what is the definition of the case study

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

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

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

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

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

Case studies

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

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

Definition of a case study

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

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

Characteristics of case studies

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

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

The role of case studies in research

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

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

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

What is the purpose of a case study?

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

Why use case studies in qualitative research?

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

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

The explanatory, exploratory, and descriptive roles of case studies

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

The impact of case studies on knowledge development

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

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

Types of case studies

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

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

Exploratory case studies

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

Descriptive case studies

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

Explanatory case studies

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

Intrinsic, instrumental, and collective case studies

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

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

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

Critical information systems research

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

Health research

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

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

Asthma research studies

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

Other fields

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

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

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

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

Propositions

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

Units of analysis

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

Argumentation

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

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

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

Defining the research question

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

Selecting and defining the case

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

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

Developing a detailed case study protocol

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

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

Collecting data

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

Analyzing and interpreting data

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

Writing the case study report

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

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

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

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

Observations

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

Documents and artifacts

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

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

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

Ensuring the quality of data collection

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

Data analysis

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

Organizing the data

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

Categorizing and coding the data

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

Identifying patterns and themes

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

Interpreting the data

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

Verification of the data

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

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

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

Benefits include the following:

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

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

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

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

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• Knowledge Base
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• Case Study | Definition, Examples & Methods

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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Organizing Your Social Sciences Research Assignments

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

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

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

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

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

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

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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Definition of case study

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Word History

1914, in the meaning defined at sense 1

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

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.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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What Is a Case Study and Why You Should Use Them

Case studies can provide more insights into your business while helping you conduct further research with robust qualitative data analysis to learn more.

If you're in charge of running a company, then you're likely always looking for new ways to run your business more efficiently and increase your customer base while streamlining as many processes as possible.

Unfortunately, it can sometimes be difficult to determine how to go about implementing the proper program in order to be successful. This is why many business owners opt to conduct a case study, which can help significantly. Whether you've been struggling with brand consistency or some other problem, the right case study can identify why your problem exists as well as provide a way to rectify it.

A case study is a great tool that many businesses aren't even aware exists, and there are marketing experts like Mailchimp who can provide you with step-by-step assistance with implementing a plan with a case study. Many companies discover that not only do they need to start a blog in order to improve business, but they also need to create specific and relevant blog titles.

If your company already has a blog, then optimizing your blog posts may be helpful. Regardless of the obstacles that are preventing you from achieving all your professional goals, a case study can work wonders in helping you reverse this issue.

What is a case study?

A case study is a comprehensive report of the results of theory testing or examining emerging themes of a business in real life context. Case studies are also often used in the healthcare industry, conducting health services research with primary research interest around routinely collected healthcare data.

However, for businesses, the purpose of a case study is to help small business owners or company leaders identify the issues and conduct further research into what may be preventing success through information collection, client or customer interviews, and in-depth data analysis.

Knowing the case study definition is crucial for any business owner. By identifying the issues that are hindering a company from achieving all its goals, it's easier to make the necessary corrections to promote success through influenced data collection.

Why are case studies important?

Now that we've answered the questions, "what is a case study?" Why are case studies important? Some of the top reasons why case studies are important include:

• Understand complex issues: Even after you conduct a significant amount of market research , you might have a difficult time understanding exactly what it means. While you might have the basics down, conducting a case study can help you see how that information is applied. Then, when you see how the information can make a difference in business decisions, it could make it easier to understand complex issues.
• Collect data: A case study can also help with data tracking . A case study is a data collection method that can help you describe the information that you have available to you. Then, you can present that information in a way the reader can understand.
• Conduct evaluations: As you learn more about how to write a case study, remember that you can also use a case study to conduct evaluations of a specific situation. A case study is a great way to learn more about complex situations, and you can evaluate how various people responded in that situation. By conducting a case study evaluation, you can learn more about what has worked well, what has not, and what you might want to change in the future.
• Identify potential solutions: A case study can also help you identify solutions to potential problems. If you have an issue in your business that you are trying to solve, you may be able to take a look at a case study where someone has dealt with a similar situation in the past. For example, you may uncover data bias in a specific solution that you would like to address when you tackle the issue on your own. If you need help solving a difficult problem, a case study may be able to help you.

Remember that you can also use case studies to target your audience . If you want to show your audience that you have a significant level of expertise in a field, you may want to publish some case studies that you have handled in the past. Then, when your audience sees that you have had success in a specific area, they may be more likely to provide you with their business. In essence, case studies can be looked at as the original method of social proof, showcasing exactly how you can help someone solve their problems.

What are the benefits of writing a business case study?

Although writing a case study can seem like a tedious task, there are many benefits to conducting one through an in depth qualitative research process.

• Industry understanding: First of all, a case study can give you an in-depth understanding of your industry through a particular conceptual framework and help you identify hidden problems that are preventing you from transcending into the business world.
• Develop theories: If you decide to write a business case study, it provides you with an opportunity to develop new theories. You might have a theory about how to solve a specific problem, but you need to write a business case study to see exactly how that theory has unfolded in the past. Then, you can figure out if you want to apply your theory to a similar issue in the future.
• Evaluate interventions: When you write a business case study that focuses on a specific situation you have been through in the past, you can uncover whether that intervention was truly helpful. This can make it easier to figure out whether you want to use the same intervention in a similar situation in the future.
• Identify best practices: If you want to stay on top of the best practices in your field, conducting case studies can help by allowing you to identify patterns and trends and develop a new list of best practices that you can follow in the future.
• Versatility: Writing a case study also provides you with more versatility. If you want to expand your business applications, you need to figure out how you respond to various problems. When you run a business case study, you open the door to new opportunities, new applications, and new techniques that could help you make a difference in your business down the road.
• Solve problems: Writing a great case study can dramatically improve your chances of reversing your problem and improving your business.
• These are just a few of the biggest benefits you might experience if you decide to publish your case studies. They can be an effective tool for learning, showcasing your talents, and teaching some of your other employees. If you want to grow your audience , you may want to consider publishing some case studies.

What are the limitations of case studies?

Case studies can be a wonderful tool for any business of any size to use to gain an in-depth understanding of their clients, products, customers, or services, but there are limitations.

One limitation of case studies is the fact that, unless there are other recently published examples, there is nothing to compare them to since, most of the time, you are conducting a single, not multiple, case studies.

Another limitation is the fact that most case studies can lack scientific evidence.

Types of case studies

There are specific types of case studies to choose from, and each specific type will yield different results. Some case study types even overlap, which is sometimes more favorable, as they provide even more pertinent data.

Here are overviews of the different types of case studies, each with its own theoretical framework, so you can determine which type would be most effective for helping you meet your goals.

Explanatory case studies

Explanatory case studies are pretty straightforward, as they're not difficult to interpret. This type of case study is best if there aren't many variables involved because explanatory case studies can easily answer questions like "how" and "why" through theory development.

Exploratory case studies

An exploratory case study does exactly what its name implies: it goes into specific detail about the topic at hand in a natural, real-life context with qualitative research.

The benefits of exploratory case studies are limitless, with the main one being that it offers a great deal of flexibility. Having flexibility when writing a case study is important because you can't always predict what obstacles might arise during the qualitative research process.

Collective case studies

Collective case studies require you to study many different individuals in order to obtain usable data.

Case studies that involve an investigation of people will involve many different variables, all of which can't be predicted. Despite this fact, there are many benefits of collective case studies, including the fact that it allows an ongoing analysis of the data collected.

Intrinsic case studies

This type of study differs from the others as it focuses on the inquiry of one specific instance among many possibilities.

Many people prefer these types of case studies because it allows them to learn about the particular instance that they wish to investigate further.

Instrumental case studies

An instrumental case study is similar to an intrinsic one, as it focuses on a particular instance, whether it's a person, organization, or something different.

One thing that differentiates instrumental case studies from intrinsic ones is the fact that instrumental case studies aren't chosen merely because a person is interested in learning about a specific instance.

Tips for writing a case study

If you have decided to write case studies for your company, then you may be unsure of where to start or which type to conduct.

