assessment of evidence against tests of varying strength for the necessity and sufficiency for accepting or rejecting a candidate hypothesis [ 26 , 27 ]. In health policy, process tracing methods have been combined to good effect with quantitative measures to examine casual processes leading to outcomes of interest. Campbell et. al. [ 28 ], for instance, used process tracing to look at four case studies of countries that had made progress towards universal health coverage (measured through routine data on maternal and neonatal health indicators), to identify key causal factors related to health care workforce.

An example of the use of process tracing in evaluation comes from Lohmann and colleagues’ [ 25 ] case study of a single country, Burkina Faso, to examine why performance based financing (PBF) fails to improve equity. PBF, coupled with interventions to improve health care take up among the poor, aims to improve health equity in low and middle-income countries, yet impact evaluations suggest that these benefits are typically not realised. This case study drew on data from the quantitative impact assessment; programme documentation; the intervention process evaluation; and primary qualitative research for the process tracing, in the light of the theory of change of the intervention. Lohmann and colleagues [ 25 ] identified that a number of conditions that would have been necessary for the intervention to work had not been met (such as eligible patients not receiving the card needed to access health care or providers not receiving timely reimbursement). A key finding was that although implementation challenges were a partial cause of policy failure, other causal conditions were external to the intervention, such as lack of attention to the non-health care costs incurred by the poorest to access care. Again, a single case, if there are good grounds for extrapolating to similar contexts (i.e., those in which transport is required to access health care), is enough to demonstrate a necessary part of the causal pathway between PBF and intended equity outcomes.

Conditions under which causal mechanisms operate

The example of ‘transport access’ as a necessary condition for PBF interventions to ‘work’ also illustrates a fourth type of causal evidence: that relating to the transferability of interventions. Transferable causal claims are essential for useful evidence: “(f)or policy and practice we do not need to know ‘it works somewhere’. We need evidence for ‘it-will-work-for-us’ claims: the treatment will produce the desired outcome in our situation as implemented there” ( [ 8 ] p1401). Some causal mechanisms operate widely (using a parachute will reduce injury from jumping from a plane; taking aspirin will relieve pain); others less so. In the context of health services and public health research, few interventions are likely to be widely generalizable, as the mechanisms will operate differently across contexts [ 7 ]. This context dependency is at the heart of realist evaluations, with the assumption that underlying causal mechanisms require particular contexts in order to operate, hence the focus on ‘how, where, and for whom’ interventions work [ 29 ]. Making useful claims therefore requires other kinds of evidence, relating to what Cartwright and Munro [ 30 ] call the ‘capacities’ of the intervention: what power it has to work reliably, what stops it working, what other conditions are needed for it to work. This evidence is critical for assessing whether an intervention is likely to work in a given context and to assess the intended and unintended consequences of intervention adoption and implementation. Cartwright and Munro’s recommendation is therefore to study causal powers rather than causes. That is, as well as interrogating whether the intervention ‘causes’ a particular outcome, it is also necessary to address the potential for and stability of that causal effect. To do that entails addressing a broader range of questions about the causal relationship, such as how the intervention operates in order to bring about changes in outcomes; what other conditions need to be present; what might constrain this effect; what other factors within the system also promote or constrain those effects; and what happens when different capacities interact? [ 30 ]. Case study research can be vital in providing this kind of evidence on the capacities of interventions [ 31 ].

One example is from Gibson and colleagues [ 32 ], who use within-case comparisons to shed light on why a ‘social prescribing’ intervention may have different effects across socioeconomic classes. These interventions, typically entailing link workers who connect people with complex health care needs to local services and resources, are often framed as a way to address enduring health inequalities. Drawing on sociological theory on how social class is reproduced through socially structured and unequal distribution of resources (‘capitals’), and through how these shape people’s practices and dispositions, Gibson and colleagues [ 32 ] explicate how capitals and dispositions shaped encounters with the intervention. Their analysis of similarities and differences within their case (of different clients) in the context of theory enables them to abstract inferences from the case. Drawing out the ways in which more advantaged clients mobilised capital in their pursuit of health, with dispositions more closely aligned to the intervention, they unravel classed differences in ability to benefit from the intervention, with less advantaged clients inevitably having ‘shorter horizons’ focused on day to day challenges: “This challenges the claim that social prescribing can reduce inequalities, instead suggesting it has the potential to exacerbate existing inequalities” ( [ 32 ], p6).

Case studies can shed light on the capacities of interventions to improve or exacerbate inequalities, including identifying unforeseen consequences. Hanckel and colleagues [ 33 , 34 ], for example, used a case study approach to explore implementation of a physical health intervention involving whole classes of children running for 15 min each day in the playground in schools in south London, UK. This documented considerable adaption of the intervention at the level of school, class and pupil, and identified different pathways through which the intervention might impact on inequalities. In terms of access, the intervention appeared to be equitable, in that there was no evidence of disproportionate roll out to schools with more affluent pupils or to those with fewer minority ethnic pupils [ 33 ]. However, identifying the ‘capacities’ of the intervention also identified other pathways through which it could have negative equity effects. The authors found that in practice, the intervention emphasised body weight rather than physical activity, and intervention roll-out reinforced class and ethnicity-based stigmatising discourses about lower income neighbourhoods [ 34 ].

Complex causality

There is increasing recognition that the systems that reproduce unequal health outcomes are complex: that is, that they consist of multiple interacting components that cannot be studied in isolation, and that change is likely to be non-linear, characterised by, for instance, phase shifts or feedback loops [ 35 ]. This has two rather different implications. First, case study designs can be particularly beneficial for taking a system perspective on interventions. Case studies enable a focus on aspects that are not well explicated through other designs, such as how context interacts with interventions within systems [ 7 ], or on how multiple conditional pathways might link interventions and outcomes [ 36 ]. Second, when causation is not linear, but ‘emergent’, in that it is not reducible to the accumulated changes at lower levels, evaluation designs focused on only one outcome at one level (such as weight loss in individuals) may fail to identify important effects. Case studies have an invaluable role here in unpacking and surfacing these effects at different levels within the systems within which interventions and services are delivered. One example is transport systems, which have been the focus of considerable public health interest to encourage more ‘active’ modes, in which more of the population walk or cycle, and fewer drive. However, more simplistic evaluations looking at one part of a causal chain (such as that between traffic calming interventions and local mode shift) may fail to appreciate how systems are dynamic, and that causation might be emergent. This is evident in a case study of transport policy impacts from Sheller [ 37 ], who takes the case of Philadelphia, USA, to reveal how this post-car trend has racialized effects that can exacerbate inequality. Weaving in data from participant observations, historical documentary sources and statistical evidence of declining car use, Sheller documents the racialized impacts of transport policies which may have reduced car use and encouraged active modes overall, but which have largely prioritised ‘young white’ mobility in the context of local gentrification and neglect of public transit.

