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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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Case Study Methods and Examples

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What is Case Study Methodology ?

Case studies in research are both unique and uniquely confusing. The term case study is confusing because the same term is used multiple ways. The term can refer to the methodology, that is, a system of frameworks used to design a study, or the methods used to conduct it. Or, case study can refer to a type of academic writing that typically delves into a problem, process, or situation.

Case study methodology can entail the study of one or more "cases," that could be described as instances, examples, or settings where the problem or phenomenon can be examined. The researcher is tasked with defining the parameters of the case, that is, what is included and excluded. This process is called bounding the case , or setting boundaries.

Case study can be combined with other methodologies, such as ethnography, grounded theory, or phenomenology. In such studies the research on the case uses another framework to further define the study and refine the approach.

Case study is also described as a method, given particular approaches used to collect and analyze data. Case study research is conducted by almost every social science discipline: business, education, sociology, psychology. Case study research, with its reliance on multiple sources, is also a natural choice for researchers interested in trans-, inter-, or cross-disciplinary studies.

The Encyclopedia of case study research provides an overview:

The purpose of case study research is twofold: (1) to provide descriptive information and (2) to suggest theoretical relevance. Rich description enables an in-depth or sharpened understanding of the case.

It is unique given one characteristic: case studies draw from more than one data source. Case studies are inherently multimodal or mixed methods because this they use either more than one form of data within a research paradigm, or more than one form of data from different paradigms.

A case study inquiry could include multiple types of data:

multiple forms of quantitative data sources, such as Big Data + a survey

multiple forms of qualitative data sources, such as interviews + observations + documents

multiple forms of quantitative and qualitative data sources, such as surveys + interviews

Case study methodology can be used to achieve different research purposes.

Robert Yin , methodologist most associated with case study research, differentiates between descriptive , exploratory and explanatory case studies:

Descriptive : A case study whose purpose is to describe a phenomenon. Explanatory : A case study whose purpose is to explain how or why some condition came to be, or why some sequence of events occurred or did not occur. Exploratory: A case study whose purpose is to identify the research questions or procedures to be used in a subsequent study.

Robert Yin’s book is a comprehensive guide for case study researchers!

You can read the preface and Chapter 1 of Yin's book here . See the open-access articles below for some published examples of qualitative, quantitative, and mixed methods case study research.

Mills, A. J., Durepos, G., & Wiebe, E. (2010).  Encyclopedia of case study research (Vols. 1-0). Thousand Oaks, CA: SAGE Publications, Inc. doi: 10.4135/9781412957397

Yin, R. K. (2018). Case study research and applications (6th ed.). Thousand Oaks: SAGE Publications.

Open-Access Articles Using Case Study Methodology

As you can see from this collection, case study methods are used in qualitative, quantitative and mixed methods research.

Ang, C.-S., Lee, K.-F., & Dipolog-Ubanan, G. F. (2019). Determinants of First-Year Student Identity and Satisfaction in Higher Education: A Quantitative Case Study. SAGE Open. https://doi.org/10.1177/2158244019846689

Abstract. First-year undergraduates’ expectations and experience of university and student engagement variables were investigated to determine how these perceptions influence their student identity and overall course satisfaction. Data collected from 554 first-year undergraduates at a large private university were analyzed. Participants were given the adapted version of the Melbourne Centre for the Study of Higher Education Survey to self-report their learning experience and engagement in the university community. The results showed that, in general, the students’ reasons of pursuing tertiary education were to open the door to career opportunities and skill development. Moreover, students’ views on their learning and university engagement were at the moderate level. In relation to student identity and overall student satisfaction, it is encouraging to state that their perceptions of studentship and course satisfaction were rather positive. After controlling for demographics, student engagement appeared to explain more variance in student identity, whereas students’ expectations and experience explained greater variance in students’ overall course satisfaction. Implications for practice, limitations, and recommendation of this study are addressed.

Baker, A. J. (2017). Algorithms to Assess Music Cities: Case Study—Melbourne as a Music Capital. SAGE Open. https://doi.org/10.1177/2158244017691801

Abstract. The global  Mastering of a Music City  report in 2015 notes that the concept of music cities has penetrated the global political vernacular because it delivers “significant economic, employment, cultural and social benefits.” This article highlights that no empirical study has combined all these values and offers a relevant and comprehensive definition of a music city. Drawing on industry research,1 the article assesses how mathematical flowcharts, such as Algorithm A (Economics), Algorithm B (Four T’s creative index), and Algorithm C (Heritage), have contributed to the definition of a music city. Taking Melbourne as a case study, it illustrates how Algorithms A and B are used as disputed evidence about whether the city is touted as Australia’s music capital. The article connects the three algorithms to an academic framework from musicology, urban studies, cultural economics, and sociology, and proposes a benchmark Algorithm D (Music Cities definition), which offers a more holistic assessment of music activity in any urban context. The article concludes by arguing that Algorithm D offers a much-needed definition of what comprises a music city because it builds on the popular political economy focus and includes the social importance of space and cultural practices.

Brown, K., & Mondon, A. (2020). Populism, the media, and the mainstreaming of the far right: The Guardian’s coverage of populism as a case study. Politics. https://doi.org/10.1177/0263395720955036

Abstract. Populism seems to define our current political age. The term is splashed across the headlines, brandished in political speeches and commentaries, and applied extensively in numerous academic publications and conferences. This pervasive usage, or populist hype, has serious implications for our understanding of the meaning of populism itself and for our interpretation of the phenomena to which it is applied. In particular, we argue that its common conflation with far-right politics, as well as its breadth of application to other phenomena, has contributed to the mainstreaming of the far right in three main ways: (1) agenda-setting power and deflection, (2) euphemisation and trivialisation, and (3) amplification. Through a mixed-methods approach to discourse analysis, this article uses  The Guardian  newspaper as a case study to explore the development of the populist hype and the detrimental effects of the logics that it has pushed in public discourse.

