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Case Study – Methods, Examples and Guide

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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 case study research?

Last updated

8 February 2023

Reviewed by

Cathy Heath

Short on time? Get an AI generated summary of this article instead

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

Organization

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

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

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

Analyze case study research

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• What are the different types of case study designs?

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

Here are the common types of case study design:

Explanatory

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

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

Descriptive

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

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

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

Exploratory

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

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

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

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

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

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

Critical instance

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

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

Instrumental

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

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

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

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

• When do you use case studies?

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

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

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

1. Select a case

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

2. Create a theoretical framework

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

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

3. Collect the data

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

4. Analyze your case

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

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

• What are some case study examples?

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

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

How can teachers enhance student participation in classrooms?

How does poverty affect literacy levels in children?

Case study topics

Case study of product marketing strategies in the Kenyan market

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

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

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

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Organizing Your Social Sciences Research Assignments

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

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

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

How to Approach Writing a Case Study Research Paper

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

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

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

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

Structure and Writing Style

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

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

I.  Introduction

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

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

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

II.  Literature Review

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

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

III.  Method

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

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

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

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

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

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

IV.  Discussion

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

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

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

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

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

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

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

V.  Conclusion

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

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

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

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

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

Problems to Avoid

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

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

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

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

Writing Tip

At Least Five Misconceptions about Case Study Research

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

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

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

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

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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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• Research Alignment Chapter 1 This link opens in a new window
• Step 1: Seek Out Evidence
• Step 2: Explain
• Step 3: The Big Picture
• Step 4: Own It
• Step 5: Illustrate
• Annotated Bibliography
• Literature Review This link opens in a new window
• Systematic Reviews & Meta-Analyses
• How to Synthesize and Analyze
• Synthesis and Analysis Practice
• Synthesis and Analysis Group Sessions
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Locating Theoretical and Conceptual Frameworks This link opens in a new window
• Quantitative Research Questions
• Qualitative Research Questions
• Trustworthiness of Qualitative Data
• Analysis and Coding Example- Qualitative Data
• Thematic Data Analysis in Qualitative Design
• Dissertation to Journal Article This link opens in a new window
• International Journal of Online Graduate Education (IJOGE) This link opens in a new window
• Journal of Research in Innovative Teaching & Learning (JRIT&L) This link opens in a new window

Writing a Case Study

What is a case study?

A Case study is: 

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

What are the different types of case studies?

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

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

Who are your case study participants?

What is triangulation ? 

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

How to write a Case Study?

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

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Designing and Conducting Case Studies

This guide examines case studies, a form of qualitative descriptive research that is used to look at individuals, a small group of participants, or a group as a whole. Researchers collect data about participants using participant and direct observations, interviews, protocols, tests, examinations of records, and collections of writing samples. Starting with a definition of the case study, the guide moves to a brief history of this research method. Using several well documented case studies, the guide then looks at applications and methods including data collection and analysis. A discussion of ways to handle validity, reliability, and generalizability follows, with special attention to case studies as they are applied to composition studies. Finally, this guide examines the strengths and weaknesses of case studies.

Definition and Overview

Case study refers to the collection and presentation of detailed information about a particular participant or small group, frequently including the accounts of subjects themselves. A form of qualitative descriptive research, the case study looks intensely at an individual or small participant pool, drawing conclusions only about that participant or group and only in that specific context. Researchers do not focus on the discovery of a universal, generalizable truth, nor do they typically look for cause-effect relationships; instead, emphasis is placed on exploration and description.

Case studies typically examine the interplay of all variables in order to provide as complete an understanding of an event or situation as possible. This type of comprehensive understanding is arrived at through a process known as thick description, which involves an in-depth description of the entity being evaluated, the circumstances under which it is used, the characteristics of the people involved in it, and the nature of the community in which it is located. Thick description also involves interpreting the meaning of demographic and descriptive data such as cultural norms and mores, community values, ingrained attitudes, and motives.

Unlike quantitative methods of research, like the survey, which focus on the questions of who, what, where, how much, and how many, and archival analysis, which often situates the participant in some form of historical context, case studies are the preferred strategy when how or why questions are asked. Likewise, they are the preferred method when the researcher has little control over the events, and when there is a contemporary focus within a real life context. In addition, unlike more specifically directed experiments, case studies require a problem that seeks a holistic understanding of the event or situation in question using inductive logic--reasoning from specific to more general terms.

In scholarly circles, case studies are frequently discussed within the context of qualitative research and naturalistic inquiry. Case studies are often referred to interchangeably with ethnography, field study, and participant observation. The underlying philosophical assumptions in the case are similar to these types of qualitative research because each takes place in a natural setting (such as a classroom, neighborhood, or private home), and strives for a more holistic interpretation of the event or situation under study.

Unlike more statistically-based studies which search for quantifiable data, the goal of a case study is to offer new variables and questions for further research. F.H. Giddings, a sociologist in the early part of the century, compares statistical methods to the case study on the basis that the former are concerned with the distribution of a particular trait, or a small number of traits, in a population, whereas the case study is concerned with the whole variety of traits to be found in a particular instance" (Hammersley 95).

Case studies are not a new form of research; naturalistic inquiry was the primary research tool until the development of the scientific method. The fields of sociology and anthropology are credited with the primary shaping of the concept as we know it today. However, case study research has drawn from a number of other areas as well: the clinical methods of doctors; the casework technique being developed by social workers; the methods of historians and anthropologists, plus the qualitative descriptions provided by quantitative researchers like LePlay; and, in the case of Robert Park, the techniques of newspaper reporters and novelists.

Park was an ex-newspaper reporter and editor who became very influential in developing sociological case studies at the University of Chicago in the 1920s. As a newspaper professional he coined the term "scientific" or "depth" reporting: the description of local events in a way that pointed to major social trends. Park viewed the sociologist as "merely a more accurate, responsible, and scientific reporter." Park stressed the variety and value of human experience. He believed that sociology sought to arrive at natural, but fluid, laws and generalizations in regard to human nature and society. These laws weren't static laws of the kind sought by many positivists and natural law theorists, but rather, they were laws of becoming--with a constant possibility of change. Park encouraged students to get out of the library, to quit looking at papers and books, and to view the constant experiment of human experience. He writes, "Go and sit in the lounges of the luxury hotels and on the doorsteps of the flophouses; sit on the Gold Coast settees and on the slum shakedowns; sit in the Orchestra Hall and in the Star and Garter Burlesque. In short, gentlemen [sic], go get the seats of your pants dirty in real research."

But over the years, case studies have drawn their share of criticism. In fact, the method had its detractors from the start. In the 1920s, the debate between pro-qualitative and pro-quantitative became quite heated. Case studies, when compared to statistics, were considered by many to be unscientific. From the 1930's on, the rise of positivism had a growing influence on quantitative methods in sociology. People wanted static, generalizable laws in science. The sociological positivists were looking for stable laws of social phenomena. They criticized case study research because it failed to provide evidence of inter subjective agreement. Also, they condemned it because of the few number of cases studied and that the under-standardized character of their descriptions made generalization impossible. By the 1950s, quantitative methods, in the form of survey research, had become the dominant sociological approach and case study had become a minority practice.

Educational Applications

The 1950's marked the dawning of a new era in case study research, namely that of the utilization of the case study as a teaching method. "Instituted at Harvard Business School in the 1950s as a primary method of teaching, cases have since been used in classrooms and lecture halls alike, either as part of a course of study or as the main focus of the course to which other teaching material is added" (Armisted 1984). The basic purpose of instituting the case method as a teaching strategy was "to transfer much of the responsibility for learning from the teacher on to the student, whose role, as a result, shifts away from passive absorption toward active construction" (Boehrer 1990). Through careful examination and discussion of various cases, "students learn to identify actual problems, to recognize key players and their agendas, and to become aware of those aspects of the situation that contribute to the problem" (Merseth 1991). In addition, students are encouraged to "generate their own analysis of the problems under consideration, to develop their own solutions, and to practically apply their own knowledge of theory to these problems" (Boyce 1993). Along the way, students also develop "the power to analyze and to master a tangled circumstance by identifying and delineating important factors; the ability to utilize ideas, to test them against facts, and to throw them into fresh combinations" (Merseth 1991).

In addition to the practical application and testing of scholarly knowledge, case discussions can also help students prepare for real-world problems, situations and crises by providing an approximation of various professional environments (i.e. classroom, board room, courtroom, or hospital). Thus, through the examination of specific cases, students are given the opportunity to work out their own professional issues through the trials, tribulations, experiences, and research findings of others. An obvious advantage to this mode of instruction is that it allows students the exposure to settings and contexts that they might not otherwise experience. For example, a student interested in studying the effects of poverty on minority secondary student's grade point averages and S.A.T. scores could access and analyze information from schools as geographically diverse as Los Angeles, New York City, Miami, and New Mexico without ever having to leave the classroom.

The case study method also incorporates the idea that students can learn from one another "by engaging with each other and with each other's ideas, by asserting something and then having it questioned, challenged and thrown back at them so that they can reflect on what they hear, and then refine what they say" (Boehrer 1990). In summary, students can direct their own learning by formulating questions and taking responsibility for the study.

Types and Design Concerns

Researchers use multiple methods and approaches to conduct case studies.

Types of Case Studies

Under the more generalized category of case study exist several subdivisions, each of which is custom selected for use depending upon the goals and/or objectives of the investigator. These types of case study include the following:

Illustrative Case Studies These are primarily descriptive studies. They typically utilize one or two instances of an event to show what a situation is like. Illustrative case studies serve primarily to make the unfamiliar familiar and to give readers a common language about the topic in question.

Exploratory (or pilot) Case Studies These are condensed case studies performed before implementing a large scale investigation. Their basic function is to help identify questions and select types of measurement prior to the main investigation. The primary pitfall of this type of study is that initial findings may seem convincing enough to be released prematurely as conclusions.

Cumulative Case Studies These serve to aggregate information from several sites collected at different times. The idea behind these studies is the collection of past studies will allow for greater generalization without additional cost or time being expended on new, possibly repetitive studies.

Critical Instance Case Studies These examine one or more sites for either the purpose of examining a situation of unique interest with little to no interest in generalizability, or to call into question or challenge a highly generalized or universal assertion. This method is useful for answering cause and effect questions.

Identifying a Theoretical Perspective

Much of the case study's design is inherently determined for researchers, depending on the field from which they are working. In composition studies, researchers are typically working from a qualitative, descriptive standpoint. In contrast, physicists will approach their research from a more quantitative perspective. Still, in designing the study, researchers need to make explicit the questions to be explored and the theoretical perspective from which they will approach the case. The three most commonly adopted theories are listed below:

Individual Theories These focus primarily on the individual development, cognitive behavior, personality, learning and disability, and interpersonal interactions of a particular subject.

Organizational Theories These focus on bureaucracies, institutions, organizational structure and functions, or excellence in organizational performance.

Social Theories These focus on urban development, group behavior, cultural institutions, or marketplace functions.

Two examples of case studies are used consistently throughout this chapter. The first, a study produced by Berkenkotter, Huckin, and Ackerman (1988), looks at a first year graduate student's initiation into an academic writing program. The study uses participant-observer and linguistic data collecting techniques to assess the student's knowledge of appropriate discourse conventions. Using the pseudonym Nate to refer to the subject, the study sought to illuminate the particular experience rather than to generalize about the experience of fledgling academic writers collectively.

For example, in Berkenkotter, Huckin, and Ackerman's (1988) study we are told that the researchers are interested in disciplinary communities. In the first paragraph, they ask what constitutes membership in a disciplinary community and how achieving membership might affect a writer's understanding and production of texts. In the third paragraph they state that researchers must negotiate their claims "within the context of his sub specialty's accepted knowledge and methodology." In the next paragraph they ask, "How is literacy acquired? What is the process through which novices gain community membership? And what factors either aid or hinder students learning the requisite linguistic behaviors?" This introductory section ends with a paragraph in which the study's authors claim that during the course of the study, the subject, Nate, successfully makes the transition from "skilled novice" to become an initiated member of the academic discourse community and that his texts exhibit linguistic changes which indicate this transition. In the next section the authors make explicit the sociolinguistic theoretical and methodological assumptions on which the study is based (1988). Thus the reader has a good understanding of the authors' theoretical background and purpose in conducting the study even before it is explicitly stated on the fourth page of the study. "Our purpose was to examine the effects of the educational context on one graduate student's production of texts as he wrote in different courses and for different faculty members over the academic year 1984-85." The goal of the study then, was to explore the idea that writers must be initiated into a writing community, and that this initiation will change the way one writes.

The second example is Janet Emig's (1971) study of the composing process of a group of twelfth graders. In this study, Emig seeks to answer the question of what happens to the self as a result educational stimuli in terms of academic writing. The case study used methods such as protocol analysis, tape-recorded interviews, and discourse analysis.

In the case of Janet Emig's (1971) study of the composing process of eight twelfth graders, four specific hypotheses were made:

• Twelfth grade writers engage in two modes of composing: reflexive and extensive.
• These differences can be ascertained and characterized through having the writers compose aloud their composition process.
• A set of implied stylistic principles governs the writing process.
• For twelfth grade writers, extensive writing occurs chiefly as a school-sponsored activity, or reflexive, as a self-sponsored activity.

In this study, the chief distinction is between the two dominant modes of composing among older, secondary school students. The distinctions are:

• The reflexive mode, which focuses on the writer's thoughts and feelings.
• The extensive mode, which focuses on conveying a message.

Emig also outlines the specific questions which guided the research in the opening pages of her Review of Literature , preceding the report.

Designing a Case Study

After considering the different sub categories of case study and identifying a theoretical perspective, researchers can begin to design their study. Research design is the string of logic that ultimately links the data to be collected and the conclusions to be drawn to the initial questions of the study. Typically, research designs deal with at least four problems:

• What questions to study
• What data are relevant
• What data to collect
• How to analyze that data

In other words, a research design is basically a blueprint for getting from the beginning to the end of a study. The beginning is an initial set of questions to be answered, and the end is some set of conclusions about those questions.

Because case studies are conducted on topics as diverse as Anglo-Saxon Literature (Thrane 1986) and AIDS prevention (Van Vugt 1994), it is virtually impossible to outline any strict or universal method or design for conducting the case study. However, Robert K. Yin (1993) does offer five basic components of a research design:

• A study's questions.
• A study's propositions (if any).
• A study's units of analysis.
• The logic that links the data to the propositions.
• The criteria for interpreting the findings.

In addition to these five basic components, Yin also stresses the importance of clearly articulating one's theoretical perspective, determining the goals of the study, selecting one's subject(s), selecting the appropriate method(s) of collecting data, and providing some considerations to the composition of the final report.

Conducting Case Studies

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of approaches and methods. These approaches, methods, and related issues are discussed in depth in this section.

Method: Single or Multi-modal?

To obtain as complete a picture of the participant as possible, case study researchers can employ a variety of methods. Some common methods include interviews , protocol analyses, field studies, and participant-observations. Emig (1971) chose to use several methods of data collection. Her sources included conversations with the students, protocol analysis, discrete observations of actual composition, writing samples from each student, and school records (Lauer and Asher 1988).

Berkenkotter, Huckin, and Ackerman (1988) collected data by observing classrooms, conducting faculty and student interviews, collecting self reports from the subject, and by looking at the subject's written work.

A study that was criticized for using a single method model was done by Flower and Hayes (1984). In this study that explores the ways in which writers use different forms of knowing to create space, the authors used only protocol analysis to gather data. The study came under heavy fire because of their decision to use only one method.

Participant Selection

Case studies can use one participant, or a small group of participants. However, it is important that the participant pool remain relatively small. The participants can represent a diverse cross section of society, but this isn't necessary.

For example, the Berkenkotter, Huckin, and Ackerman (1988) study looked at just one participant, Nate. By contrast, in Janet Emig's (1971) study of the composition process of twelfth graders, eight participants were selected representing a diverse cross section of the community, with volunteers from an all-white upper-middle-class suburban school, an all-black inner-city school, a racially mixed lower-middle-class school, an economically and racially mixed school, and a university school.

Often, a brief "case history" is done on the participants of the study in order to provide researchers with a clearer understanding of their participants, as well as some insight as to how their own personal histories might affect the outcome of the study. For instance, in Emig's study, the investigator had access to the school records of five of the participants, and to standardized test scores for the remaining three. Also made available to the researcher was the information that three of the eight students were selected as NCTE Achievement Award winners. These personal histories can be useful in later stages of the study when data are being analyzed and conclusions drawn.

Data Collection

There are six types of data collected in case studies:

• Archival records.
• Interviews.
• Direct observation.
• Participant observation.

In the field of composition research, these six sources might be:

• A writer's drafts.
• School records of student writers.
• Transcripts of interviews with a writer.
• Transcripts of conversations between writers (and protocols).
• Videotapes and notes from direct field observations.
• Hard copies of a writer's work on computer.

Depending on whether researchers have chosen to use a single or multi-modal approach for the case study, they may choose to collect data from one or any combination of these sources.

Protocols, that is, transcriptions of participants talking aloud about what they are doing as they do it, have been particularly common in composition case studies. For example, in Emig's (1971) study, the students were asked, in four different sessions, to give oral autobiographies of their writing experiences and to compose aloud three themes in the presence of a tape recorder and the investigator.

In some studies, only one method of data collection is conducted. For example, the Flower and Hayes (1981) report on the cognitive process theory of writing depends on protocol analysis alone. However, using multiple sources of evidence to increase the reliability and validity of the data can be advantageous.

Case studies are likely to be much more convincing and accurate if they are based on several different sources of information, following a corroborating mode. This conclusion is echoed among many composition researchers. For example, in her study of predrafting processes of high and low-apprehensive writers, Cynthia Selfe (1985) argues that because "methods of indirect observation provide only an incomplete reflection of the complex set of processes involved in composing, a combination of several such methods should be used to gather data in any one study." Thus, in this study, Selfe collected her data from protocols, observations of students role playing their writing processes, audio taped interviews with the students, and videotaped observations of the students in the process of composing.

It can be said then, that cross checking data from multiple sources can help provide a multidimensional profile of composing activities in a particular setting. Sharan Merriam (1985) suggests "checking, verifying, testing, probing, and confirming collected data as you go, arguing that this process will follow in a funnel-like design resulting in less data gathering in later phases of the study along with a congruent increase in analysis checking, verifying, and confirming."

It is important to note that in case studies, as in any qualitative descriptive research, while researchers begin their studies with one or several questions driving the inquiry (which influence the key factors the researcher will be looking for during data collection), a researcher may find new key factors emerging during data collection. These might be unexpected patterns or linguistic features which become evident only during the course of the research. While not bearing directly on the researcher's guiding questions, these variables may become the basis for new questions asked at the end of the report, thus linking to the possibility of further research.

Data Analysis

As the information is collected, researchers strive to make sense of their data. Generally, researchers interpret their data in one of two ways: holistically or through coding. Holistic analysis does not attempt to break the evidence into parts, but rather to draw conclusions based on the text as a whole. Flower and Hayes (1981), for example, make inferences from entire sections of their students' protocols, rather than searching through the transcripts to look for isolatable characteristics.

However, composition researchers commonly interpret their data by coding, that is by systematically searching data to identify and/or categorize specific observable actions or characteristics. These observable actions then become the key variables in the study. Sharan Merriam (1988) suggests seven analytic frameworks for the organization and presentation of data:

• The role of participants.
• The network analysis of formal and informal exchanges among groups.
• Historical.
• Thematical.
• Ritual and symbolism.
• Critical incidents that challenge or reinforce fundamental beliefs, practices, and values.

There are two purposes of these frameworks: to look for patterns among the data and to look for patterns that give meaning to the case study.

As stated above, while most researchers begin their case studies expecting to look for particular observable characteristics, it is not unusual for key variables to emerge during data collection. Typical variables coded in case studies of writers include pauses writers make in the production of a text, the use of specific linguistic units (such as nouns or verbs), and writing processes (planning, drafting, revising, and editing). In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, researchers coded the participant's texts for use of connectives, discourse demonstratives, average sentence length, off-register words, use of the first person pronoun, and the ratio of definite articles to indefinite articles.

Since coding is inherently subjective, more than one coder is usually employed. In the Berkenkotter, Huckin, and Ackerman (1988) study, for example, three rhetoricians were employed to code the participant's texts for off-register phrases. The researchers established the agreement among the coders before concluding that the participant used fewer off-register words as the graduate program progressed.

Composing the Case Study Report

In the many forms it can take, "a case study is generically a story; it presents the concrete narrative detail of actual, or at least realistic events, it has a plot, exposition, characters, and sometimes even dialogue" (Boehrer 1990). Generally, case study reports are extensively descriptive, with "the most problematic issue often referred to as being the determination of the right combination of description and analysis" (1990). Typically, authors address each step of the research process, and attempt to give the reader as much context as possible for the decisions made in the research design and for the conclusions drawn.

This contextualization usually includes a detailed explanation of the researchers' theoretical positions, of how those theories drove the inquiry or led to the guiding research questions, of the participants' backgrounds, of the processes of data collection, of the training and limitations of the coders, along with a strong attempt to make connections between the data and the conclusions evident.

Although the Berkenkotter, Huckin, and Ackerman (1988) study does not, case study reports often include the reactions of the participants to the study or to the researchers' conclusions. Because case studies tend to be exploratory, most end with implications for further study. Here researchers may identify significant variables that emerged during the research and suggest studies related to these, or the authors may suggest further general questions that their case study generated.

For example, Emig's (1971) study concludes with a section dedicated solely to the topic of implications for further research, in which she suggests several means by which this particular study could have been improved, as well as questions and ideas raised by this study which other researchers might like to address, such as: is there a correlation between a certain personality and a certain composing process profile (e.g. is there a positive correlation between ego strength and persistence in revising)?

Also included in Emig's study is a section dedicated to implications for teaching, which outlines the pedagogical ramifications of the study's findings for teachers currently involved in high school writing programs.

Sharan Merriam (1985) also offers several suggestions for alternative presentations of data:

• Prepare specialized condensations for appropriate groups.
• Replace narrative sections with a series of answers to open-ended questions.
• Present "skimmer's" summaries at beginning of each section.
• Incorporate headlines that encapsulate information from text.
• Prepare analytic summaries with supporting data appendixes.
• Present data in colorful and/or unique graphic representations.

Issues of Validity and Reliability

Once key variables have been identified, they can be analyzed. Reliability becomes a key concern at this stage, and many case study researchers go to great lengths to ensure that their interpretations of the data will be both reliable and valid. Because issues of validity and reliability are an important part of any study in the social sciences, it is important to identify some ways of dealing with results.

Multi-modal case study researchers often balance the results of their coding with data from interviews or writer's reflections upon their own work. Consequently, the researchers' conclusions become highly contextualized. For example, in a case study which looked at the time spent in different stages of the writing process, Berkenkotter concluded that her participant, Donald Murray, spent more time planning his essays than in other writing stages. The report of this case study is followed by Murray's reply, wherein he agrees with some of Berkenkotter's conclusions and disagrees with others.

