what is case study qualitative research design

What is Qualitative Research Design? Definition, Types, Methods and Best Practices

By Nick Jain

Published on: July 7, 2023

Table of Content

What is Qualitative Research Design?

Types of qualitative research design, qualitative research design methods, qualitative research design process: 9 key steps, top 12 best practices for qualitative research design.

Qualitative research design is defined as a type of research methodology that focuses on exploring and understanding complex phenomena and the meanings attributed to them by individuals or groups. It is commonly used in social sciences, psychology, anthropology, and other fields where subjective experiences and interpretations are of interest.

Qualitative research is concerned with capturing the richness and depth of human experiences, beliefs, attitudes, and behaviors. It aims to go beyond simple statistical analysis and uncover insights that quantitative research may not be able to capture.

Qualitative research design typically involves gathering data through methods such as interviews, observations, focus groups , and analysis of documents or artifacts. These methods allow researchers to collect detailed, descriptive information about participants’ perspectives, experiences, and contexts.

Key characteristics of qualitative research design include:

• Exploratory nature: Qualitative research often begins with an open-ended approach to allow for the discovery of new insights and patterns.
• Contextual understanding: It emphasizes understanding phenomena within their social, cultural, and historical contexts, as these factors shape individuals’ experiences.
• Subjectivity and reflexivity: Qualitative researchers acknowledge the influence of their own perspectives and biases and often engage in reflexivity to critically examine their role in shaping the research process and outcomes.
• Small and purposive sampling: Rather than aiming for large representative samples, qualitative research often involves selecting participants who can provide rich and diverse information relevant to the research question.
• In-depth data collection: Researchers spend considerable time with participants, collecting detailed and nuanced data, often through open-ended interviews, observations, or analysis of texts.
• Iterative data analysis: Qualitative analysis involves coding, categorizing, and interpreting data to identify patterns, themes, and relationships. This process is often iterative, with researchers revisiting and refining their analysis as new insights emerge.

There are several types of qualitative research designs, each with its own specific characteristics and purposes. Here are some common types:

• Phenomenological Research

This design aims to understand the essence and meaning of human experiences related to a particular phenomenon. Researchers explore participants’ subjective experiences through in-depth interviews or observations to uncover the underlying structures and patterns of their lived experiences.

• Ethnographic Research

Ethnography involves studying and understanding the culture, beliefs, practices, and social interactions of a specific group or community. Researchers immerse themselves in the participants’ natural environment for an extended period, often conducting participant observation, interviews, and document analysis to gain an in-depth understanding of the culture.

• Grounded Theory

Grounded theory is an approach where researchers aim to develop theories or conceptual frameworks grounded in the data. Through constant comparison and analysis of collected data, researchers identify categories, concepts, and relationships to generate a theory that explains the phenomenon under investigation.

Case study research involves an in-depth examination of a single individual, group, organization, or specific context. Researchers collect multiple sources of data such as interviews, observations, and documents to provide a comprehensive understanding of the case and to draw insights that may have broader implications.

• Narrative Research

Narrative research focuses on understanding and analyzing the stories and personal narratives shared by individuals. Researchers examine the structure, content, and context of these narratives to gain insights into how individuals construct meaning and make sense of their experiences.

• Participatory Action Research (PAR)

PAR is a collaborative approach that involves researchers working closely with participants or communities to identify and address social issues or problems. The aim is to empower participants and generate actionable knowledge through a cyclical process of reflection, action, and change.

• Constructivist/Interpretive Research

This design emphasizes the importance of understanding multiple subjective realities and interpretations of social phenomena. Researchers explore the different meanings and perspectives attributed to a phenomenon, often using interviews, focus groups , or textual analysis to uncover the complexities of individuals’ interpretations.

Learn more: What is Qualitative Market Research?

Qualitative research design employs various methods to gather data and generate insights. Here are some common methods used in qualitative research design:

• Interviews: In-depth interviews are a primary method in qualitative research . Researchers conduct structured, semi-structured, or unstructured interviews to gather rich and detailed information from participants. Interviews can be one-on-one or conducted in a group setting (focus groups) to explore participants’ perspectives, experiences, beliefs, and attitudes.
• Observations: Observational methods such as quantitative and qualitative observation , involve systematically watching and recording participants’ behavior in natural or controlled settings. Researchers may engage in participant observation, where they actively participate in the setting being studied, or non-participant observation, where they remain as an observer. Observations can provide insights into social interactions, behaviors, and contextual factors.
• Document Analysis: Researchers analyze various documents, such as diaries, letters, official records, organizational documents, or online content, to gain insights into cultural practices, historical events, or social phenomena. Document analysis helps researchers understand the context, beliefs, and values of individuals or communities.
• Focus Groups: Focus groups involve bringing together a small group of participants to discuss a specific topic or research question. A moderator guides the discussion, and participants can share their opinions, experiences, and perceptions in a group setting. Focus groups are useful for exploring group dynamics, and collective perspectives, and generating interactive discussions.
• Case Studies: Case studies involve an in-depth investigation of a single case, such as an individual, group, organization, or community. Researchers gather multiple sources of data, including interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are particularly useful for studying complex and unique phenomena within their real-world contexts.
• Ethnography: Ethnographic methods involve immersing oneself in the natural setting of the participants to gain an in-depth understanding of their culture, practices, and social interactions. Researchers spend a significant amount of time conducting participant observation, interviews, and collecting field notes to capture the nuances of the participants’ experiences.
• Visual Methods: Visual methods, such as photography, video recordings, or drawings, can be used to complement other qualitative research methods . Visual data can provide additional insights, perspectives, and documentation of participants’ experiences and environments.
• Textual Analysis: Textual analysis involves analyzing written or verbal data, such as interviews, focus group transcripts, or written documents, to identify themes, patterns, and meanings. Researchers use coding techniques to categorize and interpret the data and derive insights from the text.

The qualitative research design process typically involves several key steps. While the specific details may vary depending on the research context and methodology, here is a general overview of the steps involved:

1. Identify the Research Question

Start by providing a concise and unambiguous statement that outlines your research question or objective. What do you want to explore or understand through your qualitative research ? Ensure that the question is specific, focused, and relevant to your field of study.

2. Determine the Research Approach

Select the most appropriate qualitative research approach or design based on your research question and objectives. Consider the different types of qualitative research designs (such as phenomenology, ethnography, and grounded theory) and choose one that aligns with your research goals.

3. Develop a Research Plan

Create a research plan that outlines the steps, procedures, and timeline for your study. Identify the target population or participants, data collection methods, and data analysis techniques you intend to use.

4. Select Participants

Determine the criteria for selecting participants who can provide valuable insights related to your research question. Consider factors such as demographics, expertise, experiences, or specific characteristics relevant to your study. Choose a sampling method (e.g., purposive sampling, snowball sampling) to recruit participants.

5. Collect Data

Conduct data collection using the chosen qualitative methods . This may involve conducting interviews, observations, focus groups , or document analysis. To maintain ethical standards, it is crucial to adhere to ethical guidelines and ensure that participants provide informed consent. Consider audio or video recording to ensure accurate data capture.

6. Analyze Data

Engage in data analysis to identify patterns, themes, and insights from the collected data. This may involve coding, categorizing, and organizing the data using qualitative analysis software or manual techniques. Use iterative and reflexive processes to refine and deepen your analysis.