However, it doesn't have to be difficult or confusing to begin conducting a case study that will help you identify ways to improve your business.

Here are some helpful tips for writing your case studies:

1. Your case study must be written in the proper format

When writing a case study, the format that you should be similar to this:

Administrative summary

The executive summary is an overview of what your report will contain, written in a concise manner while providing real-life context.

Despite the fact that the executive summary should appear at the beginning of your case studies, it shouldn't be written until you've completed the entire report because if you write it before you finish the report, this summary may not be completely accurate.

Key problem statement

In this section of your case study, you will briefly describe the problem that you hope to solve by conducting the study. You will have the opportunity to elaborate on the problem that you're focusing on as you get into the breadth of the report.

Problem exploration

This part of the case study isn't as brief as the other two, and it goes into more detail about the problem at hand. Your problem exploration must include why the identified problem needs to be solved as well as the urgency of solving it.

Additionally, it must include justification for conducting the problem-solving, as the benefits must outweigh the efforts and costs.

Proposed resolution

This case study section will also be lengthier than the first two. It must include how you propose going about rectifying the problem. The "recommended solution" section must also include potential obstacles that you might experience, as well as how these will be managed.

Furthermore, you will need to list alternative solutions and explain the reason the chosen solution is best. Charts can enhance your report and make it easier to read, and provide as much proof to substantiate your claim as possible.

Overview of monetary consideration

An overview of monetary consideration is essential for all case studies, as it will be used to convince all involved parties why your project should be funded. You must successfully convince them that the cost is worth the investment it will require. It's important that you stress the necessity for this particular case study and explain the expected outcome.

Execution timeline

In the execution times of case studies, you explain how long you predict it will take to implement your study. The shorter the time it will take to implement your plan, the more apt it is to be approved. However, be sure to provide a reasonable timeline, taking into consideration any additional time that might be needed due to obstacles.

Always include a conclusion in your case study. This is where you will briefly wrap up your entire proposal, stressing the benefits of completing the data collection and data analysis in order to rectify your problem.

2. Make it clear and comprehensive

You want to write your case studies with as much clarity as possible so that every aspect of the report is understood. Be sure to double-check your grammar, spelling, punctuation, and more, as you don't want to submit a poorly-written document.

Not only would a poorly-written case study fail to prove that what you are trying to achieve is important, but it would also increase the chances that your report will be tossed aside and not taken seriously.

3. Don't rush through the process

Writing the perfect case study takes time and patience. Rushing could result in your forgetting to include information that is crucial to your entire study. Don't waste your time creating a study that simply isn't ready. Take the necessary time to perform all the research necessary to write the best case study possible.

Depending on the case study, conducting case study research could mean using qualitative methods, quantitative methods, or both. Qualitative research questions focus on non-numerical data, such as how people feel, their beliefs, their experiences, and so on.

Meanwhile, quantitative research questions focus on numerical or statistical data collection to explain causal links or get an in-depth picture.

It is also important to collect insightful and constructive feedback. This will help you better understand the outcome as well as any changes you need to make to future case studies. Consider using formal and informal ways to collect feedback to ensure that you get a range of opinions and perspectives.

4. Be confident in your theory development

While writing your case study or conducting your formal experimental investigation, you should have confidence in yourself and what you're proposing in your report. If you took the time to gather all the pertinent data collected to complete the report, don't second-guess yourself or doubt your abilities. If you believe your report will be amazing, then it likely will be.

5. Case studies and all qualitative research are long

It's expected that multiple case studies are going to be incredibly boring, and there is no way around this. However, it doesn't mean you can choose your language carefully in order to keep your audience as engaged as possible.

If your audience loses interest in your case study at the beginning, for whatever reason, then this increases the likelihood that your case study will not be funded.

Case study examples

If you want to learn more about how to write a case study, it might be beneficial to take a look at a few case study examples. Below are a few interesting case study examples you may want to take a closer look at.

• Phineas Gage by John Martin Marlow : One of the most famous case studies comes from the medical field, and it is about the story of Phineas Gage, a man who had a railroad spike driven through his head in 1848. As he was working on a railroad, an explosive charge went off prematurely, sending a railroad rod through his head. Even though he survived this incident, he lost his left eye. However, Phineas Gage was studied extensively over the years because his experiences had a significant, lasting impact on his personality. This served as a case study because his injury showed different parts of the brain have different functions.
• Kitty Genovese and the bystander effect : This is a tragic case study that discusses the murder of Kitty Genovese, a woman attacked and murdered in Queens, New York City. Shockingly, while numerous neighbors watched the scene, nobody called for help because they assumed someone else would. This case study helped to define the bystander effect, which is when a person fails to intervene during an emergency because other people are around.
• Henry Molaison and the study of memory : Henry Molaison lost his memory and suffered from debilitating amnesia. He suffered from childhood epilepsy, and medical professionals attempted to remove the part of his brain that was causing his seizures. He had a portion of his brain removed, but it completely took away his ability to hold memories. Even though he went on to live until the age of 82, he was always forced to live in the present moment, as he was completely unable to form new memories.

Case study FAQs

When should you do a case study.

There are several scenarios when conducting a case study can be beneficial. Case studies are often used when there's a "why" or "how" question that needs to be answered. Case studies are also beneficial when trying to understand a complex phenomenon, there's limited research on a topic, or when you're looking for practical solutions to a problem.

How can case study results be used to make business decisions?

You can use the results from a case study to make future business decisions if you find yourself in a similar situation. As you assess the results of a case study, you can identify best practices, evaluate the effectiveness of an intervention, generate new and creative ideas, or get a better understanding of customer needs.

How are case studies different from other research methodologies?

When compared to other research methodologies, such as experimental or qualitative research methodology, a case study does not require a representative sample. For example, if you are performing quantitative research, you have a lot of subjects that expand your sample size. If you are performing experimental research, you may have a random sample in front of you. A case study is usually designed to deliberately focus on unusual situations, which allows it to shed new light on a specific business research problem.

Writing multiple case studies for your business

If you're feeling overwhelmed by the idea of writing a case study and it seems completely foreign, then you aren't alone. Writing a case study for a business is a very big deal, but fortunately, there is help available because an example of a case study doesn't always help.

Mailchimp, a well-known marketing company that provides comprehensive marketing support for all sorts of businesses, can assist you with your case study, or you can review one of their own recently published examples.

Mailchimp can assist you with developing the most effective content strategy to increase your chances of being as successful as possible. Mailchimp's content studio is a great tool that can help your business immensely.

• First Online: 27 October 2022

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• R. M. Channaveer 4 &
• Rajendra Baikady 5  

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This chapter reviews the strengths and limitations of case study as a research method in social sciences. It provides an account of an evidence base to justify why a case study is best suitable for some research questions and why not for some other research questions. Case study designing around the research context, defining the structure and modality, conducting the study, collecting the data through triangulation mode, analysing the data, and interpreting the data and theory building at the end give a holistic view of it. In addition, the chapter also focuses on the types of case study and when and where to use case study as a research method in social science research.

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Master data management: The key to getting more from your data

Picture this: a sales representative at a multibillion-dollar organization has an upcoming meeting with a prospective client. She searches for the client in the organization’s customer relationship management software and finds several accounts with the same name. She struggles to learn more about the products and services the client is already buying, the customer contacts that have already been engaged, and the relationships the contact may have with other sales representatives within the organization. As a result, the sales representative spends several hours manually pulling together information to get organized for the upcoming meeting.

About the authors

This article is a collaborative effort by Aziz Shaikh, Holger Harreis , Jorge Machado , and Kayvaun Rowshankish , with Rachit Saxena and Rajat Jain, representing views from McKinsey Digital.

This scenario is an example of poor master data management (MDM), which commonly results in suboptimal customer and employee experience, higher costs, and lost revenue opportunities. MDM is a critical component of any organization’s data strategy (see sidebar “About master data management”). These capabilities can make or break an organization’s efficiency and reliability—particularly in complex organizations with multiple business units, where data silos can lead to inefficiencies and errors.