As is the case with other research methodologies, issues of external validity, construct validity, and reliability need to be carefully considered.

Commentary on Case Studies

Researchers often debate the relative merits of particular methods, among them case study. In this section, we comment on two key issues. To read the commentaries, choose any of the items below:

Strengths and Weaknesses of Case Studies

Most case study advocates point out that case studies produce much more detailed information than what is available through a statistical analysis. Advocates will also hold that while statistical methods might be able to deal with situations where behavior is homogeneous and routine, case studies are needed to deal with creativity, innovation, and context. Detractors argue that case studies are difficult to generalize because of inherent subjectivity and because they are based on qualitative subjective data, generalizable only to a particular context.

Flexibility

The case study approach is a comparatively flexible method of scientific research. Because its project designs seem to emphasize exploration rather than prescription or prediction, researchers are comparatively freer to discover and address issues as they arise in their experiments. In addition, the looser format of case studies allows researchers to begin with broad questions and narrow their focus as their experiment progresses rather than attempt to predict every possible outcome before the experiment is conducted.

Emphasis on Context

By seeking to understand as much as possible about a single subject or small group of subjects, case studies specialize in "deep data," or "thick description"--information based on particular contexts that can give research results a more human face. This emphasis can help bridge the gap between abstract research and concrete practice by allowing researchers to compare their firsthand observations with the quantitative results obtained through other methods of research.

Inherent Subjectivity

"The case study has long been stereotyped as the weak sibling among social science methods," and is often criticized as being too subjective and even pseudo-scientific. Likewise, "investigators who do case studies are often regarded as having deviated from their academic disciplines, and their investigations as having insufficient precision (that is, quantification), objectivity and rigor" (Yin 1989). Opponents cite opportunities for subjectivity in the implementation, presentation, and evaluation of case study research. The approach relies on personal interpretation of data and inferences. Results may not be generalizable, are difficult to test for validity, and rarely offer a problem-solving prescription. Simply put, relying on one or a few subjects as a basis for cognitive extrapolations runs the risk of inferring too much from what might be circumstance.

High Investment

Case studies can involve learning more about the subjects being tested than most researchers would care to know--their educational background, emotional background, perceptions of themselves and their surroundings, their likes, dislikes, and so on. Because of its emphasis on "deep data," the case study is out of reach for many large-scale research projects which look at a subject pool in the tens of thousands. A budget request of $10,000 to examine 200 subjects sounds more efficient than a similar request to examine four subjects.

Ethical Considerations

Researchers conducting case studies should consider certain ethical issues. For example, many educational case studies are often financed by people who have, either directly or indirectly, power over both those being studied and those conducting the investigation (1985). This conflict of interests can hinder the credibility of the study.

The personal integrity, sensitivity, and possible prejudices and/or biases of the investigators need to be taken into consideration as well. Personal biases can creep into how the research is conducted, alternative research methods used, and the preparation of surveys and questionnaires.

A common complaint in case study research is that investigators change direction during the course of the study unaware that their original research design was inadequate for the revised investigation. Thus, the researchers leave unknown gaps and biases in the study. To avoid this, researchers should report preliminary findings so that the likelihood of bias will be reduced.

Concerns about Reliability, Validity, and Generalizability

Merriam (1985) offers several suggestions for how case study researchers might actively combat the popular attacks on the validity, reliability, and generalizability of case studies:

• Prolong the Processes of Data Gathering on Site: This will help to insure the accuracy of the findings by providing the researcher with more concrete information upon which to formulate interpretations.
• Employ the Process of "Triangulation": Use a variety of data sources as opposed to relying solely upon one avenue of observation. One example of such a data check would be what McClintock, Brannon, and Maynard (1985) refer to as a "case cluster method," that is, when a single unit within a larger case is randomly sampled, and that data treated quantitatively." For instance, in Emig's (1971) study, the case cluster method was employed, singling out the productivity of a single student named Lynn. This cluster profile included an advanced case history of the subject, specific examination and analysis of individual compositions and protocols, and extensive interview sessions. The seven remaining students were then compared with the case of Lynn, to ascertain if there are any shared, or unique dimensions to the composing process engaged in by these eight students.
• Conduct Member Checks: Initiate and maintain an active corroboration on the interpretation of data between the researcher and those who provided the data. In other words, talk to your subjects.
• Collect Referential Materials: Complement the file of materials from the actual site with additional document support. For example, Emig (1971) supports her initial propositions with historical accounts by writers such as T.S. Eliot, James Joyce, and D.H. Lawrence. Emig also cites examples of theoretical research done with regards to the creative process, as well as examples of empirical research dealing with the writing of adolescents. Specific attention is then given to the four stages description of the composing process delineated by Helmoltz, Wallas, and Cowley, as it serves as the focal point in this study.
• Engage in Peer Consultation: Prior to composing the final draft of the report, researchers should consult with colleagues in order to establish validity through pooled judgment.

Although little can be done to combat challenges concerning the generalizability of case studies, "most writers suggest that qualitative research should be judged as credible and confirmable as opposed to valid and reliable" (Merriam 1985). Likewise, it has been argued that "rather than transplanting statistical, quantitative notions of generalizability and thus finding qualitative research inadequate, it makes more sense to develop an understanding of generalization that is congruent with the basic characteristics of qualitative inquiry" (1985). After all, criticizing the case study method for being ungeneralizable is comparable to criticizing a washing machine for not being able to tell the correct time. In other words, it is unjust to criticize a method for not being able to do something which it was never originally designed to do in the first place.

Annotated Bibliography

Armisted, C. (1984). How Useful are Case Studies. Training and Development Journal, 38 (2), 75-77.

This article looks at eight types of case studies, offers pros and cons of using case studies in the classroom, and gives suggestions for successfully writing and using case studies.

Bardovi-Harlig, K. (1997). Beyond Methods: Components of Second Language Teacher Education . New York: McGraw-Hill.

A compilation of various research essays which address issues of language teacher education. Essays included are: "Non-native reading research and theory" by Lee, "The case for Psycholinguistics" by VanPatten, and "Assessment and Second Language Teaching" by Gradman and Reed.

Bartlett, L. (1989). A Question of Good Judgment; Interpretation Theory and Qualitative Enquiry Address. 70th Annual Meeting of the American Educational Research Association. San Francisco.

Bartlett selected "quasi-historical" methodology, which focuses on the "truth" found in case records, as one that will provide "good judgments" in educational inquiry. He argues that although the method is not comprehensive, it can try to connect theory with practice.

Baydere, S. et. al. (1993). Multimedia conferencing as a tool for collaborative writing: a case study in Computer Supported Collaborative Writing. New York: Springer-Verlag.

The case study by Baydere et. al. is just one of the many essays in this book found in the series "Computer Supported Cooperative Work." Denley, Witefield and May explore similar issues in their essay, "A case study in task analysis for the design of a collaborative document production system."

Berkenkotter, C., Huckin, T., N., & Ackerman J. (1988). Conventions, Conversations, and the Writer: Case Study of a Student in a Rhetoric Ph.D. Program. Research in the Teaching of English, 22, 9-44.

The authors focused on how the writing of their subject, Nate or Ackerman, changed as he became more acquainted or familiar with his field's discourse community.

Berninger, V., W., and Gans, B., M. (1986). Language Profiles in Nonspeaking Individuals of Normal Intelligence with Severe Cerebral Palsy. Augmentative and Alternative Communication, 2, 45-50.

Argues that generalizations about language abilities in patients with severe cerebral palsy (CP) should be avoided. Standardized tests of different levels of processing oral language, of processing written language, and of producing written language were administered to 3 male participants (aged 9, 16, and 40 yrs).

Bockman, J., R., and Couture, B. (1984). The Case Method in Technical Communication: Theory and Models. Texas: Association of Teachers of Technical Writing.

Examines the study and teaching of technical writing, communication of technical information, and the case method in terms of those applications.

Boehrer, J. (1990). Teaching With Cases: Learning to Question. New Directions for Teaching and Learning, 42 41-57.

This article discusses the origins of the case method, looks at the question of what is a case, gives ideas about learning in case teaching, the purposes it can serve in the classroom, the ground rules for the case discussion, including the role of the question, and new directions for case teaching.

Bowman, W. R. (1993). Evaluating JTPA Programs for Economically Disadvantaged Adults: A Case Study of Utah and General Findings . Washington: National Commission for Employment Policy.

"To encourage state-level evaluations of JTPA, the Commission and the State of Utah co-sponsored this report on the effectiveness of JTPA Title II programs for adults in Utah. The technique used is non-experimental and the comparison group was selected from registrants with Utah's Employment Security. In a step-by-step approach, the report documents how non-experimental techniques can be applied and several specific technical issues can be addressed."

Boyce, A. (1993) The Case Study Approach for Pedagogists. Annual Meeting of the American Alliance for Health, Physical Education, Recreation and Dance. (Address). Washington DC.

This paper addresses how case studies 1) bridge the gap between teaching theory and application, 2) enable students to analyze problems and develop solutions for situations that will be encountered in the real world of teaching, and 3) helps students to evaluate the feasibility of alternatives and to understand the ramifications of a particular course of action.

Carson, J. (1993) The Case Study: Ideal Home of WAC Quantitative and Qualitative Data. Annual Meeting of the Conference on College Composition and Communication. (Address). San Diego.

"Increasingly, one of the most pressing questions for WAC advocates is how to keep [WAC] programs going in the face of numerous difficulties. Case histories offer the best chance for fashioning rhetorical arguments to keep WAC programs going because they offer the opportunity to provide a coherent narrative that contextualizes all documents and data, including what is generally considered scientific data. A case study of the WAC program, . . . at Robert Morris College in Pittsburgh demonstrates the advantages of this research method. Such studies are ideal homes for both naturalistic and positivistic data as well as both quantitative and qualitative information."

---. (1991). A Cognitive Process Theory of Writing. College Composition and Communication. 32. 365-87.

No abstract available.

Cromer, R. (1994) A Case Study of Dissociations Between Language and Cognition. Constraints on Language Acquisition: Studies of Atypical Children . Hillsdale: Lawrence Erlbaum Associates, 141-153.

Crossley, M. (1983) Case Study in Comparative and International Education: An Approach to Bridging the Theory-Practice Gap. Proceedings of the 11th Annual Conference of the Australian Comparative and International Education Society. Hamilton, NZ.

Case study research, as presented here, helps bridge the theory-practice gap in comparative and international research studies of education because it focuses on the practical, day-to-day context rather than on the national arena. The paper asserts that the case study method can be valuable at all levels of research, formation, and verification of theories in education.

Daillak, R., H., and Alkin, M., C. (1982). Qualitative Studies in Context: Reflections on the CSE Studies of Evaluation Use . California: EDRS

The report shows how the Center of the Study of Evaluation (CSE) applied qualitative techniques to a study of evaluation information use in local, Los Angeles schools. It critiques the effectiveness and the limitations of using case study, evaluation, field study, and user interview survey methodologies.

Davey, L. (1991). The Application of Case Study Evaluations. ERIC/TM Digest.

This article examines six types of case studies, the type of evaluation questions that can be answered, the functions served, some design features, and some pitfalls of the method.

Deutch, C. E. (1996). A course in research ethics for graduate students. College Teaching, 44, 2, 56-60.

This article describes a one-credit discussion course in research ethics for graduate students in biology. Case studies are focused on within the four parts of the course: 1) major issues, 2 )practical issues in scholarly work, 3) ownership of research results, and 4) training and personal decisions.

DeVoss, G. (1981). Ethics in Fieldwork Research. RIE 27p. (ERIC)

This article examines four of the ethical problems that can happen when conducting case study research: acquiring permission to do research, knowing when to stop digging, the pitfalls of doing collaborative research, and preserving the integrity of the participants.

Driscoll, A. (1985). Case Study of a Research Intervention: the University of Utah’s Collaborative Approach . San Francisco: Far West Library for Educational Research Development.

Paper presented at the annual meeting of the American Association of Colleges of Teacher Education, Denver, CO, March 1985. Offers information of in-service training, specifically case studies application.

Ellram, L. M. (1996). The Use of the Case Study Method in Logistics Research. Journal of Business Logistics, 17, 2, 93.

This article discusses the increased use of case study in business research, and the lack of understanding of when and how to use case study methodology in business.

Emig, J. (1971) The Composing Processes of Twelfth Graders . Urbana: NTCE.

This case study uses observation, tape recordings, writing samples, and school records to show that writing in reflexive and extensive situations caused different lengths of discourse and different clusterings of the components of the writing process.

Feagin, J. R. (1991). A Case For the Case Study . Chapel Hill: The University of North Carolina Press.

This book discusses the nature, characteristics, and basic methodological issues of the case study as a research method.

Feldman, H., Holland, A., & Keefe, K. (1989) Language Abilities after Left Hemisphere Brain Injury: A Case Study of Twins. Topics in Early Childhood Special Education, 9, 32-47.

"Describes the language abilities of 2 twin pairs in which 1 twin (the experimental) suffered brain injury to the left cerebral hemisphere around the time of birth and1 twin (the control) did not. One pair of twins was initially assessed at age 23 mo. and the other at about 30 mo.; they were subsequently evaluated in their homes 3 times at about 6-mo intervals."

Fidel, R. (1984). The Case Study Method: A Case Study. Library and Information Science Research, 6.

The article describes the use of case study methodology to systematically develop a model of online searching behavior in which study design is flexible, subject manner determines data gathering and analyses, and procedures adapt to the study's progressive change.

Flower, L., & Hayes, J. R. (1984). Images, Plans and Prose: The Representation of Meaning in Writing. Written Communication, 1, 120-160.

Explores the ways in which writers actually use different forms of knowing to create prose.

Frey, L. R. (1992). Interpreting Communication Research: A Case Study Approach Englewood Cliffs, N.J.: Prentice Hall.

The book discusses research methodologies in the Communication field. It focuses on how case studies bridge the gap between communication research, theory, and practice.

Gilbert, V. K. (1981). The Case Study as a Research Methodology: Difficulties and Advantages of Integrating the Positivistic, Phenomenological and Grounded Theory Approaches . The Annual Meeting of the Canadian Association for the Study of Educational Administration. (Address) Halifax, NS, Can.

This study on an innovative secondary school in England shows how a "low-profile" participant-observer case study was crucial to the initial observation, the testing of hypotheses, the interpretive approach, and the grounded theory.

Gilgun, J. F. (1994). A Case for Case Studies in Social Work Research. Social Work, 39, 4, 371-381.

This article defines case study research, presents guidelines for evaluation of case studies, and shows the relevance of case studies to social work research. It also looks at issues such as evaluation and interpretations of case studies.

Glennan, S. L., Sharp-Bittner, M. A. & Tullos, D. C. (1991). Augmentative and Alternative Communication Training with a Nonspeaking Adult: Lessons from MH. Augmentative and Alternative Communication, 7, 240-7.

"A response-guided case study documented changes in a nonspeaking 36-yr-old man's ability to communicate using 3 trained augmentative communication modes. . . . Data were collected in videotaped interaction sessions between the nonspeaking adult and a series of adult speaking."

Graves, D. (1981). An Examination of the Writing Processes of Seven Year Old Children. Research in the Teaching of English, 15, 113-134.

Hamel, J. (1993). Case Study Methods . Newbury Park: Sage. .

"In a most economical fashion, Hamel provides a practical guide for producing theoretically sharp and empirically sound sociological case studies. A central idea put forth by Hamel is that case studies must "locate the global in the local" thus making the careful selection of the research site the most critical decision in the analytic process."

Karthigesu, R. (1986, July). Television as a Tool for Nation-Building in the Third World: A Post-Colonial Pattern, Using Malaysia as a Case-Study. International Television Studies Conference. (Address). London, 10-12.

"The extent to which Television Malaysia, as a national mass media organization, has been able to play a role in nation building in the post-colonial period is . . . studied in two parts: how the choice of a model of nation building determines the character of the organization; and how the character of the organization influences the output of the organization."

Kenny, R. (1984). Making the Case for the Case Study. Journal of Curriculum Studies, 16, (1), 37-51.

The article looks at how and why the case study is justified as a viable and valuable approach to educational research and program evaluation.

Knirk, F. (1991). Case Materials: Research and Practice. Performance Improvement Quarterly, 4 (1 ), 73-81.

The article addresses the effectiveness of case studies, subject areas where case studies are commonly used, recent examples of their use, and case study design considerations.

Klos, D. (1976). Students as Case Writers. Teaching of Psychology, 3.2, 63-66.

This article reviews a course in which students gather data for an original case study of another person. The task requires the students to design the study, collect the data, write the narrative, and interpret the findings.

Leftwich, A. (1981). The Politics of Case Study: Problems of Innovation in University Education. Higher Education Review, 13.2, 38-64.

The article discusses the use of case studies as a teaching method. Emphasis is on the instructional materials, interdisciplinarity, and the complex relationships within the university that help or hinder the method.

Mabrito, M. (1991, Oct.). Electronic Mail as a Vehicle for Peer Response: Conversations of High and Low Apprehensive Writers. Written Communication, 509-32.

McCarthy, S., J. (1955). The Influence of Classroom Discourse on Student Texts: The Case of Ella . East Lansing: Institute for Research on Teaching.

A look at how students of color become marginalized within traditional classroom discourse. The essay follows the struggles of one black student: Ella.

Matsuhashi, A., ed. (1987). Writing in Real Time: Modeling Production Processes Norwood, NJ: Ablex Publishing Corporation.

Investigates how writers plan to produce discourse for different purposes to report, to generalize, and to persuade, as well as how writers plan for sentence level units of language. To learn about planning, an observational measure of pause time was used" (ERIC).

Merriam, S. B. (1985). The Case Study in Educational Research: A Review of Selected Literature. Journal of Educational Thought, 19.3, 204-17.

The article examines the characteristics of, philosophical assumptions underlying the case study, the mechanics of conducting a case study, and the concerns about the reliability, validity, and generalizability of the method.

---. (1988). Case Study Research in Education: A Qualitative Approach San Francisco: Jossey Bass.

Merry, S. E., & Milner, N. eds. (1993). The Possibility of Popular Justice: A Case Study of Community Mediation in the United States . Ann Arbor: U of Michigan.

". . . this volume presents a case study of one experiment in popular justice, the San Francisco Community Boards. This program has made an explicit claim to create an alternative justice, or new justice, in the midst of a society ordered by state law. The contributors to this volume explore the history and experience of the program and compare it to other versions of popular justice in the United States, Europe, and the Third World."

Merseth, K. K. (1991). The Case for Cases in Teacher Education. RIE. 42p. (ERIC).

This monograph argues that the case method of instruction offers unique potential for revitalizing the field of teacher education.

Michaels, S. (1987). Text and Context: A New Approach to the Study of Classroom Writing. Discourse Processes, 10, 321-346.

"This paper argues for and illustrates an approach to the study of writing that integrates ethnographic analysis of classroom interaction with linguistic analysis of written texts and teacher/student conversational exchanges. The approach is illustrated through a case study of writing in a single sixth grade classroom during a single writing assignment."

Milburn, G. (1995). Deciphering a Code or Unraveling a Riddle: A Case Study in the Application of a Humanistic Metaphor to the Reporting of Social Studies Teaching. Theory and Research in Education, 13.

This citation serves as an example of how case studies document learning procedures in a senior-level economics course.

Milley, J. E. (1979). An Investigation of Case Study as an Approach to Program Evaluation. 19th Annual Forum of the Association for Institutional Research. (Address). San Diego.

The case study method merged a narrative report focusing on the evaluator as participant-observer with document review, interview, content analysis, attitude questionnaire survey, and sociogram analysis. Milley argues that case study program evaluation has great potential for widespread use.

Minnis, J. R. (1985, Sept.). Ethnography, Case Study, Grounded Theory, and Distance Education Research. Distance Education, 6.2.

This article describes and defines the strengths and weaknesses of ethnography, case study, and grounded theory.

Nunan, D. (1992). Collaborative language learning and teaching . New York: Cambridge University Press.

Included in this series of essays is Peter Sturman’s "Team Teaching: a case study from Japan" and David Nunan’s own "Toward a collaborative approach to curriculum development: a case study."

Nystrand, M., ed. (1982). What Writers Know: The Language, Process, and Structure of Written Discourse . New York: Academic Press.

Owenby, P. H. (1992). Making Case Studies Come Alive. Training, 29, (1), 43-46. (ERIC)

This article provides tips for writing more effective case studies.

---. (1981). Pausing and Planning: The Tempo of Writer Discourse Production. Research in the Teaching of English, 15 (2),113-34.

Perl, S. (1979). The Composing Processes of Unskilled College Writers. Research in the Teaching of English, 13, 317-336.

"Summarizes a study of five unskilled college writers, focusing especially on one of the five, and discusses the findings in light of current pedagogical practice and research design."

Pilcher J. and A. Coffey. eds. (1996). Gender and Qualitative Research . Brookfield: Aldershot, Hants, England.

This book provides a series of essays which look at gender identity research, qualitative research and applications of case study to questions of gendered pedagogy.

Pirie, B. S. (1993). The Case of Morty: A Four Year Study. Gifted Education International, 9 (2), 105-109.

This case study describes a boy from kindergarten through third grade with above average intelligence but difficulty in learning to read, write, and spell.

Popkewitz, T. (1993). Changing Patterns of Power: Social Regulation and Teacher Education Reform. Albany: SUNY Press.

Popkewitz edits this series of essays that address case studies on educational change and the training of teachers. The essays vary in terms of discipline and scope. Also, several authors include case studies of educational practices in countries other than the United States.

---. (1984). The Predrafting Processes of Four High- and Four Low Apprehensive Writers. Research in the Teaching of English, 18, (1), 45-64.

Rasmussen, P. (1985, March) A Case Study on the Evaluation of Research at the Technical University of Denmark. International Journal of Institutional Management in Higher Education, 9 (1).

This is an example of a case study methodology used to evaluate the chemistry and chemical engineering departments at the University of Denmark.

Roth, K. J. (1986). Curriculum Materials, Teacher Talk, and Student Learning: Case Studies in Fifth-Grade Science Teaching . East Lansing: Institute for Research on Teaching.

Roth offers case studies on elementary teachers, elementary school teaching, science studies and teaching, and verbal learning.

Selfe, C. L. (1985). An Apprehensive Writer Composes. When a Writer Can't Write: Studies in Writer's Block and Other Composing-Process Problems . (pp. 83-95). Ed. Mike Rose. NMY: Guilford.

Smith-Lewis, M., R. and Ford, A. (1987). A User's Perspective on Augmentative Communication. Augmentative and Alternative Communication, 3, 12-7.

"During a series of in-depth interviews, a 25-yr-old woman with cerebral palsy who utilized augmentative communication reflected on the effectiveness of the devices designed for her during her school career."

St. Pierre, R., G. (1980, April). Follow Through: A Case Study in Metaevaluation Research . 64th Annual Meeting of the American Educational Research Association. (Address).

The three approaches to metaevaluation are evaluation of primary evaluations, integrative meta-analysis with combined primary evaluation results, and re-analysis of the raw data from a primary evaluation.