One approach to synthesising evidence from multiple case studies to make claims about complex causation is Qualitative Comparative Analysis (QCA), which combines quantitative methods (based on Boolean algebra) with detailed qualitative understanding of a small to medium N sample of cases. This has strengths for identifying multiple pathways to outcomes, asymmetrical sets of conditions which lead to success or failure, or ‘conjunctural causation’, whereby some conditions are only causally linked to outcomes in relation to others [ 38 ]. There is growing interest in using these approaches in evaluative health studies [ 39 ]. One example relating to the effectiveness of interventions addressing inequalities in health comes from Blackman and colleagues [ 36 ], who explored configurations of conditions which did or did not lead to narrowing inequalities in teenage conception rates across a series of local areas as cases. This identified some surprising findings, including that ‘basic’ rather than good or exemplary standards of commissioning were associated with narrowing the equity gap, and that the proportion of minority ethnic people in the population was a key condition.

Not all case study research aims to contribute to causal inference, and neither should it [ 1 , 5 , 40 ]. However, it can. We have identified five ways in which case study evidence has contributed to causal explanations in relation to a particularly intractable challenge: inequalities in health. It is therefore time to stop claiming that case study designs have only a supporting role to play in evaluative health research. To develop a theoretical evidence base on ‘what works’, and how, in health services and public health, particularly around complex issues such as addressing unequal health outcomes, we need to draw on a greater range of evidential resources for informing decisions than is currently used. Best explanations are unlikely to be made from single studies based on one kind of causality, but instead will demand some kind of evidential pluralism [ 41 ]. That is, one single study, of any design, is unlikely to generate evidence for all links in complex causal chains between an intervention and health outcomes. We need a bricolage of evidence from a diverse range of designs [ 42 ] to make robust and credible cases for what will improve health and health equity. This will include evidence from case studies, both from single and small N studies, and from syntheses of findings from multiple cases.

Our focus on case studies that shed light on interventions for health inequalities identified the critical role that case studies can play in theorising, illuminating and making sense of: system actors’ own causal reasoning; whether there are causal links between intervention and outcome; what mechanism(s) might link them; when, where and for whom these causal relationships operate; and how unequal outcomes can be generated from the operation of complex systems. These examples draw on a range of different theoretical and methodological approaches, often from the wider political and social sciences. The approaches illustrated are rooted in very different, even incompatible, philosophical traditions: what researchers understand by ‘causality’ is diverse [ 43 ]. However, there are two commonalities across this diversity that suggest some conditions for producing good case studies that can generate evidence to support causal inferences. The first is the need for theoretically informed and comparative analysis. As Gerring [ 14 ] notes, causal inferences rely on comparisons – across units or time within a case, or between cases. It is comparison that drives the ability to make claims about the potential of interventions to produce change in outcomes of interest, and under what conditions. There are a range of approaches to qualitative data analysis, and choice of method has to be appropriate for the kinds of causal logics being explicated, and the availability of data on particular phenomena within the case. Typically, though, this will require analysis that goes beyond descriptive thematic analysis [ 31 ]. Approaches such as process tracing or analytic induction require both fine-grained and rigorous comparative analysis, and a sound theoretical underpinning that provides a framework for making credible inferences about the relationships between phenomena within the case and to the wider population from which the case is selected.

This leads to the second commonality: the need to clarify what the case is a case ‘of’, and how it relates to other candidate cases. What constitutes a ‘case’ is inevitably study specific. The examples we have drawn on include: PBF in a country [ 25 ], transport systems in a city [ 37 ], and a social prescribing intervention in primary care [ 32 ]. Clearly, in other contexts, each of these ‘cases’ could be sampling units within variable based studies (of financing systems, or countries; of infrastructures systems, or cities in a state; of particular kinds of service intervention, or primary care systems). Conversely, these cases could be populations within which lower level phenomena (districts, neighbourhoods, patients) are studied. What leads to appropriate generalisations about causal claims is a sound theorisation of the similarities and particularities of the case compared with other candidate cases: how Burkina Faso has commonalities with, or differences from, other settings in which PBF has failed to improve equity; or the contexts of gentrification and residential churn that make Philadelphia similar to other cities in the US; or the ways in which class-based dispositions and practices intersect with similar types of service provisions.

A critical question remains: How can well-conducted case study evidence be better integrated into the evidence base? Calls for greater recognition for case study designs within health research are hardly new: Flyvberg’s advocacy for a greater role for case studies in the social sciences [ 44 ] has now been cited around 20,000 times, and calls for methodological pluralism in health research go back decades [ 42 , 45 , 46 ]. Yet, case studies remain somewhat neglected, with ongoing misconceptions about their limited role, despite calls for evidence based medicine to incorporate evidence for mechanisms as complementary to evidence of correlation, rather than as inferior [ 47 ]. Even where the value of case studies for contributing to causal inference is recognised, searching for good evidence is not straightforward. Case studies are neither consistently defined nor necessarily well reported. Some of the examples in this paper do not use the term ‘case study’ in the title or abstract, although they meet our definition. Conversely, many small scale qualitative studies describe themselves as ‘case studies’, but focus on thick description rather than generalisability, and are not aiming to contribute to evaluative evidence. It is therefore challenging, currently, to undertake a more systematic review of empirical material. Forthcoming guidance on reporting case studies of context in complex systems aims to aid discoverability and transparency of reporting (Shaw S, et al: TRIPLE C Reporting Principles for Case study evaluations of the role of Context in Complex interventions, under review). This recommends including ‘case study’ in the title, clarifying how terms are used, and explicating the philosophical base of the study. To further advance the usefulness of case study evidence, we suggest that where an aim is to contribute to causal explanations, researchers should, in addition, specify their rationales for making causal inferences, and identify what broader class of phenomena their case is a case ‘of’.

Conclusions

Case study research can and does contribute to evidence for causal inferences. On challenging issues such as addressing health inequalities, we have shown how case studies provide more than detailed description of context or process. Contributions include: describing actors’ accounts of causal relationships; demonstrating theoretically plausible causal relationships; identifying mechanisms which link cause and effect; identifying the conditions under which causal relationships hold; and researching complex causation.

Acknowledgements

The research underpinning this paper was conducted as part of the Triple C study. We gratefully acknowledge the input of the wider study team, and that of the participants at a workshop held to discuss forthcoming guidance on reporting case study research.

Abbreviations

Authors’ contributions.

BH, JG and MP drafted the first version of the paper, which was revised with theoretical input from SS and SP. All authors contributed to the paper and have reviewed and approved the final manuscript.

The research was funded by the Medical Research Council (MR/S014632/1). JG is supported with funding from the Wellcome Trust (WT203109/Z/16/Z). Additional funding for SP and SS salaries over the course of the study was provided by the UK National Institute for Health Research Oxford Biomedical Research Centre (BRC-1215–20008), Wellcome Trust (WT104830MA; 221457/Z/20/Z) and the University of Oxford's Higher Education Innovation Fund.

The views and opinions expressed herein are those of the authors. Funding bodies had no input to the design of the study and collection, analysis, and interpretation of data or preparation of this paper.

Availability of data and materials

Declarations.

Not applicable.

The authors declare that they have no competing interests.