About master data management

Typically, organizations have four types of data: transaction, reference, derived, and master. Of these, master data provides the most relevant, foundational information about entities and their attributes, unique identifiers, hierarchies, and relationships within an organization. This information is shared across business functions and systems to support business processes and decision making.

In 2023, McKinsey surveyed more than 80 large global organizations 1 Companies surveyed earned more than $100 million in annual revenue. across several industries to learn more about how they organize, use, and mature their master data. McKinsey’s Master Data Management Survey indicated that organizations have four top objectives in maturing their MDM capabilities: improving customer experience and satisfaction, enhancing revenue growth by presenting better cross- and up-selling opportunities, increasing sales productivity, and streamlining reporting (Exhibit 1).

MDM plays an important role with modern data architecture concepts and creates value in five ways:

• MDM cleans, enriches, and standardizes data for key functions, such as customer or product data, before it is loaded into the data lake. In this way, MDM ensures that data is accurate, complete, and consistent across an organization.
• In the context of data products, MDM provides a hub for high-quality data across entities, which improves the effectiveness, consistency, and reliability of data products for improved decision making, accurate reporting and analysis, and compliance with local regulations and standards.
• MDM standardizes data across entities to provide a unified view across various systems.
• MDM can act as a system of reference that shares data with applications and other domains via web services, typically representational state transfer application programming interfaces (REST APIs).
• MDM and artificial intelligence (AI) can benefit from each other. For instance, MDM can leverage AI algorithms to identify duplicate records and merge them intelligently, which can enhance the performance and reliability of generative AI systems.

But many organizations have not fully harnessed the potential of MDM. This article builds on the insights from our MDM survey, describes the common challenges companies face when integrating MDM capabilities, and highlights areas in which MDM could be optimized to help businesses gain a competitive advantage.

Common issues organizations face when implementing MDM

Small and large organizations alike can benefit from implementing MDM models, yet collecting and aggregating quality data can be difficult because of funding constraints, insufficient technological support, and low-caliber data. Based on our survey results, following are some of the most prevalent challenges to implementing MDM.

Difficulty of making a business case

Demonstrating potential savings through reduced data errors, enhanced operational efficiency, and improved decision making can provide a clear return on investment for MDM initiatives. However, this return is inherently difficult to quantify, so positioning MDM as a priority ahead of projects with more visible, immediate benefits can be challenging. Consequently, despite MDM’s potential to enhance an organization, leaders may have a difficult time building a business case for augmenting their MDM and investing in associated architecture and technology capabilities.

Creating value beyond the hype

Let’s deliver on the promise of technology from strategy to scale.

Organizational silos

Types of master data domains.

A variety of categories can serve as master data domains, and each serves a specific purpose. The most common categories include the following:

Customer data. Customer data includes key details such as customer contact information, purchasing history, preferences, and demographic data. Organizations can leverage customer data to optimize marketing strategies, personalize customer experiences, and foster long-term relationships.

Client data. Client data typically includes client names, contact information, billing and shipping addresses, payment terms, key decision makers, and other client-specific identifiers. Business-to-business (B2B) organizations can manage client data to tailor their strategies, personalize communications, and optimize sales and marketing efforts to better serve their clients’ needs and preferences.

Product data. Product data includes attributes such as product names, descriptions, SKUs, pricing, and specifications. Product data typically spans across R&D, supply chain, and sales.

Supplier data. Supplier data includes attributes such as vendor names, contact details, payment terms, tax information, and vendor-specific codes. Accurate supplier data helps to establish a single, complete, and consistent definition of vendors across the organization.

Financial data. Financial data typically includes information about legal or management entities (a company code, for instance), a chart of accounts, cost and profit centers, and financial hierarchies.

Employee data. Employee data includes attributes such as employee names, contact information, job titles, employee IDs, department assignments, and payroll information.

Asset data. Asset data includes attributes such as asset name, type, purchase date, installation date, manufacturer details, financial and depreciation details, and maintenance and repair details. Organizations can improve their operational performance by maintaining consistent, accurate, and efficient management of assets across an organization.

According to the McKinsey Master Data Management Survey 2023, 83 percent of organizations consider client and product data to be the most dominant domains.

Eighty percent of organizations responding to our survey reported that some of their divisions operate in silos, each with its own data management requirements, practices, source systems, and consumption behaviors. For example, a sales team may maintain client data in a customer relationship management (CRM) system, while a marketing team may use a client data platform (CDP) to create customer profiles and inform ad campaigns. Silos can lead to inconsistencies and errors, increasing the difficulty of making decisions related to business, data, and technology (see sidebar “Types of master data domains”).

Treating MDM as a technology discipline only

Organizations typically think of MDM as a technology discipline rather than as a differentiator that can drive enterprise value. According to our survey, only 16 percent of MDM programs are funded as organization-wide strategic programs, leaving IT or tech functions to carry the financial responsibility (Exhibit 2). Sixty-two percent of respondents reported that their organizations had no well-defined process for integrating new and existing data sources, which may hinder the effectiveness of MDM.

While technology plays a crucial role, the success of MDM initiatives requires significant business influence and sponsorship to set the strategic direction, understand data dependencies, improve the quality of data, enhance business processes, and, ultimately, support the organization in achieving its goals. It’s important for the role of data owner to be played by a business stakeholder—specifically, the head of the business unit that uses the data most, such as the head of sales and marketing for the client data domain. That leader can provide guidance for defining data requirements and data quality rules that are aligned with the business’s goals.

Poor data quality

Poor-quality data cannot deliver analytics-based insights without substantial manual adjustment. According to the MDM survey, 82 percent of respondents spent one or more days per week resolving master data quality issues, and 66 percent used manual review to assess, monitor, and manage the quality of their master data. Consequently, large, multidivisional organizations may be unable to efficiently generate KPIs or other metrics, and sales representatives may be unable to quickly generate a consistent, holistic view of prospective clients. According to the MDM survey, the most prevalent issues in organizations’ data quality were incompleteness, inconsistency, and inaccuracy (Exhibit 3).

In addition to incompleteness, inconsistency, and accuracy, many companies also contend with issues of uniqueness, or duplicate information, across systems. Traditionally, organizations classify data assets based on the stakeholders they interact with, but this approach can lead to duplication of information. For example, a supplier to an organization can also be its customer. These circumstances have led to the design of a “party” data domain that generalizes the characteristics of a person or organization and establishes the connection between them and their distinctive roles to the company.

Master data quality issues can cause customer dissatisfaction, operational inefficiencies, and poor decision making. Furthermore, companies handling private or sensitive consumer information have stricter compliance requirements and data quality, security, and privacy standards. Without good data, implementing MDM processes will be difficult.

Complex data integration requirements

Organizations may find it difficult to integrate MDM into their existing systems. Compatibility issues, data migration challenges, and system upgrades can hinder successful MDM implementation, and minimizing integration latency is crucial to provide timely and accurate data to the MDM system. Organizations may have to significantly model, map, and transform data systems so they can work with newer and older technologies.

How to effectively implement and optimize MDM capabilities

To overcome these challenges and successfully implement and optimize MDM capabilities, organizations must clearly identify the value they hope to create based on their priority business use cases such as operational efficiency and customer insights, which lead to cost savings and revenue growth. Organizations should measure the impact and effectiveness of MDM implementation using metrics such as ROI, total cost of ownership, and performance baselines. Organizations should maintain a forward-looking approach to adopt modern tools and technologies; create a robust data governance model backed by performance KPIs; and plan for capability building among stakeholders to ensure a uniform adoption of MDM principles.

The data dividend: Fueling generative AI

Build a ‘golden record’ that contains the most up-to-date information.

An MDM “golden record” is a repository that holds the most accurate information available in the organization’s data ecosystem. For example, a golden record of client data is a single, trusted source of truth that can be used by marketing and sales representatives to analyze customer preferences, trends, and behaviors; improve customer segmentation; offer personalized products and services; and increase cross-sales, interactions, customer experiences, and retention.