Stahler, T., M. (1996, Feb.) Early Field Experiences: A Model That Worked. ERIC.

"This case study of a field and theory class examines a model designed to provide meaningful field experiences for preservice teachers while remaining consistent with the instructor's beliefs about the role of teacher education in preparing teachers for the classroom."

Stake, R. E. (1995). The Art of Case Study Research. Thousand Oaks: Sage Publications.

This book examines case study research in education and case study methodology.

Stiegelbauer, S. (1984) Community, Context, and Co-curriculum: Situational Factors Influencing School Improvements in a Study of High Schools. Presented at the annual meeting of the American Educational Research Association, New Orleans, LA.

Discussion of several case studies: one looking at high school environments, another examining educational innovations.

Stolovitch, H. (1990). Case Study Method. Performance And Instruction, 29, (9), 35-37.

This article describes the case study method as a form of simulation and presents guidelines for their use in professional training situations.

Thaller, E. (1994). Bibliography for the Case Method: Using Case Studies in Teacher Education. RIE. 37 p.

This bibliography presents approximately 450 citations on the use of case studies in teacher education from 1921-1993.

Thrane, T. (1986). On Delimiting the Senses of Near-Synonyms in Historical Semantics: A Case Study of Adjectives of 'Moral Sufficiency' in the Old English Andreas. Linguistics Across Historical and Geographical Boundaries: In Honor of Jacek Fisiak on the Occasion of his Fiftieth Birthday . Berlin: Mouton de Gruyter.

United Nations. (1975). Food and Agriculture Organization. Report on the FAO/UNFPA Seminar on Methodology, Research and Country: Case Studies on Population, Employment and Productivity . Rome: United Nations.

This example case study shows how the methodology can be used in a demographic and psychographic evaluation. At the same time, it discusses the formation and instigation of the case study methodology itself.

Van Vugt, J. P., ed. (1994). Aids Prevention and Services: Community Based Research . Westport: Bergin and Garvey.

"This volume has been five years in the making. In the process, some of the policy applications called for have met with limited success, such as free needle exchange programs in a limited number of American cities, providing condoms to prison inmates, and advertisements that depict same-sex couples. Rather than dating our chapters that deal with such subjects, such policy applications are verifications of the type of research demonstrated here. Furthermore, they indicate the critical need to continue community based research in the various communities threatened by acquired immuno-deficiency syndrome (AIDS) . . . "

Welch, W., ed. (1981, May). Case Study Methodology in Educational Evaluation. Proceedings of the Minnesota Evaluation Conference. Minnesota. (Address).

The four papers in these proceedings provide a comprehensive picture of the rationale, methodology, strengths, and limitations of case studies.

Williams, G. (1987). The Case Method: An Approach to Teaching and Learning in Educational Administration. RIE, 31p.

This paper examines the viability of the case method as a teaching and learning strategy in instructional systems geared toward the training of personnel of the administration of various aspects of educational systems.

Yin, R. K. (1993). Advancing Rigorous Methodologies: A Review of 'Towards Rigor in Reviews of Multivocal Literatures.' Review of Educational Research, 61, (3).

"R. T. Ogawa and B. Malen's article does not meet its own recommended standards for rigorous testing and presentation of its own conclusions. Use of the exploratory case study to analyze multivocal literatures is not supported, and the claim of grounded theory to analyze multivocal literatures may be stronger."

---. (1989). Case Study Research: Design and Methods. London: Sage Publications Inc.

This book discusses in great detail, the entire design process of the case study, including entire chapters on collecting evidence, analyzing evidence, composing the case study report, and designing single and multiple case studies.

Related Links

Consider the following list of related Web sites for more information on the topic of case study research. Note: although many of the links cover the general category of qualitative research, all have sections that address issues of case studies.

• Sage Publications on Qualitative Methodology: Search here for a comprehensive list of new books being published about "Qualitative Methodology" http://www.sagepub.co.uk/
• The International Journal of Qualitative Studies in Education: An on-line journal "to enhance the theory and practice of qualitative research in education." On-line submissions are welcome. http://www.tandf.co.uk/journals/tf/09518398.html
• Qualitative Research Resources on the Internet: From syllabi to home pages to bibliographies. All links relate somehow to qualitative research. http://www.nova.edu/ssss/QR/qualres.html

Becker, Bronwyn, Patrick Dawson, Karen Devine, Carla Hannum, Steve Hill, Jon Leydens, Debbie Matuskevich, Carol Traver, & Mike Palmquist. (2005). Case Studies. Writing@CSU . Colorado State University. https://writing.colostate.edu/guides/guide.cfm?guideid=60

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• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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How to write qualitative research questions.

11 min read Here’s how to write effective qualitative research questions for your projects, and why getting it right matters so much.

What is qualitative research?

Qualitative research is a blanket term covering a wide range of research methods and theoretical framing approaches. The unifying factor in all these types of qualitative study is that they deal with data that cannot be counted. Typically this means things like people’s stories, feelings, opinions and emotions , and the meanings they ascribe to their experiences.

Qualitative study is one of two main categories of research, the other being quantitative research. Quantitative research deals with numerical data – that which can be counted and quantified, and which is mostly concerned with trends and patterns in large-scale datasets.

What are research questions?

Research questions are questions you are trying to answer with your research. To put it another way, your research question is the reason for your study, and the beginning point for your research design. There is normally only one research question per study, although if your project is very complex, you may have multiple research questions that are closely linked to one central question.

A good qualitative research question sums up your research objective. It’s a way of expressing the central question of your research, identifying your particular topic and the central issue you are examining.

Research questions are quite different from survey questions, questions used in focus groups or interview questions. A long list of questions is used in these types of study, as opposed to one central question. Additionally, interview or survey questions are asked of participants, whereas research questions are only for the researcher to maintain a clear understanding of the research design.

Research questions are used in both qualitative and quantitative research , although what makes a good research question might vary between the two.

In fact, the type of research questions you are asking can help you decide whether you need to take a quantitative or qualitative approach to your research project.

Discover the fundamentals of qualitative research

Quantitative vs. qualitative research questions

Writing research questions is very important in both qualitative and quantitative research, but the research questions that perform best in the two types of studies are quite different.

Quantitative research questions

Quantitative research questions usually relate to quantities, similarities and differences.

It might reflect the researchers’ interest in determining whether relationships between variables exist, and if so whether they are statistically significant. Or it may focus on establishing differences between things through comparison, and using statistical analysis to determine whether those differences are meaningful or due to chance.

• How much? This kind of research question is one of the simplest. It focuses on quantifying something. For example:

How many Yoruba speakers are there in the state of Maine?

• What is the connection?

This type of quantitative research question examines how one variable affects another.

For example:

How does a low level of sunlight affect the mood scores (1-10) of Antarctic explorers during winter?

• What is the difference? Quantitative research questions in this category identify two categories and measure the difference between them using numerical data.

Do white cats stay cooler than tabby cats in hot weather?

If your research question fits into one of the above categories, you’re probably going to be doing a quantitative study.

Qualitative research questions

Qualitative research questions focus on exploring phenomena, meanings and experiences.

Unlike quantitative research, qualitative research isn’t about finding causal relationships between variables. So although qualitative research questions might touch on topics that involve one variable influencing another, or looking at the difference between things, finding and quantifying those relationships isn’t the primary objective.

In fact, you as a qualitative researcher might end up studying a very similar topic to your colleague who is doing a quantitative study, but your areas of focus will be quite different. Your research methods will also be different – they might include focus groups, ethnography studies, and other kinds of qualitative study.

A few example qualitative research questions:

• What is it like being an Antarctic explorer during winter?
• What are the experiences of Yoruba speakers in the USA?
• How do white cat owners describe their pets?

Qualitative research question types

Marshall and Rossman (1989) identified 4 qualitative research question types, each with its own typical research strategy and methods.

• Exploratory questions

Exploratory questions are used when relatively little is known about the research topic. The process researchers follow when pursuing exploratory questions might involve interviewing participants, holding focus groups, or diving deep with a case study.

• Explanatory questions

With explanatory questions, the research topic is approached with a view to understanding the causes that lie behind phenomena. However, unlike a quantitative project, the focus of explanatory questions is on qualitative analysis of multiple interconnected factors that have influenced a particular group or area, rather than a provable causal link between dependent and independent variables.

• Descriptive questions

As the name suggests, descriptive questions aim to document and record what is happening. In answering descriptive questions , researchers might interact directly with participants with surveys or interviews, as well as using observational studies and ethnography studies that collect data on how participants interact with their wider environment.

• Predictive questions

Predictive questions start from the phenomena of interest and investigate what ramifications it might have in the future. Answering predictive questions may involve looking back as well as forward, with content analysis, questionnaires and studies of non-verbal communication (kinesics).

Why are good qualitative research questions important?

We know research questions are very important. But what makes them so essential? (And is that question a qualitative or quantitative one?)

Getting your qualitative research questions right has a number of benefits.

• It defines your qualitative research project Qualitative research questions definitively nail down the research population, the thing you’re examining, and what the nature of your answer will be.This means you can explain your research project to other people both inside and outside your business or organization. That could be critical when it comes to securing funding for your project, recruiting participants and members of your research team, and ultimately for publishing your results. It can also help you assess right the ethical considerations for your population of study.
• It maintains focus Good qualitative research questions help researchers to stick to the area of focus as they carry out their research. Keeping the research question in mind will help them steer away from tangents during their research or while they are carrying out qualitative research interviews. This holds true whatever the qualitative methods are, whether it’s a focus group, survey, thematic analysis or other type of inquiry.That doesn’t mean the research project can’t morph and change during its execution – sometimes this is acceptable and even welcome – but having a research question helps demarcate the starting point for the research. It can be referred back to if the scope and focus of the project does change.
• It helps make sure your outcomes are achievable

Because qualitative research questions help determine the kind of results you’re going to get, it helps make sure those results are achievable. By formulating good qualitative research questions in advance, you can make sure the things you want to know and the way you’re going to investigate them are grounded in practical reality. Otherwise, you may be at risk of taking on a research project that can’t be satisfactorily completed.

Developing good qualitative research questions

All researchers use research questions to define their parameters, keep their study on track and maintain focus on the research topic. This is especially important with qualitative questions, where there may be exploratory or inductive methods in use that introduce researchers to new and interesting areas of inquiry. Here are some tips for writing good qualitative research questions.

1. Keep it specific

Broader research questions are difficult to act on. They may also be open to interpretation, or leave some parameters undefined.

Strong example: How do Baby Boomers in the USA feel about their gender identity?

Weak example: Do people feel different about gender now?

2. Be original

Look for research questions that haven’t been widely addressed by others already.

Strong example: What are the effects of video calling on women’s experiences of work?

Weak example: Are women given less respect than men at work?

3. Make it research-worthy

Don’t ask a question that can be answered with a ‘yes’ or ‘no’, or with a quick Google search.

Strong example: What do people like and dislike about living in a highly multi-lingual country?

Weak example: What languages are spoken in India?

4. Focus your question

Don’t roll multiple topics or questions into one. Qualitative data may involve multiple topics, but your qualitative questions should be focused.

Strong example: What is the experience of disabled children and their families when using social services?

Weak example: How can we improve social services for children affected by poverty and disability?

4. Focus on your own discipline, not someone else’s

Avoid asking questions that are for the politicians, police or others to address.

Strong example: What does it feel like to be the victim of a hate crime?

Weak example: How can hate crimes be prevented?

5. Ask something researchable

Big questions, questions about hypothetical events or questions that would require vastly more resources than you have access to are not useful starting points for qualitative studies. Qualitative words or subjective ideas that lack definition are also not helpful.

Strong example: How do perceptions of physical beauty vary between today’s youth and their parents’ generation?

Weak example: Which country has the most beautiful people in it?

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• Open access
• Published: 27 June 2011

The case study approach

• Sarah Crowe 1 ,
• Kathrin Cresswell 2 ,
• Ann Robertson 2 ,
• Guro Huby 3 ,
• Anthony Avery 1 &
• Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

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Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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On This Page:

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

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

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

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

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

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

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

 Famous Case Studies

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

Clinical Case Studies

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

Child Psychology Case Studies

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

Types of Case Studies

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

Where Do You Find Data for a Case Study?

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

1. Primary sources

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

2. Secondary sources

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

3. Archival records

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

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

4. Organizational records

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

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

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

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

How do I Write a Case Study in Psychology?

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

1. Introduction

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

2. Case Presentation

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

3. Management and Outcome

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

4. Discussion

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

5. Additional Items

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

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

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

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

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

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

Limitations

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Further Information

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

100 Best Case Study Questions for Your Next Customer Spotlight

Published: November 29, 2022

Case studies and testimonials are helpful to have in your arsenal. But to build an effective library, you need to ask the right case study questions. You also need to know how to write a case study .

Case studies are customers' stories that your sales team can use to share relevant content with prospects . Not only that, but case studies help you earn a prospect's trust, show them what life would be like as your customer, and validate that your product or service works for your clients.

Before you start building your library of case studies, check out our list of 100 case study questions to ask your clients. With this helpful guide, you'll have the know-how to build your narrative using the " Problem-Agitate-Solve " Method.

What makes a good case study questionnaire?

The ultimate list of case study questions, how to ask your customer for a case study, creating an effective case study.

Certain key elements make up a good case study questionnaire.

A questionnaire should never feel like an interrogation. Instead, aim to structure your case study questions like a conversation. Some of the essential things that your questionnaire should cover include:

• The problem faced by the client before choosing your organization.
• Why they chose your company.
• How your product solved the problem clients faced.
• The measurable results of the service provided.
• Data and metrics that prove the success of your service or product, if possible.

You can adapt these considerations based on how your customers use your product and the specific answers or quotes that you want to receive.

What makes a good case study question?

A good case study question delivers a powerful message to leads in the decision stage of your prospective buyer's journey.

Since your client has agreed to participate in a case study, they're likely enthusiastic about the service you provide. Thus, a good case study question hands the reins over to the client and opens a conversation.

Try asking open-ended questions to encourage your client to talk about the excellent service or product you provide.

Free Case Study Templates

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Categories for the Best Case Study Questions

• Case study questions about the customer's business
• Case study questions about the environment before the purchase
• Case study questions about the decision process
• Case study questions about the customer's business case
• Case study questions about the buying team and internal advocates
• Case study questions about customer success
• Case study questions about product feedback
• Case study questions about willingness to make referrals
• Case study question to prompt quote-worthy feedback
• Case study questions about the customers' future goals

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

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

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Case Study Interview Questions About the Customer's Business

Knowing the customer's business is an excellent way of setting the tone for a case study.

Use these questions to get some background information about the company and its business goals. This information can be used to introduce the business at the beginning of the case study — plus, future prospects might resonate with their stories and become leads for you.

• Would you give me a quick overview of [company]? This is an opportunity for the client to describe their business in their own words. You'll get useful background information and it's an easy prompt to get the client talking.
• Can you describe your role? This will give you a better idea of the responsibilities they are subject to.
• How do your role and team fit into the company and its goals? Knowing how the team functions to achieve company goals will help you formulate how your solution involves all stakeholders.
• How long has your company been in business? Getting this information will help the reader gauge if pain points are specific to a startup or new company vs. a veteran company.
• How many employees do you have? Another great descriptor for readers to have. They can compare the featured company size with their own.
• Is your company revenue available? If so, what is it? This will give your readers background information on the featured company's gross sales.
• Who is your target customer? Knowing who the target audience is will help you provide a better overview of their market for your case study readers.
• How does our product help your team or company achieve its objectives? This is one of the most important questions because it is the basis of the case study. Get specifics on how your product provided a solution for your client. You want to be able to say "X company implemented our solution and achieved Y. "
• How are our companies aligned (mission, strategy, culture, etc.)? If any attributes of your company's mission or culture appealed to the client, call it out.

How many people are on your team? What are their roles? This will help describe key players within the organization and their impact on the implementation of your solution.

Case Study Interview Questions About the Environment Before the Purchase

A good case study is designed to build trust. Ask clients to describe the tools and processes they used before your product or service. These kinds of case study questions will highlight the business' need they had to fulfill and appeal to future clients.

• What was your team's process prior to using our product? This will give the reader a baseline to compare the results for your company's product.
• Were there any costs associated with the process prior to using our product? Was it more expensive? Was it worth the cost? How did the product affect the client's bottom line? This will be a useful metric to disclose if your company saved the client money or was more cost-efficient.
• What were the major pain points of your process prior to using our product? Describe these obstacles in detail. You want the reader to get as much information on the problem as possible as it sets up the reasoning for why your company's solution was implemented.
• Did our product replace a similar tool or is this the first time your team is using a product like this? Were they using a similar product? If so, having this information may give readers a reason to choose your brand over the competition.
• What other challenges were you and your team experiencing prior to using our product? The more details you can give readers regarding the client's struggles, the better. You want to paint a full picture of the challenges the client faced and how your company resolved them.
• Were there any concerns about how your customers would be impacted by using our product? Getting answers to this question will illustrate to readers the client's concerns about switching to your service. Your readers may have similar concerns and reading how your client worked through this process will be helpful.
• Why didn't you buy our product or a similar product earlier? Have the client describe any hesitations they had using your product. Their concerns may be relatable to potential leads.
• Were there any "dealbreakers" involved in your decision to become a customer? Describing how your company was able to provide a solution that worked within those parameters demonstrates how accommodating your brand is and how you put the customer first. It's also great to illustrate any unique challenges the client had. This better explains their situation to the reader.
• Did you have to make any changes you weren't anticipating once you became a customer? Readers of your case study can learn how switching to your product came with some unexpected changes (good or bad) and how they navigated them. If you helped your client with troubleshooting, ask them to explain that here.

How has your perception of the product changed since you've become a customer? Get the interviewee to describe how your product changed how they do business. This includes how your product accomplished what they previously thought was impossible.

Case Study Interview Questions About the Decision Process

Readers of the case study will be interested in which factors influenced the decision-making process for the client. If they can relate to that process, there's a bigger chance they'll buy your product.

The answers to these questions will help potential customers through their decision-making process.

• How did you hear about our product? If the client chose to work with you based on a recommendation or another positive case study, include that. It will demonstrate that you are a trusted brand with an established reputation for delivering results.
• How long had you been looking for a solution to this problem? This will add to the reader's understanding of how these particular challenges impacted the company before choosing your product.
• Were you comparing alternative solutions? Which ones? This will demonstrate to readers that the client explored other options before choosing your company.
• Would you describe a few of the reasons you decided to buy our product? Ask the interviewee to describe why they chose your product over the competition and any benefits your company offered that made you stand out.
• What were the criteria you used when deciding to buy our product? This will give readers more background insight into the factors that impacted their decision-making process.
• Were there any high-level initiatives or goals that prompted the decision to buy? For example, was this decision motivated by a company-wide vision? Prompt your clients to discuss what lead to the decision to work with you and how you're the obvious choice.
• What was the buying process like? Did you notice anything exceptional or any points of friction? This is an opportunity for the client to comment on how seamless and easy you make the buying process. Get them to describe what went well from start to finish.
• How would you have changed the buying process, if at all? This is an opportunity for you to fine-tune your process to accommodate future buyers.
• Who on your team was involved in the buying process? This will give readers more background on the key players involved from executives to project managers. With this information, readers can see who they may potentially need to involve in the decision-making process on their teams.

Case Study Interview Questions About the Customer's Business Case

Your case study questions should ask about your product or solution's impact on the customer's employees, teams, metrics, and goals. These questions allow the client to praise the value of your service and tell others exactly what benefits they derived from it.

When readers review your product or service's impact on the client, it enforces the belief that the case study is credible.

• How long have you been using our product? This will help readers gauge how long it took to see results and your overall satisfaction with the product or service.
• How many different people at your company use our product? This will help readers gauge how they can adapt the product to their teams if similar in size.
• Are there multiple departments or teams using our product? This will demonstrate how great of an impact your product has made across departments.
• How do you and your team currently use the product? What types of goals or tasks are you using the product to accomplish? Get specifics on how the product actively helps the client achieve their goals.
• If other teams or departments are using our product, do you know how they're using it? With this information, leads can picture how they can use your product across their teams and how it may improve their workflow and metrics.
• What was the most obvious advantage you felt our product offered during the sales process? The interviewee should explain the benefits they've gained from using your product or service. This is important for convincing other leads you are better than the competition.
• Were there any other advantages you discovered after using the product more regularly? Your interviewee may have experienced some additional benefits from using your product. Have them describe in detail what these advantages are and how they've helped the company improve.
• Are there any metrics or KPIs you track with our product? What are they? The more numbers and data the client can provide, the better.
• Were you tracking any metrics prior to using our product? What were they? This will allow readers to get a clear, before-and-after comparison of using your product.
• How has our product impacted your core metrics? This is an opportunity for your clients to drive home how your product assisted them in hitting their metrics and goals.

Case Study Interview Questions About the Buying Team and Internal Advocates

See if there are any individuals at the customer's company who are advocates for your product.

• Are there any additional team members you consider to be advocates for our product? For example, does anyone stick out as a "power user" or product expert on your team? You may want to interview and include these power users in your case study as well. Consider asking them for tips on using your service or product.
• Is there anyone else on your team you think we should talk to? Again, the more people can share their experience using your product, the better.
• Are there any team members who you think might not be the biggest fans of our product or who might need more training? Providing extra support to those struggling with your product may improve their user experience and turn into an opportunity to not only learn about their obstacles but turn them into a product fan
• Would you share some details about how your team implemented our product? Get as much information as possible about the rollout. Hopefully, they'll gush about how seamless the process was.
• Who from your company was involved in implementing our product? This will give readers more insight into who needs to be involved for a successful rollout of their own.
• Were there any internal risks or additional costs involved with implementing our product? If so, how did you address them? This will give insight into the client's process and rollout and this case study question will likely provide tips on what potential leads should be on the lookout for.
• Is there a training process in place for your team's use of our product? If so, what does it look like? If your company provided support and training to the client, have them describe that experience.
• About how long does it take a new team member to get up to speed with our product? This will help leads determine how much time it will take to onboard an employee to your using your product. If a new user can quickly get started seamlessly, it bodes well for you.
• What was your main concern about rolling this product out to your company? Describing their challenges in detail will provide readers with useful insight.

Case Study Interview Questions About Customer Success

Has the customer found success with your product? Ask these questions to learn more.

• By using our product can you measure any reduced costs? If it has, you'll want to emphasize those savings in your case study.
• By using our product can you measure any improvements in productivity or time savings? Any metrics or specific stories your interviewee can provide will help demonstrate the value of your product.
• By using our product can you measure any increases in revenue or growth? Again, say it with numbers and data whenever possible.
• Are you likely to recommend our product to a friend or colleague? Recommendations from existing customers are some of the best marketing you can get.
• How has our product impacted your success? Your team's success? Getting the interviewee to describe how your product played an integral role in solving their challenges will show leads that they can also have success using your product.
• In the beginning, you had XYZ concerns; how do you feel about them now? Let them explain how working with your company eliminated those concerns.
• I noticed your team is currently doing XYZ with our product. Tell me more about how that helps your business. Illustrate to your readers how current customers are using your product to solve additional challenges. It will convey how versatile your product is.
• Have you thought about using our product for a new use case with your team or at your company? The more examples of use cases the client can provide, the better.
• How do you measure the value our product provides? Have the interviewee illustrate what metrics they use to gauge the product's success and how. Data is helpful, but you should go beyond the numbers. Maybe your product improved company morale and how teams work together.