7. Interpret Findings

Interpret the findings based on the analysis of your data. Explore the emerging themes, relationships, and meanings that have emerged from the data. Consider how the findings relate to your research question and existing literature in your field.

8. Draw Conclusions and Generate Insights

Summarize the key findings of your study and draw conclusions based on your interpretation of the data. Reflect on the implications and significance of your findings for theory, practice, or future research. Identify any limitations or potential biases in your study.

9. Communicate Results

Prepare a report or manuscript to communicate your research findings. Present your qualitative data, analysis, interpretations, and conclusions in a clear and organized manner. Consider sharing your findings through presentations, publications, or other appropriate dissemination channels.

Learn more: What is Quantitative Market Research?

When conducting qualitative research , it is important to follow best practices to ensure the rigor, validity, and trustworthiness of your study. Here are some top best practices for qualitative research design:

1. Clearly Define Research Questions: Begin by clearly defining your research questions or objectives. Make sure they are specific, focused, and aligned with the purpose of your study. Clearly articulating your research questions will guide your entire research design.

2. Use a Theoretical Framework: Situate your research within a relevant theoretical framework or existing body of literature. This provides a foundation for understanding the context and helps you generate insights that contribute to theory development or refinement.

3. Select an Appropriate Research Design: Choose a qualitative research design that best suits your research questions and objectives. Consider the different approaches available, such as phenomenology, ethnography, or grounded theory, and select the one that aligns with your research goals.

4. Use Rigorous Sampling Techniques: Select participants or cases using rigorous sampling techniques. Consider purposeful sampling, where participants are chosen based on specific criteria relevant to your research question. Aim for diversity and seek saturation, where data collection reaches a point of redundancy and further data collection does not yield significant new insights.

5. Establish Trustworthiness and Credibility: Enhance the trustworthiness of your research findings by employing strategies such as member checking, where participants review and validate your interpretations, or peer debriefing, where colleagues provide feedback on your analysis and interpretations. Triangulation, or the use of multiple data sources or methods, can also strengthen the credibility of your findings.

6. Maintain Reflexivity: Be aware of your own biases, assumptions, and preconceptions throughout the research process. Engage in reflexivity by regularly reflecting on how your own perspectives may influence data collection, analysis, and interpretation. Documenting and acknowledging your own role and potential impact on the research process is essential.

7. Plan and Conduct Ethical Research: Adhere to ethical guidelines and obtain informed consent from participants. Ensure participant confidentiality, anonymity, and privacy. Seek ethics approval from relevant institutional review boards or ethics committees.

8. Use Clear and Consistent Data Collection Methods: Follow established protocols and guidelines for data collection methods such as interviews, observations, or document analysis. Develop interview guides or observation protocols to ensure consistency and standardization across participants or cases.

9. Maintain Detailed Documentation: Keep comprehensive records of your research process, including field notes, transcripts, or analysis memos. Thorough documentation allows for transparency, traceability, and the potential for independent audit or replication of your study.

10. Engage in Iterative Data Analysis: Conduct data analysis iteratively throughout the research process. Use coding techniques, thematic analysis, or other appropriate qualitative research methods to identify patterns, themes, and relationships in the data. Allow for revisions, refinements, and further exploration of emerging insights.

11. Ensure Researcher Independence and Objectivity: Be mindful of your own biases and maintain researcher independence throughout the research process. Strive for objectivity by critically examining your interpretations, seeking alternative explanations, and engaging in peer debriefing or external review.

12. Communicate Findings Effectively: Clearly communicate your research findings, including the methodology, data analysis, interpretations, and limitations. Provide rich and detailed descriptions to support your arguments and conclusions. Consider presenting findings in a way that resonates with your intended audience, whether it be academic researchers, practitioners, or policymakers.

Learn more: What is Qualitative Observation?

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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 study design: Case Studies

• Qualitative study design
• Phenomenology
• Grounded theory
• Ethnography
• Narrative inquiry
• Action research

Case Studies

• Field research
• Focus groups
• Observation
• Surveys & questionnaires
• Study Designs Home

In depth description of the experience of a single person, a family, a group, a community or an organisation.

An example of a qualitative case study is a life history which is the story of one specific person.  A case study may be done to highlight a specific issue by telling a story of one person or one group. 

• Oral recording

Ability to explore and describe, in depth, an issue or event. 

Develop an understanding of health, illness and health care in context. 

Single case can be used to develop or disprove a theory. 

Can be used as a model or prototype .  

Limitations

Labour intensive and generates large diverse data sets which can be hard to manage. 

Case studies are seen by many as a weak methodology because they only look at one person or one specific group and aren’t as broad in their participant selection as other methodologies. 

Example questions

This methodology can be used to ask questions about a specific drug or treatment and its effects on an individual.

• Does thalidomide cause birth defects?
• Does exposure to a pesticide lead to cancer?

Example studies

• Choi, T. S. T., Walker, K. Z., & Palermo, C. (2018). Diabetes management in a foreign land: A case study on Chinese Australians. Health & Social Care in the Community, 26(2), e225-e232. 
• Reade, I., Rodgers, W., & Spriggs, K. (2008). New Ideas for High Performance Coaches: A Case Study of Knowledge Transfer in Sport Science.  International Journal of Sports Science & Coaching , 3(3), 335-354. 
• Wingrove, K., Barbour, L., & Palermo, C. (2017). Exploring nutrition capacity in Australia's charitable food sector.  Nutrition & Dietetics , 74(5), 495-501. 
• Green, J., & Thorogood, N. (2018). Qualitative methods for health research (4th ed.). London: SAGE. 
• University of Missouri-St. Louis. Qualitative Research Designs. Retrieved from http://www.umsl.edu/~lindquists/qualdsgn.html   
• << Previous: Action research
• Next: Field research >>
• Last Updated: Oct 12, 2023 11:29 AM
• URL: https://deakin.libguides.com/qualitative-study-designs

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Home » Case Study – Methods, Examples and Guide

Case Study – Methods, Examples and Guide

Table of Contents

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

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

Types of Case Study

Types and Methods of Case Study are as follows:

Single-Case Study

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

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

Multiple-Case Study

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

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

Exploratory Case Study

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

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

Descriptive Case Study

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

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

Instrumental Case Study

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

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

Case Study Data Collection Methods

Here are some common data collection methods for case studies:

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

Observations

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

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

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

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

How to conduct Case Study Research

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

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

Examples of Case Study

Here are some examples of case study research:

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

Application of Case Study

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

Business and Management

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

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

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

Social Sciences

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

Law and Ethics

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

Purpose of Case Study

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

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

Case studies can also serve other purposes, including:

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

Advantages of Case Study Research

There are several advantages of case study research, including:

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

Limitations of Case Study Research

There are several limitations of case study research, including:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Race, Language, and Subjectivation pp 63–103 Cite as

Research Design and Methodology

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In this chapter I discuss the research design of the study and the methodology employed. First, I describe the qualitative approach of the study. Then I present the methodology of Grounded Theory that undergirded the preparation of the study, the data collection, and the analysis.

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See Section  3.2.2 for an overview of language classes at schools in Germany.

