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Difference Between Case Study and Phenomenology

Main difference – case study vs phenomenology.

Case study and phenomenology are two terms that are often used in the field of social science s and research. Both these terms refer to types of research methods ; however, phenomenology is also a concept in philosophical studies. As a research methodology, the main difference between case study and phenomenology is that case study is an in-depth and detailed investigation of the development of a single event, situation, or an individual over a period of time whereas phenomenology is a study that is designed to understand the subjective, lived experiences and perspectives of participants.

In this article, we will be discussing,

     1. What is a Case Study           – Definition, Use, Data Collection, Limitations      2. What is Phenomenology           – Definition, Use, Data Collection, Limitations      3. What is the difference between Case Study and Phenomenology

What is a Case Study

A case study is defined as “an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multiple sources of evidence are used” (Yin,1984).  In simple terms, it is an in-depth and detailed investigation of the development of a single event, situation, or an individual over a period of time. Case studies are often used to explore and unearth complex issues such as social issues, medical conditions, etc. Many researchers use case study method to explore social issues like prostitution, drug addiction, unemployment, and poverty. Case studies can be qualitative and/or quantitative in nature.

A case study commences with identifying and defining the research problem; then the researcher has to select the cases and decide techniques for data collection and analysis. This is followed by collecting data in the field and evaluating and analyzing the data. The final step in a case study involves preparing the research report.  Data collection methods in a case study involve observations, questionnaires, interviews, analysis of recorded data, etc. A successful case study is always context-sensitive, holistic, systematic, layered and comprehensive.

Case studies are sometimes classified into three categories known as exploratory, descriptive and explanatory case studies. Ethnographies are also considered as a type of case studies.

Although case studies offer detailed and in-depth information about a particular phenomenon, it is difficult to use this information to form generalization since they only focus on a single phenomenon.

Figure 1: Questionnaires can be used to collect data for case studies.

What is Phenomenology

Phenomenology is both a philosophy and a research method. As a philosophical study, phenomenology refers to the study of the structures of experience and consciousness. In the field of research, it refers to a study that is designed to understand the subjective, lived experiences and perspectives of participants. Phenomenology is based on the principle that a single experience can be interpreted in multiple ways and that reality consists of each participant’s interpretation of the said experience. Thus, phenomenology provides information about unique individual experiences, offering a rich and complete description of human experiences and meanings.

Data is collected in phenomenology through long and intensive, semi-structured or unstructured personal interviews. The researcher may also have to conduct several interview sessions with each participant since phenomenology relies heavily on interviews. However, the information gathered through these interviews may also depend on the interviewing skills of the researcher and the articulate skills of the participants. This is a limitation of this method.

Figure 2: Phenomenology often involves long personal interviews.

Case Study: Case study is an in-depth and detailed investigation of the development of a single event, situation, or an individual over a period of time.

Phenomenology: Phenomenology is a study that is designed to understand the subjective, lived experiences and perspectives of participants.

Data Collection

Case Study: Data collection methods include observations, interviews, questionnaires, etc.

Phenomenology: Interviews are the main method of data collection.

Case Study: Case studies focus on a single incident, event, organization, or an individual.

Phenomenology: Phenomenology focus on various individuals and their experiences.

Limitations

Case Study: The information obtained from a case study cannot be used to make generalizations.

Phenomenology: Information relies heavily on the interviewing skills of the researcher and the articulate skills of the participants.

Reference: 1. Yin, Robert. “Case study research. Beverly Hills.” (1984).

Image Courtesy: 1. “5 Candidates reading a questionnaire Photo Tony Ntumba MONUSCO” by MONUSCO Photos (CC BY-SA 2.0) via Flickr 2. “1702648” (Public Domain) via Pixabay

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Case Study vs. Phenomenology

What's the difference.

Case study and phenomenology are both research methods used in social sciences to gain a deeper understanding of a particular phenomenon. However, they differ in their approach and focus. Case study involves an in-depth analysis of a specific case or individual, aiming to provide a detailed description and explanation of the phenomenon under investigation. It often involves collecting and analyzing various types of data, such as interviews, observations, and documents. On the other hand, phenomenology focuses on understanding the lived experiences and subjective perspectives of individuals. It aims to uncover the essence and meaning of a phenomenon by exploring the thoughts, feelings, and perceptions of those involved. Phenomenology often involves interviews and reflective analysis to gain insights into the subjective experiences of individuals. Overall, while case study emphasizes detailed analysis of a specific case, phenomenology focuses on understanding the subjective experiences and meanings associated with a phenomenon.