Droy, L. T., Goodwin, J., & O’Connor, H. (2020). Methodological Uncertainty and Multi-Strategy Analysis: Case Study of the Long-Term Effects of Government Sponsored Youth Training on Occupational Mobility. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 147–148(1–2), 200–230. https://doi.org/10.1177/0759106320939893

Abstract. Sociological practitioners often face considerable methodological uncertainty when undertaking a quantitative analysis. This methodological uncertainty encompasses both data construction (e.g. defining variables) and analysis (e.g. selecting and specifying a modelling procedure). Methodological uncertainty can lead to results that are fragile and arbitrary. Yet, many practitioners may be unaware of the potential scale of methodological uncertainty in quantitative analysis, and the recent emergence of techniques for addressing it. Recent proposals for ‘multi-strategy’ approaches seek to identify and manage methodological uncertainty in quantitative analysis. We present a case-study of a multi-strategy analysis, applied to the problem of estimating the long-term impact of 1980s UK government-sponsored youth training. We use this case study to further highlight the problem of cumulative methodological fragilities in applied quantitative sociology and to discuss and help develop multi-strategy analysis as a tool to address them.

Ebneyamini, S., & Sadeghi Moghadam, M. R. (2018). Toward Developing a Framework for Conducting Case Study Research .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406918817954

Abstract. This article reviews the use of case study research for both practical and theoretical issues especially in management field with the emphasis on management of technology and innovation. Many researchers commented on the methodological issues of the case study research from their point of view thus, presenting a comprehensive framework was missing. We try representing a general framework with methodological and analytical perspective to design, develop, and conduct case study research. To test the coverage of our framework, we have analyzed articles in three major journals related to the management of technology and innovation to approve our framework. This study represents a general structure to guide, design, and fulfill a case study research with levels and steps necessary for researchers to use in their research.

Lai, D., & Roccu, R. (2019). Case study research and critical IR: the case for the extended case methodology. International Relations , 33 (1), 67-87. https://doi.org/10.1177/0047117818818243

Abstract. Discussions on case study methodology in International Relations (IR) have historically been dominated by positivist and neopositivist approaches. However, these are problematic for critical IR research, pointing to the need for a non-positivist case study methodology. To address this issue, this article introduces and adapts the extended case methodology as a critical, reflexivist approach to case study research, whereby the case is constructed through a dynamic interaction with theory, rather than selected, and knowledge is produced through extensions rather than generalisation. Insofar as it seeks to study the world in complex and non-linear terms, take context and positionality seriously, and generate explicitly political and emancipatory knowledge, the extended case methodology is consistent with the ontological and epistemological commitments of several critical IR approaches. Its potential is illustrated in the final part of the article with reference to researching the socioeconomic dimension of transitional justice in Bosnia and Herzegovina.

Lynch, R., Young, J. C., Boakye-Achampong, S., Jowaisas, C., Sam, J., & Norlander, B. (2020). Benefits of crowdsourcing for libraries: A case study from Africa . IFLA Journal. https://doi.org/10.1177/0340035220944940

Abstract. Many libraries in the Global South do not collect comprehensive data about themselves, which creates challenges in terms of local and international visibility. Crowdsourcing is an effective tool that engages the public to collect missing data, and it has proven to be particularly valuable in countries where governments collect little public data. Whereas crowdsourcing is often used within fields that have high levels of development funding, such as health, the authors believe that this approach would have many benefits for the library field as well. They present qualitative and quantitative evidence from 23 African countries involved in a crowdsourcing project to map libraries. The authors find benefits in terms of increased connections between stakeholders, capacity-building, and increased local visibility. These findings demonstrate the potential of crowdsourced approaches for tasks such as mapping to benefit libraries and similarly positioned institutions in the Global South in multifaceted ways.

Mason, W., Morris, K., Webb, C., Daniels, B., Featherstone, B., Bywaters, P., Mirza, N., Hooper, J., Brady, G., Bunting, L., & Scourfield, J. (2020). Toward Full Integration of Quantitative and Qualitative Methods in Case Study Research: Insights From Investigating Child Welfare Inequalities. Journal of Mixed Methods Research, 14 (2), 164-183. https://doi.org/10.1177/1558689819857972

Abstract. Delineation of the full integration of quantitative and qualitative methods throughout all stages of multisite mixed methods case study projects remains a gap in the methodological literature. This article offers advances to the field of mixed methods by detailing the application and integration of mixed methods throughout all stages of one such project; a study of child welfare inequalities. By offering a critical discussion of site selection and the management of confirmatory, expansionary and discordant data, this article contributes to the limited body of mixed methods exemplars specific to this field. We propose that our mixed methods approach provided distinctive insights into a complex social problem, offering expanded understandings of the relationship between poverty, child abuse, and neglect.

Rashid, Y., Rashid, A., Warraich, M. A., Sabir, S. S., & Waseem, A. (2019). Case Study Method: A Step-by-Step Guide for Business Researchers .  International Journal of Qualitative Methods .  https://doi.org/10.1177/1609406919862424

Abstract. Qualitative case study methodology enables researchers to conduct an in-depth exploration of intricate phenomena within some specific context. By keeping in mind research students, this article presents a systematic step-by-step guide to conduct a case study in the business discipline. Research students belonging to said discipline face issues in terms of clarity, selection, and operationalization of qualitative case study while doing their final dissertation. These issues often lead to confusion, wastage of valuable time, and wrong decisions that affect the overall outcome of the research. This article presents a checklist comprised of four phases, that is, foundation phase, prefield phase, field phase, and reporting phase. The objective of this article is to provide novice researchers with practical application of this checklist by linking all its four phases with the authors’ experiences and learning from recently conducted in-depth multiple case studies in the organizations of New Zealand. Rather than discussing case study in general, a targeted step-by-step plan with real-time research examples to conduct a case study is given.

VanWynsberghe, R., & Khan, S. (2007). Redefining Case Study. International Journal of Qualitative Methods, 80–94. https://doi.org/10.1177/160940690700600208

Abstract. In this paper the authors propose a more precise and encompassing definition of case study than is usually found. They support their definition by clarifying that case study is neither a method nor a methodology nor a research design as suggested by others. They use a case study prototype of their own design to propose common properties of case study and demonstrate how these properties support their definition. Next, they present several living myths about case study and refute them in relation to their definition. Finally, they discuss the interplay between the terms case study and unit of analysis to further delineate their definition of case study. The target audiences for this paper include case study researchers, research design and methods instructors, and graduate students interested in case study research.

More Sage Research Methods Community Posts about Case Study Research

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Case study methods are used by researchers in many disciplines. Here are some open-access articles about multimodal qualitative or mixed methods designs that include both qualitative and quantitative elements.

Case study methodology is both unique, and uniquely confusing. It is unique given one characteristic: case studies draw from more than one data source.