The interviewees attended elementary school for four or six years, and then attend one of three school tracks: Gymnasium, Realschule, or Hauptschule. The Gymnasium, which ends after 12 or 13 years of schooling, is the school track in which students can acquire their Abitur which allows access to university (KMK, 2015). The Hauptschule and Realschule degrees (Hauptschulabschluss, Realschulabschluss) end after 9 or 10 years after which students usually do apprenticeships and attend vocational schools (Dumont et al., 2019).

Feraye further states that her father’s family speaks French, Fula, and Wolof but that she does not speak the languages. She only started talking to her father’s family in the last years and did not have contact with her father who passed away a few years ago. She explains that she uses online translation tools to translate texts from German to French when emailing her family members.

That I position myself as cisgender means that the gender I was assigned at birth corresponds with the gender with which I identify. While often transgender identities are named and thus marked as notable deviations, marking cis people’s gender normalizes that the gender assigned at birth constitutes a social marker that does not correspond to any truth, and does not naturally constitute a person’s gender positioning (Ewert, 2020).

“Digger” or “Digga” developed from “Dicker” is publicly and academically often positioned as “Jugendsprache” (‘Youth Language’) translating to “Dude,” “Bro,” or “Buddy,” and directly translated as “Fat guy.” “Digger” is argued to have its roots in Hamburg made relevant by hip hop artists (Nausch, 2006) and is used all over Germany today (Behringer, 2019). Rapper Megaloh (in Birr, 2017) argues that the word “Digga” played an important role in rap artists using the n-word less in Germany. According to Megaloh, the n-word was considered a “cool word” (ibid., para. 35, my translation) in 90s German hip hop, and rapper Afrob (in Leopoldseder, 2014) points out that many white hip hop artists also used the term. Megaloh (2017) argues that Hamburg hip hop in the early 2000s significantly contributed to the n-word being used less by having created the possibility of using “Digga” instead.

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Rühlmann, L. (2023). Research Design and Methodology. In: Race, Language, and Subjectivation. Pädagogische Professionalität und Migrationsdiskurse. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-43152-5_5

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• Volume 13, Issue 11
• What are effective vaccine distribution approaches for equity-deserving and high-risk populations during COVID-19? Exploring best practices and recommendations in Canada: protocol for a mixed-methods multiple case codesign study
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• http://orcid.org/0000-0001-8455-0058 Monica Aggarwal 1 ,
• http://orcid.org/0000-0001-8280-7024 Alan Katz 2 , 3 ,
• http://orcid.org/0000-0002-1277-472X Kristina Marie Kokorelias 4 , 5 ,
• http://orcid.org/0000-0002-9619-9012 Sabrina T Wong 6 ,
• Fariba Aghajafari 7 ,
• Noah M Ivers 8 , 9 ,
• http://orcid.org/0000-0003-4554-7635 Ruth Martin-Misener 10 ,
• http://orcid.org/0000-0001-8680-6838 Kris Aubrey-Bassler 11 ,
• http://orcid.org/0000-0001-5713-9618 Mylaine Breton 12 ,
• Ross E G Upshur 1 , 9 ,
• http://orcid.org/0000-0002-7820-2046 Jeffrey C Kwong 1 , 9 , 13 , 14 , 15
• 1 Dalla Lana School of Public Health , University of Toronto , Toronto , Ontario , Canada
• 2 Department of Community Health Sciences , Rady Faculty of Health Sciences University of Manitoba , Winnipeg , Manitoba , Canada
• 3 Department of Family Medicine , Rady Faculty of Health Sciences University of Manitoba , Winnipeg , Manitoba , Canada
• 4 Rehabiliation Sciences Institute , Sunnybrook Research Institute , Toronto , Ontario , Canada
• 5 Rehabiliation Sciences Institute , University of Toronto Temerty Faculty of Medicine , Toronto , Ontario , Canada
• 6 Centre for Health Services and Policy Research , University of British Columbia , Vancouver , British Columbia , Canada
• 7 Family Medicine , University of Calgary , Calgary , Alberta , Canada
• 8 Department of Family and Community Medicine , Women's College Hospital , Toronto , Ontario , Canada
• 9 Department of Family and Community Medicine , University of Toronto , Toronto , Ontario , Canada
• 10 School of Nursing , Dalhousie University , Halifax , Nova Scotia , Canada
• 11 Primary Healthcare Research Unit , Memorial University , St. John's , Newfoundland , Canada
• 12 Department of Community Health Sciences , University of Sherbrooke , Longueuil , Quebec , Canada
• 13 Institute for Clinical Evaluative Sciences (ICES) , Toronto , Ontario , Canada
• 14 Public Health Ontario , Toronto , Ontario , Canada
• 15 University Health Network , Toronto , Ontario , Canada
• Correspondence to Dr Monica Aggarwal; monica.aggarwal{at}utoronto.ca

Introduction The WHO has stated that vaccine hesitancy is a serious threat to overcoming COVID-19. Vaccine hesitancy among underserved and at-risk communities is an ongoing challenge in Canada. Public confidence in vaccine safety and effectiveness and the principles of equity need to be considered in vaccine distribution. In Canada, governments of each province or territory manage their own healthcare system, providing an opportunity to compare and contrast distribution strategies. The overarching objective of this study is to identify effective vaccine distribution approaches and advance knowledge on how to design and implement various strategies to meet the different needs of underserved communities.

Methods and analysis Multiple case studies in seven Canadian provinces will be conducted using a mixed-methods design. The study will be informed by Experience-Based CoDesign techniques and theoretically guided by the Socio-Ecological Model and the Vaccine Hesitancy Matrix frameworks. Phase 1 will involve a policy document review to systematically explore the vaccine distribution strategy over time in each jurisdiction. This will inform the second phase, which will involve (2a) semistructured, in-depth interviews with policymakers, public health officials, researchers, providers, groups representing patients, researchers and stakeholders and (2b) an analysis of population-based administrative health data of vaccine administration. Integration of qualitative and quantitative data will inform the identification of effective vaccine distribution approaches for various populations. Informed by this evidence, phase 3 of the study will involve conducting focus groups with multiple stakeholders to codesign recommendations for the design and implementation of effective vaccine delivery strategies for equity-deserving and at-risk populations.

Ethics and dissemination This study is approved by the University of Toronto’s Health Sciences Research Ethics Board (#42643), University of British Columbia Behavioural Research Ethics Board (#H22-01750-A002), Research Ethics Board of the Nova Scotia Health Authority (#48272), Newfoundland and Labrador Health Research Ethics Board (#2022.126), Conjoint Health Research Ethics Board, University of Calgary (REB22-0207), and University of Manitoba Health Research Board (H2022-239). The outcome of this study will be to produce a series of recommendations for implementing future vaccine distribution approaches from the perspective of various stakeholders, including equity-deserving and at-risk populations.

• PUBLIC HEALTH
• Health policy

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/ .

http://dx.doi.org/10.1136/bmjopen-2023-072238

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Strengths and limitations of this study

The mixed-methods design of this study will provide knowledge about the vaccine distribution strategies and outcomes in seven jurisdictions across Canada.

The potential of our research to make an impact on policy and practice is strengthened by an integrated knowledge translation approach and codesign strategies involving lived experiences of diverse Canadians.