To build a golden record that contains the most up-to-date information, organizations integrate data from every business unit into the golden record and update it as more accurate information becomes available. Integrating information can be done with the help of AI and machine learning (ML) technology. Alternatively, organizations may establish one existing system as the golden record for a specific data domain to maintain consistency, precision, and timeliness across the enterprise.

Four common master data management design approaches

Organizations typically use one of four master data management design approaches, depending on the complexity of their data:

Registry MDM. This model aggregates data from multiple sources to spot duplicates in information. It is a simple, inexpensive approach that large, global organizations with many data sources often find helpful.

Consolidation MDM. This approach periodically sorts and matches information from multiple source systems to create or update the master data record. Simple and inexpensive to set up, it is a good option for organizations seeking to analyze large sets of data.

Centralized MDM. This approach establishes a single master repository to create, update, and maintain data, and shares it back with the respective source systems. This model is good for banks, insurance companies, government agencies, and hospital networks that require strict compliance to maintain integrity and control over their data.

Coexistence MDM. This approach creates and updates data in source systems, giving businesses the flexibility and autonomy to manage data attributes at the division or business-unit level while maintaining consistent core client data. This model is especially good for large, complex enterprises with many segments and business-unit structures that are frequently integrating new clients into their databases.

Organizations typically start by deploying more rudimentary MDM models, such as registry or consolidation, then evolve to more mature approaches, such as centralized or coexistence. These more mature models are more flexible but also more complex. When choosing an MDM deployment approach, organizations should consider the following questions, among others:

• How should the organization centralize and streamline master data across different systems and locations to maximize accessibility and usability?
• What methodologies should be used to manage the complexity of data relationships and structures to improve efficiency and interoperability across systems?
• What strategies need to be implemented to enable real-time master data updates and guarantee instant access to the most current and accurate information?
• How should the organization maintain consistent, high-quality data across all departments to support data-driven decision making?
• What initiatives need to be implemented to empower business units to increase autonomy and maturity, fostering innovation and agility throughout the organization?
• Which systems must be seamlessly integrated with the MDM strategy to establish a cohesive and unified data ecosystem?
• How should MDM support and enhance current and future business processes to drive sustainable growth and competitive advantage?
• What proactive measures should be in place to address regulatory and compliance requirements, ensuring risk mitigation and adherence to industry best practices?

There are four common MDM design approaches that can be used to update the golden record within the business unit data (see sidebar “Four common master data management design approaches”). Deploying a modular architecture enables fit-for-purpose consumption and integration patterns with various systems to manage the golden record. For example, every mastered client record could be linked back to the source systems and mapped to a hierarchy to show association in the MDM system. Alternatively, client data could be mastered and assigned a unique client ID within the golden record to stitch together data from all systems and create a single portfolio of a client.

Establish a robust data governance model to maintain integrity and reliability of MDM capabilities

Only 29 percent of companies responding to our survey had full upstream and downstream MDM integrations with source systems and business applications, as well as all governance or stewardship roles, in place. Organizations should clearly identify the single source of truth for data and properly train employees on handling integration failures to avoid saving stale information.

Data governance models for MDM should be designed with clear roles and responsibilities, be managed by a governance council with representatives from different business units and IT, and be shepherded by someone who can serve as an MDM liaison among business, data, and technology stakeholders. The structure should be complemented by a clearly defined policy framework and a tailored, business-backed, and IT-supported operating model for master data domains. These data governance processes will allow upstream system owners and a data governance council to address data quality issues—for example, when the MDM identifies new or updated information as conflicting with other information based on the survivorship strategy.

Choose an MDM tool that enhances data quality and accelerates transformation

MDM tools are becoming more intuitive and user-friendly, and recent innovations in AI, ML, cloud technologies, and federated architectures have opened new possibilities for data mastering and processing. For example, AI-enabled tools use pretrained AI and ML models to automate data quality, data matching, and entity resolution tasks with a higher degree of accuracy and greater efficiency. According to the survey, 69 percent of organizations are already using AI as part of their overall data management capabilities; however, only 31 percent are using advanced AI-based techniques to enhance match-and-merge capabilities and to improve master data quality more broadly.

Organizations should choose data management tools that align with their priorities and make the transition seamless. It’s also important to consider the return on investment and the incremental value that each MDM tool can bring to the organization. When choosing an MDM tool, relevant business stakeholders should understand data processes and requirements, including the data elements that affect business operations and the priority use cases, and then help determine the technology capabilities and workflows that are required to integrate new systems.

For example, stakeholders should assess the maturity of their organization’s capabilities, including its data quality, matching, and entity resolution, to determine how easily new systems will be able to integrate with existing systems and technologies. It is also important to consider these systems’ scalability and flexibility to accommodate future growth and evolving data management needs. Moreover, AI and ML capabilities should be considered to help the MDM tool automate tasks to improve data quality.

Plan for capability building and change management

Organizations that implement technology without changing their processes and the way people work with master data may not fully reap the benefits of MDM.

Change management is crucial to ensure that employees understand and embrace the changes brought about by MDM implementation. It typically includes securing executive sponsorship to demonstrate the importance of MDM to the organization; engaging with business and technology stakeholders to communicate the vision; setting expectations for accountability and processes; and rolling out comprehensive training programs to educate employees on MDM and data principles, processes, and tools.

Start with a pilot implementation

Organizations can start integrating MDM tools by first piloting MDM in one domain to validate its design, governance model, and workflows in a controlled environment. Organizations can then easily identify any potential issues or challenges and make the necessary adjustments before scaling up the implementation to other master data domains or to the entire organization. Piloting these tools also allows organizations to gather feedback from users and stakeholders to understand the user experience, identify areas for improvement, and make necessary changes to optimize the MDM tool and workflows.

Implementing and optimizing MDM capabilities can seem daunting, especially for large organizations with multiple complex systems. But once successfully deployed across master data domains—using an optimal design approach, an efficient governance structure, and sufficient change management efforts—MDM can ensure that high-quality data is available for strategic decision making, leading to cost savings and revenue opportunities across an organization.

Aziz Shaikh and Jorge Machado are partners in McKinsey’s New York office, where Kayvaun Rowshankish is a senior partner, Rachit Saxena is a consultant, and Rajat Jain is an associate partner. Holger Harreis is a senior partner in the Düsseldorf office.

The authors wish to thank Vladimir Alekseev for his contributions to this article.

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Study Design

Participants, rickets screening procedures, laboratory methods and radiographic interpretations, case definition, statistical analysis, maternal and infant characteristics, effect of maternal vitamin d supplementation on biochemical rickets, subgroup analyses, infant bone biomarkers, radiographically confirmed rickets, conclusions, acknowledgments, maternal vitamin d supplementation and infantile rickets: secondary analysis of a randomized trial.

FUNDING: This work was supported in part by the Bill & Melinda Gates Foundation (OPP1066764). Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission. Dr Lautatzis received salary support from the Canadian Pediatric Endocrine Group Fellowship Program and CIHR Canada Graduate Scholarship. The funding agencies were not involved in the design, implementation, analysis, or interpretation of the data.

CONFLICT OF INTEREST DISCLOSURES: There are no conflicts of interest to disclose.

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Maria-Elena Lautatzis , Farhana K. Keya , Abdullah Al Mahmud , Ulaina Tariq , Carol Lam , Shaun K. Morris , Jennifer Stimec , Stanley Zlotkin , Tahmeed Ahmed , Jennifer Harrington , Daniel E. Roth; Maternal Vitamin D Supplementation and Infantile Rickets: Secondary Analysis of a Randomized Trial. Pediatrics 2024; e2023063263. 10.1542/peds.2023-063263

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The role of maternal vitamin D supplementation in the prevention of infantile rickets is unknown, particularly in low- and middle-income countries without routine infant vitamin D supplementation. Through secondary analysis of a randomized, placebo-controlled trial in Bangladesh, we examined the dose-ranging effects of maternal vitamin D supplementation on the risk of biochemical rickets at 6 to 12 months of age.