Further Detail

Introduction.

Research methodologies play a crucial role in understanding and exploring various phenomena in different fields. Two commonly used methodologies are case study and phenomenology. While both approaches aim to gain insights and generate knowledge, they differ in their focus, data collection methods, and analysis techniques. In this article, we will compare the attributes of case study and phenomenology, highlighting their similarities and differences.

Case study is a research method that involves an in-depth investigation of a particular individual, group, or phenomenon within its real-life context. It aims to provide a comprehensive understanding of the subject under study by examining multiple variables and their interrelationships. Case studies often utilize a combination of qualitative and quantitative data, including interviews, observations, documents, and archival records.

One of the key strengths of case study research is its ability to provide rich and detailed descriptions of complex phenomena. By focusing on a specific case, researchers can explore the intricacies and nuances that may not be captured by broader research designs. Case studies also allow for the examination of rare or unique cases, providing valuable insights that can contribute to theory development or inform practical applications.

However, case studies also have limitations. Due to their in-depth nature, they may be time-consuming and resource-intensive. Generalizability can be a concern, as findings from a single case may not be applicable to other contexts or populations. Additionally, the subjective interpretation of data by the researcher can introduce bias, potentially impacting the validity and reliability of the study.

Phenomenology

Phenomenology is a qualitative research approach that focuses on understanding the lived experiences of individuals and the meanings they attribute to those experiences. It aims to explore the essence and structure of a phenomenon as it is perceived by the participants. Phenomenological research often involves in-depth interviews, participant observations, and analysis of personal narratives or texts.

One of the main strengths of phenomenology is its emphasis on capturing the subjective experiences of individuals. By delving into the lived experiences, emotions, and perspectives of participants, researchers can gain a deeper understanding of the phenomenon under investigation. Phenomenology also allows for the exploration of complex and abstract concepts, shedding light on the underlying meanings and motivations.

However, phenomenology also has its limitations. The findings may be highly subjective and context-dependent, limiting their generalizability. The researcher's interpretation and biases can influence the analysis and findings. Additionally, the process of phenomenological analysis can be time-consuming and require significant expertise in qualitative research methods.

While case study and phenomenology differ in their focus and approach, they share some commonalities. Both methodologies involve an in-depth exploration of a particular subject, aiming to gain a comprehensive understanding of the phenomenon under study. They both utilize qualitative data collection methods, such as interviews and observations, to gather rich and detailed information.

However, there are also notable differences between case study and phenomenology. Case study research often examines multiple variables and their interrelationships, while phenomenology focuses on the subjective experiences and meanings attributed by individuals. Case studies aim to provide a holistic view of a complex phenomenon within its real-life context, whereas phenomenology aims to uncover the essence and structure of a phenomenon as it is perceived by the participants.

Another difference lies in the analysis techniques employed. In case study research, data analysis often involves a combination of qualitative and quantitative methods, allowing for a comprehensive examination of the subject. Phenomenological analysis, on the other hand, focuses on identifying themes, patterns, and structures within the qualitative data, aiming to uncover the underlying meanings and essences.

Furthermore, case studies are often used in applied fields, such as psychology, business, and education, where practical implications and real-life contexts are of particular interest. Phenomenology, on the other hand, is commonly employed in fields such as sociology, anthropology, and philosophy, where understanding subjective experiences and exploring abstract concepts are central to the research objectives.

Case study and phenomenology are two distinct research methodologies that offer valuable insights into various phenomena. While case study research provides a comprehensive understanding of complex phenomena within their real-life contexts, phenomenology focuses on exploring the subjective experiences and meanings attributed by individuals. Both approaches have their strengths and limitations, and the choice between them depends on the research objectives, the nature of the phenomenon under study, and the available resources. By understanding the attributes of case study and phenomenology, researchers can make informed decisions about the most appropriate methodology to employ in their studies.