Codesigning with high-risk and equity-deserving populations, including those with no-to-low English/French fluency, has the potential for national generalisability and transferability to international contexts.

The analysis of administrative data from each province will depend on the availability and timeliness of data access.

This study does not focus on Indigenous communities due to the short time between the launch of the request for proposals and the application deadline, and the lack of established relationships.

Introduction

The WHO has stated that vaccine hesitancy is one of the worst threats to overcoming COVID-19. 1 2 Vaccine hesitancy, defined as a ‘delay in acceptance or refusal of vaccines despite availability of vaccination services’ 3 among underserved, at-risk communities, is an ongoing challenge in Canada. 1

In Canada, provincial and territorial governments are responsible for their regional health systems, including allocating, distributing, administering, monitoring, and reporting the uptake of vaccines. This results in differing vaccine distribution approaches across jurisdictions.

During the rollout of COVID-19 vaccines, all jurisdictions prioritised specific populations: those at high risk of severe illness and death; those most likely to transmit COVID-19; those contributing to essential services and Indigenous communities. 4 As of December 2022, 84% of Canadians aged 5+ were vaccinated with two or more doses, ranging from 95% of individuals who have received two doses of the vaccine in Newfoundland and Labrador to a low of 80% in Alberta. 5 Only 3.5% and 41% of Canadians aged 6 months to 4 years and 5–11 years have received the primary series, respectively. Vaccination rates for the booster dose were lower: 53% of Canadians aged 5+ had received one booster, and only 23% received two booster doses. 5 One reason is that individuals are uncertain if the booster can protect against new variants. 6

Multiple factors influence vaccine hesitancy and, consequently, COVID-19 vaccination uptake. A scoping review found individual (sociodemographic (eg, age and sex)), social networks (eg, religious affiliations), 7 and organisational (eg, the role of institutions, healthcare providers, and employers) factors all play a key role. 8 Informational factors (eg, social media) and characteristics of COVID-19 vaccines (eg, efficacy, safety, and side effects) influence public attitudes towards the uptake of COVID-19 vaccines. 8 9 Vaccine policies (eg, programmes and communication) and the advice of healthcare professionals also influence vaccine uptake. 7 8 10 11 However, there is a paucity of evidence on how distribution approaches affect the uptake and acceptance of COVID-19 vaccines across Canada. In a previous study, we found that most articles on vaccine distribution strategies are commentary or editorial documents. 12 Thus, the literature on equitable vaccine distribution approaches is limited, and the factors influencing these approaches are even more scarce.

In Canada, vaccine channels used to distribute COVID-19 include mass clinics, vaccine delivery in hospitals, pharmacies, public health units, primary care clinics, mobile clinics, schools, and long-term care facilities. It has been suggested that strategies that engaged primary care providers, 13 including pharmacists, 14 from the start of vaccine rollout strategies, may have helped to overcome vaccine hesitancy through the pre-existence of trusting provider–patient relationships 13 and that distribution channels through local communities may have helped overcome vaccine hesitancy for equity-deserving groups. 15 These findings indicate that some approaches may have a greater impact on alleviating vaccine hesitancy among individuals than others.

Canadian context for COVID-19 vaccine distribution

In Canada, vaccine distribution typically began with a mass vaccine clinic ‘supersite’ approach due to concerns about the viability of the vaccine when transported. 16 17 This strategy was sometimes coupled with low-cost transportation for individuals unable to access vaccination appointments 18 and drive-through vaccine clinics. 19 Ontario and Quebec offered several employer-led workplace vaccination clinics. 19 20 Other distribution strategies included peer navigators, religious institutions, music bands for teenagers, schools, and family practices. 21 Some jurisdictions tailored communications and educational material for culturally and linguistically diverse groups and at-risk populations and videos for the general public to learn how to register for vaccination through the online portal. 19 However, jurisdictions have encountered various barriers to vaccine distribution, including the crashing of booking systems, poor vaccine supply, and inadequate processes to verify the eligibility of individuals for vaccination. 22 On the other hand, Newfoundland has been praised as having one of the most vaccinated jurisdictions in North America. 23 Quebec, Alberta, and Manitoba are perceived to have been ‘rolling out vaccines efficiently’, attributed to clear, transparent communication to the public. 22

There are no best-practice guidelines on effective vaccine distribution approaches for diverse groups of equity-deserving individuals and at-risk populations. 24 Thus, there is a need to shape and inform present and future implementation strategies as vaccine rollout initiatives continue across Canada.

Goals and objectives

The overarching goal of this study is to identify effective vaccine distribution approaches and advance knowledge on how to codesign and implement strategies to meet the needs of diverse communities.

Specific objectives are to:

Identify existing COVID-19 vaccine distribution approaches across Canada over time and among equity-deserving and at-risk populations

Examine the factors that may influence different vaccine distribution approaches

Compare vaccination rates for various populations associated with different vaccine delivery channels

Provide recommendations for future vaccine distribution approaches aimed at vaccine-hesitant groups for successful implementation from the perspective of various stakeholders

Theoretical framework

Our study will use Socio-Ecological Model (SEM) 25 and the Vaccine Hesitancy Matrix (VHM) 26 to identify factors that may influence different vaccine distribution approaches and their impact on vaccine uptake. SEM is widely accepted and used in the literature to understand vaccine intention, 27 vaccine uptake, 28 and vaccine hesitancy; 8 however, no study has employed SEM to understand the factors influencing different vaccine distribution approaches. The SEM is best suited to understand barriers and facilitators of various vaccine distribution approaches because it describes factors at multiple levels, including intrapersonal (individual), interpersonal, organisational, community, and policy. We also adopted the VHM since it has been used to understand drivers of COVID-19 vaccine acceptance from the perspective of contextual influences, individual and group influences, and vaccine/vaccination-specific issues. As such we have adopted the VHM conceptualisation of contextual factors, which includes historical, sociocultural, environmental, health system/institutional, and economic as well as policy factors. See figure 1 .

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Socio-Ecological Model and Vaccine Hesitancy Matrix as a framework to understand factors influencing vaccine distribution approaches.

Intrapersonal-level factors may influence the success of vaccine distribution approaches. These include individuals’ attitudes towards different vaccine delivery channels, perceived effectiveness of vaccine delivery approaches, and individual preference for a specific vaccine delivery channel. The individual’s preference for a specific vaccine distribution approach can be shaped by an individual’s personal characteristics, including age, gender, academic qualification, professional experience, technological access, technological literacy, language barriers, and other factors (eg, perception about vaccine characteristics). 8 25 27

The interpersonal-level factors explain the role of social networks, including family, peers, neighbours, and friends, in influencing the uptake of vaccine distribution approaches. Interpersonal factors that may influence the success of various vaccine delivery channels include the attitudes of significant others towards different vaccine distribution approaches, perceived effectiveness of vaccine distribution approaches among social networks, and preference for a specific vaccine delivery channel among friends, neighbours, and family members. 8 25 27

Organisational-level factors describe the role of institutions, healthcare providers, and employers in shaping the individual’s attitudes towards various vaccine distribution approaches. These include institutional factors related to vaccine availability, accessibility, administration, information on different vaccine distribution approaches, availability of different vaccine delivery channels, availability of human resources, technology, 29 and the role of healthcare providers in shaping individual decisions. 8 25 27