What is case study methodology? It is unique given one characteristic: case studies draw from more than one data source. In this post find definitions and a collection of multidisciplinary examples.

Find discussion of case studies and published examples.

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

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Research bias

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

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Qualitative Research Guide : Case Studies

• Gray Literature
• Action Research
• Bibliometrics
• Case Studies

What are Case Studies?

Books about case studies, resources on case studies, case studies in the literature.

• Content Analysis
• Ethnographic Research
• Focus Groups
• Grounded Theory
• Life Histories
• Mixed Methods
• Participant Observation
• Statistics and Data
• Data Analysis and Software
• Writing About Qualitative Research
• Sharing Qualitative Data

According to the book Understanding Case Study Research , case studies are "small scale research with meaning" that generally involve the following:

• The study of a particular case, or a number of cases.
• That the case will be complex and bounded.
• That it will be studied in its context.
• That the analysis undertaken will seek to be holistic.

The following books are available as ebooks through the UCSF Library unless otherwise noted

• Case Studies A tutorial on case study research from Colorado State University.
• Case Study: A Strategic Research Methodology An article from the American Journal of Applied Sciences by Khairul Baharein Mohd Noor. This article defends case study methodology as an appropriate methodology, giving a description, the process and its strengths and weaknesses.
• The Case Study Approach This article by Crowe et al gives a nice overview of case studies and includes several examples from health science research
• Five Misunderstandings About Case-Study Research This article examines five common misunderstandings about case-study research
• How to do Case Study Research This article from Donna Zucker at the University of Massachusetts College of Nursing describes how to design and write about case study research

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• Neurol Res Pract

How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.

The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.

What is qualitative research?

Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].

Why conduct qualitative research?

Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.

While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig.  1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.

Iterative research process

While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].

Data collection

The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].

Document study

Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.

Observations

Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].

Semi-structured interviews

Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].

Focus groups

Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.

Choosing the “right” method

As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.

Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig.  2 .

Possible combination of data collection methods

Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project

The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].

Data analysis

To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig.  3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].

From data collection to data analysis

Attributions for icons: see Fig. ​ Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project

How to report qualitative research?

Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

Three common mixed methods designs

In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.

How to assess qualitative research?

A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.

Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].

Reflexivity

While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].

Sampling and saturation

The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].

This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).

Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].

Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.

Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.

Member checking

Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].

Stakeholder involvement

In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.

How not to assess qualitative research

The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.

Protocol adherence

Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.

Interrater reliability, variability and other “objectivity checks”

The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].

Not being quantitative research

Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

Acknowledgements

Abbreviations.

Authors’ contributions

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

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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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Qualitative case study data analysis: an example from practice

Affiliation.

• 1 School of Nursing and Midwifery, National University of Ireland, Galway, Republic of Ireland.
• PMID: 25976531
• DOI: 10.7748/nr.22.5.8.e1307

Aim: To illustrate an approach to data analysis in qualitative case study methodology.

Background: There is often little detail in case study research about how data were analysed. However, it is important that comprehensive analysis procedures are used because there are often large sets of data from multiple sources of evidence. Furthermore, the ability to describe in detail how the analysis was conducted ensures rigour in reporting qualitative research.

Data sources: The research example used is a multiple case study that explored the role of the clinical skills laboratory in preparing students for the real world of practice. Data analysis was conducted using a framework guided by the four stages of analysis outlined by Morse ( 1994 ): comprehending, synthesising, theorising and recontextualising. The specific strategies for analysis in these stages centred on the work of Miles and Huberman ( 1994 ), which has been successfully used in case study research. The data were managed using NVivo software.

Review methods: Literature examining qualitative data analysis was reviewed and strategies illustrated by the case study example provided. Discussion Each stage of the analysis framework is described with illustration from the research example for the purpose of highlighting the benefits of a systematic approach to handling large data sets from multiple sources.

Conclusion: By providing an example of how each stage of the analysis was conducted, it is hoped that researchers will be able to consider the benefits of such an approach to their own case study analysis.

Implications for research/practice: This paper illustrates specific strategies that can be employed when conducting data analysis in case study research and other qualitative research designs.

Keywords: Case study data analysis; case study research methodology; clinical skills research; qualitative case study methodology; qualitative data analysis; qualitative research.

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Qualitative Research: Case Studies

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What is a case study?

• Attempts to shed light on a phenomena by studying a single case example.
• Focuses on an individual person, an event, a group, or an institution.
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• Yin, R.K. (2009) Case study research: Design and methods. Los Angeles: Sage.
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Definition of case study in qualitative research.

Home » Definition of Case Study in Qualitative Research

In the realm of qualitative research, understanding the definition of a case study is crucial. Through contextual in-depth analysis, researchers can explore complex phenomena within real-life contexts. This approach enables them to gather rich, detailed data that reveals the intricacies of participants' experiences and behaviors.

Case studies stand out for their ability to provide comprehensive insights into specific instances, allowing for a nuanced exploration of subjects. By employing contextual in-depth analysis, researchers can uncover patterns and themes that inform broader theoretical or practical implications. This method not only enhances understanding but also enriches the overall qualitative research experience.

What is a Case Study? A Contextual In-Depth Analysis

A case study is a detailed examination of a particular instance or event, providing valuable insights into its context and circumstances. It serves as a powerful method of qualitative research, allowing researchers to gather in-depth perspectives that quantitative data cannot offer. Through a contextual in-depth analysis, case studies explore the nuances of specific situations, revealing underlying patterns, motivations, and outcomes. This framework encourages a thorough understanding of the complexities involved, facilitating actionable conclusions that drive future decision-making.

In qualitative research, case studies are particularly effective in various fields, including healthcare, business, and education. They often encompass an array of data sources, such as interviews, observations, and document analysis. The key elements in conducting a contextual in-depth analysis include identifying the subject focus, collecting diverse data, and interpreting findings to highlight their significance. This comprehensive approach not only enhances knowledge about the specific case but also contributes to broader theories and practices within the discipline.

Historical Background of Case Studies

The evolution of case studies in qualitative research is marked by a progression toward a more contextual in-depth analysis. Originally rooted in disciplines like sociology and psychology, these studies emerged as a way to understand complex social phenomena through detailed examination. Researchers began to appreciate the intricate dynamics at play within specific cases, revealing layers of meaning often missed by quantitative approaches.