Publisher’s Note

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

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Case Study Research Method in Psychology

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

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Olivia Guy-Evans, MSc

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On This Page:

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

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

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

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

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

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

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

case study

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

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Doing Comparative Case Studies: New Designs and Directions

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Comparative Case Studies: New Designs and Directions extends the comparative case study methodology established by Bartlett and Vavrus and employed in many areas of social research, especially in education. This volume unites a diverse, international group of education scholars whose work exemplifies the affordances and constraints of the comparative case study (CCS) approach and offers new theoretical and empirical directions for researchers. In 11 engaging chapters, experts in comparative education, early childhood education, peace education, refugee education, special education, and teacher education discuss their use of the CCS approach to produce new ways of knowing and to address challenges of multi-scalar and multi-sited research. The first section, Conceptualizing Cases and Case Selection, emphasizes the importance of carefully selecting cases during different phases of research while continuously reflecting on how these choices influence the findings. The second section, Balancing Specificity and Generalizability, addresses the challenge of balancing the need for rich, deep data while including multiple sites. The third section, Enabling Processual Analysis across Sites and Scales, demonstrates the fit between the CCS approach and qualitative research that unfolds over time and space. Addressing the Transversal Axis, the fourth section, showcases research with a strong temporal dimension. The final section, New Directions, suggests inspiring and innovative methods. Offering rich methodological examples and provocative discussion questions, this volume will appeal to undergraduate and graduate students in education and research design courses, and to scholars and policymakers in diverse fields seeking to design studies of complex phenomena at different sites and scales.

Bibliographical note

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Y1 - 2022/1/1

N2 - Comparative Case Studies: New Designs and Directions extends the comparative case study methodology established by Bartlett and Vavrus and employed in many areas of social research, especially in education. This volume unites a diverse, international group of education scholars whose work exemplifies the affordances and constraints of the comparative case study (CCS) approach and offers new theoretical and empirical directions for researchers. In 11 engaging chapters, experts in comparative education, early childhood education, peace education, refugee education, special education, and teacher education discuss their use of the CCS approach to produce new ways of knowing and to address challenges of multi-scalar and multi-sited research. The first section, Conceptualizing Cases and Case Selection, emphasizes the importance of carefully selecting cases during different phases of research while continuously reflecting on how these choices influence the findings. The second section, Balancing Specificity and Generalizability, addresses the challenge of balancing the need for rich, deep data while including multiple sites. The third section, Enabling Processual Analysis across Sites and Scales, demonstrates the fit between the CCS approach and qualitative research that unfolds over time and space. Addressing the Transversal Axis, the fourth section, showcases research with a strong temporal dimension. The final section, New Directions, suggests inspiring and innovative methods. Offering rich methodological examples and provocative discussion questions, this volume will appeal to undergraduate and graduate students in education and research design courses, and to scholars and policymakers in diverse fields seeking to design studies of complex phenomena at different sites and scales.

AB - Comparative Case Studies: New Designs and Directions extends the comparative case study methodology established by Bartlett and Vavrus and employed in many areas of social research, especially in education. This volume unites a diverse, international group of education scholars whose work exemplifies the affordances and constraints of the comparative case study (CCS) approach and offers new theoretical and empirical directions for researchers. In 11 engaging chapters, experts in comparative education, early childhood education, peace education, refugee education, special education, and teacher education discuss their use of the CCS approach to produce new ways of knowing and to address challenges of multi-scalar and multi-sited research. The first section, Conceptualizing Cases and Case Selection, emphasizes the importance of carefully selecting cases during different phases of research while continuously reflecting on how these choices influence the findings. The second section, Balancing Specificity and Generalizability, addresses the challenge of balancing the need for rich, deep data while including multiple sites. The third section, Enabling Processual Analysis across Sites and Scales, demonstrates the fit between the CCS approach and qualitative research that unfolds over time and space. Addressing the Transversal Axis, the fourth section, showcases research with a strong temporal dimension. The final section, New Directions, suggests inspiring and innovative methods. Offering rich methodological examples and provocative discussion questions, this volume will appeal to undergraduate and graduate students in education and research design courses, and to scholars and policymakers in diverse fields seeking to design studies of complex phenomena at different sites and scales.

UR - http://www.scopus.com/inward/record.url?scp=85141458166&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85141458166&partnerID=8YFLogxK

U2 - 10.4324/9781003216551

DO - 10.4324/9781003216551

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BT - Doing Comparative Case Studies

PB - Taylor and Francis

Hertz CEO Kathryn Marinello with CFO Jamere Jackson and other members of the executive team in 2017

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

  • Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
  • Fifty four percent of raw case users came from outside the U.S..
  • The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
  • Twenty-six of the cases in the list are raw cases.
  • A third of the cases feature a woman protagonist.
  • Orders for Yale SOM case studies increased by almost 50% compared to 2020.
  • The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

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Perspective

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The Daily

New research from Case Western Reserve University aims to block tumor growth in colorectal cancer patients

School of medicine awarded five-year, $1.84m grant from national institutes of health’s national cancer institute.

Researchers at  Case Western Reserve University’s School of Medicine  believe they have found information that could lead to developing new treatment options for people with metastatic colorectal cancer.

With a new five-year, $1.84 million grant from the  National Cancer Institute of the National Institutes of Health , they hope to take a step closer by studying how a protein (LRG1) involved in colorectal cancer growth functions.

“The goal of this research is to identify the precise drivers of cancer cell proliferation and survival, specifically in metastatic colorectal cancer,” said  Rui Wang , an assistant professor in the  School of Medicine’s Department of Surgery and the study’s lead researcher.  “By understanding these mechanisms, we hope to develop new therapies that can block tumor growth and improve outcomes for patients.”

case studies new research

The liver is the main organ where colorectal cancer cells proliferate. Clinical studies show patients with liver metastases from pancreatic, colon and other cancers don’t respond to medication as well as those without liver growth.

LRG1 is extensively dispersed throughout very small, specific areas of many cancers and contributes to vascular dysfunction. Wang recently discovered that, when secreted from the liver, the protein promotes colon cancer-cell growth. But researchers don’t know why.

According to Wang, his lab is working to find out why patients who have liver growth do not fare as well as those who do not. The lab has already made progress in understanding how the liver fosters the growth of cancer cells.

“Our research involves using an antibody to block communications between the liver and colon cancer cells,” Wang said. “In experimental models, preliminary data suggests that this approach could effectively block the growth of metastatic tumors, which would be encouraging for those afflicted with this terrible disease.

For more information, please contact Patty Zamora at [email protected] .

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Red briefing graphic

Resolving Workforce Skills Gaps with AI-Powered Insights

Ongoing digital transformation requires a workforce that is proficient in a wide variety of new skills. This briefing explores the use of AI in quantifying such proficiency, through a process known as skills inference. We introduce this concept by means of a case study of Johnson & Johnson, showing how skills inference can provide detailed insight into workforce skills gaps and thereby guide employees’ career development and leaders’ strategic workforce planning.

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Author Nick van der Meulen reads this research briefing as part of our audio edition of the series. Follow the series on SoundCloud.

DOWNLOAD THE TRANSCRIPT

Digital transformation is a continuous journey, with new technologies emerging on an ongoing basis. Yet for organizations to harness these technologies, their workforce needs to develop an increasingly expanding variety of skills. Many organizations struggle here: leaders responding to a 2022 MIT CISR survey[foot]MIT CISR 2022 Decision Rights for the Digital Era Survey (N=342).[/foot] estimated that on average 38 percent of their organization’s workforce required fundamental retraining or replacement within three years to address workforce skills gaps.[foot]Workforce skills gaps are the discrepancy between the collective skills proficiency that an organization requires to achieve its strategic objectives and the current skills proficiency of its workforce.[/foot]

To make evidence-based decisions on how to best resolve such skills gaps, however, organizations first need to move beyond estimates. What’s required is precise insight into their workforce’s current skills and how proficiency in these skills differs from that needed for future success. Functional competency models often fall short in this regard, as they need to be validated for each job and thus can’t keep pace with rapid technological change. Relying on employee or manager feedback from interviews and surveys may lead to inaccuracies because of inherent biases. And active assessment of an entire workforce across a wide range of skills is both impractical and costly.