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Research Design 101

Everything You Need To Get Started (With Examples)

By: Derek Jansen (MBA) | Reviewers: Eunice Rautenbach (DTech) & Kerryn Warren (PhD) | April 2023

Navigating the world of research can be daunting, especially if you’re a first-time researcher. One concept you’re bound to run into fairly early in your research journey is that of “ research design ”. Here, we’ll guide you through the basics using practical examples , so that you can approach your research with confidence.

Overview: Research Design 101

What is research design.

• Research design types for quantitative studies
• Video explainer : quantitative research design
• Research design types for qualitative studies
• Video explainer : qualitative research design
• How to choose a research design
• Key takeaways

Research design refers to the overall plan, structure or strategy that guides a research project , from its conception to the final data analysis. A good research design serves as the blueprint for how you, as the researcher, will collect and analyse data while ensuring consistency, reliability and validity throughout your study.

Understanding different types of research designs is essential as helps ensure that your approach is suitable  given your research aims, objectives and questions , as well as the resources you have available to you. Without a clear big-picture view of how you’ll design your research, you run the risk of potentially making misaligned choices in terms of your methodology – especially your sampling , data collection and data analysis decisions.

The problem with defining research design…

One of the reasons students struggle with a clear definition of research design is because the term is used very loosely across the internet, and even within academia.

Some sources claim that the three research design types are qualitative, quantitative and mixed methods , which isn’t quite accurate (these just refer to the type of data that you’ll collect and analyse). Other sources state that research design refers to the sum of all your design choices, suggesting it’s more like a research methodology . Others run off on other less common tangents. No wonder there’s confusion!

In this article, we’ll clear up the confusion. We’ll explain the most common research design types for both qualitative and quantitative research projects, whether that is for a full dissertation or thesis, or a smaller research paper or article.

Research Design: Quantitative Studies

Quantitative research involves collecting and analysing data in a numerical form. Broadly speaking, there are four types of quantitative research designs: descriptive , correlational , experimental , and quasi-experimental . 

Descriptive Research Design

As the name suggests, descriptive research design focuses on describing existing conditions, behaviours, or characteristics by systematically gathering information without manipulating any variables. In other words, there is no intervention on the researcher’s part – only data collection.

For example, if you’re studying smartphone addiction among adolescents in your community, you could deploy a survey to a sample of teens asking them to rate their agreement with certain statements that relate to smartphone addiction. The collected data would then provide insight regarding how widespread the issue may be – in other words, it would describe the situation.

The key defining attribute of this type of research design is that it purely describes the situation . In other words, descriptive research design does not explore potential relationships between different variables or the causes that may underlie those relationships. Therefore, descriptive research is useful for generating insight into a research problem by describing its characteristics . By doing so, it can provide valuable insights and is often used as a precursor to other research design types.

Correlational Research Design

Correlational design is a popular choice for researchers aiming to identify and measure the relationship between two or more variables without manipulating them . In other words, this type of research design is useful when you want to know whether a change in one thing tends to be accompanied by a change in another thing.

For example, if you wanted to explore the relationship between exercise frequency and overall health, you could use a correlational design to help you achieve this. In this case, you might gather data on participants’ exercise habits, as well as records of their health indicators like blood pressure, heart rate, or body mass index. Thereafter, you’d use a statistical test to assess whether there’s a relationship between the two variables (exercise frequency and health).

As you can see, correlational research design is useful when you want to explore potential relationships between variables that cannot be manipulated or controlled for ethical, practical, or logistical reasons. It is particularly helpful in terms of developing predictions , and given that it doesn’t involve the manipulation of variables, it can be implemented at a large scale more easily than experimental designs (which will look at next).

That said, it’s important to keep in mind that correlational research design has limitations – most notably that it cannot be used to establish causality . In other words, correlation does not equal causation . To establish causality, you’ll need to move into the realm of experimental design, coming up next…

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Experimental Research Design

Experimental research design is used to determine if there is a causal relationship between two or more variables . With this type of research design, you, as the researcher, manipulate one variable (the independent variable) while controlling others (dependent variables). Doing so allows you to observe the effect of the former on the latter and draw conclusions about potential causality.

For example, if you wanted to measure if/how different types of fertiliser affect plant growth, you could set up several groups of plants, with each group receiving a different type of fertiliser, as well as one with no fertiliser at all. You could then measure how much each plant group grew (on average) over time and compare the results from the different groups to see which fertiliser was most effective.