As case studies gained prominence, their methodology evolved, incorporating diverse perspectives from various fields. This approach allowed for the exploration of human behavior, cultural contexts, and real-world implications, thereby enriching the dataset produced by traditional research. Consequently, the historical background of case studies emphasizes their role in providing profound insights into human experiences, ultimately better equipping researchers to address contemporary issues in a more nuanced manner. Understanding this historical context is essential for grasping how case studies have become indispensable tools in qualitative research.

Key Characteristics of a Qualitative Case Study

A qualitative case study is characterized by its emphasis on contextual in-depth analysis, which allows researchers to explore complex phenomena within real-life contexts. This approach involves gathering rich, detailed information through various data collection methods, such as interviews, observations, and document analysis. The goal is to gain insights into participants' experiences and perspectives, offering a multifaceted view of the subject under investigation.

Key characteristics of qualitative case studies include their focus on a specific case, the use of diverse data sources, and an iterative analysis process. Researchers often engage deeply with their subjects, fostering a relationship that grants access to nuanced insights. Additionally, qualitative case studies are inherently flexible, allowing researchers to adapt their methods as new information emerges. This adaptability is crucial for preserving the depth and complexity inherent in real-world situations, which quantitative methods may overlook.

Conducting a Case Study: Steps for a Contextual In-Depth Analysis

When conducting a case study, the steps involved ensure a contextual in-depth analysis of the subject matter. The first step is to clearly define the research objectives to guide the entire investigation. Having a solid foundation allows researchers to focus on the essential questions that will uncover rich insights. Following that, selecting suitable data collection methods is crucial for gathering relevant information. This includes interviews, observations, and document reviews.

Next, organizing and analyzing the collected data requires careful attention. Researchers should look for patterns and themes while maintaining a contextual understanding of the subject. Additionally, documenting the findings can enhance the clarity of the analysis. Lastly, drawing conclusions and implications from the case study closes the loop, allowing for relevant recommendations. By systematically following these steps, a contextual in-depth analysis can be effectively achieved and contribute valuable insights.

Selecting a Case: Factors to Consider

Selecting an appropriate case for study requires careful consideration of several key factors. First, the context of the case is crucial. Understanding the setting, background, and conditions surrounding the case allows for a contextual in-depth analysis. A rich context not only enhances the quality of the insights gleaned but also adds depth to the research findings.

Additionally, it is essential to consider the significance of the case to the field of study. Selecting a case that addresses a pertinent issue or gap in the literature will contribute meaningfully to the discipline. Furthermore, the availability of data and accessibility of participants can significantly influence the feasibility of conducting an in-depth study. Selecting a case that aligns with these practical considerations will facilitate a more thorough exploration of the research questions. Ultimately, careful selection enhances the robustness and relevance of the findings.

Data Collection Methods in Qualitative Research

In qualitative research, data collection methods play a crucial role in gathering rich, contextual insights. Researchers often rely on techniques such as interviews, focus groups, and observations. Through these methods, data can be collected in ways that reveal deeper meaning, allowing for contextual in-depth analysis of participant experiences and perspectives. Gathering qualitative data emphasizes understanding the nuances within contexts, which can unveil complex relationships or themes relevant to the research focus.

For effective data collection, researchers should consider several key methods. First, semi-structured interviews provide flexibility, allowing for probing questions that yield detailed responses. Second, focus groups foster discussion among participants, generating diverse viewpoints that enrich the data set. Lastly, observational methods capture real-world behaviors and contexts, offering insight into participants' actions. By implementing these methods thoughtfully, researchers can enhance their data collection process, ultimately contributing to a robust understanding of the case study context.

Conclusion: The Importance of Contextual In-Depth Analysis in Defining Case Studies

In qualitative research, the significance of contextual in-depth analysis cannot be overstated. This approach transforms mere data collection into rich, nuanced insights. By examining circumstances surrounding each case, researchers gain a deeper understanding of the complexities involved. Effectively contextualized case studies not only highlight unique patterns but also help avoid oversimplification, enabling more robust conclusions.

Moreover, incorporating contextual in-depth analysis fosters a more comprehensive exploration of various factors influencing outcomes. This method equips researchers to interpret the emotional, social, and environmental dynamics at play. Ultimately, the careful consideration of context leads to a more accurate and holistic definition of case studies, enriching the overall qualitative research process.

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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

School of Education

Doctor of Philosophy in Education (PhD)

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

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Curriculum and Instruction | Elementary Education

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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Explaining asylum law using qualitative comparative analysis.

1. Introduction

2. applying qca to case law, 2.1. the confluences of boolean logic for qca and legal reasoning, 2.2. constructing case populations, 2.3. calibrating data, 3. a qca analysis of appellate court asylum decisions, 3.1. constructing the case population, 3.2. family-membership as a grounds for seeking relief from persecution, 3.3. describing the case population, 3.4. explaining decisions on cases with a kinship-based protected ground, 4. discussion, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Kretsedemas, P. Explaining Asylum Law Using Qualitative Comparative Analysis. Laws 2024 , 13 , 53. https://doi.org/10.3390/laws13040053

Kretsedemas P. Explaining Asylum Law Using Qualitative Comparative Analysis. Laws . 2024; 13(4):53. https://doi.org/10.3390/laws13040053

Kretsedemas, Philip. 2024. "Explaining Asylum Law Using Qualitative Comparative Analysis" Laws 13, no. 4: 53. https://doi.org/10.3390/laws13040053

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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.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

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• Management of febrile convulsion in home settings: a qualitative study of multiple caregiver practices in the Cape Coast Metropolis in Ghana
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• http://orcid.org/0000-0002-6216-4006 Bernard Afriyie Owusu
• Department of Population and Health , University of Cape Coast , Cape Coast , Ghana
• Correspondence to Mr Bernard Afriyie Owusu; bernard.owusu{at}stu.ucc.edu.gh

Background Febrile convulsion (FC) among children is a common emergency concern received in hospitals and clinics. However, in Ghana, FC is commonly perceived as a non-hospital disease and usually managed at home. There is limited research on the home management of FC. This study, therefore, explored the home management of FC.

Methods The study design was a descriptive and interpretive phenomenology. Data sources were triangulated among 42 participants across 5 communities within 2 km distance from regional hospitals in the Cape Coast Metropolis. Participants were purposively selected and interviewed face to face in their homes and treatment centres using semistructured interview guides. Interviews were transcribed and thematically analysed with QSR NVivo V.14.