Artificial intelligence (AI) offers a new and scalable alternative to such approaches by enabling skills inference , which we define as the process of analyzing employee data to quantify skills proficiency. This allows for detailed insight into workforce skills gaps, which can, for instance, be broken down by line of business and geography. In this briefing we explore the AI-powered skills inference process, and illustrate how resulting insights can help resolve workforce skills gaps by drawing on lessons learned from a case study of global healthcare company Johnson & Johnson (J&J).

Digital Talent Transformation at J&J

J&J’s mission is to profoundly impact health for humanity. As the trajectory of health and wellbeing is increasingly determined by emerging technology and a growth in data and computing power, J&J’s Technology group has become a cornerstone for the organization’s future success. It drives technological innovation at J&J and modernizes the organization’s tech ecosystem. More importantly, however, the Technology group is enabling J&J to evolve as a digital organization by helping to develop the digital acumen of its global workforce of over 130,000 employees.[foot]This case study of J&J draws from N. van der Meulen, O. Tona, I. A. Someh, B. H. Wixom, and D. E. Leidner, “Developing a Digital-First Workforce: AI-Driven Skills Enablement at Johnson & Johnson,” MIT CISR Working Paper No. 461, November 2023, https://cisr.mit.edu/publication/MIT_CISRwp461_JohnsonandJohnsonAIDrivenSkills_VanderMeulenTonaSomehWixomLeidner .[/foot]

To build a digital organization, you’ve got to take people’s amazing talents and create an “ and ” strategy for technology. To be relevant and future ready, you for instance need to have your commercial expertise and digital expertise. Scientific expertise and digital. You can have the best technology, but without that integrated way of thinking, it won’t transform anything.

Jim Swanson, Executive Vice President and Chief Information Officer, Johnson & Johnson

In early 2020, J&J’s Technology group began its journey of building the organization’s digital acumen with the help of AI-powered skills inference, starting with its own workforce of 4,000 technologists. By the time the group introduced skills inference to other parts of J&J in 2021, it had successfully put in place a three-step process, as illustrated in figure 1. First, it created a skills taxonomy , defining what skills would be required across the organization to reimagine business processes and develop future digital offerings. Second, the group gathered skills evidence by selecting and preparing employee data sources to analyze. And third, it conducted a passive skills assessment , for which it trained a machine learning model to measure the skills proficiencies of each employee. The result was workforce insights that guided employees’ personal development and enhanced leaders’ strategic workforce planning, both of which reduced skills gaps at J&J.[foot]J&J used skills insights only as a guide for employees’ own development; the insights did not factor into employees’ performance reviews. The organization used deidentified insights at an aggregate level to support strategic workforce planning.[/foot]

Figure 1: The Three Steps of the Skills Inference Process

Figure 1: The Three Steps of the Skills Inference Process

Skills inference involves (1) defining a taxonomy of skills required to realize your organization’s purpose and strategic objectives, (2) gathering employee data as evidence of these skills, and (3) conducting an assessment of this evidence to quantify employees’ skill proficiency.

Defining a Skills Taxonomy

The journey of J&J’s Technology group began with figuring out what future skills J&J would need. Guided by industry benchmarks, its Digital Talent team—a team dedicated to driving the organization’s transformation with the best and most diverse talent—examined strategic plans throughout the organization to create a J&J-specific skills taxonomy. This taxonomy comprised a list of forty-one skills the team referred to as “future ready” (e.g., master data management, robotic process automation) grouped into eleven capabilities (e.g., “Scientific & Digital Health Technology”) that would be required to realize the organization’s purpose and strategic objectives.

To ensure the taxonomy’s accuracy and gain broad support for it, the Digital Talent team asked over one hundred senior leaders from across the company to validate the list. Each indicated whether the taxonomy reflected the needs of their area of business—both at that moment and in the long term—and offered their perception of the current and required state of the listed skills. Given the diversity of J&J’s operations, required proficiency levels naturally varied by functional area. For instance, employees in Innovative Medicine might need stronger capabilities in data engineering and analytics, whereas those in MedTech might need to be especially skilled in software engineering.

Additional tailoring of the taxonomy’s skill and proficiency definitions to J&J’s unique context and terminology fell to subject matter experts (SMEs), employees known for their expertise and thought leadership in a particular future-ready skill. These SMEs crafted current, precise, and yet broadly applicable definitions that novices and experts alike could understand. The result was a skills taxonomy that clearly communicated to every employee what future-ready skills were considered top priorities for J&J’s leadership. Moreover, the taxonomy specified how skills would manifest in employees’ data.

Gathering Skills Evidence

As a machine learning algorithm can only learn from provided data, the quality of chosen data sources is key to the overall skills inference process. As such, the Digital Talent team collaborated with HR data experts to identify data sources that were used across most of the organization yet also provided enough semantic data to calculate skill proficiency, ideally providing evidence for 60 to 70 percent of each employee’s skills. Four of J&J’s data sources fit these criteria: the organization’s HR information system, recruiting database, and learning management system, and one of its project management platforms.

To improve data quality, leaders encouraged employees to update the data fields in those systems that the algorithm would use to infer their skill proficiency. For instance, J&J’s HR information system allowed employees to showcase their experiences and accomplishments by sharing information about their job history, education, certifications, recognitions, goals, personal interests, and volunteering activities. If these fields were missing or incomplete, the algorithm could not infer from them. The Digital Talent team therefore also illustrated how employees could update their data most effectively by providing examples of rich statements that the algorithm could pick up on in gradations of good, better, and best quality.

For employees to be willing to provide additional data for the AI to infer from, however, they first had to trust the skills inference initiative and the intended purpose of the AI model. In accordance with J&J’s commitment to the transparent use of AI, the Digital Talent team and senior leaders communicated early and often with employees—both electronically and in person. They explained how the skills inference process could help employees identify their current skills proficiency and discover new development opportunities. They also gave them the option to opt out at any time. In addition, the Digital Talent team enhanced employee trust and engagement by establishing strict norms of acceptable data use with the help of HR data experts, multiple oversight functions at J&J, and external partners. These norms safeguarded compliance, but also respected employee privacy and reduced the risk of bias by maximizing accountability, explainability, fairness, privacy, and transparency regarding the skills inference process.

Conducting a Skills Assessment

To measure employees’ skills proficiency, the Digital Talent team relied on a proven machine learning model augmented by human input. An experienced solution provider supported the team and provided the model, which used natural language processing to generate proficiency scores for each of the forty-one future-ready skills in J&J’s taxonomy.[foot]Looking ahead, the Digital Talent team is now exploring whether generative AI can further enhance the skills inference process at J&J.[/foot] These scores ranged from zero (no skill detected) to five (thought leadership).