Community-level factors explain the role of settings, such as schools, workplaces, and neighbourhoods, in influencing individuals’ intentions towards various vaccine delivery channels. Community-level factors that may influence the success of different vaccine distribution approaches include the perceived risk of COVID-19 in the community, the perceived effectiveness of various vaccine distribution approaches, and community preference for the specific delivery channel. 8 25 27

Contextual-level factors are drawn from VHM, 30 which looks at the broad societal-level factors influencing the individual’s attitudes and intentions towards different vaccine delivery channels. These factors include: communication and media environment, 31 32 the role of influential and religious leaders, the influence of vaccine programme gatekeepers and antivaccination and provaccination lobbies such as the pharmaceutical industry, historical influences, sociocultural and economic influences, geographic circumstances, and the country’s culture, and solidarity. 8 25 27

Policy-level factors are part of the contextual factors in the VHM 30 and explain the role of policies and laws that are instigated at the local, national, and global levels to influence individuals’ attitudes and intentions towards vaccine distribution approaches. These include politics of remuneration between providers, policies and regulations related to vaccine production, distribution, and cost, and health system preparedness for the uptake of various vaccine distribution approaches. 8 25 27

Our study will apply the SEM and VHM frameworks to explore the intrapersonal, interpersonal, organisational, community, policy, and contextual factors that influenced the success or failure of various vaccine distribution approaches across the seven jurisdictions. The SEM and VHM frameworks will explore the experiences of policymakers, public health officials, stakeholders, researchers, patient groups, equity-deserving populations, and clinicians with a vaccine distribution approach.

Methods and analysis

Design and setting.

A multiple case study design informed by Experience-Based CoDesign techniques (EBCD) to collaborate with key stakeholders 33–38 and an equity lens is proposed for a cross-case analysis of seven provinces in Canada. We employ two phases (objectives 1–3) to inform knowledge translation codesign sessions (objective 4 in phase 3). 33 Each province is considered a case consisting of a mixed-methods design (illustrated in figure 2 ). We will investigate objective 1 and objective 2 using the policy document review and qualitative methods; qualitative data for these objectives will consist of semistructured, in-depth interviews to understand the experiences of policymakers, public health officials, organisations representing patients, researchers, providers, stakeholders, and researchers with existing vaccine distribution approaches in British Columbia, Alberta, Manitoba, Ontario, Quebec, Newfoundland, and Labrador and Nova Scotia. 39 We will collect information on approaches (target audience, processes, and vaccination rates), facilitators and barriers (provincial/federal, community, and structural) to implementation, and areas of improvement. We will also identify the vaccine distribution approaches for equity-deserving and at-risk populations. ‘Effective’ will be defined as approaches that have resulted in high vaccination rates (ie, over 75% of vaccination coverage) 34 for equity-deserving (seeking) and at-risk populations. We will adopt the City of Toronto definition for equity-deserving groups (eg, black, racialised, LGBTQ2S+, and low-income communities, immigrants, persons experiencing housing precarity, and persons with low English/French fluency). 35 Populations at risk of contracting COVID-19 include children under 12, older adults over the age of 80, and persons with comorbidities. 40 We will investigate objective 3 using quantitative methods; data consist of linked administrative health data to compare vaccination rates and the characteristics of the populations served by effective distribution approaches and programmes in each jurisdiction. In phase 3, we will execute codesign focus groups with individuals with lived experience, family caregivers, healthcare providers, public health experts, and policymakers. We will integrate the results and inferences from objectives 1, 2, and 3 with objective 4 41 to identify highly effective distribution approaches. This study will occur from March 2022 to February 2024.

Flowchart of the multiple case study approach. SEM, Socio-Ecological Model; VHM, Vaccine Hesitancy Matrix.

Our study design treats qualitative and quantitative methods and all seven case studies with equal status. Thus, data sources will play a supportive role in conceptualising our codesign sessions. However, we will be open to considering new approaches to inform phase 3. We will consider combining data from our document review, qualitative interviews, and the codesign session to meet objectives 1 and 2. Previous health service research studies have combined interviews and codesign sessions 42 43 to understand experiences and determine improvement recommendations (objective 4).

Phase 1: policy document analysis using read approach

In phase 1, we will conduct a policy document analysis using the READ (Ready materials, Extract data, Analyse data, Distill) approach 44 for collecting policy documents to obtain information on the vaccine distribution approaches implemented over time (general population, equity-deserving and at-risk populations) and barriers and facilitators for each of the seven jurisdictions. We will gather evidence by: reading materials, extracting data,analysing data, and distilling findings. First, we will identify formal documents (official policies and strategies) and ‘grey literature’ (reports, websites) through a review of documents in the COVID-19 Intervention Scan by the Canadian Institute for Health Information (CIHI) 45 and online searches using Google. The search will be done from December 2020 to August 2022. Next, data will be extracted for each research question using an excel spreadsheet. An analytic summary will be created for each province. Data will be analysed using thematic analysis to identify similarities and differences in vaccine distribution channels over time for different groups across the seven jurisdictions. Finally, the results will be depicted in a graphic for the seven jurisdictions. In addition, interviews will be conducted with knowledge users (phase 2 of the study) to validate the findings of policy document analysis.

Phase 2: qualitative and quantitative data collection and analysis for each case

(2 a) We will explore stakeholders’ (ie, policy leaders, public health experts, stakeholders, etc.) experiences with existing vaccine strategies. We will use a qualitative descriptive approach 46 and a quantitative approach. Qualitative description entails a concise and descriptively rich analysis that produces a report of experiences with phenomena (ie, vaccination strategies) within each case (ie, each of the seven provinces) (objectives 1 and 2). 46 (2b) This phase will also quantitatively compare vaccination rates and the characteristics of the populations served by distribution approaches and programmes across the seven cases by analysing available administrative data (objective 3). We will analyse data currently held at the provincial data centres in the participating provinces. 47

Qualitative study

Prior to commencing the qualitative study, the investigative team will engage in a series of reflexive practices, including reflexive journaling and team discussions, to make explicit their own standpoints and positionality that they bring to the study design. 48

Sample size

Past qualitative studies have reached data saturation 49 with 10–20 interviews per case. For the proposed project, we anticipate reaching saturation of ideas after 10 interviews with policy leaders, public health officials, stakeholders, researchers, providers, and patient groups from each of the seven provinces (total n=70). If further data are needed for data saturation, 50 we will conduct additional interviews to round out key ideas. We acknowledge that human and financial resources will constrain the number of rich interviews we can conduct.

Participants and recruitment

We will recruit participants from each jurisdiction via email from local senior researchers (co-PIs). We will also ask participants to identify other individuals for the study. To increase the response rate, two reminder emails will be sent out at 2 week intervals.

Data collection

We will conduct one-on-one telephone and online interviews with participants using a semistructured interview guide. Interview guides will explore vaccine distribution approaches for addressing the needs of equity-seeking individuals and at-risk populations, the strengths and limitations of various approaches, barriers and facilitators, areas for improvement, and factors that influenced their adoption to support at-risk populations (including children under 12). We will also request any data collected on vaccination rates and the current risk of COVID-19 hospitalisations for various populations. We will collect demographic data from all participants.