Pregnant women ( n = 1300) were randomized into 5 groups: placebo, or vitamin D 4200 IU/week, 16 800 IU/week, or 28 000 IU/week from second trimester to delivery and placebo until 6 months postpartum; or 28 000 IU/week prenatally and until 6 months postpartum. Infants underwent biochemical rickets screening from 6 to 12 months of age ( n = 790). Relative risks (RR) and 95% confidence intervals (95% CI) of biochemical rickets were estimated for each group versus placebo.

Overall, 39/790 (4.9%) infants had biochemical rickets. Prevalence was highest in the placebo group (7.8%), and the risk was significantly lower among infants whose mothers received combined prenatal and postpartum vitamin D at 28 000 IU/week (1.3%; RR, 0.16; 95% CI, 0.03–0.72). Risks among infants whose mothers received only prenatal supplementation (4200 IU, 16 800 IU, 28 000 IU weekly) were not significantly different from placebo: 3.8% (RR, 0.48; 95% CI, 0.19–1.22), 5.8% (RR, 0.74; 95% CI, 0.33–1.69), and 5.7% (RR, 0.73; 95% CI, 0.32–1.65), respectively.

Maternal vitamin D supplementation (28 000 IU/week) during the third trimester of pregnancy until 6 months postpartum reduced the risk of infantile biochemical rickets. Further research is needed to define optimal postpartum supplementation dosing during lactation.

Maternal vitamin D supplementation during pregnancy and lactation modifies infant vitamin D status, but its effects on the risk of infantile rickets have not previously been established.

High-dose maternal vitamin D supplementation during the third trimester of pregnancy and up to 6-months postpartum reduced the risk of infantile rickets in Bangladesh. Maternal postpartum vitamin D supplementation may be an alternative to direct infant supplementation for rickets prevention.

Nutritional rickets is one of the most common causes of pediatric bone disease globally. 1 Biochemical abnormalities are detectable at an early stage of rickets across all age groups and have an important role in screening and diagnosis. 2 , – 6 Young infants with rickets often have a more subtle bony phenotype compared with older children given their lack of substantial weight bearing and may remain undiagnosed until later stages of the disease. However, the high metabolic demand for calcium resulting from rapid growth in infancy can lead to acute presentations of rickets with hypocalcemia before the emergence of other clinical or radiologic signs. 7 , – 9 Compared with older children, there may be substantial morbidity associated with infantile rickets given sequelae such as hypocalcemic seizures and, in rare cases, cardiomyopathy. 10 , – 12  

Vitamin D deficiency is the predominant cause of nutritional rickets worldwide, particularly in infants. Maternal prenatal vitamin D status is the primary determinant of newborn vitamin D status. 13 , – 17 The major circulating metabolite of vitamin D, 25-hydroxyvitamin D (25(OH)D), crosses the placenta such that cord blood concentrations are highly correlated with maternal values at term. 18 However, the influence of maternal prenatal vitamin D status on infant vitamin D stores diminishes by 2 months of age and infants become dependent on other vitamin D sources. 19 In the Maternal Vitamin D for Infant Growth (MDIG) trial, 20 there was a dose-response effect of prenatal vitamin D supplementation on cord blood and infant vitamin D blood concentrations up to 3 months of age, as has been observed in other prenatal vitamin D supplementation trials. 21 , 22 Therefore, although deficiency in the early postnatal period may be caused primarily by maternal prenatal vitamin D deficiency, 23 vitamin D deficiency later in infancy is attributable to other risk factors. Because breast milk is a poor source of vitamin D if a lactating mother has inadequate vitamin D intake/status, prolonged breast feeding without vitamin D supplementation is an important cause of vitamin D deficiency in infants. However, adequate maternal intake of vitamin D during lactation can support vitamin D sufficiency in the breastfed infant. 24 For example, the MDIG trial demonstrated that continued maternal postpartum supplementation (28 000 IU/week) maintained infant 25(OH)D concentrations at or above 30 nmol/L up to 6 months of age. 20  

The role of vitamin D in fetal calcium homeostasis is uncertain; whereas animal studies suggest transplacental transfer may be independent of prenatal maternal vitamin D status, some human studies have provided evidence that maternal prenatal vitamin D status affects fetal calcium accrual. 25 Immediately after delivery, vitamin D is required as an essential regulator of infant intestinal calcium absorption and bone mineral metabolism, similar to older children. 26 Therefore, it is plausible that maternal vitamin D supplementation in the prenatal and postpartum period would reduce the risk of infantile rickets by supporting fetal calcium accrual, neonatal vitamin D endowment, and infant vitamin D intake via breastmilk.

Although there is limited evidence establishing the effect of postpartum vitamin D supplementation in breastfeeding women on the risk of infantile rickets, 27 , 28 there have not been published trials examining prenatal supplementation alone or in combination with postpartum supplementation. Such evidence would be particularly relevant to many low- and middle-income countries such as Bangladesh, where there is a high burden of vitamin D deficiency among both women of child-bearing age and newborns and vitamin D supplementation in infants is not a routine practice. 17 , 29 , – 31 In this substudy of a randomized controlled trial, we aimed to estimate the effect of a range of doses of maternal vitamin D supplementation during pregnancy and continued supplementation during lactation, compared with placebo, on the risk of infantile biochemical rickets at 6 to 12 months of age in Dhaka, Bangladesh.

This study was based on secondary analyses of data from the MDIG trial, conducted in Dhaka, Bangladesh, from 2014 to 2018. This was a randomized double-blinded, placebo-controlled, dose-ranging trial of maternal vitamin D supplementation (from mid-gestation up to 6 months postpartum) for which the primary outcome was infant growth. 20 , 32 Briefly, 1300 generally healthy females 18 years of age or older were enrolled in the second trimester of pregnancy and randomized into 1 of 5 intervention groups: (1) placebo in prenatal and postpartum; (2) prenatal vitamin D3 (4200 IU/week) and placebo postpartum; (3) prenatal vitamin D3 (16 800 IU/week) and placebo postpartum; (4) prenatal vitamin D3 (28 000 IU/week) and placebo postpartum; or (5) vitamin D3 (28 000 IU/week) prenatal and to 6 months postpartum. Supplementation was administered weekly under direct supervision by trained study personnel either in the participant’s home or in the clinic. Participants in all groups were provided daily calcium (500 mg) and iron–folic acid supplements. Ethics approval for secondary use of the trial data for this sub-study was provided by the Research Ethics Board at the Hospital for Sick Children in Canada (REB #1000061259).

Individuals were excluded from the MDIG if there was history of medical conditions with altered vitamin D metabolism and/or hypercalcemia, were having a high-risk pregnancy, were unwilling to stop taking nonstudy vitamin D or calcium supplements or multivitamins containing calcium and/or vitamin D, or were currently being prescribed vitamin D supplements as part of a physician’s treatment plan for vitamin D deficiency. Infants in the MDIG cohort were eligible for biochemical screening at or after 6 months of age; those included in this substudy had at least 1 measurement of serum alkaline phosphatase (ALP) between 6 and 12 months of age ( Supplemental Fig 2 ). Infants with known disorders that affect calcium homeostasis or known skeletal dysplasia would have been excluded from the study, yet no such cases were identified.

Infants in the MDIG were born between June 2014 and February 2016. Systematic screening for rickets at 6-month follow-up visits was launched in May 2016. The biochemical screening panel included serum concentrations of ALP, calcium, and phosphate. Any of the initial parameters found to be outside of established reference ranges prompted a physician referral for assessment and treatment, facilitation of radiographs of wrists and/or knees and an extended laboratory panel (including parathyroid hormone [PTH] and 25(OH)D) that were managed according to the treating physician.