Case Study Interview Questions About Product Feedback

Ask the customer if they'd recommend your product to others. A strong recommendation will help potential clients be more open to purchasing your product.

• How do other companies in this industry solve the problems you had before you purchased our product? This will give you insight into how other companies may be functioning without your product and how you can assist them.
• Have you ever talked about our product to any of your clients or peers? What did you say? This can provide you with more leads and a chance to get a referral.
• Why would you recommend our product to a friend or client? Be sure they pinpoint which features they would highlight in a recommendation.
• Can you think of any use cases your customers might have for our product? Similar industries may have similar issues that need solutions. Your interviewee may be able to provide a use case you haven't come up with.
• What is your advice for other teams or companies who are tackling problems similar to those you had before you purchased our product? This is another opportunity for your client to talk up your product or service.
• Do you know someone in X industry who has similar problems to the ones you had prior to using our product? The client can make an introduction so you can interview them about their experience as well.
• I noticed you work with Company Y. Do you know if they are having any pain points with these processes? This will help you learn how your product has impacted your client's customers and gain insight into what can be improved.
• Does your company participate in any partner or referral programs? Having a strong referral program will help you increase leads and improve customer retention.
• Can I send you a referral kit as a thank-you for making a referral and give you the tools to refer someone to us? This is a great strategy to request a referral while rewarding your existing customers.
• Are you interested in working with us to produce additional marketing content? The more opportunities you can showcase happy customers, the better.

Case Study Interview Questions About Willingness to Make Referrals

• How likely are you to recommend our product to a friend or client? Ideally, they would definitely refer your product to someone they know.
• Can you think of any use cases your customers might have for our product? Again, your interviewee is a great source for more leads. Similar industries may have similar issues that need solutions. They may be able to provide a use case you haven't come up with.
• I noticed you work with Company Y; do you know if they are having any pain points with these processes? This will help you learn how your product has impacted your client's customers and gain insight into what can be improved.

Case Study Interview Questions to Prompt Quote-Worthy Feedback

Enhance your case study with quotable soundbites from the customer. By asking these questions, prospects have more insight into other clients and their success with your product — which helps build trust.

• How would you describe your process in one sentence prior to using our product? Ideally, this sentence would quickly and descriptively sum up the most prominent pain point or challenge with the previous process.
• What is your advice to others who might be considering our product? Readers can learn from your customer's experience.
• What would your team's workflow or process be like without our product? This will drive home the value your product provides and how essential it is to their business.
• Do you think the investment in our product was worthwhile? Why? Have your customer make the case for the value you provide.
• What would you say if we told you our product would soon be unavailable? What would this mean to you? Again, this illustrates how integral your product is to their business.
• How would you describe our product if you were explaining it to a friend? Your customers can often distill the value of your product to their friends better than you can.
• What do you love about your job? Your company? This gives the reader more background on your customer and their industry.
• What was the worst part of your process before you started using our product? Ideally, they'd reiterate how your product helped solve this challenge.
• What do you love about our product? Another great way to get the customer's opinion about what makes your product worth it.
• Why do you do business with us? Hopefully, your interviewee will share how wonderful your business relationship is.

Case Study Interview Questions About the Customers' Future Goals

Ask the customer about their goals, challenges, and plans for the future. This will provide insight into how a business can grow with your product.

• What are the biggest challenges on the horizon for your industry? Chances are potential leads within the same industry will have similar challenges.
• What are your goals for the next three months? Knowing their short-term goals will enable your company to get some quick wins for the client.
• How would you like to use our product to meet those challenges and goals? This will help potential leads understand that your product can help their business as they scale and grow.
• Is there anything we can do to help you and your team meet your goals? If you haven't covered it already, this will allow your interviewee to express how you can better assist them.
• Do you think you will buy more, less, or about the same amount of our product next year? This can help you gauge how your product is used and why.
• What are the growth plans for your company this year? Your team? This will help you gain insight into how your product can help them achieve future goals.
• How can we help you meet your long-term goals? Getting specifics on the needs of your clients will help you create a unique solution designed for their needs.
• What is the long-term impact of using our product? Get their feedback on how your product has created a lasting impact.
• Are there any initiatives that you personally would like to achieve that our product or team can help with? Again, you want to continue to provide products that help your customers excel.
• What will you need from us in the future? This will help you anticipate the customer's business needs.
• Is there anything we can do to improve our product or process for working together in the future? The more feedback you can get about what is and isn't working, the better.

Before you can start putting together your case study, you need to ask your customer's permission.

If you have a customer who's seen success with your product, reach out to them. Use this template to get started:

Thank you & quick request

Hi [customer name],

Thanks again for your business — working with you to [solve X, launch Y, take advantage of Z opportunity] has been extremely rewarding, and I'm looking forward to more collaboration in the future.

[Name of your company] is building a library of case studies to include on our site. We're looking for successful companies using [product] to solve interesting challenges, and your team immediately came to mind. Are you open to [customer company name] being featured?

It should be a lightweight process — [I, a product marketer] will ask you roughly [10, 15, 20] questions via email or phone about your experience and results. This case study will include a blurb about your company and a link to your homepage (which hopefully will make your SEO team happy!)

In any case, thank you again for the chance to work with you, and I hope you have a great week.

[Your name]

If one of your customers has recently passed along some praise (to you, their account manager, your boss; on an online forum; to another potential customer; etc.), then send them a version of this email:

Hey [customer name],

Thanks for the great feedback — I'm really glad to hear [product] is working well for you and that [customer company name] is getting the results you're looking for.

My team is actually in the process of building out our library of case studies, and I'd love to include your story. Happy to provide more details if you're potentially interested.

Either way, thank you again, and I look forward to getting more updates on your progress.

You can also find potential case study customers by usage or product data. For instance, maybe you see a company you sold to 10 months ago just bought eight more seats or upgraded to a new tier. Clearly, they're happy with the solution. Try this template:

I saw you just [invested in our X product; added Y more users; achieved Z product milestone]. Congratulations! I'd love to share your story using [product] with the world -- I think it's a great example of how our product + a dedicated team and a good strategy can achieve awesome results.

Are you open to being featured? If so, I'll send along more details.

Case Study Benefits

• Case studies are a form of customer advocacy.
• Case studies provide a joint-promotion opportunity.
• Case studies are easily sharable.
• Case studies build rapport with your customers.
• Case studies are less opinionated than customer reviews.

1. Case studies are a form of customer advocacy.

If you haven't noticed, customers aren't always quick to trust a brand's advertisements and sales strategies.

With every other brand claiming to be the best in the business, it's hard to sort exaggeration from reality.

This is the most important reason why case studies are effective. They are testimonials from your customers of your service. If someone is considering your business, a case study is a much more convincing piece of marketing or sales material than traditional advertising.

2. Case studies provide a joint-promotion opportunity.

Your business isn't the only one that benefits from a case study. Customers participating in case studies benefit, too.

Think about it. Case studies are free advertisements for your customers, not to mention the SEO factor, too. While they're not promoting their products or services, they're still getting the word out about their business. And, the case study highlights how successful their business is — showing interested leads that they're on the up and up.

3. Case studies are easily sharable.

No matter your role on the sales team, case studies are great to have on hand. You can easily share them with leads, prospects, and clients.

Whether you embed them on your website or save them as a PDF, you can simply send a link to share your case study with others. They can share that link with their peers and colleagues, and so on.

Case studies can also be useful during a sales pitch. In sales, timing is everything. If a customer is explaining a problem that was solved and discussed in your case study, you can quickly find the document and share it with them.

4. Case studies build rapport with your customers.

While case studies are very useful, they do require some back and forth with your customers to obtain the exact feedback you're looking for.

Even though time is involved, the good news is this builds rapport with your most loyal customers. You get to know them on a personal level, and they'll become more than just your most valuable clients.

And, the better the rapport you have with them, the more likely they'll be to recommend your business, products, or services to others.

5. Case studies are less opinionated than customer reviews.

Data is the difference between a case study and a review. Customer reviews are typically based on the customer's opinion of your brand. While they might write a glowing review, it's completely subjective and there's rarely empirical evidence supporting their claim.

Case studies, on the other hand, are more data-driven. While they'll still talk about how great your brand is, they support this claim with quantitative data that's relevant to the reader. It's hard to argue with data.

An effective case study must be genuine and credible. Your case study should explain why certain customers are the right fit for your business and how your company can help meet their specific needs. That way, someone in a similar situation can use your case study as a testimonial for why they should choose your business.

Use the case study questions above to create an ideal customer case study questionnaire. By asking your customers the right questions, you can obtain valuable feedback that can be shared with potential leads and convert them into loyal customers.

Editor’s Note: This article was originally published in June 2021 and has been updated for comprehensiveness.

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• eureka moment (struggling to understand a concept and then finally being able to crack it OR a creative idea) after reading story or better yet, a group of stories. Group of stories can include things like case study collections, compendiums, or anything including more than one case.
• Bridging the gap between theory and practice as a result of reading a story.

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• Instead of using the questionnaire & research questions in the paper "Large scale agile at Ericsson", try to understand from the paper what theoretical framework, theory / theories, questionnaire the author(s) had derived? Because your conceptual framework should underpinning on sound theoretical framework / theory. From there you can adopt / adapt the previous theoretical framework / questionnaire to form your own conceptual framework / questionnaire.
• Is the current company that you are researching in Network Equipment Provider (NEP) / Telco similar business or capacity of Ericsson? Why need to benchmark with Ericsson in terms of large scale Agile Transformation?

• 14 Jun 2018

• Read, re-read, and re-read (or listen, re-listen) to get familiar with data
• Code data into categories, sub-categories, and themes
• Write memos/notes to answer 'questions' emerging from codes
• Develop diagrams to connect segments (themes/categories/sub-categories) of data in relation to certain topics/themes
• Develop matrixes to compare, contrast between groups/cases in your data
• Develop a storyline to connect all themes appearing
• Compare and contrast with themes existing in literature
• Develop an overall theoretical framework to answer your research questions
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• Compared to other research methods such as surveys, narrative study, ethnography, etc., case study design in general offers a flexibility in combining a vast of methods (qualitative and quantitative) in sampling, data collection, data validation and analysis, and can offer great details of a certain phenomenon. Its general weakness might be limitation in generalising information to larger population.
• Compared to exploratory and explanatory case study designs: Strengths are that descriptive case study focuses on illuminating a phenomenon, it does not be limited to a part of bigger research like exploratory design, and also it does not have to design theoretical proposition beforehand. Weakness is thus that it cannot provide a comprehensive understanding of a phenomenon by proving/justifying theoretical linkages between components of such phenomenon.
• Yes, I think it is possible since case study design in general allows you to use vast of data collection techniques in collecting your data. However, quantitative data here cannot be used to generalised to a larger population outside the case under study.
• You need to justify how to combine these two approaches in collecting data, and more importantly, integrating those separate findings into your report.
• It depends on the way you define your case. Please refer to my answer to another question on case study design. https://www.researchgate.net/post/Hi_everyone_so_am_working_on_a_case_study_research_thesis_and_want_to_use_focus_group_discussion_What_is_the_best_way_to_select_FGD_participants#view=5add568acbdfd4486508e948
• In other words, you must define that group as the case itself, then participants in that group are sub-units.
• This design, according to Yin (2013) is 'to describe a phenomenon in its real world context'. It only helps you to describe. 'Describe' in its truest sense is just to provide a general image of a phenomenon. You may not have enough evidence to explain how and why that phenomenon works out like that. To answer the how- and why- questions, you need explanatory design.
• Sure, you can. But you cannot generalise them to a larger population. For instance, your case is a neighbourhood in a city. You cannot generalise statistically your findings of the case to that city.

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Doctoral Dissertations and Projects

Teacher's experiences of the response to intervention model implementation in state-ranked new jersey schools: a qualitative case study.

Kimberly Myers , Liberty University Follow

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Doctor of Philosophy in Education (PhD)

RTI, interventions, multi-tiered support systems, curriculum, professional development, teacher experiences, administrative support

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Recommended Citation

Myers, Kimberly, "Teacher's Experiences of the Response to Intervention Model Implementation in State-Ranked New Jersey Schools: A Qualitative Case Study" (2024). Doctoral Dissertations and Projects . 5873. https://digitalcommons.liberty.edu/doctoral/5873

The purpose of this case study was to discover and describe teachers’ experiences of RTI implementation for kindergarten through grade five general education teachers at state-ranked suburban New Jersey schools. The theory guiding this study is Bandura’s theory of self-efficacy, as it applies to teachers’ experiences of the effectiveness of the RTI process. According to Bandura, self-efficacy is the perception of how well one can execute a task. Self-efficacy can connect to teacher efficacy through the feeling of understanding the job requirements and the intended goals. This case study assessed how teachers’ experiences of the RTI process impact the overall program effectiveness in proper implementation and data collection. The central research question that this study addressed was: What are the experiences of kindergarten through grade five teachers when implementing RTI in the general education classrooms? To address this question, a group of ten general education teachers were individually interviewed, focus group interviews were conducted, and documents were analyzed to collect pertinent data to answer this case study’s driving research questions. Multiple means of data collection allowed for coding and thematic analysis to take place. This study’s findings showed the need for general education elementary teachers to be provided additional training and have administrative support in order to raise levels of teacher efficacy and create a successful RTI program. By understanding teachers' experiences with RTI implementation, future professional development and collaboration throughout school districts can be developed.

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How to Write a Research Proposal: (with Examples & Templates)

Table of Contents

Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

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

Published on 14.8.2024 in Vol 8 (2024)

A Chatbot (Juno) Prototype to Deploy a Behavioral Activation Intervention to Pregnant Women: Qualitative Evaluation Using a Multiple Case Study

Authors of this article:

Original Paper

• Elisa Mancinelli 1, 2 , BSc, MSc   ; 
• Simone Magnolini 3 , PhD   ; 
• Silvia Gabrielli 2 , PhD   ; 
• Silvia Salcuni 1 , PhD  

1 Department of Developmental and Socialization Psychology, University of Padova, Padova, Italy

2 Digital Health Lab, Centre for Digital Health and Wellbeing, Fondazione Bruno Kessler, Povo, Trento, Italy

3 Intelligent Digital Agents, Centre for Digital Health and Wellbeing, Fondazione Bruno Kessler, Povo, Trento, Italy

Corresponding Author:

Elisa Mancinelli, BSc, MSc

Department of Developmental and Socialization Psychology, University of Padova

Via Venezia 8

Padova, 35131

Phone: 39 3342799698

Email: [email protected]

Background: Despite the increasing focus on perinatal care, preventive digital interventions are still scarce. Furthermore, the literature suggests that the design and development of these interventions are mainly conducted through a top-down approach that limitedly accounts for direct end user perspectives.

Objective: Building from a previous co-design study, this study aimed to qualitatively evaluate pregnant women’s experiences with a chatbot (Juno) prototype designed to deploy a preventive behavioral activation intervention.

Methods: Using a multiple–case study design, the research aims to uncover similarities and differences in participants’ perceptions of the chatbot while also exploring women’s desires for improvement and technological advancements in chatbot-based interventions in perinatal mental health. Five pregnant women interacted weekly with the chatbot, operationalized in Telegram, following a 6-week intervention. Self-report questionnaires were administered at baseline and postintervention time points. About 10-14 days after concluding interactions with Juno, women participated in a semistructured interview focused on (1) their personal experience with Juno, (2) user experience and user engagement, and (3) their opinions on future technological advancements. Interview transcripts, comprising 15 questions, were qualitatively evaluated and compared. Finally, a text-mining analysis of transcripts was performed.

Results: Similarities and differences have emerged regarding women’s experiences with Juno, appreciating its esthetic but highlighting technical issues and desiring clearer guidance. They found the content useful and pertinent to pregnancy but differed on when they deemed it most helpful. Women expressed interest in receiving increasingly personalized responses and in future integration with existing health care systems for better support. Accordingly, they generally viewed Juno as an effective momentary support but emphasized the need for human interaction in mental health care, particularly if increasingly personalized. Further concerns included overreliance on chatbots when seeking psychological support and the importance of clearly educating users on the chatbot’s limitations.

Conclusions: Overall, the results highlighted both the positive aspects and the shortcomings of the chatbot-based intervention, providing insight into its refinement and future developments. However, women stressed the need to balance technological support with human interactions, particularly when the intervention involves beyond preventive mental health context, to favor a greater and more reliable monitoring.

Introduction

User-centered design of digital mental health interventions.

eHealth is a burgeoning field that integrates medical informatics, public health, and business. It encompasses delivering health services and information through the internet and digital technologies. In this domain, e-mental health specifically focuses on leveraging technologies, such as smartphone apps, websites, chatbots, and virtual reality, to enhance and support mental health care [ 1 - 3 ]. e-Mental health holds many advantages, including the increased scalability of mental services, in terms of screening, prevention, and treatment, leading to reduced costs for the broader health care system [ 4 - 6 ]. However, while the potential benefits of digital technology can be considerable, their actual implementation and use, especially within the field of e-mental health, often fall short. The journey from preuse considerations to initial adoption and, crucially, sustained use poses challenges that need careful navigation and understanding. In this regard, a recent review [ 7 ] exploring design methods and approaches for digital tools in mental health emphasized that human-centered design methods, thus those focusing on user experience (UX) rather than just engineering design, are not fully integrated into the field. The reported design approaches are predominantly external, lacking the perspective of the end users for whom the tool is intended. Indeed, when developing digital solutions, it is essential to consider 4 key components: the design issue and solution, the context in which the design occurs, the dynamics and organization of the design activity, and the actors contributing to the design [ 8 - 10 ]. Within the context of e-mental health intervention, the above altogether emphasizes the significance of co-design, a collaborative process strongly involving targeted end users to contribute to all stages of e-mental health intervention development. This inclusive approach encompasses needs assessment, content development, pilot-testing, and finally, dissemination [ 11 ]. The Obesity-Related Behavioral Intervention Trials (ORBIT) model [ 12 ] is instrumental to this end. The ORBIT model, which uses a user-centered design, provides a methodological framework encompassing a pliable and iterative progressive procedure, predefined clinically significant milestones for advancement, and the option to revert to a prior phase of refinement in case of suboptimal outcomes. Its primary emphasis is on pre-efficacy development and testing, yet not failing to incorporate subsequent research phases to illustrate that treatment optimization is viable even for interventions that have attained the efficacy or effectiveness stage [ 12 ].

e-Mental Health in Perinatal Care: A Focus on Prevention Interventions

The World Health Organization (WHO) [ 13 ] has consistently emphasized the significance of identifying and preventing risks, with the WHO and the United Nations Population Fund acknowledging maternal mental health as a pivotal factor in accomplishing the Millennium Development Goals [ 14 ]. The transition to motherhood involves various intrapersonal and interpersonal changes and challenges that can have negative effects on women’s mental health, increasing the risk of developing peripartum depression [ 15 - 17 ]. However, despite the negative repercussions this poses on the women, the child, and the whole family [ 18 ], as well as the broader society [ 19 - 21 ], it often goes untreated. There are various reasons for this. On the one hand, few women proactively seek professional assistance for their mental health problems, mainly due to factors such as lack of mental health literacy; stigma; and practical barriers like childcare, professional, and financial constraints [ 22 ]. By contrast, women face limited access to specialized perinatal mental health services, which is attributed to the capacity constraints of existing services and long waiting times for those in need of support [ 23 , 24 ]. Therefore, many women never receive any support or treatment. Indeed, this situation has sparked interest in the potential of e-mental health. It can circumvent some of the aforementioned barriers, ultimately facilitating a more widespread help-seeking process; this has led to the creation and dissemination of scalable and more far-reaching tools to support the well-being and mental health of perinatal women [ 25 , 26 ]. In this context, the stepped-care model is noteworthy, as its intentions are focused on promoting the dissemination of mental health programs by facilitating coordination between primary and secondary mental health services [ 27 ], and this coordination can be facilitated through e-mental health. This would ultimately align with the evidence that engaging in help-seeking behaviors increases the likelihood of perinatal women seeking further assistance for their depression symptoms [ 28 ]. In this regard, structured, evidence-based interventions such as behavioral activation (BA) might be particularly suitable. BA is a behavioral intervention designed to alleviate symptoms of depression [ 29 - 32 ] by offering individuals practical strategies to improve their adjustment and well-being and supporting participation in enjoyable and positive activities while reducing engagement in behaviors that worsen depressive symptoms [ 29 , 33 ]. As such, these interventions hold great potential as initial broad-case preventive work. However, when specifically focusing on peripartum depression, there appears to be a deficiency in digital prevention and treatment programs at large [ 34 ], and of BA interventions as well [ 35 ], in addressing depression symptoms during pregnancy compared with the postpartum period, thus underscoring the necessity to boost the development and evaluation of primary mental health services.

This Study: Within the Iterative Design Phase

This study arises from the results obtained by a previous exploratory co-design study [ 36 ] investigating the feasibility of an internet-based BA intervention for pregnant women showing subclinical symptoms of depression. As such, it constitutes the second phase of investigation within the “design phase” foreseen by the above-reported ORBIT model [ 12 ]. This prior exploratory study not only aimed to assess the initial feasibility of the intervention but also sought to gather valuable feedback directly from pregnant women. This then guided the adjustment of the intervention’s content and structure while promoting the use of a different digital solution. More specifically, the study aimed to compare a guided and unguided version of the digital intervention, with the guided group involving psychologists who engaged in weekly text message conversations with women to support them in the intervention content revision. In this respect, data suggested that the guided group showed greater adherence and were more willing overall to finish the intervention than the unguided group. Building on this and in line with the existing literature [ 37 , 38 ] highlighting the potential benefit of including chatbots within psychological interventions by fostering intervention adherence through increased engagement and involvement, a new structuring of the BA intervention as a chatbot-delivered intervention was prototyped. Chatbots are artificial intelligence–enabled engagement technologies, falling under the category of technologies that enable interaction with patients through natural language processing by engaging in limited text conversations intending to support subsequent behavior-change tasks [ 39 ]. It is crucial to emphasize that in this context, chatbots are conceptualized as tools suitable for educational purposes, facilitating the acquisition of specific evidence-based techniques or skills [ 40 ] resulting in suitability for application in preventive contexts.