Results Three themes were identified from the inductive analysis. These themes were treatment, prevention and case referral. Subthemes on treatment were tepid sponging with lukewarm water, the use of herbal medicine and spiritual approaches. FC was referred to as ‘asram suro’. The ‘asram’ literally means the moon, and ‘suro’ connotes the skies, indicating possibly that the condition emanates from a god of the moon. Caregivers prevented FC through behavioural approaches, herbal medicine, and mystical approaches including making scarification and tying amulets and beads particularly on the child’s face and wrists respectively. FC cases were referred for clinical attention after home care resulted in undesirable treatment outcomes. A conceptual framework depicting the decision-making and practices towards FC management is presented.

Conclusion FC is commonly managed at home independent of orthodox care availability. Caregivers employed herbal and ad hoc treatment regimens, usually unwarranted, visually frightening and spiritual approaches which were not the best home management approaches. These findings call for the need to educate caregivers about the best home management of FC.

• QUALITATIVE RESEARCH
• COMPLEMENTARY MEDICINE
• Health Education
• Paediatric intensive & critical care

Data availability statement

Data are available on reasonable request. Data are available on reasonable request from the Department of Population and Health, University of Cape Coast. Email address: [email protected]

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2023-075541

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STRENGTHS AND LIMITATIONS OF THIS STUDY

The strength of this study lies in its methodology and theoretical contributions as the data sources and methods were triangulated, and quality assurance mechanisms were embedded in the planning, data collection, and analysis phases.

Concerning the study’s limitations, first, the use of a snowball approach to identify participants could lead to some selection bias.

Second, evidence was drawn from participants’ ability to recall treatment regimens over the past 24 months.

Third, the study provides insights that are bounded by geographical and socio-cultural beliefs. Thus, the results are non-generalisable to populations and sub-groups not considered in this study.

Introduction

Febrile convulsion (FC) in children below age 5 is a common health condition especially in deprived/resource-limited areas. 1 2 FC is defined as a seizure accompanied by fever (38°C by any method), without central nervous system infection, which occurs in infants and children 6–60 months of age. 3 It occurs in about 5% of all children, making it the most common convulsive event in children younger than 60 months. 3 The direct cause of FC is unknown. 4 Nonetheless, it is associated with genetic, intrauterine, and metabolic abnormalities. 5 Beyond this, FC is highly prevalent in malaria endemic regions, and therefore common in underdeveloped areas particularly in rural Africa. 5–7 FC is usually benign and self-limiting with a favourable prognosis. 6 Yet, complex FC (typically lasting over 15 minutes, focal, and recurrent) can lead to neurological, cognitive, and behavioural disorders, 5 8 9 including seizure disorders, 10 paralysis, speech, and hearing disabilities, as well as long-term adverse intellectual and behavioural outcomes if not properly managed. 6 11 12 The consequences of FC transcend children to affect the psychosocial well-being of their caregivers. 13

In Ghana, whereas FC is one of the most common emergency concerns received in hospitals and clinics, several cases are not reported. 14 This is due to several socio-cultural norms, beliefs, and practices including community and/or household decision-making processes which influences folks perception and beliefs about the causes of ill-health. 6 15 Consequently, FC is generally perceived as a non-hospital illness, and heavily managed at home by practitioners who are known to be bearers of indigenous knowledge. 6 16 Against this backdrop, existing studies on FC are largely health facility-based and clinical, 17 18 with few studies focusing on the home setting. 6 19 Perhaps, this could be due to contexts where FC is highly managed in healthcare facilities, or limited research attention to the interplay of culture, indigenous knowledge, and health. This study, also underpinned by the household decision-making and pathways of care model (HDMPCM) 15 20 sought to fill this research gap by drawing qualitative evidence from caregivers at home.

The HDMPCM is composed of four constructs which are: caregiver recognition and response; seeking advice and negotiating access; using the middle layer between home and clinic and accessing orthodox care. 15 20 Concerning caregiver recognition and response, the ability of caregivers to timely recognise and act to prevent or lessen any risks to health (in the case of a dangerous environment) is critical. Standards for home response include caregiver calmness, airway obstruction circumvention, sideways child positioning, tepid sponging and avoidance of oral fluids and substances such as putting a spoon in the child’s mouth. 21 22 As a condition generally perceived as ‘non-hospital’, caregiver use of non-hospital approaches to manage/treat FC among children needs to be studied due to its implications on childs health and well-being. 6 16 The household decision-making model, thus, provides key theoretical constructs to aid our understanding of care seeking for ill-health, especially those that are deep-rooted in beliefs, and those whose management transcends individual to social/communal control (both typical of FC).

Undoubtedly, the healthcare setting guarantees optimum care and favourable outcomes for ill health. This is because orthodox care entails clinical attention that provides a 24-hour access to trained staff with expertise in resuscitation and lumber puncture for children younger than 18 months. 23–25 Further, drugs such as diazepam 0.5 mg/kg intravenous can be safely administered, and prophylaxis may be considered for recurrent convulsion. 26 27 There is research evidence in other developing countries to suggest that children who experience FC have delayed access to orthodox care until unfavourable treatment outcomes. 28 29 Using qualitative approaches, this study sought to explore the home-managment of FC in communities which are closer to regional health faciltities in the Central region, Ghana.

Materials and methods

Study context and participants selection.

Data were drawn from a qualitative study that explored the perceived causes and treatment of FC in rural contexts in the Cape Coast Metropolis, Ghana. The study was a descriptive and interpretive phenomenology. Phenomenology investigates people’s ‘pure’ experiences (descriptive) to interpret what’s ‘hidden’ in them—interpretive. 30 Primary data were collected from 20 November 2020 to 13 December 2020 from 42 participants across 5 localities in the metropolis. The metropolis hosts the regional Cape Coast Teaching hospital and the University of Cape Coast Hospital. There are several community health planning centres, locally known as CHP zones. Data sources were triangulated across mothers, traditional health practitioners (THPs), herbalists, grandparents and faith healer’s resident in the area. They were purposively recruited using a maximum variation, and snowball sampling techniques (traditional healers who were the first point of call directed field officers to the homes of their FC clients). The field officers approached the traditional healers to inform and build a good rapport a day before the data collection. Using a screening form (see online supplemental file ), the study employed the inclusion criteria below:

Supplemental material

Participants must be a resident of the study area and either a parent or guardian of a child who has experienced FC. To reduce recall bias, FC management must have occurred within the past 24 months preceding the study.