Overall, experimental research design provides researchers with a powerful way to identify and measure causal relationships (and the direction of causality) between variables. However, developing a rigorous experimental design can be challenging as it’s not always easy to control all the variables in a study. This often results in smaller sample sizes , which can reduce the statistical power and generalisability of the results.

Moreover, experimental research design requires random assignment . This means that the researcher needs to assign participants to different groups or conditions in a way that each participant has an equal chance of being assigned to any group (note that this is not the same as random sampling ). Doing so helps reduce the potential for bias and confounding variables . This need for random assignment can lead to ethics-related issues . For example, withholding a potentially beneficial medical treatment from a control group may be considered unethical in certain situations.

Quasi-Experimental Research Design

Quasi-experimental research design is used when the research aims involve identifying causal relations , but one cannot (or doesn’t want to) randomly assign participants to different groups (for practical or ethical reasons). Instead, with a quasi-experimental research design, the researcher relies on existing groups or pre-existing conditions to form groups for comparison.

For example, if you were studying the effects of a new teaching method on student achievement in a particular school district, you may be unable to randomly assign students to either group and instead have to choose classes or schools that already use different teaching methods. This way, you still achieve separate groups, without having to assign participants to specific groups yourself.

Naturally, quasi-experimental research designs have limitations when compared to experimental designs. Given that participant assignment is not random, it’s more difficult to confidently establish causality between variables, and, as a researcher, you have less control over other variables that may impact findings.

All that said, quasi-experimental designs can still be valuable in research contexts where random assignment is not possible and can often be undertaken on a much larger scale than experimental research, thus increasing the statistical power of the results. What’s important is that you, as the researcher, understand the limitations of the design and conduct your quasi-experiment as rigorously as possible, paying careful attention to any potential confounding variables .

Research Design: Qualitative Studies

There are many different research design types when it comes to qualitative studies, but here we’ll narrow our focus to explore the “Big 4”. Specifically, we’ll look at phenomenological design, grounded theory design, ethnographic design, and case study design.

Phenomenological Research Design

Phenomenological design involves exploring the meaning of lived experiences and how they are perceived by individuals. This type of research design seeks to understand people’s perspectives , emotions, and behaviours in specific situations. Here, the aim for researchers is to uncover the essence of human experience without making any assumptions or imposing preconceived ideas on their subjects.

For example, you could adopt a phenomenological design to study why cancer survivors have such varied perceptions of their lives after overcoming their disease. This could be achieved by interviewing survivors and then analysing the data using a qualitative analysis method such as thematic analysis to identify commonalities and differences.

Phenomenological research design typically involves in-depth interviews or open-ended questionnaires to collect rich, detailed data about participants’ subjective experiences. This richness is one of the key strengths of phenomenological research design but, naturally, it also has limitations. These include potential biases in data collection and interpretation and the lack of generalisability of findings to broader populations.

Grounded Theory Research Design

Grounded theory (also referred to as “GT”) aims to develop theories by continuously and iteratively analysing and comparing data collected from a relatively large number of participants in a study. It takes an inductive (bottom-up) approach, with a focus on letting the data “speak for itself”, without being influenced by preexisting theories or the researcher’s preconceptions.

As an example, let’s assume your research aims involved understanding how people cope with chronic pain from a specific medical condition, with a view to developing a theory around this. In this case, grounded theory design would allow you to explore this concept thoroughly without preconceptions about what coping mechanisms might exist. You may find that some patients prefer cognitive-behavioural therapy (CBT) while others prefer to rely on herbal remedies. Based on multiple, iterative rounds of analysis, you could then develop a theory in this regard, derived directly from the data (as opposed to other preexisting theories and models).

Grounded theory typically involves collecting data through interviews or observations and then analysing it to identify patterns and themes that emerge from the data. These emerging ideas are then validated by collecting more data until a saturation point is reached (i.e., no new information can be squeezed from the data). From that base, a theory can then be developed .

As you can see, grounded theory is ideally suited to studies where the research aims involve theory generation , especially in under-researched areas. Keep in mind though that this type of research design can be quite time-intensive , given the need for multiple rounds of data collection and analysis.

Ethnographic Research Design

Ethnographic design involves observing and studying a culture-sharing group of people in their natural setting to gain insight into their behaviours, beliefs, and values. The focus here is on observing participants in their natural environment (as opposed to a controlled environment). This typically involves the researcher spending an extended period of time with the participants in their environment, carefully observing and taking field notes .