Mindful of the above, this study aims to qualitatively evaluate, through a multiple case study, pregnant women’s experience and perception of a chatbot prototype to deploy a BA preventive support tool and intervention. In this regard, incorporating a dedicated prototype evaluation during co-design can streamline the process of conducting rigorous evaluations in real-world settings during the subsequent evaluative phases, which may involve activities such as pilot-testing and subsequent randomized controlled trials [ 41 ]. Furthermore, women’s desire for improvement and technological advancements of chatbot-based technology in the field of perinatal mental health was also investigated. As such, this study bounds the design and evaluation of the chatbot and prevention intervention it deploys within the ORBIT methodological framework [ 12 ], in favor of a thorough and meticulous evaluation of the intervention design phase regarding both definition and refinement. In line with this, a multiple–case study design is used as it permits the conduct of a comparative analysis of cases, aiming to identify both similarities and differences among them and, thus, in the perception of the chatbot and the content it deploys. In addition, this approach seeks to unveil patterns and themes that arise from the cross-case analysis. By evaluating the phenomenon of interest across different contexts, a multicase study might enhance the validity of findings by investigating in depth how the phenomenon may vary or remain consistent under various circumstances [ 42 ].

Ethical Considerations

Ethical considerations adhered to the guidelines outlined in the Declaration of Helsinki [ 43 ] and European data protection laws (EU GDPR 679/2016). Approval for the study was obtained from the Ethical Committee of the Psychology Department at the University of Padova (approval 5434/2023). Participants provided their informed consent to participation and data publication for scientific reasons.

Participants and Enrolment Procedure

Women aged >18 years and between the 12th and 30th week of gestation could take part in this study. Exclusion criteria were the following: clinically significant depression symptoms (Patient Health Questionnaire-9 [PHQ-9] [ 44 ] score≥15), suicidal ideation (PHQ-9 item 9), present or past history of psychiatric disorders, and experiencing an artificially induced pregnancy. To allow participation, a Google Form link containing the baseline questionnaires was shared through social media platforms (ie, Facebook and Instagram) in pregnancy-related national groups and pages. After the inclusion and exclusion criteria evaluation, women were provided with the information needed to start the interaction with the chatbot in Telegram and sent a copy of the informed consent they had agreed on that was reported within the web-based questionnaire. To uphold confidentiality, each participant was assigned a unique alphanumeric code. Women were granted the autonomy to withdraw from participation at any point without the obligation to provide reasons and without facing any adverse consequence. Furthermore, they were clearly informed that the software (ie, Telegram and the chatbot) did not constitute a medical device, as its use does not extend to the diagnosis, prevention, monitoring, prediction, prognosis, treatment, or alleviation of diseases. It was, instead, clarified that the developed support intervention and related software were exclusively intended for research purposes and used for the sole collection, storage, transmission of data and administration of questionnaires.

A total of 12 women completed the baseline questionnaire. Among them, 2 dropped out after the first interaction (week 1), 2 after completing the interaction in week 2, and 2 following the third interaction (week 3). One participant withdrew after completing the interaction in week 4. Among those who dropped out in the early weeks, 5 reported medical conditions: Crohn disease, risk of miscarriage associated with a shortened cervix and hypertonic pelvic floor, gestational diabetes, hypothyroidism, and fibroma. Ultimately, 5 participants were included in the multiple–case study evaluation, with none reporting any medical conditions. Of them, 4 (80%) participants reached the postintervention questionnaire evaluation, while 1 (20%) had to interrupt the interaction after week 4; however, she agreed to participate in the final semistructured interview. Given that this study aimed to qualitatively evaluate the perception and experience with a chatbot prototype, the decision was made to include this participant despite not finishing the study since she nonetheless was able to engage with the chatbot for more than half of the anticipated interactions.

The Intervention Content and Structuring

This study aligns with the iterative process outlined in the ORBIT model [ 12 ] for intervention design and evaluation. Specifically, it falls within the refined subphase of the initial design phase, in which practical aspects such as mode and agent of delivery, as well as the frequency and duration of contact, are evaluated to identify the most efficient ways to achieve clinical targets. Parallel to this, and in reference to the Digital Product Lifecycle, we care to emphasize that this project is at the beginning stages of the product life cycle, thus moving back and forth between the “definition phase” (in which the product or intervention concepts and related digital requirements are defined) and the “design phase” (which involves prototyping and pilot-testing the product) [ 45 , 46 ].

Accordingly, this study focuses on evaluating a revised version of an intervention based on an evidence-based BA intervention protocol (behavioral activation treatment for depression-revised) [ 47 ]. This revised intervention represents a second evaluation that builds upon exploratory testing conducted in a preceding co-design study [ 36 ]; as such, thorough information on the intervention content and rationality can be found in this prior study paper. However, commencing with the results from this latter study, in this study, the intervention was organized into 6 weekly sessions ( Figure 1 A), omitting the 3 additional ones previously included. The intervention content was streamlined by eliminating separate in-between–session homework. Instead, the essential components of the homework were incorporated within the main sessions or interactions as on-the-moment exercises strategically designed to promote the original intent of the homework. In this context, it is noteworthy that while the original protocol may not explicitly encompass a comprehensive functional analysis, several treatment components seamlessly aligned within such a framework and were further enhanced in the modified version of the intervention. This alignment is underscored by BA’s dual objectives of pinpointing factors that sustain or reinforce depressive behaviors (both positive and negative reinforcement) and identifying positive reinforcers that can support healthy behavioral patterns ( Figure 1 A). This process thus forms the basis for understanding the functional aspects of behavior, laying the groundwork for targeted strategies that can aid the person in autonomously addressing and modifying the maladaptive behavioral patterns effectively.

Moreover, there was a modification in the mode of delivering the intervention. Specifically, the content, previously structured as an e-learning course, was facilitated through a rule-based chatbot named Juno, operationalized within the Telegram platform with the sole purpose of delivering the intervention. As such, information was delivered through text messages, complemented by explanatory videos and images using the Telegram interface. The text messages were sent by Juno, which adhered to a preestablished protocol that had to be followed sequentially, enabling structured dialogues in which women engaged primarily by selecting the predefined buttons to navigate the conversation. Due to the rule-based nature of Juno, individualized feedback was not provided. In this regard, Figure 1 B depicts a simulation of the interaction between Juno and the user, showing how Juno responds and guides the user during the on-the-moment exercises (the reported example is an exercise conducted during week 2 reported in Figure 1 A “The bidirectional link between behavior and emotions”).

Moreover, by using the Telegram interface, participants can access multimedia resources such as videos and images in the multimedia section of the app. In addition, they could scroll back through the chat history to review past topics, although there was not a specific page summarizing the weekly intervention topics. This allowed participants to revisit and reinforce previous discussions as needed while maintaining the logical sequencing of the intervention. Conversations were structured to last around 10 minutes per session.

The Implementation of the Chatbot Juno in Telegram

The chatbot Juno was developed drawing inspiration from the methodology used in designing Motibot, a chatbot dedicated to providing psychosocial support to adults with diabetes mellitus [ 48 ]. Leveraging the capabilities of the Rasa open-source platform [ 49 ], which has been explicitly tailored for chatbot development and training, became viable owing to the domain-agnostic nature of Motibot’s core structure, which provided a remarkably flexible foundation. The Rasa platform seamlessly integrates advanced machine learning techniques and harnesses pretrained embeddings from language models. This integration empowers the construction of a chatbot finely tuned to a specific language. The synergy of machine learning techniques with crafted rules ensures a chatbot that is not only dynamic but also highly responsive. Within Juno, the pivotal role played by natural language understanding [ 50 ] became evident in interpreting user messages while considering the conversational history. A carefully defined set of variables facilitated a smooth transition between turns in the dialogue.

For instance, named entity recognition, a specific natural language understanding task, was used to interpret the intent “say your name” and identify the entity “user’s name.” Juno optimally used Telegram as its user interface, offering numerous advantages to users while streamlining the development process. In addition, Telegram’s built-in support for interactive tools, including buttons, links, and images, enhanced the overall UX. In this regard, enhancing UX involves using personalized interaction time frames. Juno, as part of its intervention process, prompted users at the end of the initial day to specify when they prefer follow-up contacts. This proactive approach assisted users in scheduling their intervention; Juno uses Rasa’s reminder interface to accomplish this task. However, potential server malfunctions can affect this tool. To mitigate such issues, Juno allows users to initiate the interaction (eg, by writing the message “Can we start?”) if the reminder date passes without any notification. Despite being a solution to a possible interaction problem, this approach should maintain a positive UX. Furthermore, it should be acknowledged that in this initial phase of development, the possibility that the chatbot could occasionally overlook an appointment was a possibility.

Moreover, in line with what was reported above, it is noteworthy that Juno follows an expert-written structured script to maintain focus on the intervention content and avoid deviating from the intended topics. Users can provide input by selecting predefined buttons or providing written responses, but they do not receive personalized feedback based on their input. If users attempt to engage with Juno outside the scope of the intervention, Juno informs them that it cannot respond to such queries and returns to the predefined interaction by starting from where they had left off.

With regard to data storage, no further development was required, as the native support of Rasa for storing interactions in a MongoDB database (ie, a universal time stamp) ensures both consistency and the archiving of users’ data (ie, log-in information, the time spent by each user interacting with Juno, etc).

Measurement Instruments

During the baseline assessment, women were asked the following demographic information: age, gestational week, if the pregnancy was physiological or induced through medically assisted techniques, marital status, educational level, category of occupation, living location, past and present psychiatric history, and presence of any medical condition (both pregnancy-related and not). Moreover, during the baseline assessment, participants completed questionnaires assessing psychological symptoms, levels of BA, and perceived environmental reward. The same questionnaires were administered at the end of the sixth week of interactions, facilitated by Juno in the Telegram Chat, for a postintervention evaluation; the UX and user engagement (UE) measures were included in the postintervention assessment.

Psychological Symptoms

Depression symptoms were evaluated through 2 unidimensional self-report tools: the PHQ-9 [ 44 , 51 ] and the Edinburgh Postnatal Depression Scale [ 52 , 53 ]. The PHQ-9 assesses the severity of depression symptoms over the past 2 weeks through 9 items measured on a 4-point Likert scale (0=“not at all”; 3=“almost every day”). Items align with the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders , Fourth Edition [ 54 ]. A score of ≤9 indicates mild or no depression symptoms, between 10 and 14 indicates moderate symptoms, and ≥15 indicates severe symptoms. Item 9 specifically assesses suicidal ideation. The Edinburgh Postnatal Depression Scale also assesses the severity of depression symptoms, yet on the previous week and more specifically in association with the perinatal period. It comprises 10 items measured on a 4-point Likert scale (0=“no, not at all”; 3=“yes, always”), with item 10 assessing suicidal ideation. Scores range between 0 to 30, and a score of ≥13 suggests probable depression. Anxiety symptoms were measured through the Generalized Anxiety Disorder-7 [ 51 , 55 ], a unidimensional self-report tool gauging the severity of these symptoms over the past 2 weeks through 7 items measured on a 4-point Likert scale (0=“never”; 3=“almost every day”). Scores range between 0 and 21; a score between 0 and 4 suggests minimal anxiety, between 5 and 9 mild anxiety symptoms, between 10 and 14 moderate anxiety symptoms, and ≥15 severe anxiety symptoms. Finally, stress symptoms were assessed through the Perceived Stress Scale-10 [ 56 , 57 ], a unidimensional self-report tool assessing stress symptoms over the past month using 10 items measured on a 4-point Likert scale (0=“never”; 3=“quite often”). Scores range between 10 and 40, with scores ranging from 0 to 13 suggesting lower stress levels, between 14 and 26 moderate stress levels, and ≥27 high perceived stress levels.

BA Measures

The BA for Depression Scale-Short Form [ 58 ] was used to measure changes in avoidance and activation during BA interventions for depression over the past week. It is a self-report featuring 9 items measured on a 7-point Likert scale (0=“not at all”; 6=“completely”), providing scores for BA, behavioral avoidance, and a total score ranging from 0 to 54. The Environmental Reward Observation Scale [ 59 ], a unidimensional self-report tool, was also used; it measures the level of environmental reward perceived in recent months through 10 items rated on a 4-point Likert scale (1=“strongly disagree”; 4=“strongly agree”). Scores range from 10 to 40.

The UX was evaluated through the Mobile Application Rating Scale [ 60 ], a self-report tool evaluating the quality of an app and its features. Comprising 23 items scored on a 5-point Likert scale (1=“poor”; 5=“excellent”), it assesses 4 dimensions of objective quality: engagement, functionality, esthetics, and information, along with a subjective quality scale. Only subscales related to “information,” “subjective app quality,” and “app-specific” (function) were considered for this study, totaling 17 items. UE was instead evaluated through the User Engagement Scale-Short Form [ 61 ], a short self-report tool assessing UE with a digital solution. With 12 items based on a 5-point Likert scale (1=“strongly disagree”; 5=“strongly agree”), it encompasses factors such as focused attention, perceived usability, esthetic attractiveness, and reward. Higher scores index a more positive evaluation.

Semistructured Interviews

Semistructured interviews, conducted by the first author between October and December 2023, featured 15 main questions tailored to the study. The semistructured interview comprehends 3 main blocks of questions and related probing questions: one focused on women’s personal experience with the intervention content (4 questions), another focused on their experience with the chatbot and the overall platforms (5 questions), and the last one inquired on opinions for future technological advancements (6 questions). Before asking the last block of questions, participants were provided with the definitions of digital intervention and technological advancement within the context of chatbot technologies, as reported in the Multimedia Appendix 1 . The interviews were conducted approximately 10 to 14 days after the participants had finished the interactions with the chatbot Juno; they were conducted either by phone call or through Google Meet, based on the participants’ preference. With the participants’ consent, the interviews were audio recorded for transcription and evaluation.

Data Analysis

All the analyses were computed with RStudio (RStudio IDE). Participants’ questionnaire scores were assessed, and score differences in psychological symptoms and activation levels, between preintervention and postintervention time points, were calculated by subtracting the postintervention scores from the baseline ones. Relying on the qualitative meaning of response points (particularly for the psychological symptoms, measured on a 4-point Likert scale), differences between time points were commented on when they differed by a minimum of +3 or –3 score points.

The semistructured interviews were evaluated in 2 different but complementary manners. First, a purely qualitative descriptive evaluation was conducted by extracting and evaluating the key points reported by each case in the related interview transcript for each question. Subsequently, a text-mining analysis was performed using the R package quanteda [ 62 ]. To this end, (1) the transcripts, written in Italian, were tokenized by using the specific quanteda function and converting uppercase letters into lowercase letters, removing numbers, punctuation, and stop words. Subsequently, (2) user responses were subdivided and grouped based on the question they referred to in separate .txt files. Finally, (3) recurrent words (ie, word stems) and their diagrams (ie, pairs of reoccurring word stems) were extracted; the former were considered recurrent if they appeared at least 3 times, while the latter if they appeared at least 2 times across interviews. The 3-occurrences criterion threshold was defined in line with past research [ 48 ]. In particular, the 3-occurrences criterion for including a stem was chosen based on the assumption that through this, an occurrence is expected to belong to the 5% most recurrent ones. This criterion resulted in the extraction of between 2.4% and 9.2% of the most recurrent stems (average 5.5%) for the different questions, reasonably complying with the assumed 5% threshold. In addition, for a given question, the average occurrence of stems was 1.3; thus, a 3-occurrences threshold was equivalent to the condition of a stem recurring with a frequency corresponding to more than twice the average occurrence.

Cases Presentation

Table 1 shows the participant’s demographic information. Figure 2 shows their scores regarding psychological symptoms, activity level, and environmental reward at baseline ( Figure 2 A) and the postintervention time point ( Figure 2 B), further plotting the difference between the 2 time points ( Figure 2 C). Of the 5 cases, participant E completed the interaction with Juno until (and including) week 4 because of a technical issue with the server provider of the chatbot (the update of the server’s public certificate resulted in a compromised connection between the Rasa server and Telegram, and despite efforts within the support time frame, communication restoration was unsuccessful). As such, her postintervention evaluation measurements are not available. It should also be noted that because of technical issues linked to the temporalization of the interactions, participant B skipped the interaction of week 2, participant A skipped the interaction of week 3 ( Figure 1 ), and participant D skipped the interaction of weeks 3 and 5. Furthermore, all participants had to autonomously prompt the interaction with Juno at least once.

Differences and Similarities Across Cases: Questionnaire Scores

Regarding the trend of change between the 2 time points, women showed comparable levels of psychological symptoms, BA, and environmental reward at baseline, which instead seem slightly different at the postintervention time point. More specifically, participant C stands out as the only one showing a reduction in all psychological symptom variables, with changes ranging from 3 to 4 score points. However, the levels of BA and environmental reward appear seemingly unchanged. By contrast, participant A seems to exhibit a peak in the reduction of stress symptoms and an increase in BA. Interestingly, participant B demonstrated a trend of increase in anxiety symptoms, alongside a trend of reduction in depression symptoms and a notable peak in increased BA.

In contrast, participant D appears to demonstrate a negative peak in BA (ie, a decrease), while the other dimensions seem unchanged. Notwithstanding, it should be stressed that at either time point, none of the participants reported clinically relevant symptoms in terms of depression, anxiety, and stress symptoms. Finally, Figure 3 plots the participants’ evaluation of UX and UE. Taken together, participant B provided, in all dimensions, the lowest UX and UE scores, while participant D had the highest scores. More specifically, all showed a quite high appreciation for the esthetic of the interactions (mean 4, SD 0) and a modest to high perceived usability of the chat (mean 3.67, SD 0.82), which although seems particularly true for participant D, while less so for participant B.

Furthermore, the latter reported a particularly low sense of absorption during the interaction, which was quite low also for participant C. This sense of absorption was instead moderate for participants A and D (mean 2.42, SD 1.17). These 2, together with participant C, also reported a moderate to quite high sense of reward from the interactions (mean 3.33, SD 0.72), instead lower for participant B. A comparable pattern emerged regarding UX-information (mean 4.08, SD 0.63); in addition, participant B, for whom the information was of modest quality, participants A, C, and D instead evaluated them as high-quality information in terms of credible sources, quantity, and clearness. An almost equal score distribution emerged for the app-specific function (ie, the app operation in terms of easy learning, logical flow, and gesture interaction design; mean 3.38, SD 0.75) and subjective quality (ie, the actual availability of using the app; mean 2.69, SD 1.01), with the latter being way lower.

Multimedia appendix 1 shows participants’ specific scores reported in Figures 2 and 3 .

Differences and Similarities Across Cases: Qualitative Evaluation of the Semistructured Interviews’ Answers and Text-Mining Results

A summary of the key concepts that emerged from the answers provided during the semistructured interviews is reported in Tables 2 - 4 , separately for each case. In this regard, it is worth noting the answers provided for q00 regarding the motivation for participation; only participant B reported a more personal motive linked to a desire to enrich her pregnancy experience. Differently, participants C, D, and E (participant E revealed during the semistructured interview that she is a perinatal psychologist and that she participated in the study because she was curious to experience firsthand the potentiality of digital tools in this context) were pushed by curiosity and a personal propensity to help with research. Finally, participant A reported that her curiosity was sparked by seeing one of the institutions that is part of this study.

a d/n: did not know what to answer.

a FAQ: frequently asked question.

b Not applicable.

Focusing on the text-mining analysis performed, the interview length ranged between 27.41 and 60.02 (mean 42.3, SD 12.63) minutes. After deleting the stop words, transcripts included a mean of 1732.8 (SD 795.78) words per participant. Overall, the aggregated results (text mining) are shown in Figures 4 - 6 . The nodes (ie, word stems) dimension illustrates the proportion of concept occurrences across transcripts for a specific question, all appearing at least 3 times. Word stems connected by arrows represent diagrams that have occurred at least twice. The word stems are translated after analysis for inclusion in the plots; therefore, the direction of the arrows reflects the Italian syntax.

Personal Experience With the Chatbot Juno

As for the text-mining aggregated results, the transcript of the interviews regarding participants’ personal experience with Juno included, after deleting the stop words, a mean of 67.56 (SD 28.39) words per question. Results are summarized for each question in Figure 4 . Instead, Table 2 summarizes, separately, the participants’ answers to each question. In this respect, all participants reported feeling negative regarding the technical problems encountered, except participant C, who felt indifferent to them. Noteworthy is that although all skipped at least 1 interaction, participant C is the sole one that had not skipped any interaction, while further reporting that she “knew that this is a research project,” thereby highlighting that she had foreseen some issues to occur. In line with this, the text-mining results highlighted the feelings of displeasure , untimely making the experience less impactful ( made it→less→impactful; q01).

Nonetheless, the experience (in terms of the content of the interactions) was liked and felt very interesting , in particular, the content of the exercises/questions (q02). However, participant A specified that she would have preferred if the latter were proposed in a more structured manner while also allowing for the possibility to continue practicing them in between the interactions to favor a sense of continuity. Furthermore, participant D felt that some of the questions (part of the exercises) were redundant. Participants B, C, and D instead stressed their appreciation for how the broader content was deployed in terms of videos and images, while participant E specifically appreciated how the messages were phrased. The overall content of the interactions, particularly the initial psychoeducation, was felt as pertinent and adequate. Coherently, the text-mining results highlighted that the interactions’ content was felt useful , allowing participants to take a moment to pay attention to themselves (q03). In this regard, they all reported that the content was pertinent to the pregnancy period ( period→pregnancy ) but could also be useful during the postpartum and the future in general , supporting them in asking for help ( ask→help ; q03 and q04) and in general favoring a self-awareness that can transversally be applied to life in favor of well-being. However, focusing on the subjective answers, while participant B felt that the content was suited for the beginning of the second trimester, participant C felt that such a period was already too late and that the support provided by the chatbot was better suited for the emotional tumult of the first trimester.

At last, all women felt the 6-week length of the intervention was adequate , although, given the length of the pregnancy period, they could have followed it even for a longer time (q05). This latter aspect was stressed by all those who had skipped at least 1 week of interaction and not by participant C, who had followed all 6.

UX With the Chatbot Juno in Telegram

The transcript of the interviews regarding participants’ UX with the chatbot Juno in Telegram included, after deleting the stop words, a mean of 69.65 (SD 29.95) words per question. Results are summarized for each question in Figure 5 , while Table 3 reports participants’ answers. With regard to women UX in interacting with Juno, as previously outlined, experiences were quite different, albeit the technical problems with the chatbot Juno have emerged as a matter to particularly account for (q08). In this regard, participant B pointed out the importance of providing clearer guidance, ideally beforehand, on how to autonomously deal with technical issues to help avoid feelings of confusion. Notwithstanding, all women showed appreciation for the esthetic of the material ( esthetic→material ) describing it as cute . Furthermore, it mostly brought the focus of the UX to the way Juno answered their inputs, highlighting the relevance of this aspect, thereby wishing for an increased personalization of the answers (q06). However, despite this, participant A perceived that because of the way messages, in general, were phrased and of the overall interaction flow, these made her at times “forget that there was not a person on the other side.” This is instead different from participant B’s perception, who considered the messages to be a bit sterile. In between these 2 polarities is instead the perception of participants D and E, the former describing them as “sufficiently spontaneous and realistic” and the latter further stressing that, although she felt properly guided by Juno, perceiving clearly that Juno was virtually created made her feel reassured. Coherently, when asked about their opinion on using a chatbot as a means to deploy psychological content (q07), participant A reported that the interactions’ limits (in terms of chatbot freedom) were both a limit and a strength. Nonetheless, overall, women felt that it could be an effective medium that can provide a kind of momentary containment ( type→containment ) and that it might work as a cue to subsequently reach for in- person support. Indeed, they felt that beyond its application in preventive contexts, a psychologist is needed ( go→psychologist→instead ; q07), and even in the context of this study, participant B felt the need for human contact at least by telephone call.