Participants must have treated/participated in the treatment of FC among children <age 5.

THPs must be registered under the Ghana Federation of Traditional Medicine (GFTMP). This was because, according to an earlier report, traditional medicine remains in the hands of quack practitioners. 31 The aim was to recruit practitioners with a good reputation in treatment.

Data collection procedure

Two semistructured interview guides (see online supplemental file ) were developed for parents and folk healers (THPs, herbalists, faith healers) based on a thorough review of related literature and gaps in knowledge. The interview guides were pretested in a nearby locality, refined and used for the data collection. Data collection was assisted by two trained postgraduate field assistants who have in-depth experience in qualitative research. Research assistants had a one-to-one and a face-to-face interview with caregivers in their homes and treatment centres. An interview was conducted by each field assistant each day and transcribed. Interviewers had a face-to-face interaction with participants, allowing for several observations to be made. Interviews were conducted in a local dialect (Fanti or Twi) best understood and spoken by participants and were audio recorded. Each interview lasted between 45 and 120 min, and fieldnotes were taken. In all, seven participants were excluded from the study as they had not treated FC within the past 2 years. No new information related to the established objectives and criteria came forth after the 42nd interview where data saturation was judged. Voucher specimens of medicinal plants that were received from practitioners were preserved for later discussion with experts at the Herbarium Unit of UCC and with literature.

Patients and public involvement in the research

It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research. This is because the patients were children. As such, caregivers were the participants who provided in-depth information about their care-seeking behaviour during episodes of FC.

Quality assurance was based on Connelly classifications. 32 Credibility measures entailed the presentation and interpretation of results based on participants’ experiences. Participants were interviewed in their homes/treatment centres, and medicinal plants were verified from the herbarium unit of UCC. Data sources and methods were triangulated, also to ensure that the results were confirmable. Independent checking of codes and generation of themes were done, and discrepant information was presented as well. The data presented represent a significant chunk of the study results and are, therefore, consistent with the findings. Reporting followed the Consolidated criteria for Reporting Qualitative research. 33 The methods employed are reported for replication purposes.

Data analysis and presentation

The transcripts were imported into QSR NVivo V.14 for a computer-assisted qualitative data analysis. The analytical technique was thematic. It followed Colaizzi’s (1978) seven-staged thematic analysis structure including—familiarisation, coding, meaning-making, categories or theming, integrated exhaustive description and participant validation. 34 Three themes which are treatment, prevention and referral were identified from the inductive data analysis. Three themes on treatment (tepid sponging, herbal medicine and spiritual healing), prevention (behavioural, herbal and spiritual) and two themes on referral (folk referral and orthodox care) were the subthemes identified. Specific significant statements were placed within the author’s sentence for thought coherence during the presentation of the data. Where appropriate, block quotes were employed to interview excerpts over 40 words. In vivo quotes were contextualised to maintain grammatical integrity while maintaining participants meaning.

Background characteristics of participants

42 participants were interviewed in the Metropolis. They were mostly farmers, traders of farm produce and fishmongers. The communities were traditional, with residents living in deprived water, sanitation and hygiene conditions. Two of the communities had a poorly resourced community-based health planning service (CHPS) centre. In terms of sociodemographic characteristics, the parents were mostly in their middle ages (30–39 years), compared with the herbalists, THPs and faith healers who were over age 50 years, mostly with no formal education. Only 6/42 participants had attained a senior high school level of education. The THPs had undergone non-formalised training mostly from their older relatives and had stayed and practised folk medicine in the communities for over 4 decades. All parents, grandmothers and faith healers professed to be Christians (32) while herbalists and THPs were mostly traditionalists. Most of the participants were married or divorced, with three of the THPs being in polygamous marriages. The sociodemographic characteristics of the participants are presented in table 1 .

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Background characteristics of study participants

Three themes were identified from the data. These themes were treatment, prevention and case referral. These themes and subthemes are shown in figure 1 .

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Themes and subthemes on FC management practices in home settings. FC, febrile convulsion.

Among the dominant ethnic group (Akan’s), FC was locally referred to as ‘asram suro’. The ‘asram’ literally means the moon and ‘suro connotes the skies.

Treatment of FC

Tepid sponging.

A common and palliative approach participants employed to treat FC was tepid sponging. Caregivers dipped, washed and bathed children who suffered FC in a bowl of lukewarm water, sometimes mixed with herbal products. For instance, a mother aged 30–40 years narrated that ‘When it (convulsion) came like that, I placed the child in a big bowl and we [together with grandmother] washed the child with cold water from the legs towards the head. The subsequent one [convulsion], I did it myself ’. This was confirmed by a mother aged 40–50 years who shared that ‘I slowly lowered my child in a big bowl and washed him gently with cold water from the bottom up. After that I wrapped him in a big wet towel ’. In some instances, herbal medicine was added to the water. For instance, a mother aged 30–40 years shared that ‘I mixed the Ocimum spp [3me] in a half-filled bucket with water and bathed my child with it .

Use of herbal antidotes

Herbal antidotes (HA) were heavily used in the treatment of FC. All participants’ categories, particularly the older ones employed HA or a preparation from it to treat FC. In explaining the use of HAs, this was what was said:

My mother said convulsion is treated at home with herbs. She said before the hospital came into existence; our ancestors had a way of treating convulsion with herbs. Herbs are very common, and the child could die on your way to the hospital ’ (a 40-50-year-old mother).

The practice entailed forcing herbal products into the mouth, anus or nostrils of the child. For instance, ‘ my friend rushed out and came with some herbs and garlic, she slopped and dropped its content into the nostrils of my child ’ (a 50–60 year-old mother). This was confirmed by a 50–60 year-old THP who said, ‘I mix ‘kakapenpen (Rauvolfia vomitoria) ‘and ‘onyankomawa (Myrianthus arboreus)’ with local garlic to enema the children ’. Table 2 summarises the common herbal medicine and other food products used to treat FC. The herbal medicines were believed to have spiritual potency. For instance, a mother aged 30–40 years had this to say:

The herbalist gave me some herbs to bath the child with it for a full month without soap and sponge. He then asked me to throw the residue on a crossroad deep in the night and come home and worry no more!