To improve the accuracy and reliability of the inferred scores, the Digital Talent team asked employees to self-assess their skills proficiency and managers to evaluate that of their direct reports. To avoid bias, the solution showed the proficiency scores inferred by the AI only after the participants submitted their perceptions of proficiency levels. With this input, the model generated an “agreement score” that quantified the consistency between the perceived levels and inferred scores. The goal was not to achieve perfect agreement, but rather directional accuracy: the Digital Talent team considered the inferred scores usable if they deviated by at most one point (out of five) from the perceived proficiency levels.

Limit Use Cases for Workforce Insights

Skill proficiency data has many potential uses. Yet, for employees to trust the skills inference process and not opt out of it or otherwise skew the data, it is important to limit what this data is used for. J&J therefore only used skills inference to provide more personalized career development journeys for employees, and (at an aggregate level) to support leaders’ strategic workforce planning efforts. Other use cases were not permitted by J&J’s Privacy function.

With a detailed understanding of their skills proficiency, employees could chart personalized career paths, supported by learning and development opportunities uniquely tailored to their skill proficiency levels. After the first round of skills inference, J&J saw a 20 percent uptick in participants’ voluntary learning activities. These activities not only enhanced practical expertise but also fostered habits of continuous learning and increased knowledge sharing within the organization. In subsequent years, these habits of continuous learning have only become more ingrained, as demonstrated by strong adoption of J&J Learn, the organization’s global, AI-powered learning and development ecosystem that offers training programs, growth assignments, and mentoring opportunities. By March 2024, over 90 percent of employees in J&J’s Technology group had accessed J&J Learn.

Leaders used an executive dashboard to gauge aggregated employee skills proficiency, with insights broken down by geographic region and line of business. This dashboard, displayed as a heat map, resulted in more informed hiring processes, enhanced retention efforts, and improved talent movement and advancement across J&J. The executive committee used a scorecard to track key performance indicators related to these outcomes, while each operating company and supporting function devised its own metrics based on its strategic plans and the capabilities it had to develop.

Skills Inference: People + Technology = Workforce Insights

Resolving skills gaps no longer falls to human resources or learning and development functions alone. Instead, it has become a strategic imperative, reshaping organizational capabilities based on workforce insights. AI emerged as a powerful tool in this endeavor, enabling skills inference at a scale previously unimaginable. However, the success of this process hinges on more than just advanced technologies. It continuously requires collective effort, trust, and support of stakeholders—including employees—across many organizational levels and functions. Just as digital transformation is an ongoing journey, so too is the need to regularly (re)define the skills taxonomy, gather new skills evidence, and conduct skills assessments as required skills evolve.

For those looking to embark on their own skills inference journey today, we suggest you first focus on these inherently human success factors. Begin by generating employee support with a bounded use case that embraces your workforce’s potential and signals a commitment to developing employee skills. Then gather broad input from experts to declare your desired workforce capabilities in the form of a skills taxonomy that is aligned with your purpose and strategic objectives. That way, your employees can focus their development efforts while simultaneously providing more informed input for an eventual AI to process. Start by laying this groundwork today, so that your organization may reap the rewards of AI-powered workforce insights in the future.

© 2024 MIT Center for Information Systems Research, van der Meulen, Tona, and Leidner. MIT CISR Research Briefings are published monthly to update the center’s member organizations on current research projects.

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About the Researchers

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Nick van der Meulen, Research Scientist, MIT Center for Information Systems Research (CISR)

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Olgerta Tona, Lecturer, University of Gothenburg and Academic Research Fellow, MIT CISR

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Dorothy E. Leidner, Professor, University of Virginia and Academic Research Fellow, MIT CISR

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New EY US Consulting study: employees overwhelmingly expect empathy in the workplace, but many say it feels disingenuous

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The majority (86%) of employees believe empathetic leadership boosts morale while 87% of employees say empathy is essential to fostering an inclusive environment.

As many employees face downsizings, restructurings and a looming global recession, most say that empathic leadership is a desired attribute but feel it can be disingenuous when not paired with action, according to the 2023 Ernst & Young LLP ( EY US )  Empathy in Business Survey .

The study of more than 1,000 employed US workers examines how empathy affects leaders, employees, and operations in the workplace. The survey follows the initial EY Consulting analysis of empathy in 2021 and finds workers feel that mutual empathy between company leaders and employees leads to increased efficiency (88%), creativity (87%), job satisfaction (87%), idea sharing (86%), innovation (85%) and even company revenue (83%).

“A  transformation’s success  or failure is rooted in human emotions, and this research spotlights just how critical empathy is in leadership,” said  Raj Sharma , EY  Americas Consulting  Vice Chair. “Recent years taught us that leading with empathy is a soft and powerful trait that helps empower employers and employees to collaborate better, and ultimately create a culture of accountability.”

The evolving state of empathy in the workplace

There are many upsides to empathetic leadership in the workplace, including:

  • Inspiring positive change within the workplace (87%)
  • Mutual respect between employees and leaders (87%)
  • Increased productivity among employees (85%)
  • Reduced employee turnover (78%)

“Time and again we have found through our research that in order for businesses to successfully transform, they must put humans at the center with empathetic leadership to create transparency and provide employees with psychological safety,” said  Kim Billeter , EY Americas  People Advisory Services  Leader. “Empathy is a powerful force that must be embedded organically into every aspect of an organization, otherwise the inconsistency has a dramatic impact on the overall culture and authenticity of an organization.”

In fact, half (52%) of employees currently believe their company’s efforts to be empathetic toward employees are dishonest ― up from 46% in 2021, and employees increasingly report a lack of follow-through when it comes to company promises (47% compared to 42% in 2021).

To fulfill the authenticity equation, previous EY research indicates offering flexibility is essential. In the 2022 EY US Generation Survey, 92% of employees surveyed across all four workplace generations said that company culture has an impact on their decision to remain with their current  employer.

Lead with empathy  now  to combat the workplace challenges ahead

While leaders may experience lower employee attrition rates now when compared to the Great Resignation, a resurgence is brewing. Many economists expect a soft landing from the looming recession and with it may come turnover, particularly if employees already feel disconnected from their employer or from each other.

In fact, failing to feel a sense of belonging at work or connection with coworkers is a growing reason why employees quit their jobs. About half (50% and 48% in 2021) left a previous job because they didn’t feel like they belonged, and more employees now say they left a previous job because they had difficulty connecting with colleagues (42% vs. 37% in 2021).

“What happens outside of work has a direct impact on how people show up. It’s no longer enough for leaders to think of a person in one dimension – as an employee or as a professional within the organization,” said  Ginnie Carlier , EY Americas Vice Chair – Talent. “Leading with empathy helps move from the transactional and to the transformational Human Value Proposition, where people feel supported both personally and professionally.”

2023 EY Empathy in Business Survey methodology

EY US  commissioned a third-party vendor to conduct the 2023 EY Empathy in Business Survey, following the 2021 Empathy in Business Survey. The survey among 1,012 Americans who are employed, either full-time or part-time, was completed between October 23 and November 6, 2022. At the total level, the study has a margin of error of +/- 3 percentage points at the 95% confidence level.