Finally, focusing on the app itself, women all agreed on the convenience ( convenient→app ) of Telegram as an interface, allowing them to avoid downloading another app and describing it as an optimal channel that they already knew and that is easy to use (q09).

Opinions on Future Technological Advancement

The transcript of the interviews’ answers regarding the participants’ desired technological advancement included, after deleting the stop words, a mean of 159.49 (SD 53.01) words per question. Results are summarized for each question in Figure 6 ; Table 4 reports the participants’ answers. Overall, when asked about opinions on future technical advancements, women’s answers were quite cohesive. In line with this, when asked about how they would image an ideal app in the context of perinatal care (q10), the greater focus was on the information content ( content→information ) related to what happens during pregnancy and in the different trimesters ( happens→trimester ) as well psychologically ( well-being→psychological ). It was also focused on the possibility of searching for this information and reading about it ( go→search ) freely.

Furthermore, they reported interest in having a chat with a chatbot within the app mainly to ask personal questions related to their personal experience ( linked to→experience→personal ). In this regard, focusing specifically on the potential technological advancements that could be foreseen for chatbots like Juno (q11), women showed a lack of interest in including vocal commands in terms of sending and receiving audios ( command→vocal→no ) and did not show a particular interest in personalizing the chatbot appearance ( personalization→appearance→chatbot ), albeit recognizing that others might. The sole exception was participant E; she reported voice commands as the first thing she would have liked to add, perceiving it as a way to optimize time. Regarding personalization , this aspect was again prominent among all women, stressing their desire to receive more personalized ( personal ) answers . However, albeit desired, such increased personalization and freedom of the chatbot also emerged as women’s main concern regarding the application of these tools in the mental health context (q12). As such, women reported the need to maintain human→monitoring . Indeed, worries were expressed regarding the kind of information the chatbot might give if unsupervised.

Furthermore, they expressed worries related to increased freedom and resemblance to human interactions, with the idea that this might lead to an overreliance on these tools. Indeed, they stressed the risk of these substituting interactions ( substitute→interaction ) with professionals and psychologists ( support→psychologist→risk→more→freedom→chatbot ), which was not desired. In line with this, participants believed that although a main advantage of these technological→tools is that they can be valuable in supporting psychological→well-being in preventive contexts ( preventive→terms ) or to satisfy specific needs without waiting to make an appointment , they cannot equate a therapeutic→intervention delivered in-person, particularly during pregnancy (q13). To deal with the concerns and risks reported, women agreed on the importance of underlining and reminding of what to expect from these tools ( meaning→tools ) and clearly stating their limits , thereby distinguishing the kind of support that can be received by a physical person versus a digital tool ( digital→person ). This would then also work as a disclaimer, thus preventing them from feeling disappointment when perceiving the limits of these tools (q14). In line with the above, women expressed a strong desire for an app that could be integrated within the health (care) →system, perceiving it as something that could create a shared space that facilitates interactions with gynecologists , thereby allowing the latter to account for women’s psychological well-being together with the medical aspects.

Principal Findings

This study aimed to use a multiple–case study design to evaluate and compare pregnant women’s experience and perception of Juno, a chatbot prototype to deploy a BA preventive support intervention; their opinions regarding desired improvements and technological advancements were also investigated. The insights gained from this study are valuable and in line with previous studies emphasizing the importance and essential nature of evaluating prototypes during the design stages of a digital tool and chatbot in particular [ 41 , 63 ]. Within this context, the adoption of a multicase study design [ 42 ] allowed us to gather valuable in-depth information on the similarities and differences in pregnant women’s perceptions, opinions, and desires while also evaluating the technical issues encountered and their impact on women’s experience [ 63 ].

Focusing on the implementation and operationalization of Juno in Telegram allowed women to benefit from the lack of installation requirements, experiencing an interface within a familiar environment; this is an advancement from the platform used in the previous study [ 36 ]. Instead, feedback regarding the materials’ esthetic and intervention content at large was again appreciated, and the content, in particular, was described as sound and useful. Women expressed specific appreciation for the exercises proposed by Juno as part of the BA intervention, assessing that they favored self-reflection. Differently from the previous study [ 36 ], most women would have liked for the intervention to be longer. This might be linked to the weeks of interaction skipped since only participant C who had completed all 6 interactions would have not lengthened the intervention. Another explanation could, instead, be linked to the change of platform and even more the new structuring of the exercises. Compared with the previous structuring [ 36 ], they have been changed so to be as short, simple, and effortless as possible, and as such, they were turned into on-the-moment reasoning exercises guided by Juno and no longer as in-between–session homework. This altogether seems to have been appreciated by women, except for 1 participant A, who instead stressed that she would have preferred to have the possibility to continue training them autonomously through practical exercises also in between the interactions. The desire for continuity became evident throughout her interview, suggesting that the digital tool was perceived as a companion to turn to when extra support was needed by providing a personal space to freely take care of herself. Participant E also highlighted this, considering it as something with added value, especially during the postpartum period, helping her take care of herself to then potentially better care for the newborn.

Mindful of the above, it is pivotal to remember that women in this study can be deemed “healthy,” as none of them present medical conditions, and all psychological symptom variables were below the clinical thresholds. Notwithstanding, it is worth noting that participant C, who besides having cleared the 6 interactions, also reported the highest symptomatic scores at baseline, showed the greatest and most consistent trend of reduction in symptom scores. However, despite some pretest-posttest changes in symptom variables scores, none of the participants ever reached clinical relevance, so they should be regarded as normal fluctuations in the state of well-being and ill-being occurring during pregnancy [ 64 ]. As such, the positive feedback on the meaning of the content and the exercises proposed is important since within a preventive context, the goal is not symptom reduction or resolution but to emphasize the awareness of psychosocial functioning and the intricate relationship between emotions and behaviors. This would ultimately allow the development of transversally applicable personal resources that can be applied across life situations, thus fostering adaptation capacities at large. Women here appeared to have perceived these benefits, acknowledging that the intervention content was relevant to the pregnancy period and could potentially be helpful during the postpartum and in the future. However, it is worth highlighting a difference in its perceived usefulness as a function of the pregnancy period during which they thought that the intervention should be deployed. Participant B considered it suitable for the early pregnancy period, around the beginning of the second trimester, while participant C suggested it was more beneficial for the emotional tumult of the first trimester. It is noteworthy that both women followed the intervention during the same gestational week. Such individual differences in the perception of need are though important in terms of motivation in following the preventive intervention and in the foreseen impact of the information received.

Notwithstanding these individual differences, consistent patterns across women’s feedback were identified, particularly when asking them how their ideal digital tool developed to provide psychological support during pregnancy should be. The first thing they stressed regarded the content; within a preventive context, all women felt the need for more holistic information in which the medical and the psychological aspects are integrated, helping them understand how the 2 influence each other to then receive guidance in understanding what is “normal” and what is not. They expressed a preference for this information to be readily available, giving them the freedom to access it as they preferred. This could indeed support their empowerment [ 26 ] and aligns with the evidence highlighting that engaging in help-seeking–related behaviors increases the likelihood of perinatal women seeking further assistance in the future if needed [ 28 ]. As for receiving support for their own subjective experience, women pointed to chatbots, seeing them as having the potential to provide a 24/7 means to answer their pregnancy-related questions. This was viewed in the context of containing worries without the need to wait or continually seek assistance for potentially smaller concerns. However, all women consistently emphasized that chatbots should not be intended to substitute in-person support or human relationships more broadly. They highlighted the importance of the perception of contact and vicinity for pregnant women. Furthermore, although recognizing the potential benefits in preventive contexts, in situations of greater need and increased psychological symptoms, women stressed that chatbots should always be accompanied by human monitoring.

Keeping this in mind, it is important to reason about the technical problems encountered with the chatbot Juno. Except for the sole woman who did not skip any interactions (participant C), all other women reported their dissatisfaction with the technical problems encountered. Their reactions varied from feeling that the intervention content became less impactful to experiencing frustration, disappointment, confusion, and a perception of loss of control. These aspects are particularly significant in a mental health context, even if preventive, since such perceptions might reduce the willingness to follow the intervention by hindering their sense of agency. Notably, participant B, who participated with the desire to enrich her pregnancy experience, reported higher and more personal expectations toward the intervention. Consistently, her scores on the UX and UE questionnaires and the results from the semistructured interview suggest that she felt the most negative about the technical problems encountered. In contraposition, participant C, who assessed that she knew that interactions with Juno were “part of a research project,” acknowledged the technical problems but remained indifferent. However, it is crucial to consider the reported feelings of confusion and loss of control. While desiring a more personalized chatbot to receive answers that are more in tune with their individual needs, participants themselves emphasized the importance of clear explanations and reminders about the chatbot’s capabilities and limitations as it becomes more sophisticated and autonomous. This is essential to prevent overreliance on the chatbot and to avoid potential disappointment and iatrogenic effects that could decrease the likelihood of seeking help in the future. When discussing the use of chatbots like Juno as a means to deliver psychological content, participants acknowledged its effectiveness in providing momentary containment and serving as an initial step before seeking further support. However, they also underscored the need for human psychologists or professionals in preventive contexts. Participant B, in particular, expressed a desire for some “human” contact, even by telephone while interacting with Juno. This resonates with a compelling argument made by Sedlakova and Trachsel [ 40 ]; they conducted an epistemic analysis of chatbots’ adoption within mental health or therapeutic contexts, prompting the need to carefully reason about how chatbots can be perceived. As such, in line with women’s desire for increased chatbot personalization but worries linked to its potential increased freedom, the authors [ 40 ] suggested balancing the number of humanlike characteristics and features of chatbots and that their application should be confined to specific functions.

Focusing on the broader real-life application of apps and chatbots in contexts such as the health care system, beyond being highly desired, they were seen as tools that could bridge between women and clinical professionals. Moreover, in line with the above, women reported that having such tools would make them feel like their psychological well-being was accounted for together with their physical well-being since the former is felt neglected. Another aspect that has emerged is that they could help favor self-monitoring and monitoring from the clinician; existing literature does indicate that tools of this nature are acceptable to perinatal women as a means of monitoring mood symptoms [ 65 ]. In this regard, the Interactive Centre of Perinatal Excellence developed by the Australian Centre of Perinatal Excellence [ 66 , 67 ] is noteworthy. It is an interactive digital screening app integrated into the health care system and designed to facilitate screening for perinatal depression and anxiety symptoms. It provides women with feedback on the screening results while generating related reports for the clinician. It can support the prevention of perinatal mental health disorders by empowering women, streamlining the screening process, and saving time and resources for both women and clinicians. In such a context, the inclusion of a tool like Juno within an app to “educate” and guide women through their pregnancy and postpartum while allowing for symptom monitoring might hold great potential; what if, within such an app, the preventive BA intervention deployed through Juno was proposed to women showing mild and/or moderate depression symptoms?

The literature highlights consistent prevalence metrics of depression symptoms throughout the whole pregnancy period (worldwide, 20.7%; Europe, 17.9% [ 68 ]; Italy, 6%-22% [ 69 - 72 ]), pointing at it as among the main predictors of postpartum depression [ 16 , 73 ], with repercussions on the quality of life of women [ 74 ] as well as on the child’s development and well-being [ 75 - 77 ]. These metrics highlight the necessity of collaborative efforts in designing and implementing tailored programs, particularly in primary prevention (to prevent symptoms before they start) and secondary prevention (targeting individuals at risk or with subclinical symptoms) [ 78 ]. This is especially crucial, given the unique characteristics of peripartum depression, referring to its direct association with the challenges and bodily changes inherent to the perinatal period [ 79 ] and stressing the need for tailored intervention programs. In this regard, taken together, our results suggest that Juno holds potential for apps in a preventive context, which is of value considering the paucity of preventive perinatal tools [ 34 ]. However, it has also emerged that within this context, a tool like Juno is not deemed as sufficient. In this regard, the comments made by participant A are emblematic; she felt that what Juno could give within the broader perinatal period was like “a drop in the ocean.” This is further exemplified by the dropout of all women with medical conditions, which suggests that in its current form, the intervention deployed through Juno would have limited application. As such, data indicate that its real-life adoption might be scarce if not inserted within a broader context that can better signify its value while allowing us to account for women’s differences in need, which influences the type and amount of use they would make of it. Furthermore, beyond ensuring a better functioning of the tool itself, a thorough action plan linked to problem resolution should be defined and provided to women (both in research and real-life contexts). However, the evaluation of these issues resonated with literature emphasizing the advantages of incorporating dedicated prototyping and implementation phases during the co-design of digital tools [ 41 ].

Study Limitations and Future Directions

Although the results’ generalizability cannot a priori be expected in this study design, women’s high educational level and residency in northern Italy still represent a limitation. Perinatal depression symptoms tend to be higher among women with lower educational levels [ 80 ], suggesting a potential bias in the sample. In addition, the mentioned sample’s characteristics may reduce the variability of analyzed cases, impacting the generalizability of the findings. A further limitation regards data collection, as it relied on self-reports and semistructured interviews, which are indeed vulnerable to social desirability biases. Moreover, in this study, women’s experience with depression symptoms and their use of e-mental health tools were not measured, thus representing a limit of the study. Nonetheless, assessing these matters could provide valuable insights into their perceptions and potential use of chatbots during pregnancy. These dimensions warrant consideration in future studies to better understand the factors influencing women’s engagement with digital interventions during this critical period.

Being at the beginning of the product life cycle [ 45 , 46 ], referring specifically to the technical problems encountered, while they represent a limitation in the study, their management by the research team was invaluable in providing insights into the software used and the potential of Rasa. This understanding contributes to a more flexible problem-solving approach for addressing current and potential future issues. Proactively addressing such problems helps users maintain a sense of control and proficiency with the tool. In addition, these issues offer important information on how problem resolution, or lack thereof, impacts the overall UX. In this regard, it is noteworthy that the users did not express dissatisfaction with the simplicity of the solution, which primarily operated on rule-based mechanisms. This emphasizes the significance of incorporating user-centered design principles in developing natural language processing solutions that effectively meet end users’ needs and expectations.

Conclusions

In line with this, good practices can be outlined to construct appropriate validity and mitigate any negative effects on the user, thus ensuring ethical standards [ 81 - 86 ]: (1) ground intervention content in evidence-based data pertinent to the perinatal literature; (2) seek input from both end users and clinical professionals to evaluate needs and gather feedback on intervention content and e-mental health tool usability; (3) conduct feasibility and pilot-testing to ensure acceptability, feasibility, efficacy, and effectiveness, along with evaluating e-mental health tool use (both frequency and duration); (4) use adequate measures and evaluate appropriate outcomes to assess intervention success; (5) ensure that end users are provided with a clear informed consent regarding intervention purpose, content, and e-mental health tool capacities, risks, and limits; (6) incorporate safety measures, including clear procedures for managing situations of need and heightened distress, such as providing crisis support services and establishing connections with reference clinicians or public health services, while also monitoring end user mental health; (7) continuously monitor intervention progress to refine effectiveness and minimize potential negative effects; and (8) ensure clinical professionals are properly guided and informed with up-to-date evidence on available e-mental health interventions, their effectiveness, suitability, and safety. Aligning with this, to ensure a consistently high-quality technical solution for end users, substantial investments in assistance and infrastructure are imperative. The insights from this study underscore the importance of prioritizing UX and technical reliability to enhance the effectiveness and adoption of preventive perinatal tools like Juno in real-world contexts. Although Juno already aligns with ethical standards 1 to 5, the results of this study indicate that the tool’s capacities, risks, and limitations need to be greatly reported (point 5). In addition, safety measures were limited to self-reported depression, anxiety, and stress levels, with no specific process for monitoring intervention progress (point 6). Therefore, future developments of Juno should incorporate comprehensive safety measures and test their feasibility and acceptability. This includes integrating technological requirements to establish a more specific procedure for monitoring intervention progress (point 7).

Conflicts of Interest

None declared.

Definitions of digital intervention and technological advancement provided to participants during the semistructured interviews and the participants’ scores.

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Abbreviations

Edited by A Mavragani; submitted 21.03.24; peer-reviewed by AR Yameogo, C-M Huang; comments to author 24.04.24; revised version received 14.05.24; accepted 17.06.24; published 14.08.24.

©Elisa Mancinelli, Simone Magnolini, Silvia Gabrielli, Silvia Salcuni. Originally published in JMIR Formative Research (https://formative.jmir.org), 14.08.2024.

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• Published: 10 August 2024

Mapping biomimicry research to sustainable development goals

• Raghu Raman 1 ,
• Aswathy Sreenivasan 2 ,
• M. Suresh 2 &
• Prema Nedungadi 3  

Scientific Reports volume  14 , Article number:  18613 ( 2024 ) Cite this article

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• Environmental sciences
• Environmental social sciences

This study systematically evaluates biomimicry research within the context of sustainable development goals (SDGs) to discern the interdisciplinary interplay between biomimicry and SDGs. The alignment of biomimicry with key SDGs showcases its interdisciplinary nature and potential to offer solutions across the health, sustainability, and energy sectors. This study identified two primary thematic clusters. The first thematic cluster focused on health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's role in healthcare innovations, sustainable collaboration, and land management. This cluster demonstrates the potential of biomimicry to contribute to medical technologies, emphasizing the need for cross-sectoral partnerships and ecosystem preservation. The second thematic cluster revolves around clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), showcasing nature-inspired solutions for sustainable development challenges, including energy generation and water purification. The prominence of SDG 7 within this cluster indicates that biomimicry significantly contributes to sustainable energy practices. The analysis of thematic clusters further revealed the broad applicability of biomimicry and its role in enhancing sustainable energy access and promoting ecosystem conservation. Emerging research topics, such as metaheuristics, nanogenerators, exosomes, and bioprinting, indicate a dynamic field poised for significant advancements. By mapping the connections between biomimicry and SDGs, this study provides a comprehensive overview of the field's trajectory, emphasizing its importance in advancing global sustainability efforts.

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Introduction.

Biomimicry, which combines 'bio' (life) and 'mimicry' (imitation), uses nature's patterns to solve human problems, aligning with the SDGs by fostering innovations 1 . This discipline studies natural processes to inspire sustainable designs and promote responsible consumption and production 2 . Biomimicry emphasizes sustainability, ideation, and education in reconnecting with nature to achieve the SDGs 3 . Collaboration among designers, technologists, and business experts is vital for translating natural mechanisms into commercial solutions 4 . Biomimetics, which aims for radical innovations by replicating living systems, strives for breakthroughs in economic growth 5 . By promoting systemic change through the emulation of nature's regenerative processes, biomimicry's alignment with the SDGs could enhance sustainability efforts. Merging biomimicry insights with SDGs could exceed sustainability benchmarks.

Integrating biomimicry with sustainable development goals (SDGs) is crucial for addressing global challenges. The SDGs offer a blueprint for global well-being and environmental stewardship by 2030 6 . They aim to protect the environment and foster social and economic development. Biomimicry provides innovative approaches to these objectives, drawing from natural strategies. While SDGs offer clear targets, biomimicry complements these by providing a unique lens for solutions 7 . The investigation of biomimicry in conjunction with the SDGs is based on the understanding that the development of biologically inspired materials, structures, and systems offers a novel and sustainable solution to design problems, particularly in the built environment 8 . By mimicking nature's answers to complicated challenges, biomimicry produces creative, clever, long-lasting, and environmentally responsible ideas.

The SDGs outline a comprehensive sustainability agenda targeting social equity, environmental conservation, and poverty alleviation 9 . The use of biomimicry in research can lead to the development of solutions that mimic natural efficiency 10 , revolutionizing industries with resource-efficient technologies and enhancing sustainability. This synergy could lead to environmentally friendly products, improved energy solutions, and effective waste management systems. Integrating biomimicry into industry and education promotes environmental stewardship and ecological appreciation 11 . Marrying biomimicry research with SDGs has accelerated progress toward sustainable development.

Biomimicry can provide insightful and useful solutions consistent with sustainability ideals by imitating the adaptability and efficiency observed in biological systems 12 . The built environment's use of biomimicry has a greater sustainable impact when circular design features are included 13 . Reusing materials, cutting waste, and designing systems that work with natural cycles are all stressed in a circular design. Combining biomimicry and circular design promotes social inclusion, environmental resilience, resourcefulness, and compassionate governance, all of which lead to peaceful coexistence with the environment. This all-encompassing strategy demonstrates a dedication to tackling the larger social and environmental concerns that the SDGs represent and design challenges 14 . Complementing these studies, Wamane 7 examined the intersection of biomimicry, the environmental, social, and governance (ESG) framework, and circular economy principles, advocating for an economic paradigm shift toward sustainability.

A key aspect of realizing the impact of biomimicry on SDGs is the successful translation and commercialization of biomimicry discoveries. This involves overcoming barriers such as skill gaps, the engineering mindset, commercial acumen, and funding. Insights from the "The State of Nature-Inspired-Innovation in the UK" report provide a comprehensive analysis of these challenges and potential strategies to address them, underscoring the importance of integrating commercial perspectives into biomimicry research.

This research employs bibliometric techniques to assess the integration and coherence within circular economy policy-making, emphasizing the potential for a synergistic relationship between environmental stewardship, economic growth, and social equity to foster a sustainable future.

In addressing the notable gap in comprehensive research concerning the contribution of biomimicry solutions to specific SDGs, this study offers significant insights into the interdisciplinary applications of biomimicry and its potential to advance global sustainability efforts. Our investigation aims to bridge this research gap through a systematic analysis, resulting in the formulation of the following research questions:

RQ1: How does an interdisciplinary analysis of biomimicry research align with and contribute to advancing specific SDGs?

RQ2: What emerging topics within biomimicry research are gaining prominence, and how do they relate to the SDGs?

RQ3 : What are the barriers to the translation and commercialization of biomimicry innovations, and how can these barriers be overcome to enhance their impact on SDGs?

RQ4: Based on the identified gaps in research and the potential for interdisciplinary collaboration, what innovative areas within biomimicry can be further explored to address underrepresented SDGs?

The remainder of this paper is arranged as follows. Section " Literature review " focuses on the literature background of biomimicry, followed by methods (section " Methods ") and results and discussion, including emerging research topics (section " Results and discussion "). Section " Conclusion " concludes with recommendations and limitations.

Literature review

The potential of biomimicry solutions for sustainability has long been recognized, yet there is a notable lack of comprehensive studies that explore how biomimicry can address specific sustainable development goals (SDGs) (Table 1 ). This research aims to fill this gap by investigating relevant themes and building upon the literature in this field.