Infant serum calcium, phosphate, and ALP concentrations were measured using quantitative colorimetric assays (Beckman Coulter OSR60117, OSR6122, and OSR6104) at the Clinical Biochemistry Laboratory in Dhaka (icddr,b). Serum 25(OH)D concentrations were measured at the Analytical Facility for Bioactive Molecules (AFBM) in Toronto using high-performance liquid chromatography-tandem mass spectrometry, as previously described. 33 Infant intact PTH concentrations were quantified using a sandwich enzyme-linked immunosorbent assay kit (Immunotopic 60-3100) at AFBM. Clinical management by physicians in Dhaka was informed by local radiologist interpretations of wrist and/or knee radiographs, where available. However, if possible, wrist and/or knee radiographs obtained from children who screened positive for biochemical rickets were further reviewed using a standardized approach by a pediatric radiologist who was blinded to the clinical and laboratory data, as previously described. 20  

Biochemical rickets is marked by an elevated ALP level, which is indicative of increased bone turnover; this is a nearly universal feature of rickets and usually the earliest biochemical abnormality. 34 A common compensatory response to hypocalcemia is an elevation in PTH, which promotes the mobilization of calcium from bones. The development of hypocalcemia and hypophosphatemia may occur as the disease progresses or in the presence of an inadequate PTH response. 35 , 36 However, there are no standardized cutoff points for these biochemical markers that define onset or stages of progression of rickets. Age-specific reference ranges must be used for these biochemical markers; ALP in particular is highly dependent on age and rate of bone growth. Here, we defined “biochemical rickets” as (1) ALP ≥ 450 U/L or (2) ALP ≥ 350 U/L plus at least 1 of the following: calcium ≤ 2.2 mmol/L or phosphate ≤ 1.6 mmol/L or PTH ≥ 6.9 pmol/L. The cutoffs for this definition were consensus-based among investigators. This definition used for analytical purposes differed slightly from the definition used to prompt clinical referral during the MDIG study because PTH was not available in real time as part of the initial screening panel.

Left skewing of ALP was noted with a higher-than-expected proportion of low values; of 790 infants in this substudy, 132 (17%) had ALP <90 U/L. These low values were distributed throughout the study period. Following an extensive review, no preanalytical factors were identified that might have artifactually lowered ALP. The distribution of other biochemical markers analyzed in the same samples were similarly distributed in the low ALP and non–low ALP groups (data not shown), ruling out overdilution as an explanation. Hypercalcemia was not observed in the infants with low ALP, making hereditary hypophosphatasia less likely. Malnutrition is known to decrease ALP production, 37 although we did not find differences in anthropometric parameters (weight for age z -score and height for age z -score at 6 months of age) between the low ALP and non–low ALP groups (data not shown). A set of serum samples ( n = 244) from infants in the MDIG across a wider age range than included in this study was tested at the AFBM laboratory at The Hospital for Sick Children using a different colorimetric assay (Alkaline Phosphatase Colorimetric Assay Kit; ab83369); 8.2% (20/244) were found to have ALP <90 IU/L compared with a frequency of 12% among all samples tested at the Clinical Biochemistry Laboratory (135/1085), suggesting that the high proportion of low values in this cohort was a reproducible finding.

Participant characteristics and biomarker concentrations were expressed as mean ± SD, median (25th and 75th percentiles), or frequencies and percentages. PTH was log-transformed because of right-skewing. Participant demographics across the 5 maternal vitamin D treatment arms were compared using analysis of variance for normally distributed continuous variables, Kruskal-Wallis for nonnormally distributed continuous variables, and χ-squared tests for categorical variables. To estimate the relative risk (RR) of infantile rickets in each prenatal and postnatal maternal vitamin D supplementation group, versus placebo, we used a modified Poisson regression with robust error variance. 38 Planned subgroup analyses included unadjusted regression models stratified by child sex, maternal vitamin D status at randomization (25(OH)D ≥30 nmol/L vs <30 nmol/L), and gestational age (term ≥ 37 weeks), respectively. All point estimates were presented with 95% confidence intervals (95% CI) and P values (α < 0.05 considered statistically significant). Data were analyzed using Stata version 16.1 (StataCorp 2019).

Characteristics of participants included in this substudy were similar across the 5 intervention groups ( Table 1 ), as previously reported for the MDIG trial. 20  

Demographics and Characteristics of Participants, Stratified by Vitamin D Treatment Group

LAZ, length for age z-score; WAZ, weight for age z-score

Maternal prenatal vitamin D supplementation (second trimester to delivery); postnatal maternal supplementation (0–6 mo).

p value for Kruskal Wallis, Pearson χ 2 , or analysis of variance test.

Based on Intergrowth-21 growth standards, by gestational age, within first 48 h of life, n = 566.

Based on Intergrowth-21st growth standards, by gestational age, within first 48 h of life, n = 550.

Ever consumed a vitamin/supplement containing or possibly containing vitamin D from birth to 1 y.

Number of weeks a supplement containing or possibly containing vitamin D was consumed among infants with at least 1 wk of reported consumption from birth to 6 mo of age, median (interquartile range).

A total of 39 cases of biochemical rickets were identified among 790 infants who underwent biochemical screening. Of these 39 cases, 10 met the criteria based on ALP ≥450 U/L alone, 12 had ALP ≥350 U/L and phosphate ≤1.6 mmol/L as the only abnormalities, 14 had ALP ≥350 U/L and intact PTH ≥6.9 pmol/L as the only abnormalities, and 3 had more than 2 abnormalities.

The highest prevalence of rickets (7.9%) was found in the placebo group ( Table 2 ). The lowest prevalence (1.3%) was in the high-dose supplementation group in which mothers received 28 000 IU prenatally and up to 6 months postpartum; this corresponded to a significantly reduced risk of infantile biochemical rickets compared with placebo ( Table 2 ). High-dose vitamin D during the prenatal period alone (4200 IU/week, 16 800 IU/week, and 28 000 IU/week) did not have a significant effect on the risk of rickets, although there were fewer rickets cases identified in each of these groups compared with placebo ( Table 2 ).

RR of Rickets in Each Treatment Arm Compared With Placebo

RR, relative risk.

Poisson regression model with robust error variance used to obtain RR.

In an analysis restricted to infants born to women with baseline 25(OH)D <30 nmol/L during the second trimester of pregnancy ( n = 507), inferences were unchanged ( Fig 1 ). Inferences also remained the same in stratified analysis by sex (males or females), albeit more male than female infants were affected by rickets overall. Inferences remained the same when analysis was restricted to infants born at term ( ⁠ ≥ 37 weeks’ gestation) ( Supplemental Tables 3 – 5 ).

The relative risk of biochemical rickets among varying doses of maternal prenatal and postpartum vitamin D supplementation compared with placebo using modified Poisson regression (blue bars). Subgroup analysis assessing the effect of maternal vitamin D supplementation on infantile rickets among women with vitamin D deficiency (25(OH)D <30 nmol) at baseline ( n = 507). The circles represent the effect estimates, with 95% confidence interval (CI) bars.

Serum calcium concentrations were highest in the combined supplementation group and lowest in the placebo group; however, these differences were not statistically significant ( Supplemental Fig 4 ). Phosphate concentrations were significantly higher and ALP concentrations were significantly lower in the combined supplementation group compared with placebo ( Supplemental Fig 4 ).

Of the 39 infants with biochemical rickets, 16 had radiographs of the wrist and/or knee available for review by the SickKids radiologist, of whom 4 were found to have radiographic findings of rickets, as previously reported. 20 Three of the 4 infants were in the placebo group, and the fourth was in the group administered 4200 IU/week prenatally. Mean ALP was higher at presentation for these infants, at 705 U/L, compared with mean 439 U/L for the other infants with biochemical rickets. All 4 infants were hypophosphatemic (serum phosphate <1.56 mmol/), and 1 was hypocalcemic (serum calcium <2.1 mmol/L). Radiographs were not available for all infants with biochemical rickets. In large part, this was because infants who met criteria of ALP ≥ 350 U/L and PTH ≥ 6.9 pmol/L were not flagged for imaging because PTH was not available in real time as part of the initial screening panels.