Qualitative data analysis

Data analysis and collection will occur simultaneously so that emerging data can inform probing during subsequent interviews. Interviews will be transcribed verbatim. We will follow Braun and Clarke’s six phases of thematic analysis. 51–53 Our analysis aims to ‘identify repeated patterns of meaning’. 53 First, transcripts will be read and reread for data familiarisation by three research assistants (RAs) and the principal investigator (PI). Next, codebook thematic analysis will be conducted such that data collection will begin deductively and become increasingly inductive with deeper engagement with the data. 53–56 In the first coding phase, we will code and analyse data from each province using a deductive coding framework informed by the SEM and VHM models. The SEM and VHM will allow us to explore how an individual’s behaviour is integrated with a dynamic network of intrapersonal characteristics, interpersonal processes, institutional factors, community features, and public policies and the relationships between these factors. 57 Initially, three RAs and the PI will open-code five transcripts to identify initial codes. 58 This coding stage will allow the research team to remain open to ideas emerging in the data that were not considered in these frameworks. The RAs will meet with the rest of the research team to refine and finalise the codebook to describe the coding schema (a mix of new and existing codes). The coding framework will then be tested on two transcripts by RAs to develop a final codebook. This coding framework will be used to code the rest of the data, including reanalysing the first five transcripts. The codebook will be iteratively amended to incorporate emerging codes. NVivo V.12 software will help to organise the qualitative analysis process. 59 The coded data will be shared with research team members, who will discuss common themes relating to research questions. The RAs will then review the data and develop summaries for each theme and subtheme. 60 The summaries will be generated by identifying patterns in transcripts in each and across jurisdictions on factors that influenced vaccine distribution. Once preliminary themes within each case are determined, the research team will conduct a comparative analysis to compare differences and similarities in themes across the cases and determine if there are any overlapping themes. This will enable continuous refinement of themes. The similarities and differences across stakeholder groups and vaccination places (eg, different provinces and vaccine distribution channel sites) will be highlighted. We will also explore divergence within the data. The findings will be presented to members of the national research team who were not involved in the analysis process for this paper to contribute to the credibility of the data interpretation. 61

Demographic questionnaire data will be analysed using descriptive statistics. 62

Quantitative study

Administrative data that are available at the time of this study will be accessed.

Participants

Individuals who reside in the jurisdiction during the pandemic will be eligible for inclusion.

Data analysis

Simultaneously, quantitative data from April 2020 to March 2022 will be analysed for each case. The analysis will include equity indicators previously validated for linkage in each jurisdiction, including, but not limited to, sex, age deprivation index (derived from census data), comorbidities, rurality, and socioeconomic status. The analysis will be performed separately in each case, and results will be combined with the qualitative case analysis to have a holistic understanding of each case. As jurisdictions adjust their vaccination approaches at different times, the analyses will consider these changes. Analyses will accommodate changes in vaccine approaches through time-series analysis. 63 At the individual level, Cox proportional hazard models will test whether the time to vaccination differs by sociodemographic characteristics. Modelling will include previous influenza vaccination history where available to account for personal vaccination behaviours. Once data have been analysed for each jurisdiction (ie, case), the research team will meet to discuss similarities and differences across jurisdictions and note any nuances. While we will strive to have consistent analyses across the jurisdictions, the analyses will be adapted to accommodate differences due to differences in provincial data available. Any discrepancies will be acknowledged as limitations.

Cross case analysis

We will develop initial ‘meta-inferences’ (overall conclusions or understanding) 43 within each case by identifying where the results and inferences from qualitative thematic analysis and quantitative modelling data analyses complement (eg, see agreement where the qualitative data can explain the quantitative data) and diverge (eg, where the qualitative data suggested an effective approach, but there are low vaccinated individuals from equity-deserving backgrounds) from one another within each province. Next, we will explore differences and similarities among the cases through cross-cutting themes and concepts. 64 To inform our codesign sessions, we will combine our integrative analyses into a larger understanding of the various effective vaccine delivery channels across the seven provinces. The research team will review any discrepancies between the qualitative and quantitative results and decide which approaches will be investigated in the study’s second phase.

Phase 3: Codesigning recommendations

We will integrate codesign principles into developing recommendations for an equity-informed vaccine distribution strategy. 37 65 66 For this research, we define codesign as a process in which diverse participants involved in a design project come together to collectively identify the problem, generate potential solutions, and assess the effectiveness of those solutions. This entails a collaborative and inclusive approach, where individuals with different perspectives and expertise collaborate to foster innovation and problem-solving. 67 Through this process, the aim is to leverage the participants’ collective knowledge, creativity, and insights to drive the design process and arrive at meaningful and effective recommendations for vaccine distribution. 67 The EBCD 36 process entails inviting stakeholders (identified in phase 2) to participate in focus groups where they will collaboratively develop and implement improvements to the health service of interest (ie, vaccine delivery channels). 37 Most EBCD processes commence by gaining an insight into experiences, desires, and behaviours. 65 From there, key concepts and recommendations can be formulated, which are subsequently tested and adjusted. 43 65 68

For our proposed project, we will host one full-day workshop (focus groups) in each jurisdiction (n=7 in total). The workshop will involve activities to understand experiences through focus group questions and then progress to codesign activities to develop and refine recommendations for an equitable vaccine distribution strategy. 69 Workshops will be done in-person or remotely, depending on the COVID-19 context (ie, government restrictions and safety considerations). This will ensure that more stakeholders can participate. We will embed codesign principles by acknowledging the value of all lived experiences and thoughts shared, as well as establishing and nurturing relationships throughout codesign workshops. 70 Before the first workshop, the authors will repeat their reflexive processes by making explicit their positionality and relationship in contrast to others who are engaged in the codesign process (participants) and other members of the research team. 48 Moreover, the team will explore the power differentials that could occur between the research team and study participants.

For each of the seven provinces, individuals with lived experience, family caregivers, healthcare providers, public health experts, and policymakers will be recruited. 71 72 This aligns with the suggestion that codesign should involve individuals with diverse experiences. For this phase, we will select equity-deserving and at-risk populations with low vaccination rates in each province based on available data or in consultation with policymakers. We will purposively seek representation in gender to ensure diversity in perspectives. We will also involve a patient partner from each jurisdiction to centre the lived experiences of individuals within this research. 73 Strategies recommended in the Culturally Competent Research Criteria for Methodological Areas framework 74 will support the recruitment of a diverse sample of equity-deserving populations and at-risk populations. Study advertisements will be posted within religious organisations (eg, churches, gurdwaras, and mosques) and/or culturally tailored community programmes. 75 We will also seek assistance with recruitment from community gatekeepers (eg, patient partners, religious leaders, community schools, teachers, and primary care providers). We will recruit parents from elementary schools and community centres. Translators will be available for individuals with difficulty speaking/understanding English or French to build trust and explore their interest in the study. 74 These strategies have been used successfully to recruit diverse research participants. 76 We will also hire a layperson with lived experience to guide recruitment strategies. Participants can consent to attend all or some of the workshops. This will facilitate the participation of individuals who may not be able to accommodate a half-day. Participants will receive a gift card for their participation. Workshops will be facilitated by a neutral, professional facilitator (ie, someone not known to the research team but who experience with various patient populations), and a patient partner. 68 During the session, facilitators will check-in on participants’ well-being, provide frequent breaks and provide information on resources for counselling support within local resources. 68 77 They will be supported by researchers, translators, and at least two additional individuals (eg, RA) who will be coached on how to facilitate codesign workshops. All facilitators will be responsible for applying codesign methods and fostering the collaborative and ‘safe-space’ group dynamic throughout the workshops (ie, focus group and codesign activities). 78 Facilitators will guide participants through the focus group questions and codesign activities to ensure all participant voices are represented. 78 RAs will support the workshops with secretarial and logistical duties. 78