Common herbal medicines, food items and their use for FC treatment

Beyond science/spiritual approaches

As indicated earlier, the indigenous name of FC (asram suro) connotes a disease from the skies. As such, most participants perceive that FC was caused by evil spirits, and therefore, treated it in spiritual ways. They employed supernatural approaches such as incantation and mystical products, as well as allowing older women to urinate directly on the convulsing child. Some mothers who took their children who suffered FC to a THP demonstrated how the practice was done.

I rushed the child to his [THP) compound and he took two bunch of brooms. He placed one broom on the ground, placed the child’s head on the broom and used the other broom to hit him slightly for 3 times, the twitching receded, and he crashed herbs and dropped them into the child’s nostrils.

As indicated, THPs enabled a postmenopausal woman to urinate on the convulsing child to ward off evil spirits that were believed to have possessed the child. Several in vivo quotations, also from women aged 30–40 years, support this finding. ‘An older woman who had completed menstruation urinated directly on my child whilst the child was on the floor .

Prevention of FC

Participants shared that FC can be prevented and demonstrated three ways. These were behavioural including self-medication and good childcare practices, supernatural including the making of scarification and the use of herbal medicine.

Prevention of FC: behavioural approaches

Several approaches in the form of childcare practices including nutrition, periodic hospital reviews and self-medication were employed to prevent FC Concerning childcare practices and nutrition, a mother aged 20–30 years shared that ‘I take good care of them [two of her children had FC] in terms of providing them with a well-balanced diet . Also, a THP aged 50–60 years with 37 years of work experience narrated that ‘I don’t allow the children to eat pawpaw and coconut after treatment. These foods are usually stricken by thunder and convulsion destroys its victims as a thunder does to a coconut tree ’. The practice of preventing children from eating pawpaw and coconut was only affirmed by this practitioner. Pawpaw and coconut trees were known to be stricken by thunderstorm in ways that children are ‘stricken’ by convulsion. Eating from them could mean making children vulnerable to convulsion strikes. At home, mothers gave medications to their children when they had a fever, a mother aged 40–50 years reported that ‘When the child is feverish, I give him paracetamol . Some mothers learnt to seek orthodox healthcare whenever they sense an increased child’s body temperature. For instance, a mother aged 30–40 years reported that ‘My mother told me that I should rush the child to the hospital when I sense that he has a fever, ’.

Prevention of FC: spiritual approaches

Spiritual approaches to the prevention of FC were the making of scarification, tying of beads and amulets around the child’s wrist and prayers. The most common approach was the making of scarification either on the child’s face, ears, chest, hands or a combination of several parts. A mother aged 30–40 years stated that ‘ after the incident, the THP made scarification around both of his ears, three at the back of both of his hands and three on his chest’ . Others insisted that scarification was made. In the words of a mother aged 40–50 years, ‘ I insisted that scarification’s were made on the child’s face because when my first child had convulsion, the THP did not make the scarification and the convulsion occurred again, so the second convulsion, I insisted that it was made ’. Also, several local products such as amulets and beads were tied on the child’s wrist to prevent convulsion. For instance, a faith healer reported that ‘ after treatment, I pray over a local bead fit together with a thread and put it on the child’s wrists’ . Also, a mother aged 30–40 years stated that ‘ a woman who was no more menstruating in the house took her underwear [‘3tam’ o ‘amoasin], tore a thread from it and tied it around the child’s wrist .

Prevention of FC: use of medicinal preparations

Participants applied herbal preparations to prevent FC after treatment. These were already prepared either by herbalists, grandmothers or THPs and periodically applied. For instance, a mother aged 30–40 years stated that ‘ I prepare the herb and pour it in a small cup for him to drink. Since then, the child has not experienced convulsion in his life’ . A THP aged 50–60 years stated that ‘ I boil the concoction for the parents to keep, and then serve the child on a teaspoon three times a day continuously for three months . Also, a mother aged 30–40 years had this to say, ‘ my mother has been applying local herbs to prevent subsequent convulsion .

FC case referral

Folk referral.

Referrals were commonly done at the emergency phase of the convulsion. However, this was mostly done by mothers to herbalists, THPs and faith healers nearby rather than to a colleague folk healer. Thus, referrals from one practitioner to the other were uncommon. For instance, a faith healer aged 60–70 years reported that ‘ I have never referred anyone to a different faith healer or pastor because my clients trust me’ . In most instances, practitioners admitted FC cases for days. For instance, ‘ all the rooms you see here are for sick people including FC that are brought here. Some take about 3 days, a week or even a month (a 70–80 year-old faith healer).

Referral for orthodox care

Orthodox care was sought after home care or folk care resulting in undesirable health outcomes. For instance, a THP aged 50–60 years shared that ‘ I only refer children to the hospital when they found it difficult to breathe, or when they looked pale after treatment’ . Similarly, parents referred FC cases for clinical attention when they were unable to adequately manage the convulsion at home. A woman aged 40–50 years reported that ‘ after tepid sponging, he was still feverish, so I took him to the hospital’ . This was confirmed by a father aged 40–50 years ‘ the child was still not fit, so I sent her to the hospital .

Based on the decisions and practices regarding FC caregiving at home, a conceptual framework shown in figure 2 has been developed. In conceptual terms, caregivers characteristics including age, sex, type (parent/grandparent), and FC experiences influenced their recognition and response at the FC pre-attack, attack, and during the attack phases. For instance, early/first-time mothers could only identify FC during the attack/twitching phase compared with the grandparents who could pre-empt seizure following a child’s increased body temperature, but in most instances, misconstrued it to be malaria. During the attack/seizure phase, first-time mothers were very apprehensive regarding an immediate action, leading to older relatives/neighbours playing critical roles such as making decisions on actions and/or treatment to be provided. As indicated, FC cases were commonly managed at home and later referred for orthodox care when home management resulted in unfavourable treatment outcomes including shortness of breath and anaemia. Referral among traditional caregivers was reported to be uncommon. Upon their return from orthodox healthcare facilities, parents and home caregivers employed a combination of clinical knowledge (checking body temperature and tepid sponging), and indigenous knowledge and practices including scarification, herbal medicine, and prayer to manage/prevent FC reoccurrence (management pluralism).

A conceptual framework showing the pathway of febrile convulsion management in home settings. FC, febrile convulsion; THP, traditional health practitioner.