Biomimicry, with its roots tracing back to approximately 500 BC, began with Greek philosophers who developed classical concepts of beauty and drew inspiration from natural organisms for balanced design 15 . This foundational idea of looking to nature for design principles continued through history, as exemplified by Leonardo Da Vinci's creation of a flying machine inspired by birds in 1482. This early instance of biomimicry influenced subsequent advancements, including the Wright brothers' development of the airplane in 1948 12 , 15 . The term "bionics," coined in 1958 to describe "the science of natural systems or their analogs," evolved into "biomimicry" by 1982. Janine Benyus's 1997 book, “Biomimicry: Innovation Inspired by Nature,” and the founding of the Biomimicry Institute (Biomimicry 16 ) were pivotal, positioning nature as a guide and model for sustainable design. Benyus’s work underscores the potential of biomimicry in tackling contemporary environmental challenges such as climate change and ecosystem degradation 12 , 17 .

In recent years, the call for more targeted research in biomimicry has grown, particularly in terms of architecture and energy use. Meena et al. 18 and Varshabi et al. 19 highlighted the need for biomimicry to address energy efficiency in building design, stressing the potential of nature-inspired solutions to reduce energy consumption and enhance sustainability. This perspective aligns with that of Perricone et al. 20 , who explored the differences between artificial and natural systems, noting that biomimetic designs, which mimic the principles of organism construction, can significantly improve resource utilization and ecosystem restoration. Aggarwal and Verma 21 contributed to this discourse by mapping the evolution and applications of biomimicry through scientometric analysis, revealing the growing significance of nature-inspired optimization methodologies, especially in clustering techniques. Their work suggested that these methodologies not only provide innovative solutions but also reflect a deeper integration of biomimetic principles in technological advancements. Building on this, Pinzón and Austin 22 emphasized the infancy of biomimicry in the context of renewable energy, advocating for more research to explore how nature can inspire new energy solutions. Their work connects with that of Carniel et al. 23 , who introduced a natural language processing (NLP) technique to identify research themes in biomimicry across disciplines, facilitating a holistic understanding of current trends and future directions.

To further illustrate the practical applications of biomimicry, Nasser et al. 24 presented the Harmony Search Algorithm (HSA), a nature-inspired optimization technique. Their bibliometric analysis demonstrated the algorithm's effectiveness in reducing energy and resource consumption, highlighting the practical benefits of biomimicry in technological innovation. Rusu et al. 25 expanded on these themes by documenting significant advancements in soft robotics, showing how biomimicry influences design principles and applications in this rapidly evolving field. Their findings underscore the diverse applications of biomimetic principles, from robotics to building design. Shashwat et al. 26 emphasized the role of bioinspired solutions in enhancing energy efficiency within the built environment, promoting the use of high solar reflectance surfaces that mimic natural materials. This perspective is in line with that of Pires et al. 27 , who evaluated the application of biomimicry in dental restorative materials and identified a need for more clinical studies to realize the full potential of biomimetic innovations in healthcare. Liu et al. 28 explored the application of nature-inspired design principles in software-defined networks, demonstrating how biomimetic algorithms can optimize resource and energy utilization in complex systems. This study builds on the broader narrative of biomimicry's potential to transform various sectors by offering efficient, sustainable solutions. Finally, Hinkelman et al. 29 synthesized these insights by discussing the transdisciplinary applications of ecosystem biomimicry, which supports sustainable development goals by integrating biomimetic principles across engineering and environmental disciplines. This comprehensive approach underscores the transformative potential of biomimicry, suggesting that continued interdisciplinary research and innovation are crucial for addressing global sustainability challenges effectively.

PRISMA framework

This study utilizes the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to structure its analysis, following the established five-step protocol: formulating research questions, defining a search strategy, executing a literature search, screening identified literature, and analyzing the findings (Page et al., 2021). The application of the PRISMA guidelines across various research domains, including the SDGs, is well documented 30 .

To ensure a comprehensive search, we searched the Scopus database, a widely utilized resource for bibliometric studies 31 (Donthu et al. 82 ), which led to the discovery of 46,141 publications from 2013 to 2023. This period marked significant research activity following the introduction of the SDGs at the Rio + 20 summit in 2012. Publications were identified using the following terms in the title and abstract: “ (biomimic* OR biomimetic* OR bioinspired OR bioinsp* OR bionic* OR nature-inspired OR "biologically inspired" OR bioinspiration OR biomimesis OR biognosis).”

During the screening phase, publications lacking complete author details were reviewed, narrowing the field to 46,083 publications for further analysis. The eligibility phase utilized proprietary algorithms to map publications to the 17 SDGs, informed by initiatives such as the University of Auckland (Auckland’s SDG mapping 32 ) and Elsevier's SDG Mapping Initiatives (Elsevier's SDG Mapping 33 ). The selection of the Elsevier SDG Mapping Initiative for this study was based on its seamless integration with Scopus, facilitating the use of predefined search queries for each SDG and employing a machine learning model that has been refined through expert review. This approach has been utilized in various studies to analyze research trends within emerging fields. For example, the exploration of green hydrogen was detailed by Raman et al. 34 , while investigations into Fake News and the Dark Web were conducted by Raman et al. 35 , 36 , 37 and Rama et al. 38 , respectively. These examples demonstrate the efficacy of SDG mapping in elucidating how research outputs align with and contribute to sustainable development goals in these emerging domains. This phase identified 13,287 publications as mapped to SDGs. In the inclusion phase, stringent criteria further filtered the publications to English-language journals and review articles, culminating in 13,271 publications deemed suitable for in-depth analysis. This process ensures a comprehensive and high-quality dataset for the study, reflecting the robust and systematic approach afforded by the PRISMA framework in evaluating literature relevant to SDGs.

Our keyword search strategy, while comprehensive, may capture papers that do not genuinely contribute to the field. To mitigate this, we employed manual verification. After the automated search, the authors conducted a manual review of a subset of the final set of identified papers to assess their relevance and authenticity in the context of biomimicry. The subset was based on 20 highly cited papers from each year. We believe that papers that are frequently cited within the community are more likely to be accurately classified. The authors mainly reviewed the introduction, methodology, and results sections to confirm the relevance and authenticity of the papers. However, we acknowledge that these steps may not fully eliminate the inclusion of irrelevant papers, which could skew the results of our meta-analysis.

SDG framework

The examination of sustainable development goals (SDGs) reveals their interconnected nature, where the achievement of one goal often supports progress in others. Studies by Le Blanc (2015) and Allison et al. (2016) have mapped out the complex web of relationships among the SDGs, identifying both strong and subtle linkages across different objectives. To visualize these connections, we employed a cocitation mapping approach using VOSviewer 39 , which allows us to depict the semantic relationships between SDGs through their cocitation rates in scholarly works. This approach generates a visual map where each SDG is represented as a node, with the node size reflecting the goal's research prominence and the thickness of the lines between nodes indicating the frequency of cocitations among the goals. This visual representation reveals the SDGs as an intricate but unified framework, emphasizing the collaborative nature of global sustainability initiatives.

Topic prominence percentile

The Scopus prominence percentile is a crucial metric indicating the visibility and impact of emerging research topics within the scientific community. High-ranking topics in this percentile are rapidly gaining attention, highlighting emerging trends and areas poised for significant advancements. This tool enables researchers and policymakers to identify and focus on innovative topics, ensuring that their efforts align with the forefront of scientific development 35 , 36 , 37 . Topics above the 99.9th percentile were used in this study.

Results and discussion

Rq1: sdg framework and interdisciplinary research (rq4).

This study evaluates biomimicry research through the framework of SDGs. A cocitation SDG map shows two clusters and provides insights into the interplay between biomimicry themes and SDGs, highlighting the cross-disciplinary nature of this research (Fig.  1 ). The blue box hidden behind the “3 – Good Health and Well-being” and “7 – Affordable and Clean Energy” is “11 – Sustainable cities and Communities”. The blue box hidden behind “15 – Life on Land” is “16 – Peace, Justice and Strong institutions”.

Interdisciplinary SDG network of biomimicry research.

Cluster 1 (Red): Biomimetic innovations for health, partnership, and life on land

This cluster comprises a diverse array of research articles that explore the application of biomimicry across various SDGs 3 (health), 17 (partnership), and 15 (land). The papers in this cluster delve into innovative biomimetic ideas, each contributing uniquely to the intersection of sustainable development and biological inspiration. SDG 3, emphasizing good health and well-being for all, is significantly represented, indicating a global effort to leverage biomimicry for advancements in healthcare, such as new medication delivery systems and medical technologies. Similarly, the frequent citations of SDG 17 underscore the vital role of partnerships in achieving sustainable growth, especially where bioinspired solutions require interdisciplinary collaboration to address complex challenges. Finally, the prominence of 15 SDG citations reflects a commitment to preserving terrestrial ecosystems, where biomimicry is increasingly applied in land management, demonstrating nature's adaptability and resilience as a model for sustainable practices. Table 2 lists the top 5 relevant papers from Cluster 1, further illustrating the multifaceted application of biomimicry in addressing these SDGs.

A unique binary variant of the gray wolf optimization (GWO) technique, designed especially for feature selection in classification tasks, was presented by Emary et al. 40 . GWO is a method inspired by the social hierarchy and hunting behavior of gray wolves to find the best solutions to complex problems. This bioinspired optimization technique was used to optimize SDG15, which also highlights its ecological benefits. The results of the study highlight the effectiveness of binary gray wolf optimization in identifying the feature space for ideal pairings and promoting environmental sustainability and biodiversity. Lin et al. 41 focused on SDG 3 by examining catalytically active nanomaterials as potential candidates for artificial enzymes. While acknowledging the limits of naturally occurring enzymes, this study explores how nanobiotechnology can address problems in the food, pharmaceutical, and agrochemical sectors.

The investigation of enzymatic nanomaterials aligns with health-related objectives, highlighting the potential for major improvements in human health. Parodi et al. 42 used biomimetic leukocyte membranes to functionalize synthetic nanoparticles, extending biomimicry into the biomedical domain. To meet SDG 3, this research presents "leukolike vectors," which are nanoporous silicon particles that can communicate with cells, evade the immune system, and deliver specific payloads. In line with the SDGs about health, this study emphasizes the possible uses of biomimetic structures in cancer detection and treatments. A novel strategy for biological photothermal nanodot-based anticancer therapy utilizing peptide‒porphyrin conjugate self-assembly was presented by Zou et al. 43 . For therapeutic reasons, efficient light-to-heat conversion can be achieved by imitating the structure of biological structures. By providing a unique biomimetic approach to cancer treatment and demonstrating the potential of self-assembling biomaterials in biomedical applications, this research advances SDG 3. Finally, Wang et al. 44 presented Monarch butterfly optimization (MBO), which is a bioinspired algorithm that mimics the migration patterns of monarch butterflies to solve optimization problems effectively. This method presents a novel approach to optimization, mimicking the migration of monarch butterflies, aligning with SDG 9. Comparative analyses highlight MBO's exceptional performance and demonstrate its capacity to address intricate issues about business and innovation, supporting objectives for long-term collaboration and sector expansion.

The publications in Cluster 1 show a wide range of biomimetic developments, from ecological optimization to new optimization techniques and biomedical applications. These varied contributions highlight how biomimicry can advance sustainable development in health, symbiosis, and terrestrial life.

Cluster 2 (green): Nature-inspired solutions for clean water, energy, and infrastructure

Cluster 2, which focuses on the innovative application of biomimicry in sustainable development, represents a range of research that aligns with SDGs 6 (sanitation), 7 (energy), 9 (infrastructure), and 14 (water). This cluster is characterized by studies that draw inspiration from natural processes and structures to offer creative solutions to sustainability-related challenges. The papers in this cluster, detailed in Table 3 , demonstrate how biomimicry can address key global concerns in a varied and compelling manner.

Within this cluster, the high citation counts for SDG 7 underscore the significance of accessible clean energy, a domain where biomimicry contributes innovative energy generation and storage solutions inspired by natural processes. This aligns with the growing emphasis on sustainable energy practices. The prominence of SDG 9 citations further highlights the global focus on innovation and sustainable industry, where biomimicry's role in developing nature-inspired designs is crucial for building robust systems and resilient infrastructure. Furthermore, the substantial citations for SDG 6 reflect a dedicated effort toward ensuring access to clean water and sanitation for all. In this regard, biomimicry principles are being applied in water purification technologies, illustrating how sustainable solutions modeled after natural processes can effectively meet clean water objectives.

The study by Sydney Gladman et al. (2016), which presented the idea of shape-morphing systems inspired by nastic plant motions, is one notable addition to this cluster. This discovery creates new opportunities for tissue engineering, autonomous robotics, and smart textile applications by encoding composite hydrogel designs that exhibit anisotropic swelling behavior. The emphasis of SDG 9 on promoting industry, innovation, and infrastructure aligns with this biomimetic strategy. SDGs 7 and 13 are addressed in the study of Li et al. 45 , which is about engineering heterogeneous semiconductors for solar water splitting. This work contributes to the goals of inexpensive, clean energy and climate action by investigating methods such as band structure engineering and bionic engineering to increase the efficiency of solar water splitting. Li et al. 46 conducted a thorough study highlighting the importance of catalysts for the selective photoreduction of CO2 into solar fuels. This review offers valuable insights into the use of semiconductor catalysts for selective photocatalytic CO2 reduction. Our work advances sustainable energy solutions by investigating biomimetic, metal-based, and metal-free cocatalysts and contributes to SDGs 7 and 13. Wang et al. 47 address the critical problem of water pollution. Creating materials with superlyophilic and superlyophobic qualities offers a creative method for effectively separating water and oil. This contributes to the goals of clean water, industry, innovation, and life below the water. It also correlates with SDGs 6, 9, and 14. Singh et al. 48 also explored the 'green' synthesis of metals and their oxide nanoparticles for environmental remediation, which furthers SDG 9. This review demonstrates the environmentally benign and sustainable features of green synthesis and its potential to lessen the environmental impact of conventional synthesis methods.

Cluster 2 provides nature-inspired solutions for clean water, renewable energy, and sustainable infrastructure, demonstrating the scope and importance of biomimicry. The varied applications discussed in these papers help overcome difficult problems and advance sustainable development in line with several SDGs.

RQ2: Emerging research topics

Temporal evolution of emerging topics.

Figure  2 displays the publication counts for various emerging topics from 2013 to 2022, indicating growth trends over the years. For 'Metaheuristics', there is a notable increase in publications peaking in approximately 2020, suggesting a surge in interest. 'Strain sensor' research steadily increased, reaching its highest publication frequency toward the end of the period, which is indicative of growing relevance in the field. 'Bioprinting' sharply increased over the next decade, subsequently maintaining high interest, which highlights its sustained innovation. In contrast, 'Actuators' showed fluctuating publication counts, with a recent upward trend. 'Cancer' research, while historically a major topic, displayed a spike in publications in approximately 2018, possibly reflecting a breakthrough or increased research funding. 'Myeloperoxidase' has a smaller presence in the literature, with a modest peak in 2019. The number of 'Water '-related publications remains relatively low but shows a slight increase, suggesting a gradual but increasing recognition of its importance. Research on exosomes has significantly advanced, particularly since 2018, signifying a greater area of focus. 'Mechanical' topic publications have moderate fluctuations without a clear trend, indicating steady research interest. 'Micromotors' experienced an initial publication surge, followed by a decline and then a recent resurgence, possibly due to new technological applications. 'Nanogenerators' have shown a dramatic increase in interest, particularly in recent years, while 'Hydrogel' publications have varied, with a recent decline, which may point toward a shift in research focus or maturity of the topic.

Evolution of emerging topics according to publications (y-axis denotes the number of publications; x-axis denotes the year of publication).

Figure  3 presents the distribution of various research topics based on their prominence percentile and total number of publications. Topics above the 99.9th percentile and to the right of the vertical threshold line represent the most emergent and prolific topics of study. Next, we examine the topics within each of the four quadrants, focusing on how each topic has developed over the years in relation to SDGs and the key phrases associated with each topic.

Distribution of research topics based on prominence percentile and total number of publications.

Next, we examine each research topic in four quadrants, assessing their evolution concerning SDGs. We also analyze the keyphrase cloud to identify which keyphrases are most relevant (indicated by their font size) and whether they are growing or not. In the key phrase cloud, green indicates an increasing relevance of the key phrase, grey signifies that its relevance remains constant, and blue represents a declining relevance of the key phrase.

Niche biomimetic applications

These are topics with a lower number of publications and prominence percentiles, indicating specialized or emerging areas of research that are not yet widely recognized or pursued (Quadrant 1—bottom left).

Myeloperoxidase; colorimetric; chromogenic compounds

The inclusion of myeloperoxidase indicates that inflammation and the immune system are the main research topics. The focus on chromogenic and colorimetric molecules suggests a relationship to analytical techniques for identifying biological materials. The evolution of the research is depicted in Fig.  4 a shows an evolving emphasis on various sustainable development goals (SDGs) over time. The research trajectory, initially rooted in SDG 3 (Good Health and Well-being), has progressively branched out to encompass SDG 7 (Affordable and Clean Energy) and SDG 6 (Clean Water and Sanitation), reflecting an expanding scope of inquiry within the forestry sciences. More recently, the focus has transitioned toward SDG 15 (Life on Land), indicating an increased recognition of the interconnectedness between forest ecosystems and broader environmental and sustainability goals. This trend underscores the growing complexity and multidisciplinary nature of forestry research, highlighting the need to address comprehensive ecological concerns along with human well-being and sustainable development.

Evolution of research ( a ) and key phrases ( b ).

The word cloud in Fig.  4 b highlights key phrases such as 'Biocompatible', 'Actuator', and 'Self-healing Hydrogel', reflecting a focus on advanced materials, while terms such as 'Elastic Modulus' and 'Polymeric Networks' suggest an emphasis on the structural properties essential for creating innovative diagnostic and environmental sensing tools. Such developments are pertinent to health monitoring and water purification, resonating with SDG 3 (Good Health and Well-being) and SDG 6 (Clean Water and Sanitation). The prominence of 'Self-healing' and 'Bioinspired' indicates a shift toward materials that emulate natural processes for durability and longevity, supporting sustainable industry practices aligned with SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), contributing to the overarching aim of sustainable development.

Next, we analyzed the top 3 cited publications. Catalytically active nanomaterials, or nanozymes, are exciting candidates for artificial enzymes, according to Lin et al. 41 . The authors explore the structural features and biomimetics applications of these enzymes, classifying them as metal-, carbon-, and metal oxide-based nanomaterials. This study emphasizes the benefits of enzymes over natural enzymes, including their high stability, variable catalytic activity, and controlled production. Wang et al. 49 developed biomimetic nanoflowers made from nanozymes to cause intracellular oxidative damage in hypoxic malignancies. Under both normoxic and hypoxic conditions, the nanoflowers demonstrated catalytic efficiency. By overcoming the constraints of existing systems that depend on oxygen availability or external stimuli, this novel technique represents a viable treatment option for malignant neoplasms. Gao et al. 50 investigated the use of a dual inorganic nanozyme-catalyzed cascade reaction as a biomimetic approach for nanocatalytic tumor therapy. This approach produces a high level of therapeutic efficacy by cascading catalytic events inside the tumor microenvironment. This study highlights the potential of inorganic nanozymes for achieving high therapeutic efficacy and outstanding biosafety, which adds to the growing interest in nanocatalytic tumor therapy.

Water; hydrophobicity; aerogels

With an emphasis on hydrophobicity, aerogel use, and water-related features, this topic relates to materials science and indicates interest in cutting-edge materials with unique qualities. From Fig.  5 a, we can see that, initially, the focus was directed toward SDG 6 (Clean Water and Sanitation), which is intrinsically related to the research theme, as biomimetic approaches are leveraged to develop innovative water purification and management solutions. As the research progressed, the scope expanded to intersect with SDG 14 (Life Below Water) and SDG 7 (Affordable and Clean Energy), signifying a broadened impact of biomimetic innovations in marine ecosystem conservation and energy-efficient materials. The gradual involvement with SDG 9 (industry, innovation, and infrastructure) and SDG 13 (climate action) indicates the interdisciplinary reach of this research, which aims to influence industrial practices and climate change mitigation strategies.

The word cloud in Fig.  5 b reinforces this narrative by showcasing key phrases such as 'Hydrophobic', 'Bioinspired', 'Emulsion', and 'Oil Pollution', which reflect the emphasis on developing materials and technologies that mimic natural water repellency and separation processes. 'Aerogel' and 'polydopamine', along with 'Underwater' and 'Biomimetic Cleaning', suggest a strong focus on creating lightweight, efficient materials capable of self-cleaning and oil spill remediation. These keywords encapsulate the essence of the research theme, demonstrating a clear alignment with the targeted SDGs and the overall aim of sustainable development through biomimicry.

Three highly referenced works that have made substantial contributions to the field of biomimetic materials for oil/water separation are included in the table. The development of superlyophilic and superlyophobic materials for effective oil/water separation was examined by Wang et al. 47 . This review highlights the applications of these materials in separating different oil-and-water combinations by classifying them according to their surface wettability qualities. The excellent efficiency, selectivity, and recyclability of the materials—which present a viable treatment option for industrial oily wastewater and oil spills—are highlighted in the paper. Su et al. 51 explored the evolution of super wettability systems. The studies included superhydrophobicity, superoleophobicity, and undersea counterparts, among other extreme wettabilities. The kinetics, material structures, and wetting conditions related to obtaining superwettability are covered in the article. This demonstrates the wide range of uses for these materials in chemistry and materials science, including self-cleaning fabrics and systems for separating oil and water. Zhang et al. 52 presented a bioinspired multifunctional foam with self-cleaning and oil/water separation capabilities. To construct a polyurethane foam with superhydrophobicity and superoleophobicity, this study used porous biomaterials and superhydrophobic self-cleaning lotus leaves. Foam works well for separating oil from water because of its slight weight and ability to float on water. It also shows exceptional resistance to corrosive liquids. According to the article, multifunctional foams for large-scale oil spill cleaning might be designed using a low-cost fabrication technology that could be widely adopted.

Growing interest in bioinspired healthcare

These topics have a higher prominence percentile but a lower number of publications, suggesting growing interest and importance in the field despite a smaller body of research (Quadrant 2—top left).

Exosomes; extracellular vesicles; MicroRNAs

Exosomes and extracellular vesicles are essential for intercellular communication, and reference to microRNAs implies a focus on genetic regulation. The evolution of this topic reflects an increasing alignment with specific sustainable development goals (SDGs) over the years. The initial research focused on SDG 3 (good health and well-being) has expanded to encompass SDG 9 (industry, innovation, and infrastructure) and SDG 6 (clean water and sanitation), showcasing the multifaceted impact of biomimetic research in healthcare (Fig.  6 a). The research trajectory into SDG 9 and SDG 6 suggests broader application of bioinspired technologies beyond healthcare, potentially influencing sustainable industrial processes and water treatment technologies, respectively.