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Striking findings from 2023

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Pew Research Center has gathered data around some of this year’s defining news stories, from the rise of artificial intelligence to the debate over affirmative action in college admissions . Here’s a look back at 2023 through some of our most striking research findings.

These findings only scratch the surface of the Center’s research from this past year .

A record-high share of 40-year-olds in the U.S. have never been married, according to a Center analysis of the most recent U.S. Census Bureau data . As of 2021, a quarter of 40-year-olds had never been married – up from 6% in 1980.

A line chart showing the share of 40-year-olds who have never been married from 1900 to 2021 by decade. The highest level is 2021, when 25% were never married. The prior high point was 1910, when 16% of 40-year-olds had never married. The share never married declines through the 20th century and reaches its lowest point in 1980, when 6% of 40-year-olds had never been married.

In 2021, the demographic groups most likely not to have ever been married by age 40 include men, Black Americans and those without a four-year college degree.

A Center survey conducted in April found that relatively few Americans see marriage as essential for people to live a fulfilling life compared with factors like job satisfaction and friendship. While majorities say that having a job or career they enjoy (71%) and having close friends (61%) are extremely or very important for living a fulfilling life, far fewer say this about having children (26%) or being married (23%). Larger shares, in fact, say having children (42%) or being married (44%) are not too or not at all important.

About half of Americans say the increased use of artificial intelligence in daily life makes them feel more concerned than excited – up 14 percentage points from last year, according to an August survey . Overall, 52% of Americans say they feel this way, an increase from 38% in December 2022.

Just 10% of adults say they are more excited than concerned about the increased use of AI, while 36% say they feel an equal mix of these emotions.

A bar chart showing that concern about artificial intelligence in daily life far outweighs excitement.

The rise in concern about AI has taken place alongside growing public awareness of the technology. Nine-in-ten adults say they have heard either a lot (33%) or a little (56%) about artificial intelligence. The share of those who have heard  a lot  is up 7 points since December 2022.

For the first time in over 30 years of public opinion polling, Americans’ views of the U.S. Supreme Court are more negative than positive, a July survey found . A narrow majority (54%) have an unfavorable view of the high court, while fewer than half (44%) express a favorable one.

A line chart showing that favorable views of Supreme Court at lowest point in more than three decades of public opinion polling.

The court’s favorable rating has declined 26 percentage points since 2020, following a series of high-profile rulings on issues including affirmative action in college admissions, LGBTQ+ rights and student loans. The drop in favorability is primarily due to a decline among Democrats and Democratic-leaning independents, just 24% of whom express a favorable opinion of the court.

A growing share of U.S. adults say the federal government should take steps to restrict false information online, even if it limits freedom of information, a June survey found . The share of U.S. adults with this view has risen from 39% in 2018 to 55% in 2023.

In the most recent survey, 42% of adults took the opposite view, saying the government should protect freedom of information, even if it means false information can be published.

Still, Americans remain more likely to say that tech companies – rather than the U.S. government – should be responsible for restricting false information online. About two-thirds (65%) said this in June.

A bar chart showing that support for the U.S. government and tech companies restricting false information online has risen steadily in recent years.

The number of U.S. children and teens killed by gunfire rose 50% in just two years, according to a 2023 analysis of data from the Centers for Disease Control and Prevention (CDC). In 2019, there were 1,732 gun deaths among U.S. children and teens under 18. By 2021, that figure had increased to 2,590.

The gun death  rate  among children and teens – a measure that adjusts for changes in the nation’s population – rose 46% during that span.

A chart that shows a 50% increase in gun deaths among U.S. kids between 2019 and 2021.

Both the number and rate of children and teens killed by gunfire in 2021 were the highest since at least 1999, the earliest year for which this information is available in the CDC’s mortality database.

Most Asian Americans view their ancestral homelands favorably – but not Chinese Americans, according to a multilingual, nationally representative survey of Asian American adults .

A dot plot showing that most Asian American adults have positive views of the homelands of their ancestors. Taiwanese, Japanese, Korean, Indian, Filipino and Vietnamese adults have majority favorable views of their ancestral homelands. Only 41% of Chinese American adults have a favorable view of China.

Only about four-in-ten Chinese Americans (41%) have a favorable opinion of China, while 35% have an unfavorable one. Another 22% say they have a neither favorable nor unfavorable view. This stands in contrast to how other Asian Americans view their ancestral homelands. For instance, about nine-in-ten Taiwanese and Japanese Americans have a very or somewhat favorable opinion of their place of origin, as do large majorities of Korean, Indian and Filipino Americans.

While Chinese Americans’ views of China are more mixed, they still have a more favorable opinion of the country than other Asian adults do. Just 14% of other Asian Americans view China favorably.

Even before the Israel-Hamas war, Israelis had grown more skeptical of a two-state solution. In a survey conducted in March and April , prior to the war, just 35% of Israelis thought “a way can be found for Israel and an independent Palestinian state to coexist peacefully.” This share had declined by 9 percentage points since 2017 and 15 points since 2013.

A line chart showing that fewer Israelis now believe that Israel and an independent Palestine can coexist peacefully.

Among both Arabs and Jews living in Israel, there have been declines over the past decade in the share of people who believe that a peaceful coexistence between Israel and an independent Palestinian state is possible.

A majority of Americans say they would tip 15% or less for an average restaurant dining experience, including 2% who wouldn’t leave a tip at all, an August survey shows . The survey presented respondents with a hypothetical scenario in which they went to a sit-down restaurant and had average – but not exceptional – food and service. About six-in-ten (57%) say they would leave a tip of 15% or less in this situation. Another 12% say they would leave a tip of 18%, and a quarter of people say they’d tip 20% or more.

Adults in lower-income households and those ages 65 and older are more likely than their counterparts to say they would tip 15% or less in a situation like this.

Bar chart showing that a 57% majority of U.S. adults say they would tip 15% or less for an average meal at a sit-down restaurant.

Partisan views of Twitter – the social media platform now called X – have shifted over the last two years, with Republican users’ views of the site growing more positive and those of Democratic users becoming more negative, according to a March survey . The share of Republican and GOP-leaning users who said the site is mostly bad for American democracy fell from 60% in 2021 to 21% earlier this year. At the same time, the share of Republican users who said the site is mostly good for democracy rose from 17% to 43% during the same span.

Democrats’ views moved in the opposite direction during that time frame. The percentage of Democratic and Democratic-leaning Twitter users who said the platform is good for American democracy decreased from 47% to 24%, while the share who said it is bad for democracy increased – though more modestly – from 28% to 35%.

These changes in views follow Elon Musk’s takeover of the platform in fall 2022.

A collection of charts showing a partisan divide over whether misinformation, harassment and civility are major problems on Twitter.

Nearly half of U.S. workers who get paid time off don’t take all the time off their employer offers, according to a February survey of employed Americans . Among those who say their employer offers paid time off for vacation, doctors’ appointments or to deal with minor illnesses, 46% say they take less time off than they are allowed. A similar share (48%) say they typically take all the time off they are offered.

Among those who don’t take all their paid time off, the most common reasons cited are not feeling the need to take more time off (52% say this), worrying they might fall behind at work (49%), and feeling badly about their co-workers taking on additional work (43%).