This study explored the home management of FC in the Cape Coast metropolis in Ghana. The results show that caregivers managed FC by tepid sponging with lukewarm water, use of medicinal plants, and beyond-science/supernatural approaches including urine therapy. Similarly, they prevented FC through behavioural approaches such as good childcare practices, herbal medicine and supernatural approaches including making scarification and tying amulets and beads, particularly on the child’s face and wrists respectively. FC cases were referred for clinical attention after home care resulted in undesirable treatment outcomes.

Tepid sponging and use of herbal medicine were the common ways of managing FC at home, and this is confirmed in multiple studies. 16 20 35–37 The practice of tepid sponging entailed pouring/dipping/sprinkling lukewarm water on the convulsing child to reduce the fever and/or induce consciousness. Similarly, several medicinal plants/preparations were used to manage FC. Herbal medicine used as anticonvulsion are widely reported in other studies. 38 Plants such as A. sativum ‘local garlic’, 39 40 Capsicum (pepper) 41 and Elaeis guineensis were used in the treatment of convulsion among infants in South-western Nigeria, India and Malaysia. 42–44 In other studies, parents applied a mixture of onion and honey, a residue of meals from a cooking pot on a child’s body, and put pepper in the fire as a means to treat FC. 45

The role of supernatural beliefs in FC management is widely known. In Ghana, FC is commonly perceived as a non-hospital disease. 6 16 Among the dominant Akan ethnic group in Ghana, FC is locally referred to as ‘asram suro ’ . The ‘ asram’ literally means the moon, and ‘ suro’ connotes the skies, indicating possibly that the condition emanates from a god of the moon. To exorcise the evil spirit that was believed to have possessed the child, caregivers used urine therapy, made scarification on the child’s face and wrists, and used herbal products. Making scarification was geared towards making the child dreadful for evil attacks due to a belief system that evil spirits attack adorable children. The practice of urinating directly on a convulsion child has been confirmed in other studies in Tanzania where mothers urinated on the convulsing child. 46 In southern Nigeria, cow or human urine concoctions were used in the treatment of FC. 47–50 The use of cow urine in Nigeria and human urine in Ghana could be due to cultural variations that exist in the beliefs and practices regarding childhood fever. 51 Evidence suggests that, despite the popular use of urine therapy in deprived contexts, it can lead to several complications including hypoglycaemia, cortical blindness, and ironically, rather cause convulsion. 47 Faith healing is a common treatment practice confirmed in related studies in Nigeria as well. 47–50 Healers recited the Holy Quran as well as made incantations as ways of treating FC. 47 Accepting the Bible/Quran as the literal truth, most religious groups including Christians and Traditional worshippers believe in the idea of divine healing. Consequently, faith healers are revered to have powers to exorcise evil spirits that are believed to have attacked children. Other management practices such as tying beads, and making scarification are also consistent with related studies. 16 37 45 47

The use of herbal medicine and spiritual approaches to manage FC is widespread and consistent with related studies across Africa. One of the conundrums of people including researchers is whether herbal medicines such as those employed in treating FC work, are harmful, or useless. While acknowledging this general concern, these practices satisfied the needs of parents and practitioners alike despite limited scientific evidence, especially from clinical trials. Pessimists may argue that folk medicine is no more effective than a placebo. 52 Whereas this study did not focus on the effectiveness of folk medicine, it has revealed that folk medicine is a common practice in FC management, and delayed access to orthodox care. In most instances, children were admitted at healing/treatment centres for days and later referred for clinical attention after home treatment resulted in undesirable outcomes including shortness of breath and anaemia. Late referral as reported in this study has been confirmed in related studies. 28 53

Folk approaches have been related to adverse consequences including choking, pneumonitis, eye damage, contractures, bacterial infection, speech, walking, and hearing disabilities, and deaths. 47 48 54 55 It is therefore critical to assess the realities of care delivery in traditional settings, and consider feasible options for improving childhood healthcare. For instance, the urgency of FC caregiving in the face of medical pluralism (Figure 2) implies that adequate treatment knowledge could offer better caregiving choices. This will require the need for the community health planning services (CHPS), working together with registered traditional medicine practitioners to educate caregivers about the optimal ways of managing FC at home, and feasible/practical linkages to orthodox healthcare. Such health education could demystify FC as a non-hospital disease, as well as discourage urine therapy and supernatural approaches as they seem to proffer no scientifically proven benefits for children. Further, socio-culturally adapting the recommendations by the consensus statements on the information to deliver after a febrile seizure during health education could enhance better treatment outcomes for children. 56 The spiritual beliefs about the causes of FC could blur other possible behavioural and environmental factors, as such, non-pharmacological practices which directly or indirectly reduce the risk of seizures including breastfeeding, hygiene, and proper nutrition could be reinforced, believing that these are daily practices and would be better accepted in the community, and help with the child’s overall health.

Nonetheless, much can be learnt from the herbal preparations reported ( table 2 ) as they have been applied to manage FC across different countries. 39–43 In terms of policy, both local and global organisations including the WHO have a keen interest in documenting herbal medicine used in the treatment of human ailments. 57 58 This research, therefore, echoes the feasibility of orthodox and non-orthodox healthcare integration. Similar recommendations for FC treatment have been put forth in Korea. 44 It is essential in terms of research to scientifically evaluate the use of the medicinal plants reported in this study via pharmacological, toxicological and clinical studies for safety concerns and possible drug discovery.

FC is a common childhood illness commonly managed at home despite orthodox healthcare availability. FC caregivers at home were parents, older relatives, herbalists, traditional, and faith healers who provided first level of care, and subsequently supported in prevention modalities. They employed ad hoc treatment regimens, usually unwarranted by clinicians, visually frightening, and beyond science modalities which were not the best home management approaches. The management approaches, however, delayed orthodox care, and caregivers sought clinical attention after home management resulted in undesirable treatment outcomes including shortness of breath and anaemia. These results call for the need to educate caregivers about optimal FC management practices at home, as well as enhance appropriate and timely linkage to orthodox healthcare.

Ethics statements

Patient consent for publication.

Consent obtained from parent(s)/guardian(s).

Ethics approval

This study involves human participants and ethical clearance (Clearance ID: UCCIRB/CHLS/2020/42) was sought from the University of Cape Coast Ethical Review Board and the Department of Population and Health. Participants gave informed consent to participate in the study before taking part.

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X @b_owusuafriyie

Contributors BAO: conceptualisation, data collection, analysis, writing, figure, review, editing, submission and act as the study guarantor.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

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

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