The word cloud (Fig.  6 b) underscores the central role of 'Extracellular Vesicles' and 'Exosomes' as platforms for 'Targeted Drug Delivery' and 'Nanocarrier' systems, which are key innovations in medical biotechnology. The prominence of terms such as 'Bioinspired', 'Biomimetic', 'Liposome', and 'Gold Nanoparticle' illustrates the inspiration drawn from biological systems for developing advanced materials and delivery mechanisms. These key phrases indicate significant advancements in 'Controlled Drug Delivery Systems', 'Cancer Chemotherapy', and 'Molecular Imaging', which have contributed to improved diagnostics and treatment options, consistent with the objectives of SDG 3.

The work by Jang et al. 53 , which introduced bioinspired exosome-mimetic nanovesicles for improved drug delivery to tumor tissues, is one of the most cited articles. These nanovesicles, which resemble exosomes but have higher creation yields, target cells and slow the growth of tumors in a promising way. Yong et al.'s 54 work presented an effective drug carrier for targeted cancer chemotherapy, focusing on biocompatible tumor cell-exocytosed exosome-biomimetic porous silicon nanoparticles. A paper by Cheng et al. 55 discussed the difficulties in delivering proteins intracellularly. This study suggested a biomimetic nanoparticle platform that uses extracellular vesicle membranes and metal–organic frameworks. These highly cited studies highlight the importance of biomimetic techniques in improving drug delivery systems for improved therapeutic interventions.

Nanogenerators; piezoelectric; energy harvesting

This topic advises concentrating on technology for energy harvesting, especially for those that use piezoelectric materials and nanogenerators. We see a rising focus on medical applications of biomimetics, from diagnostics to energy harvesting mimicking biological systems.

The evolution of this research topic reflects a broader contribution to the SDGs by not only addressing healthcare needs but also by promoting sustainable energy practices and supporting resilient infrastructure through biomimetic innovation (Fig.  7 a). Initially, the emphasis on SDG 3 (Good Health and Well-being) suggested the early application of biomimetic principles in healthcare, particularly in medical devices and diagnostics leveraging piezoelectric effects. Over time, the transition toward SDG 7 (Affordable and Clean Energy) and SDG 9 (Industry, Innovation, and Infrastructure) indicates an expansion of bioinspired technologies into sustainable energy solutions and industrial applications. Nanogenerators and energy harvesting techniques draw inspiration from biological processes and structures, aiming to optimize energy efficiency and contribute to clean energy initiatives.

The word cloud in Fig.  7 b emphasizes key phrases such as 'Piezoelectric', 'Energy Harvesting', 'Tactile Sensor', 'Triboelectricity', and 'Nanogenerators', highlighting the core technologies that are being developed. These terms, along with 'Bioinspired', 'Wearable Electronic Devices', and 'Energy Conversion Efficiency', illustrate the convergence of natural principles with advanced material science to create innovative solutions for energy generation and sensor technology.

Yang et al.'s 56 study in Advanced Materials presented the first triboelectrification-based bionic membrane sensor. Wearable medical monitoring and biometric authentication systems will find new uses for this sensor since it allows self-powered physiological and behavioral measurements, such as noninvasive human health evaluation, anti-interference throat voice recording, and multimodal biometric authentication. A thorough analysis of the state-of-the-art in piezoelectric energy harvesting was presented by Sezer and Koç 57 . This article addresses the fundamentals, components, and uses of piezoelectric generators, highlighting their development, drawbacks, and prospects. It also predicts a time when piezoelectric technology will power many electronics. The 2021 paper by Zhao et al. 58 examines the use of cellulose-based materials in flexible electronics. This section describes the benefits of these materials and the latest developments in intelligent electronic device creation, including biomimetic electronic skins, optoelectronics, sensors, and optoelectronic devices. This review sheds light on the possible drawbacks and opportunities for wearable technology and bioelectronic systems based on cellulose.

Leading edge of biomimetic sensing and electronics

This quadrant represents topics with both a high number of publications and a prominence percentile, indicating well-established and influential research areas (Quadrant 3—top right).

Strain sensor; flexible electronics; sensor

Figure  8 a highlights the progress of research on bioinspired innovations, particularly in the development of strain sensors and flexible electronics for adaptive sensing technologies. Initially, concentrated on health applications aligned with SDG 3 (Good Health and Well-being), the focus has expanded. The integration of SDG 9 (Industry, Innovation, and Infrastructure) indicates a shift toward industrial applications, while the incorporation of SDG 7 (Affordable and Clean Energy) suggests a commitment to energy-efficient solutions. Additionally, the mention of SDG 11 (Sustainable Cities and Communities) and SDG 12 (Responsible Consumption and Production) reflects the broadening scope to include urban sustainability and eco-friendly manufacturing practices.

Figure  8 b provides insight into the key phrases associated with this research topic, highlighting terms such as 'Bioinspired', 'Self-healing', 'Wearable Electronic Devices', 'Flexible Electronics', and 'Pressure Sensor'. These key phrases speak to the innovative approaches for creating sensors and electronics that are not only inspired by biological systems but also capable of seamlessly integrating human activity and environmental needs. The mention of 'Wearable Sensors' and 'Tactile Sensor' indicates a focus on user interaction and sensitivity, which is crucial for medical applications and smart infrastructure.

The top three articles with the most citations represent the cutting edge of this topic’s study. Chortos et al. 59 investigated how skin characteristics can be replicated for medicinal and prosthetic uses. Kim et al. 60 focused on creating ultrathin silicon nanoribbon sensors for smart prosthetic skin, opening up new possibilities for bionic systems with many sensors. A bioinspired microhairy sensor for ultraconformability on nonflat surfaces was introduced in Pang et al.'s 61 article, which significantly improved signal-to-noise ratios for accurate physiological measurements.

Cancer; photoacoustics; theranostic nanomedicine

Modern technologies such as photoacoustics, theranostic nanomedicine, and cancer research suggest that novel cancer diagnosis and therapy methods are highly needed. Figure  9 a traces the research focus that has evolved across various SDGs over time, commencing with SDG 3 (Good Health and Well-being), which is indicative of the central role of health in biomimetic research. It then extends into SDG 9 (Industry, Innovation, and Infrastructure) and SDG 7 (Affordable and Clean Energy), illustrating the cross-disciplinary applications of biomimetic technologies from healthcare to the energy and industrial sectors.

Figure  9 b provides a snapshot of the prominent keywords within this research theme, featuring terms such as “photodynamic therapy”, “photothermal chemotherapy”, “nanocarrier”, and “controlled drug delivery”. These terms underscore the innovative therapeutic strategies that mimic biological mechanisms for targeted cancer treatment. 'Bioinspired' and 'Biomimetic Synthesis' reflect the approach of deriving design principles from natural systems for the development of advanced materials and medical devices. 'Theranostic nanomedicine' integrates diagnosis and therapy, demonstrating a trend toward personalized and precision medicine.

A study conducted by Yu et al. 62 presented a novel approach for synergistic chemiexcited photodynamic-starvation therapy against metastatic tumors: a biomimetic nanoreactor, or bio-NR. Bio-NRs use hollow mesoporous silica nanoparticles to catalyze the conversion of glucose to hydrogen peroxide for starvation therapy while also producing singlet oxygen for photodynamic therapy. Bio-NR is promising for treating cancer metastasis because its coating on cancer cells improves its biological qualities. Yang et al.'s 63 study focused on a biocompatible Gd-integrated CuS nanotheranostic agent created via a biomimetic approach. This drug has low systemic side effects and good photothermal conversion efficiency, making it suitable for skin cancer therapy. It also performs well in imaging. The ultrasmall copper sulfide nanoparticles generated within ferritin nanocages are described in Wang et al.’s 64 publication. This work highlights the possibility of photoacoustic imaging-guided photothermal therapy with improved therapeutic efficiency and biocompatibility. These highly referenced articles highlight the significance of biomimetic techniques in furthering nanotheranostics and cancer therapy.

Established biomimetic foundations

Here, there are topics with a greater number of publications but a lower prominence percentile, which may imply areas where there has been significant research but that may be waning in influence or undergoing a shift in focus (Quadrant 4—bottom right).

Metaheuristics; Fireflies; Chiroptera

This topic is a fascinating mix of subjects. Using Firefly and Chiroptera in metaheuristic optimization algorithms provides a bioinspired method for resolving challenging issues. The thematic progression of research papers suggests the maturation of biomimetic disciplines that resonate with several SDGs (Fig.  10 a). The shift from initially aligning with SDG 3 (Good Health and Well-being) extends to intersecting with goals such as SDG 9 (Industry, Innovation, and Infrastructure), SDG 7 (Affordable and Clean Energy), SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land). This diversification reflects the expansive utility of biomimetic approaches, from health applications to broader environmental and societal challenges.

The top keyphrases, such as 'Swarm Intelligence', 'Global Optimization', 'Cuckoo Search Algorithm', and 'Particle Swarm Optimization', are shown in Fig.  10 b highlights the utilization of nature-inspired algorithms for solving complex optimization problems. These terms, along with the 'Firefly Algorithm' and 'Bat Algorithm', underscore the transition of natural phenomena into computational algorithms that mimic the behavioral patterns of biological organisms, offering robust solutions in various fields, including resource management, logistics, and engineering design.

The three highly referenced metaheuristic publications centered around the “Moth Flame Optimization (MFO),” Salp Swarm Algorithm (SSA),” and Whale Optimization Algorithm (WOA).” The WOA, authored by Mirjalili and Lewis 65 , is a competitive solution for mathematical optimization and structural design issues because it emulates the social behavior of humpback whales. Inspired by the swarming behavior of salps, Mirjalili et al. 66 introduced the SSA and multiobjective SSA. This shows how well they function in optimizing a variety of engineering design difficulties. Finally, Mirjalili 67 suggested the MFO algorithm, which is modeled after the navigational strategy of moths and exhibits competitive performance in resolving benchmark and real-world engineering issues.

Bioprinting; three-dimensional printing; tissue engineering

The emphasis on sophisticated manufacturing methods for biological applications in this field suggests a keen interest in the nexus of biology and technology, especially in tissue engineering. As shown in Fig.  11 a, the topic's evolution encompasses Sustainable Development Goals (SDGs) that have transitioned over the years, including SDG 3 (Good Health and Well-being), which is inherently connected to the advancement of medical technologies and tissue engineering for health applications. This research also touches upon SDG 6 (Clean Water and Sanitation) and SDG 7 (Affordable and Clean Energy), suggesting applications of bioprinting technologies in the environmental sustainability and energy sectors. The progression toward SDG 9 (Industry, Innovation, and Infrastructure) and SDG 15 (Life on Land) reflects a broader impact, where biomimetic principles are applied to foster innovation in industrial processes and contribute to the preservation of terrestrial ecosystems.

Key phrases emerging from the word cloud in Fig.  11 b, such as “Hydrogel”, “Biofabrication”, “Tissue Scaffold”, and “Regenerative Medicine”, highlight the specialized methodologies and materials that are inspired by natural processes and structures. Terms such as 'Three-Dimensional Printing' and 'Bioprinting' underscore the technological advancements in creating complex biological structures, aiming to revolutionize the field of tissue engineering and regenerative medicine.

Three widely referenced papers about advances in 3D printing—particularly in bioprinting, soft matter, and the incorporation of biological tissue with functional electronics—are described next. Truby and Lewis’s 68 review of light- and ink-based 3D printing techniques is ground-breaking. This highlights the technology's capacity to create soft matter with tunable properties and its potential applications in robotics, shape-morphing systems, biologically inspired composites, and soft sensors. Ozbolat, and Hospodiuk 69 provide a thorough analysis of “extrusion-based bioprinting (EBB).” The adaptability of EBB in printing different biologics is discussed in the paper, with a focus on its uses in pharmaceutics, primary research, and clinical contexts. Future directions and challenges in EBB technology are also discussed. Using 3D printing, Mannoor et al. 70 presented a novel method for fusing organic tissue with functioning electronics. In the proof-of-concept, a hydrogel matrix seeded with cells and an interwoven conductive polymer containing silver nanoparticles are 3D printed to create a bionic ear. The improved auditory sensing capabilities of the printed ear show how this novel technology allows biological and nanoelectronic features to work together harmoniously.

RQ3: Translation and commercialization

Biomimicry offers promising solutions for sustainability in commercial industries with environmentally sustainable product innovation and energy savings with reduced resource commitment 71 . However, translating biomimicry innovations from research to commercialization presents challenges, including product validation, regulatory hurdles, and the need for strategic investment, innovative financial models, and interdisciplinary collaboration 71 , 72 , 73 , 74 . Ethical considerations highlight the need for universally applicable ethical guidelines regarding the moral debates surrounding biomimicry, such as motivations for pursuing such approaches and the valuation of nature 75 .

Addressing these barriers requires interdisciplinary collaboration, targeted education, and training programs. Strategic investment in biomimicry research and development is also crucial. Encouraging an engineering mindset that integrates biomimicry principles into conventional practices and developing commercial acumen among researchers is essential for navigating the market landscape 76 . Securing sufficient funding is essential for the development, testing, and scaling of these innovations 76 .

Successful case studies illustrate that the strategic integration of biomimicry enhances corporate sustainability and innovation (Larson & Meier 2017). In biomedical research, biomimetic approaches such as novel scaffolds and artificial skins have made significant strides (Zhang 2012). Architecture benefits through energy-efficient building facades modeled after natural cooling systems (Webb et al. 2017). The textile industry uses biomimicry to create sustainable, high-performance fabrics 77 .

RQ4: Interdisciplinary collaboration

Agricultural innovations (sdgs 1—no poverty and 2—zero hunger).

Environmental degradation, biodiversity loss, poverty, and hunger highlight the need for sustainable agricultural methods to mimic natural ecosystems. This includes computational models for ecological interactions, field experiments for biomimetic techniques, and novel materials inspired by natural soil processes. Research can develop solutions such as artificial photosynthesis for energy capture, polyculture systems mimicking ecosystem diversity, and bioinspired materials for soil regeneration and water retention 28 . These innovations can improve sustainability and energy efficiency in agriculture, addressing poverty and hunger through sustainable farming practices.

Educational models (SDG 4—Quality education)

Integrating sustainability principles and biomimicry into educational curricula at all levels presents opportunities for innovation. Collaborations between educators, environmental scientists, and designers can create immersive learning experiences that promote sustainability. This includes interdisciplinary curricula with biomimicry case studies, digital tools, and simulations for exploring biomimetic designs, and participatory learning approaches for engaging students with natural environments. Designing biomimicry-based educational tools and programs can help students engage in hands-on, project-based learning 10 , fostering a deeper understanding of sustainable living and problem-solving.

Gender-inclusive design (SDG 5—Gender inequality)

Gender biases in design and innovation call for research into biomimetic designs and technologies that facilitate gender equality. This includes participatory design processes involving women as cocreators, studying natural systems for inclusive strategies, and applying biomimetic principles to develop technologies supporting gender equality. Bioinspired technologies can address women's specific needs, enhancing access to education, healthcare, and economic opportunities. Interdisciplinary approaches involving gender studies, engineering, and environmental science can uncover new pathways for inclusive innovation.

Inclusive urban solutions (SDG 11—Sustainable cities and communities)

Rapid urbanization challenges such as housing shortages, environmental degradation, and unsustainable transportation systems require innovative solutions. Methodologies include systems thinking in urban planning, simulation tools for modeling biomimetic solutions, and pilot projects testing bioinspired urban innovations. Research on biomimetic architecture for affordable housing, green infrastructure for climate resilience, and bioinspired transportation systems can offer solutions. Collaborative efforts among architects, urban planners, ecologists, and sociologists are essential 78 .

Peace and justice (SDG 16—Peace, justice and institutions)

Social conflicts and weak institutions necessitate innovative approaches that integrate political science, sociology, and biology. Methods involve case studies, theoretical modeling, and participatory action research to develop strategies for peacebuilding and institutional development.

This research provides a comprehensive exploration of the multifaceted dimensions of biomimicry, SDG alignment, and interdisciplinary topics, demonstrating a clear trajectory of growth and relevance. Interdisciplinary collaboration has emerged as a pivotal strategy for unlocking the full potential of biomimicry in addressing underexplored SDGs.

While answering RQ1, the interdisciplinary analysis underscores the significant alignment of biomimicry research with several SDGs. This reflects the interdisciplinary nature of biomimicry and its ability to generate solutions for societal challenges. The analysis of two thematic clusters revealed the broad applicability of biomimicry across various sustainable development goals (SDGs). The first cluster includes health, partnership, and life on land (SDGs 3, 17, and 15), highlighting biomimicry's potential in medical technologies, sustainability collaborations, and land management. The second cluster encompasses clean water, energy, infrastructure, and marine life (SDGs 6, 7, 9, and 14), demonstrating innovative approaches to clean energy generation, sustainable infrastructure, and water purification.

In response to RQ2, this study highlights emerging topics within biomimicry research, such as metaheuristics and nanogenerators, which reflect a dynamic and evolving field that is swiftly gaining attention. These topics, alongside sensors, flexible electronics, and strain sensors, denote evolving research objectives and societal demands, pointing to new areas of study and innovation. This focus on interdisciplinary topics within biomimicry underscores the field’s adaptability and responsiveness to the shifting landscapes of technological and societal challenges.

In addressing RQ3, biomimicry holds potential for sustainable innovation but faces challenges in commercialization. Biomimicry inspires diverse technological and product innovations, driving sustainable advancements (Lurie-Luke 84 ). Overcoming these barriers through strategic investment, training, interdisciplinary collaboration, and ethical guidelines is essential for unlocking their full potential.

For RQ4 , the recommendations are formulated based on underexplored SDGs like 1, 4, 5, and 10 where biomimicry could play a pivotal role.

Future research could apply generative AI models to this dataset to validate the findings and explore additional insights. While our current study did not explore this topic, we see significant potential for this approach. Generative AI models can process extensive datasets and reveal patterns, potentially offering insights into biomimetic research correlations. The interpretation required for context-specific analysis remains challenging for generative AI 36 , 37

Our study provides valuable insights, but some limitations are worth considering. The chosen database might limit the comprehensiveness of the research captured, potentially excluding relevant work from other sources. Additionally, while the combination of cocitation mapping and BERTopic modeling provides a powerful analysis, both methods have inherent limitations. They may oversimplify the complexities of the field or introduce bias during theme interpretation, even with advanced techniques. Furthermore, our use of citations to thematically clustered publications as a proxy for impact inherits the limitations of citation analysis, such as biases toward established ideas and potential misinterpretations 79 , 80 . Another limitation of our study is the potential for missing accurate SDG mappings, as multiple SDG mapping initiatives are available, and our reliance on a single, Scopus-integrated method may not capture all relevant associations. Consequently, this could have resulted in the exclusion of papers that were appropriately aligned with certain SDGs but were not identified by our chosen mapping approach. Given these limitations, this study provides a valuable snapshot for understanding biomimicry research.

Data availability

All data generated or analyzed during this study are included in this published article and its supplementary information files.

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Raman, R., Sreenivasan, A., Suresh, M. et al. Mapping biomimicry research to sustainable development goals. Sci Rep 14 , 18613 (2024). https://doi.org/10.1038/s41598-024-69230-9

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Biomedical Engineering’s Hamid Charkhkar comments on a research study linking new neural interface to thigh nerve endings

People can move this bionic leg just by thinking about it

MIT Technology Review :  Hamid Charkhkar , research assistant professor in the Department of Biomedical Engineering, commented on a research study into a new neural interface that links a prosthetic limb to thigh nerve endings and enables the limb to be controlled by the brain. “It’s a very forward-thinking approach. Our limbs are not like shoes. They’re not worn over our bodies. They are integrally attached to our bodies via bones, muscles, and nerves,” said Charkhkar, who was not involved in the study.

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Laboratory Research Scientist - Tybulewicz Lab

Tybulewicz lab

Immune Cell Biology Laboratory & Down Syndrome Laboratory

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Laboratory Research Scientist - Genetics of Down Syndrome

This is a full-time, 3-year fixed term contract on Crick terms and conditions of employment.

The Tybulewicz group

Genetics of Down Syndrome Laboratory

The lab is studying the genetics of Down Syndrome (DS). Our aim is to identify genes on human chromosome 21 that are required in three copies to cause DS phenotypes and to establish how increased dosage of these genes causes different aspects of DS pathology. A major focus of the group is to understand why congenital heart defects occur in DS. With collaborators we are also working to understand the neurological aspects of DS. We have generated a series of genetically modified mouse strains with which we can map the location of causative genes, and study pathological mechanisms. The lab currently consists of around 12 researchers including PhD students, postdocs and laboratory research scientists. For more information see the lab website .

Lana-Elola, E. ... Tybulewicz, V. L. J. (2016). Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel. eLife , 5 :e11614. doi:10.7554/eLife.11614.001. PMID: 26765563 .

Watson-Scales, S. ... Tybulewicz, V. L. J. (2018). Analysis of Motor Dysfunction in Down Syndrome reveals Motor Neuron Degeneration. PLoS Genetics , 14 :e1007383. PMID: 29746474 .

Ahlfors, H., ... Tybulewicz, V. L. J. (2019). Gene Expression Dysregulation Domains are not a Specific Feature of Down Syndrome. Nat Comms , 10 :2489. doi: 10.1038/s41467-019-10129-9. PMID: 31171815 .

Lana-Elola, E, ... Tybulewicz, VLJ (2021). Comprehensive phenotypic analysis of the Dp1Tyb mouse strain reveals a broad range of Down Syndrome-related phenotypes. Dis Model Mech , 14 , dmm.049157. PMID: 34477842 .

Lana-Elola, E, Aoidi, R ... Tybulewicz, VLJ (2024). Congenital heart defects in Down syndrome are caused by increased dosage of DYRK1A. Sci Transl Med , 16 :eadd6883. PMID: 38266108 .

The role of the Laboratory Research Scientist will be to support the postdocs and PhD students working on the genetics of DS, reporting to the Group Leader, Victor Tybulewicz. The postholder will be responsible for the maintenance of multiple genetically altered mouse colonies that are being used to study the genetics of DS, and for the supply of experimental animals from these colonies to members of the group and to several collaborators outside the group. The postholder may on occasion need to organise the import and rederivation of novel genetically altered mouse strains. Furthermore, the postholder will be actively involved in studies of congenital heart defects in DS, using high resolution imaging microscopy and other cutting-edge imaging methods. The postholder may be involved in the generation of novel genetically altered mouse strains. Finally, the postholder will be responsible for general lab management, including ordering for the lab.

Key responsibilities

These include but are not limited to:

Maintenance of mouse colonies

Ordering for the lab

General Lab management

Supporting research projects of the postdocs and students working on the genetics of Down Syndrome

Analysis of congenital heart defects in mouse models of Down Syndrome

Key experience and competencies

The post holder should embody and demonstrate our core Crick values: bold, open, and collegial, in addition to the following:

BSc (or higher) degree in a relevant subject, e.g. biomedical sciences, genetics

Experience of management of genetically altered mouse strains

Knowledge of mouse genetics

Excellent organisational skills

Experience of mammalian developmental biology

Experience of image analysis

Crick lab/facility

Victor tybulewicz.

• Job title: Principal Group Leader - Assistant Research Director

The Francis Crick Institute is a unique partnership between