Bar chart showing more than four-in-ten workers who get paid time off say they take less time off than their employer allows

Smaller shares cite other concerns, including the feeling that taking more time off might hurt their chances for job advancement (19%) or that they might risk losing their job (16%). Some 12% say their manager or supervisor discourages them from taking time off.

An overwhelming majority of Americans (79%) express a negative sentiment when asked to describe politics in the United States these days, a July survey found . Just 2% offer a positive word or phrase, while 10% say something neutral.

Among those who volunteered an answer, 8% use the word “ divisive” or variations of it, while 2% cite the related term “polarized.” “Corrupt” is the second-most frequent answer, given by 6% of respondents.

The top 15 most cited words also include “messy,” “chaos,” “broken” and “dysfunctional.” Many respondents are even more negative in their views: “terrible,” “disgusting,” “disgrace” and the phrase “dumpster fire” are each offered by at least 1% of respondents.

Chart shows ‘Divisive,’ ‘corrupt,’ ‘messy’ among the words used most frequently to describe U.S. politics today

Around half of Americans (53%) say they have ever been visited by a dead family member in a dream or in another form, according to a spring survey . Overall, 46% of Americans report that they’ve been visited by a dead family member in a dream, while 31% report having been visited by dead relatives in some other form.

A bar chart that shows 6 in 10 members of the historically Black Protestant tradition say they've been visited by a dead relative in a dream.

Women are more likely than men to report these experiences.

While the survey asked whether people have had interactions with dead relatives, it did not ask for explanations. So, we don’t know whether people view these experiences as mysterious or supernatural, whether they see them as having natural or scientific causes, or some of both.

For example, the survey did not ask what respondents meant when they said they had been visited in a dream by a dead relative. Some might have meant that relatives were trying to send them messages or information from beyond the grave. Others might have had something more commonplace in mind, such as dreaming about a favorite memory of a family member.

More Americans disapprove than approve of selective colleges and universities taking race and ethnicity into account when making admissions decisions, according to another spring survey , fielded before the Supreme Court ruled on the practice in June. Half of U.S. adults disapprove of colleges considering race and ethnicity to increase diversity at the schools, while a third approve and 16% are not sure.

A diverging bar chart showing that half of U.S. adults disapprove of selective colleges considering race and ethnicity in admissions decisions, while a third approve.

Views differ widely by party, as well as by race and ethnicity. Around three-quarters of Republicans and Republican leaners (74%) disapprove of the practice, while 54% of Democrats and Democratic leaners approve of it.

Nearly half of Black Americans (47%) say they approve of colleges and universities considering race and ethnicity in admissions, while smaller shares of Hispanic (39%), Asian (37%) and White (29%) Americans say the same.

The share of Americans who say science has had a mostly positive effect on society has declined since 2019, before the coronavirus outbreak, a fall survey shows : 57% say science has had a mostly positive effect on society, down from 73% in 2019.

About a third of adults (34%) now say the impact of science on society has been equally positive and negative. And 8% say science has had a mostly negative impact on society.

Chart shows Fewer Americans now say science has had a mostly positive effect on society

Democrats have become much more likely than Republicans to say science has had a mostly positive impact on society (69% vs. 47%). This gap is the result of steeper declines in positive ratings among Republicans than among Democrats since 2019 (down 23 points and 8 points, respectively).

Nearly three-in-ten Americans express an unfavorable opinion of both major political parties – the highest share in at least three decades, according to a July survey . Overall, 28% of Americans have an unfavorable opinion of both the Republican and Democratic parties. This is more than quadruple the share in 1994, when just 6% of Americans viewed both parties negatively.

Chart shows Since the mid-1990s, the share of Americans with unfavorable views of both parties has more than quadrupled

A majority of Americans say TikTok is a threat to national security, according to a survey conducted in May . About six-in-ten adults (59%) see the social media platform as a major or minor threat to national security in the United States. Just 17% say it is  not  a threat to national security and another 23% aren’t sure.

A bar chart showing that a majority of Americans say TikTok is a national security threat, but this varies by party, ideology and age.

Views vary by partisanship and age. Seven-in-ten Republicans and GOP leaners say TikTok is at least a minor threat to national security, compared with 53% of Democrats and Democratic leaners. Conservative Republicans are more likely than moderate or liberal Republicans – or Democrats of any ideology – to say the view the app as a major threat.

Nearly half of those ages 65 and older (46%) see TikTok as a major threat to national security, compared with a much smaller share (13%) of adults ages 18 to 29.

Read the other posts in our striking findings series:

  • Striking findings from 2022
  • Striking findings from 2021
  • 20 striking findings from 2020
  • 19 striking findings from 2019
  • 18 striking findings from 2018
  • 17 striking findings from 2017
  • 16 striking findings from 2016
  • 15 striking findings from 2015
  • 14 striking findings from 2014
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Dozens of COVID Virus Mutations Arose in Man With Longest Known Case

By Dennis Thompson HealthDay Reporter

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FRIDAY, April 19, 2024 (HealthDay News) -- An immune-compromised man with a year-and-a-half-long COVID infection served as a breeding ground for dozens of coronavirus mutations, a new study discovered.

Worse, several of the mutations were in the COVID spike protein, indicating that the virus had attempted to evolve around current vaccines, researchers report.

“This case underscores the risk of persistent SARS-CoV-2 infections in immunocompromised individuals, as unique SARS-CoV-2 viral variants may emerge,” said the research team led by Magda Vergouwe . She's a doctoral candidate with Amsterdam University Medical Center in The Netherlands.

The patient in questioned endured the longest known COVID infection to date, fighting with the virus for 613 days before dying from the blood disease that had compromised his immune system, researchers said.

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Immune-compromised patients who suffer persistent infections give the COVID virus an opportunity to adapt and evolve, the investigators explained.

For instance, the Omicron variant is thought to have emerged in an immune-compromised patient initially infected with an earlier form of COVID, researchers said.

In this latest report, the man was admitted to Amsterdam University Medical Center in February 2022 with a COVID infection at age 72, after he’d already received multiple vaccinations.

He suffered from myelodysplastic and myeloproliferative overlap syndrome , a disease in which the bone marrow makes too many white blood cells, according to the U.S. National Cancer Institute.

Following a stem cell transplant, the man also had developed lymphoma, a cancer of the white blood cells, researchers said.

A drug he took for lymphoma, rituximab , depleted all the immune cells that normally produce antibodies for COVID, they added.

To clear his COVID, the man received a monoclonal antibody cocktail that ultimately proved ineffective.

In fact, gene sequencing showed that the coronavirus started mutating to evade the antibodies he’d received, a step that could have potentially undermined the effectiveness of the treatment in others, researchers said.

Gene sequencing of 27 nasal specimens taken from the man revealed more than 50 mutations in the COVID virus, including variants with changes in the spike protein targeted by vaccines.

“The prolonged infection has led to the emergence of a novel immune-evasive variant due to the extensive within-host evolution,” researchers said.

Such cases pose a “potential public health threat of possibly introducing viral escape variants into the community,” they added.

However, they noted that there had been no documented transmission of any COVID variants from the man into other people.

The researchers will present their findings at the European Society of Clinical Microbiology and Infectious Diseases meeting next week in Barcelona. Findings presented at medical meetings should be considered preliminary until published in a peer-reviewed journal.

More information

The U.S. Centers for Disease Control and Prevention has more about COVID .