Each jurisdictional workshop will consist of 12–16 individuals with diverse lived experiences (eg, patient partners, healthcare professionals, policymakers, and public health officials). Participants will be reminded that the information is confidential. 68 Throughout the workshop, participants will be divided into groups based on their backgrounds (ie, individuals with lived experience or professional) to offer safe spaces. 79 This will also allow separate discussions and contrasting views between stakeholder groups. However, as the workshop progresses, facilitators will encourage a collaboration between different groups of individuals within a ‘favourable environment’ 80 (p. 3). To account for the evolving COVID-19 pandemic, we will provide participants with various scenarios (eg, when new policy announcements were made, such as boosters) and ask them to recall their experiences with these scenarios. Participants will discuss these in individual groups and then share the information with the larger group. Next, facilitators will encourage participants to brainstorm the essential components and delivery of future vaccination approaches, including vaccination approach elements such as location, modality of booking (eg, in-person, telephone, and virtual), and advocacy (eg, who needs to support different elements). This will be done through a series of small group activities before the facilitators bring the group together to discuss and make recommendations. Workshop activities will be audiorecorded and transcribed verbatim. Immediately after each codesign workshop, field notes will be recorded by each researcher/facilitator in attendance. Within 2 days of each workshop, the facilitators will meet with either the PI to discuss the workshop proceedings.

As codesign research requires an iterative evaluation of the data generated, 81 we will use thematic analysis as in phase 2 to identify the core group of recommendations (objective 4). 53 Thematic analysis will be done within and across each case. Moreover, to advance quality and transparency in codesign, the guidelines for reporting on patient and public involvement in health and social care research (GRIPP2) will be followed. 82

Patient and public involvement

This study involves the participation of equity-deserving individuals and key informants from public health and healthcare policy. 24 Equity-deserving individuals are recognised as experts with ‘lived experience’ who play an integral role in innovating healthcare services. 83

Since this research aims to identify and implement effective evidence and equity-informed vaccination strategy for diverse populations, an integrated knowledge translation approach will be used to cocreate this strategy with equity-deserving and at-risk populations. Patient partners will be involved in the codesign process to assist with recruiting and supporting participants and member-checking of findings. 73

Ethics and dissemination

This project will produce evidence-informed and experience-informed recommendations to inform the design and implementation of effective vaccine distribution approaches that will meet communities’ needs and reduce the risk of exacerbating health and social inequalities. The findings of this research could have significant health and social benefits for equity-deserving and at-risk populations in Canada and abroad. Since this research aims to develop and implement an evidence and equity-informed vaccination strategy, we are taking an integrated knowledge translation approach. The literature has strongly advocated for the rigorous, prospective use of knowledge translation frameworks to guide implementation projects. 84 As such, we are engaging research users (eg, policymakers) throughout the research process, which will accelerate the uptake and impact of this research. Doing so will strengthen its potential for integration into current and future vaccination efforts. We will also disseminate our findings through various academic outputs, including manuscripts and conference proceedings.

Ethics statements

Patient consent for publication.

Consent obtained directly from patient(s).

Acknowledgments

We would like to acknowledge our knowledge users for supporting this grant: Dr. Penny Ballem, Dr. Eileen deVilla, Catherine Donavon, Melanie Hnatiuk, Kavita Mehta, Dr. Tara Sampalli, Carine Sauvé, Scott Sinclair, and Dr. Gail Tomblin Murphy. We want to acknowledge Anam Shahil for research assistance.

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Contributors MA is the principal investigator who conceived the original study and obtained funding. MA, AK, and KMK developed the study design. All authors (STW, FA, NMI, RM-M, KA-B, MB, REGU, and JCK) participated in revisions to the study design for important intellectual content. MA led the development of the study protocol, and all other authors (AK, KMK, STW, FA, NMI, RM-M, KA-B, MB, REGU, and JCK) read, revised, and approved the final version of the manuscript.

Funding This project is supported by a grant awarded to MA by the Canadian Institute for Health Research (CIHR) grant number (#477174).

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.

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Case Study Research Design

The case study research design have evolved over the past few years as a useful tool for investigating trends and specific situations in many scientific disciplines.

This article is a part of the guide:

• Research Designs
• Quantitative and Qualitative Research
• Literature Review
• Quantitative Research Design
• Descriptive Research

Browse Full Outline

• 1 Research Designs
• 2.1 Pilot Study
• 2.2 Quantitative Research Design
• 2.3 Qualitative Research Design
• 2.4 Quantitative and Qualitative Research
• 3.1 Case Study
• 3.2 Naturalistic Observation
• 3.3 Survey Research Design
• 3.4 Observational Study
• 4.1 Case-Control Study
• 4.2 Cohort Study
• 4.3 Longitudinal Study
• 4.4 Cross Sectional Study
• 4.5 Correlational Study
• 5.1 Field Experiments
• 5.2 Quasi-Experimental Design
• 5.3 Identical Twins Study
• 6.1 Experimental Design
• 6.2 True Experimental Design
• 6.3 Double Blind Experiment
• 6.4 Factorial Design
• 7.1 Literature Review
• 7.2 Systematic Reviews
• 7.3 Meta Analysis

The case study has been especially used in social science, psychology, anthropology and ecology.

This method of study is especially useful for trying to test theoretical models by using them in real world situations. For example, if an anthropologist were to live amongst a remote tribe, whilst their observations might produce no quantitative data, they are still useful to science.

What is a Case Study?

Basically, a case study is an in depth study of a particular situation rather than a sweeping statistical survey . It is a method used to narrow down a very broad field of research into one easily researchable topic.

Whilst it will not answer a question completely, it will give some indications and allow further elaboration and hypothesis creation on a subject.

The case study research design is also useful for testing whether scientific theories and models actually work in the real world. You may come out with a great computer model for describing how the ecosystem of a rock pool works but it is only by trying it out on a real life pool that you can see if it is a realistic simulation.

For psychologists, anthropologists and social scientists they have been regarded as a valid method of research for many years. Scientists are sometimes guilty of becoming bogged down in the general picture and it is sometimes important to understand specific cases and ensure a more holistic approach to research .

H.M.: An example of a study using the case study research design.

The Argument for and Against the Case Study Research Design

Some argue that because a case study is such a narrow field that its results cannot be extrapolated to fit an entire question and that they show only one narrow example. On the other hand, it is argued that a case study provides more realistic responses than a purely statistical survey.

The truth probably lies between the two and it is probably best to try and synergize the two approaches. It is valid to conduct case studies but they should be tied in with more general statistical processes.

For example, a statistical survey might show how much time people spend talking on mobile phones, but it is case studies of a narrow group that will determine why this is so.

The other main thing to remember during case studies is their flexibility. Whilst a pure scientist is trying to prove or disprove a hypothesis , a case study might introduce new and unexpected results during its course, and lead to research taking new directions.