Combined prenatal and postpartum maternal supplementation (28 000; 28 000 IU/week) decreased the risk of biochemical rickets compared with placebo among infants 6 to 12 months of age. However, maternal prenatal supplementation alone at any dose, without postpartum continuation, did not significantly decrease the risk of biochemical rickets. Prenatal maternal vitamin D supplementation influences early postnatal infant 25(OH)D, but postpartum continuation was required to maintain 25(OH)D ≥30 nmol/L up to 6 months of age, as previously reported in the MDIG trial ( Supplemental Fig 3 ). 20 Therefore, the present findings strongly support the hypothesis that vitamin D deficiency (marked by inadequate circulating 25(OH)D), is an important cause of biochemical rickets in this infant population. As previously reported, all the cases of radiographically confirmed rickets were in the placebo and lowest-dose prenatal supplementation (4200 IU weekly prenatally) groups, further supporting the potential role of vitamin D in rickets prevention. However, we cannot rule out other causes of rickets in this setting; moreover, most infants with 25(OH)D <30 nmol/L did not have biochemical rickets, indicating that other contributing factors act in concert with vitamin D deficiency.

There were relatively more male infants affected by biochemical rickets in our study. It has been speculated that rickets may occur more frequently in boys because of greater linear bone growth and increased skeletal demands during times of rapid growth. Although not seen consistently, this phenomenon has been noted in several studies evaluating rickets in infancy. 39 , – 41 The present findings are consistent with evidence from 2 smaller randomized trials in India that previously found that there were fewer cases of biochemical rickets among infants of mothers who received postpartum supplementation. 27 , 28 Although it has been well established that infant 25(OH)D status can be influenced by maternal supplementation during lactation, the dose-response relationship remains uncertain. 24 , 42 Human milk is considered a poor source of vitamin D3 unless the lactating woman has high amount of vitamin D intake. 43 The transfer of the vitamin D parent compound (vitamin D3) is favored over 25(OH)D in the mammary gland, suggesting that the vitamin D concentration of breast milk is primarily affected by maternal vitamin D intake or cutaneous synthesis rather than maternal vitamin D status (ie, circulating 25(OH)D). 44 , 45 This distinction is important because the short half-life of vitamin D3 (12–24 hours) implies that an analogous dose of vitamin D is consumed by the infant soon after the corresponding maternal ingestion. 46 However, low daily doses of maternal vitamin D supplementation may not achieve sufficiently high circulating levels of vitamin D in breast milk to impact infant 25(OH)D, even if they prevent maternal vitamin D deficiency. 47 High-dose maternal supplementation, often greater than the Institute of Medicine–recommended upper limit of 4000 IU/day, 48 has been previously shown to have similar effects on breastfeeding infant 25(OH)D as daily infant vitamin D supplementation. 42 , 49 , 50 Further research involving direct comparison of various doses, including daily maternal dosing compared with intermittent weekly or bolus dosing regimens, is required to determine the minimum effective maternal postpartum dose to maintain 25(OH)D sufficiency in infants and in turn minimize the risk of rickets.

A strength of this study is that the randomized, dose-ranging, placebo-controlled design of the MDIG trial and the lack of routine infant supplementation permitted causal inferences regarding the effects of maternal vitamin D supplementation on the risk of biochemical rickets. However, several limitations of the study should be acknowledged. This is a substudy of a previous trial; the mother and infant pairs included were selected from the existing MDIG cohort based on data availability, which may have compromised the generalizability of the findings. Although the participants in this substudy were similar to the remainder of the MDIG cohort, it is possible that this cohort was not fully representative of the mothers and infants in the MDIG trial or of the general population in Dhaka. The biochemical case definition was useful for identifying early disease because infants with rickets may present without skeletal abnormalities; however, we lacked complete radiographic information for all the infants who met biochemical rickets criteria, and the longer term clinical significance of infantile biochemical rickets is uncertain. Because the diagnosis of biochemical rickets was based on cross-sectional biochemical evaluation starting at 6 months of age, we were unable to determine the precise age of onset of the abnormalities. Furthermore, a greater number of infants screened late in infancy or at older ages might have enabled us to describe the natural history of this process in the absence of routine supplementation or vitamin D treatment of those who screened positive in early infancy.

High-dose maternal postpartum vitamin D supplementation may serve as a viable public health strategy for rickets prevention by effectively increasing infant 25(OH)D status in conjunction with efforts to promote breastfeeding. Other low- and middle-income countries in South Asia that have similar burdens of maternal and infant vitamin D deficiency and do not have vitamin D supplementation programs could benefit from this strategy. Future studies should include comparisons of different doses of maternal postpartum supplementation and longer term follow-up including radiologic assessments and clinical outcomes.

We thank Huma Qamar of The Global Centre for Child Health, The Hospital for Sick Children, for her assistance with data organization and Talia Wolfe, former summer student at The Global Centre for Child Health, The Hospital for Sick Children, for her work on the initial data analysis.

Dr Roth is the principal investigator, conceptualized, designed, and supervised the study, drafted the initial manuscript, and critically reviewed and revised the manuscript; Dr Lautatzis designed the study, performed statistical analysis, drafted the initial manuscript, and critically reviewed and revised the manuscript; Dr Al Mahmud supervised data collection and field study activities in Dhaka and critically reviewed and revised the manuscript; Drs Ahmed and Keya contributed to local implementation of the study and data collection in Dhaka, and critically reviewed and revised the manuscript; Ms Tariq contributed to study design, performed statistical analysis, drafted the initial manuscript, and critically reviewed and revised the manuscript; Dr Harrington, Dr Zlotkin, Dr Lam, and Dr Morris contributed to study design, and critically reviewed and revised the manuscript; Dr Stimec provided expert review of radiographic data and critically reviewed and revised the manuscript; and all authors read and approved the final manuscript and agree to be accountable for all aspects of the work. The authors report no conflicts of interest or financial relationships relevant to this article to disclose.

Clinical Trial Registration: This trial has been registered at www.clinicaltrials.gov (identifier NCT01924013).

25-hydroxyvitamin D

95% confidence interval

Analytical Facility for Bioactive Molecules

alkaline phosphatase

Maternal Vitamin D for Infant Growth

parathyroid hormone

relative risk

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• About Adverse Childhood Experiences
• Risk and Protective Factors
• Program: Essentials for Childhood: Preventing Adverse Childhood Experiences through Data to Action
• Adverse childhood experiences can have long-term impacts on health, opportunity and well-being.
• Adverse childhood experiences are common and some groups experience them more than others.

What are adverse childhood experiences?

Adverse childhood experiences, or ACEs, are potentially traumatic events that occur in childhood (0-17 years). Examples include: 1

• Experiencing violence, abuse, or neglect.
• Witnessing violence in the home or community.
• Having a family member attempt or die by suicide.

Also included are aspects of the child’s environment that can undermine their sense of safety, stability, and bonding. Examples can include growing up in a household with: 1

• Substance use problems.
• Mental health problems.
• Instability due to parental separation.
• Instability due to household members being in jail or prison.

The examples above are not a complete list of adverse experiences. Many other traumatic experiences could impact health and well-being. This can include not having enough food to eat, experiencing homelessness or unstable housing, or experiencing discrimination. 2 3 4 5 6

Quick facts and stats

ACEs are common. About 64% of adults in the United States reported they had experienced at least one type of ACE before age 18. Nearly one in six (17.3%) adults reported they had experienced four or more types of ACEs. 7

Preventing ACEs could potentially reduce many health conditions. Estimates show up to 1.9 million heart disease cases and 21 million depression cases potentially could have been avoided by preventing ACEs. 1

Some people are at greater risk of experiencing one or more ACEs than others. While all children are at risk of ACEs, numerous studies show inequities in such experiences. These inequalities are linked to the historical, social, and economic environments in which some families live. 5 6 ACEs were highest among females, non-Hispanic American Indian or Alaska Native adults, and adults who are unemployed or unable to work. 7

ACEs are costly. ACEs-related health consequences cost an estimated economic burden of $748 billion annually in Bermuda, Canada, and the United States. 8

ACEs can have lasting effects on health and well-being in childhood and life opportunities well into adulthood. 9 Life opportunities include things like education and job potential. These experiences can increase the risks of injury, sexually transmitted infections, and involvement in sex trafficking. They can also increase risks for maternal and child health problems including teen pregnancy, pregnancy complications, and fetal death. Also included are a range of chronic diseases and leading causes of death, such as cancer, diabetes, heart disease, and suicide. 1 10 11 12 13 14 15 16 17

ACEs and associated social determinants of health, such as living in under-resourced or racially segregated neighborhoods, can cause toxic stress. Toxic stress, or extended or prolonged stress, from ACEs can negatively affect children’s brain development, immune systems, and stress-response systems. These changes can affect children’s attention, decision-making, and learning. 18

Children growing up with toxic stress may have difficulty forming healthy and stable relationships. They may also have unstable work histories as adults and struggle with finances, jobs, and depression throughout life. 18 These effects can also be passed on to their own children. 19 20 21 Some children may face further exposure to toxic stress from historical and ongoing traumas. These historical and ongoing traumas refer to experiences of racial discrimination or the impacts of poverty resulting from limited educational and economic opportunities. 1 6

Adverse childhood experiences can be prevented. Certain factors may increase or decrease the risk of experiencing adverse childhood experiences.