SOURCE: European Society of Clinical Microbiology and Infectious Diseases, news release, April 19, 2024

Copyright © 2024 HealthDay . All rights reserved.

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  6. 49 Free Case Study Templates ( + Case Study Format Examples + )

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  3. Master case writing

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  5. Data Management & Case Report in Clinical Trials: Development of Case Report Forms Part 2

  6. How to write a case series? Journal paper writing, article publishing basics

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  1. Case Study

    The findings of a case study are often used to develop theories, inform policy or practice, or generate new research questions. Types of Case Study. Types and Methods of Case Study are as follows: Single-Case Study. A single-case study is an in-depth analysis of a single case. This type of case study is useful when the researcher wants to ...

  2. What Is a Case Study?

    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 ...

  3. Case Study Methodology of Qualitative Research: Key Attributes and

    A case study is one of the most commonly used methodologies of social research. This article attempts to look into the various dimensions of a case study research strategy, the different epistemological strands which determine the particular case study type and approach adopted in the field, discusses the factors which can enhance the effectiveness of a case study research, and the debate ...

  4. Case Study Method: A Step-by-Step Guide for Business Researchers

    Although case studies have been discussed extensively in the literature, little has been written about the specific steps one may use to conduct case study research effectively (Gagnon, 2010; Hancock & Algozzine, 2016).Baskarada (2014) also emphasized the need to have a succinct guideline that can be practically followed as it is actually tough to execute a case study well in practice.

  5. How to Use Case Studies in Research: Guide and Examples

    1. Select a case. Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research. 2.

  6. Writing a Case Study

    The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case ...

  7. Case Study

    A case study research design usually involves qualitative methods, but quantitative methods are sometimes also used. Case studies are good for describing, ... Open up new directions for future research; Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies ...

  8. What is a Case Study?

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

  9. Perspectives from Researchers on Case Study Design

    Case study research is typically extensive; it draws on multiple methods of data collection and involves multiple data sources. The researcher begins by identifying a specific case or set of cases to be studied. Each case is an entity that is described within certain parameters, such as a specific time frame, place, event, and process.

  10. Designing research with case study methods

    The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case. Robert Yin, methodologist most associated with case study research, differentiates between descriptive, exploratory and explanatory case studies:

  11. LibGuides: Research Writing and Analysis: Case Study

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

  12. Writing a Case Analysis Paper

    Case studies are a choice of methodological design intended to create new knowledge about resolving a research problem. A case analysis is a mode of teaching and learning intended to create new understanding and an awareness of uncertainty applied to practice through acts of critical thinking and reflection.

  13. The case study approach

    A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table.

  14. Case Study Design

    Case study methodology has a relatively long history within the sciences, social sciences, and humanities..Despite this long history and widespread use, case study research has received perhaps the least attention among the various methodologies in the social scientist′s research arsenal.á Only a few texts deal directly with it as a central subject, and no encyclopedic reference provides a ...

  15. The "case" for case studies: why we need high-quality examples of

    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.

  16. Case study research and causal inference

    Calls for greater recognition for case study designs within health research are hardly new: Flyvberg's advocacy for a greater role for case studies in the social sciences has now been cited around 20,000 times, and calls for methodological pluralism in health research go back decades [42, 45, 46].

  17. Technology: News, Articles, Research, & Case Studies

    by Rachel Layne. Many companies build their businesses on open source software, code that would cost firms $8.8 trillion to create from scratch if it weren't freely available. Research by Frank Nagle and colleagues puts a value on an economic necessity that will require investment to meet demand. 12 Mar 2024.

  18. Case Study Research Method in Psychology

    Case studies are in-depth investigations of a person, group, event, or community. Typically, data is gathered from various sources using several methods (e.g., observations & interviews). The case study research method originated in clinical medicine (the case history, i.e., the patient's personal history). In psychology, case studies are ...

  19. Doing Comparative Case Studies: New Designs and Directions

    Abstract. Comparative Case Studies: New Designs and Directions extends the comparative case study methodology established by Bartlett and Vavrus and employed in many areas of social research, especially in education. This volume unites a diverse, international group of education scholars whose work exemplifies the affordances and constraints of ...

  20. Top 40 Most Popular Case Studies of 2021

    Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT's (Case Research and Development Team) 2021 top 40 review of cases. Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019.

  21. (PDF) The case study as a type of qualitative research

    Abstract. This article presents the case study as a type of qualitative research. Its aim is to give a detailed description of a case study - its definition, some classifications, and several ...

  22. Impact Case Studies

    AHRQ's evidence-based tools and resources are used by organizations nationwide to improve the quality, safety, effectiveness, and efficiency of health care. The Agency's Impact Case Studies highlight these successes, describing the use and impact of AHRQ-funded tools by State and Federal policy makers, health systems, clinicians ...

  23. Research News : NPR

    New advances in science, medicine, health, and technology.Stem cell research, drug research, and new treatments for disease. ... a new study says. ... A case of bronchitis in 2014 left Sanna ...

  24. New research from Case Western Reserve University aims to block tumor

    School of Medicine awarded five-year, $1.84M grant from National Institutes of Health's National Cancer Institute Researchers at Case Western Reserve University's School of Medicine believe they have found information that could lead to developing new treatment options for people with metastatic colorectal cancer. With a new five-year, $1.84 million grant from the National Cancer Institute ...

  25. Research on Improving Patient Experience

    The research team collaborated with New York-Presbyterian Hospital to assess whether an online interactive report designed to facilitate interpretation of patients' narrative feedback produces change in ambulatory staff learning, behavior at the individual staff and practice level, and patient experience survey scores. Key Findings

  26. Resolving Workforce Skills Gaps with AI-Powered Insights

    Ongoing digital transformation requires a workforce that is proficient in a wide variety of new skills. This briefing explores the use of AI in quantifying such proficiency, through a process known as skills inference. We introduce this concept by means of a case study of Johnson & Johnson, showing how skills inference can provide detailed insight into workforce skills gaps and thereby guide ...

  27. New EY US Consulting study: employees overwhelmingly expect empathy in

    Case studies. Energy and resources. ... New EY US Consulting study: employees overwhelmingly expect empathy in the workplace, but many say it feels disingenuous. ... To fulfill the authenticity equation, previous EY research indicates offering flexibility is essential. In the 2022 EY US Generation Survey, 92% of employees surveyed across all ...

  28. Shaping the future of behavioral and social research at NIA

    For decades, NIA has examined aging from an interdisciplinary perspective and expanded research infrastructure and evidence-based tools to support this work. Highlights include: Cultivating robust population-level, longitudinal studies: NIA has funded generations of population-level data from longitudinal studies. A leading example is the ...

  29. Striking findings from 2023

    Here's a look back at 2023 through some of our most striking research findings. These findings only scratch the surface of the Center's research from this past year. A record-high share of 40-year-olds in the U.S. have never been married, according to a Center analysis of the most recent U.S. Census Bureau data. As of 2021, a quarter of 40 ...

  30. Dozens of COVID Virus Mutations Arose in Man With Longest Known Case

    FRIDAY, April 19, 2024 (HealthDay News) -- An immune-compromised man with a year-and-a-half-long COVID infection served as a breeding ground for dozens of coronavirus mutations, a new study ...