The argument between case study and statistical method also appears to be one of scale. Whilst many 'physical' scientists avoid case studies, for psychology, anthropology and ecology they are an essential tool. It is important to ensure that you realize that a case study cannot be generalized to fit a whole population or ecosystem.

Finally, one peripheral point is that, when informing others of your results, case studies make more interesting topics than purely statistical surveys, something that has been realized by teachers and magazine editors for many years. The general public has little interest in pages of statistical calculations but some well placed case studies can have a strong impact.

How to Design and Conduct a Case Study

The advantage of the case study research design is that you can focus on specific and interesting cases. This may be an attempt to test a theory with a typical case or it can be a specific topic that is of interest. Research should be thorough and note taking should be meticulous and systematic.

The first foundation of the case study is the subject and relevance. In a case study, you are deliberately trying to isolate a small study group, one individual case or one particular population.

For example, statistical analysis may have shown that birthrates in African countries are increasing. A case study on one or two specific countries becomes a powerful and focused tool for determining the social and economic pressures driving this.

In the design of a case study, it is important to plan and design how you are going to address the study and make sure that all collected data is relevant. Unlike a scientific report, there is no strict set of rules so the most important part is making sure that the study is focused and concise; otherwise you will end up having to wade through a lot of irrelevant information.

It is best if you make yourself a short list of 4 or 5 bullet points that you are going to try and address during the study. If you make sure that all research refers back to these then you will not be far wrong.

With a case study, even more than a questionnaire or survey , it is important to be passive in your research. You are much more of an observer than an experimenter and you must remember that, even in a multi-subject case, each case must be treated individually and then cross case conclusions can be drawn .

How to Analyze the Results

Analyzing results for a case study tends to be more opinion based than statistical methods. The usual idea is to try and collate your data into a manageable form and construct a narrative around it.

Use examples in your narrative whilst keeping things concise and interesting. It is useful to show some numerical data but remember that you are only trying to judge trends and not analyze every last piece of data. Constantly refer back to your bullet points so that you do not lose focus.

It is always a good idea to assume that a person reading your research may not possess a lot of knowledge of the subject so try to write accordingly.

In addition, unlike a scientific study which deals with facts, a case study is based on opinion and is very much designed to provoke reasoned debate. There really is no right or wrong answer in a case study.

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• Published: 27 June 2011

The case study approach

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

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

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

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Introduction

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

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

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

What is a case study?

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

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

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

What are case studies used for?

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

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

How are case studies conducted?

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

Defining the case

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

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

Selecting the case(s)

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

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

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

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

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

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

Collecting the data

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

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

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

Analysing, interpreting and reporting case studies

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

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

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

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

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

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

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

Conclusions

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

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Acknowledgements

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

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Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

• Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

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.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

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

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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What is Qualitative Research Design? Methods and Types

Qualitative research targets on conveying meaning and comprehension via detailed description. Due to which, it can be a powerful method for exploring educational issues, that demands to develop a comprehension of complex social settings and the meaning that people within those settings bring to their real-life experience.The qualitative design is completely opposite to the quantitative research approach. At the forefront, it differs in the problematic field.

The approaches vary in a philosophical view of the world, in a set of goals and in methods, designs used for research.Qualitative research vs. quantitative relies on quality or meaning of experience trying to describe or comprehend the essence or nature of human experience. Qualitative vs. quantitative research integrates more subjective human experience rather than purely objective external reality.

It refers to the school of constructivism or interpretivism, while quantitative research is grounded in positivism.Additionally, qualitative research aims to describe, comprehend, discover the value or install a hypothesis or theory which extremely differs from quantitative targets – to control, predict, test and confirm the hypothesis.

What is Qualitative Research Design?

When designing your qualitative research project keep in mind several useful design tips:

• Establish a purpose for your qualitative study.
• Locate your method.
• Scope your project.
• Plan the nature of your data.
• Think ahead.

Qualitative research is subjective. It challenges the qualitative researcher to analyze data in order to form ideas. As we’ve already learned, it often uses open-ended questions for interviews. Let’s regard an example of qualitative research design. Imagine, you want to find out if a youth program affects the lives of underprivileged teens.

First of all, you talk to the participants and ask them what the real situation is. Then interpret the collected answers.Let’s take a look at the example of narrative research. It gathers data through stories. You use it when someone is willing to tell his or her story, and it’s worth reporting, or when you want a microanalytic picture. When focusing on qualitative narrative research follow this design:

• Choose a participant, who can give you the right and concrete information about the issue you’re studying.
• Collect the data from that participant.
• 4Retell or restore the story in chronological order.
• Cooperate with the individual.
• Write a story about the participant’s experience.
• Confirm the accuracy of the report and be happy, because you’ve completed qualitative research.

5 TYPES OF QUALITATIVE METHODS

Qualitative methodology field includes 5 principal methods. Those are:

• case study (investigates an activity, an event, a process or one, or several individuals in depth);
• ethnography (studies a cultural group in a common setting for a prolonged period of time);
• grounded theory (derives a general abstract theory of an action, process or influence based on the views of participants);
• narrative approaches (study the information that participants tell about their lives and experiences);
• phenomenology (identifies the essence of human experiences).

As well as, a case study has an opportunity to bend several methods into justified research design. A case study is, perhaps, the most widely used methodology due to its flexibility.Data for qualitative researches are typically obtained from different sources such as focus groups, interviews, observations of real-life settings, and documents.

As you plan your research study, you must complete justification for your data collection methods. In order to define, why the methods you are going to use are the most suitable and most productive ways to comprehend the focus of your study. Qualitative researches follow three basic steps when analyzing the data:

• Drafting and organizing data. This could be transcribing the interview, organizing field notes from observations or ensuring all documents used in the analysis are available.
• Categorizing data into themes. The qualitative researches identify the data by themes, coding data elements and creating categories.
• Presenting the collected data.

From now on, do not hesitate! Use the qualitative research and affect the world.

Related posts:

• Quantitative Research Design: Definition, Methods and Types
• Qualitative vs Quantitative Research: What difference?
• Research Design: Definition, Types and How to Write
• Descriptive Research Design: Definition, Methods and Examples
• Exploratory Research Design: Definition, Types and Ways to Implement
• Qualitative and Quantitative Methods
• Qualitative Design

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The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

2 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Ann Robertson

3 School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

Anthony Avery

Aziz sheikh.

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

Introduction

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

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

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables ​ Tables1, 1 , ​ ,2, 2 , ​ ,3 3 and ​ and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table ​ (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

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

These are however not necessarily mutually exclusive categories. In the first of our examples (Table ​ (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables ​ Tables2, 2 , ​ ,3 3 and ​ and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table ​ (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables ​ Tables2 2 and ​ and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table ​ (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table ​ (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

How are case studies conducted?

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

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table ​ Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table ​ (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table ​ (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

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

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

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table ​ Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

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

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

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table ​ (Table2 2 )[ 4 ].

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

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

Analysing, interpreting and reporting case studies

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

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table ​ (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table ​ (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table ​ (Table4 4 )[ 6 ].

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

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table ​ Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

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

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table ​ (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table ​ Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table ​ (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 8 ]

Conclusions

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

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

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

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

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

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