Preventing adverse childhood experiences requires understanding and addressing the factors that put people at risk for or protect them from violence.

Creating safe, stable, nurturing relationships and environments for all children can prevent ACEs and help all children reach their full potential. We all have a role to play.

• Merrick MT, Ford DC, Ports KA, et al. Vital Signs: Estimated Proportion of Adult Health Problems Attributable to Adverse Childhood Experiences and Implications for Prevention — 25 States, 2015–2017. MMWR Morb Mortal Wkly Rep 2019;68:999-1005. DOI: http://dx.doi.org/10.15585/mmwr.mm6844e1 .
• Cain KS, Meyer SC, Cummer E, Patel KK, Casacchia NJ, Montez K, Palakshappa D, Brown CL. Association of Food Insecurity with Mental Health Outcomes in Parents and Children. Science Direct. 2022; 22:7; 1105-1114. DOI: https://doi.org/10.1016/j.acap.2022.04.010 .
• Smith-Grant J, Kilmer G, Brener N, Robin L, Underwood M. Risk Behaviors and Experiences Among Youth Experiencing Homelessness—Youth Risk Behavior Survey, 23 U.S. States and 11 Local School Districts. Journal of Community Health. 2022; 47: 324-333.
• Experiencing discrimination: Early Childhood Adversity, Toxic Stress, and the Impacts of Racism on the Foundations of Health | Annual Review of Public Health https://doi.org/10.1146/annurev-publhealth-090419-101940 .
• Sedlak A, Mettenburg J, Basena M, et al. Fourth national incidence study of child abuse and neglect (NIS-4): Report to Congress. Executive Summary. Washington, DC: U.S. Department of Health an Human Services, Administration for Children and Families.; 2010.
• Font S, Maguire-Jack K. Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse Negl. 2016;51:390-399.
• Swedo EA, Aslam MV, Dahlberg LL, et al. Prevalence of Adverse Childhood Experiences Among U.S. Adults — Behavioral Risk Factor Surveillance System, 2011–2020. MMWR Morb Mortal Wkly Rep 2023;72:707–715. DOI: http://dx.doi.org/10.15585/mmwr.mm7226a2 .
• Bellis, MA, et al. Life Course Health Consequences and Associated Annual Costs of Adverse Childhood Experiences Across Europe and North America: A Systematic Review and Meta-Analysis. Lancet Public Health 2019.
• Adverse Childhood Experiences During the COVID-19 Pandemic and Associations with Poor Mental Health and Suicidal Behaviors Among High School Students — Adolescent Behaviors and Experiences Survey, United States, January–June 2021 | MMWR
• Hillis SD, Anda RF, Dube SR, Felitti VJ, Marchbanks PA, Marks JS. The association between adverse childhood experiences and adolescent pregnancy, long-term psychosocial consequences, and fetal death. Pediatrics. 2004 Feb;113(2):320-7.
• Miller ES, Fleming O, Ekpe EE, Grobman WA, Heard-Garris N. Association Between Adverse Childhood Experiences and Adverse Pregnancy Outcomes. Obstetrics & Gynecology . 2021;138(5):770-776. https://doi.org/10.1097/AOG.0000000000004570 .
• Sulaiman S, Premji SS, Tavangar F, et al. Total Adverse Childhood Experiences and Preterm Birth: A Systematic Review. Matern Child Health J . 2021;25(10):1581-1594. https://doi.org/10.1007/s10995-021-03176-6 .
• Ciciolla L, Shreffler KM, Tiemeyer S. Maternal Childhood Adversity as a Risk for Perinatal Complications and NICU Hospitalization. Journal of Pediatric Psychology . 2021;46(7):801-813. https://doi.org/10.1093/jpepsy/jsab027 .
• Mersky JP, Lee CP. Adverse childhood experiences and poor birth outcomes in a diverse, low-income sample. BMC pregnancy and childbirth. 2019;19(1). https://doi.org/10.1186/s12884-019-2560-8 .
• Reid JA, Baglivio MT, Piquero AR, Greenwald MA, Epps N. No youth left behind to human trafficking: Exploring profiles of risk. American journal of orthopsychiatry. 2019;89(6):704.
• Diamond-Welch B, Kosloski AE. Adverse childhood experiences and propensity to participate in the commercialized sex market. Child Abuse & Neglect. 2020 Jun 1;104:104468.
• Shonkoff, J. P., Garner, A. S., Committee on Psychosocial Aspects of Child and Family Health, Committee on Early Childhood, Adoption, and Dependent Care, & Section on Developmental and Behavioral Pediatrics (2012). The lifelong effects of early childhood adversity and toxic stress. Pediatrics, 129(1), e232–e246. https://doi.org/10.1542/peds.2011-2663
• Narayan AJ, Kalstabakken AW, Labella MH, Nerenberg LS, Monn AR, Masten AS. Intergenerational continuity of adverse childhood experiences in homeless families: unpacking exposure to maltreatment versus family dysfunction. Am J Orthopsych. 2017;87(1):3. https://doi.org/10.1037/ort0000133 .
• Schofield TJ, Donnellan MB, Merrick MT, Ports KA, Klevens J, Leeb R. Intergenerational continuity in adverse childhood experiences and rural community environments. Am J Public Health. 2018;108(9):1148-1152. https://doi.org/10.2105/AJPH.2018.304598 .
• Schofield TJ, Lee RD, Merrick MT. Safe, stable, nurturing relationships as a moderator of intergenerational continuity of child maltreatment: a meta-analysis. J Adolesc Health. 2013;53(4 Suppl):S32-38. https://doi.org/10.1016/j.jadohealth.2013.05.004 .

Adverse Childhood Experiences (ACEs)

ACEs can have a tremendous impact on lifelong health and opportunity. CDC works to understand ACEs and prevent them.

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Publications

Sensitivity of the pseudo-global warming method under flood conditions: a case study from the northeastern us.

Intensified extreme precipitation and corresponding floods are the most relevant consequences of climate change over the northeastern US (NEUS). To evaluate the impacts of climate change or certain climate perturbations on future extreme weather events which are dynamically similar to historic analogs, the pseudo-global warming (PGW) method has been frequently employed; however, this method lacks precise definition and guidelines, thus limiting its application. More specifically, three key questions related to the application of the PGW method remain unanswered: at what spatial scale should climate perturbations be applied? Among the different meteorological variables available, which ones should be perturbed? And will PGW projections vary significantly when different perturbations are applied? To address these questions, we examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments with varied perturbation spatial scales and choice of perturbed meteorological variables. The results show that the projections of precipitation and other essential variables at the regional mean scale are consistent across the PGW simulations, with a relative difference of much less than 10 %; however, different perturbation modifications can cause significant displacements of the storm events being simulated. Several previously assumed advantages of modifying only the temperature at regional mean scale, such as the preservation of geostrophic balance, do not appear to hold. Also, for these experiments, we find the regional mean perturbation produces a positive precipitation bias because it ignores the land–ocean warming contrast, which is a robust regional response to global warming. Overall, PGW experiments with perturbations from temperature or the combination of temperature and wind at the grid point scale are both recommended, depending on the research questions. The first approach can isolate the spatially dependent thermodynamic impact, and the latter incorporates both the thermodynamic and dynamic impacts.