All of this is not to say that ethnographic research design relies purely on observation. On the contrary, this design typically also involves in-depth interviews to explore participants’ views, beliefs, etc. However, unobtrusive observation is a core component of the ethnographic approach.

As an example, an ethnographer may study how different communities celebrate traditional festivals or how individuals from different generations interact with technology differently. This may involve a lengthy period of observation, combined with in-depth interviews to further explore specific areas of interest that emerge as a result of the observations that the researcher has made.

As you can probably imagine, ethnographic research design has the ability to provide rich, contextually embedded insights into the socio-cultural dynamics of human behaviour within a natural, uncontrived setting. Naturally, however, it does come with its own set of challenges, including researcher bias (since the researcher can become quite immersed in the group), participant confidentiality and, predictably, ethical complexities . All of these need to be carefully managed if you choose to adopt this type of research design.

Case Study Design

With case study research design, you, as the researcher, investigate a single individual (or a single group of individuals) to gain an in-depth understanding of their experiences, behaviours or outcomes. Unlike other research designs that are aimed at larger sample sizes, case studies offer a deep dive into the specific circumstances surrounding a person, group of people, event or phenomenon, generally within a bounded setting or context .

As an example, a case study design could be used to explore the factors influencing the success of a specific small business. This would involve diving deeply into the organisation to explore and understand what makes it tick – from marketing to HR to finance. In terms of data collection, this could include interviews with staff and management, review of policy documents and financial statements, surveying customers, etc.

While the above example is focused squarely on one organisation, it’s worth noting that case study research designs can have different variation s, including single-case, multiple-case and longitudinal designs. As you can see in the example, a single-case design involves intensely examining a single entity to understand its unique characteristics and complexities. Conversely, in a multiple-case design , multiple cases are compared and contrasted to identify patterns and commonalities. Lastly, in a longitudinal case design , a single case or multiple cases are studied over an extended period of time to understand how factors develop over time.

As you can see, a case study research design is particularly useful where a deep and contextualised understanding of a specific phenomenon or issue is desired. However, this strength is also its weakness. In other words, you can’t generalise the findings from a case study to the broader population. So, keep this in mind if you’re considering going the case study route.

How To Choose A Research Design

Having worked through all of these potential research designs, you’d be forgiven for feeling a little overwhelmed and wondering, “ But how do I decide which research design to use? ”. While we could write an entire post covering that alone, here are a few factors to consider that will help you choose a suitable research design for your study.

Data type: The first determining factor is naturally the type of data you plan to be collecting – i.e., qualitative or quantitative. This may sound obvious, but we have to be clear about this – don’t try to use a quantitative research design on qualitative data (or vice versa)!

Research aim(s) and question(s): As with all methodological decisions, your research aim and research questions will heavily influence your research design. For example, if your research aims involve developing a theory from qualitative data, grounded theory would be a strong option. Similarly, if your research aims involve identifying and measuring relationships between variables, one of the experimental designs would likely be a better option.

Time: It’s essential that you consider any time constraints you have, as this will impact the type of research design you can choose. For example, if you’ve only got a month to complete your project, a lengthy design such as ethnography wouldn’t be a good fit.

Resources: Take into account the resources realistically available to you, as these need to factor into your research design choice. For example, if you require highly specialised lab equipment to execute an experimental design, you need to be sure that you’ll have access to that before you make a decision.

Keep in mind that when it comes to research, it’s important to manage your risks and play as conservatively as possible. If your entire project relies on you achieving a huge sample, having access to niche equipment or holding interviews with very difficult-to-reach participants, you’re creating risks that could kill your project. So, be sure to think through your choices carefully and make sure that you have backup plans for any existential risks. Remember that a relatively simple methodology executed well generally will typically earn better marks than a highly-complex methodology executed poorly.

Recap: Key Takeaways

We’ve covered a lot of ground here. Let’s recap by looking at the key takeaways:

• Research design refers to the overall plan, structure or strategy that guides a research project, from its conception to the final analysis of data.
• Research designs for quantitative studies include descriptive , correlational , experimental and quasi-experimenta l designs.
• Research designs for qualitative studies include phenomenological , grounded theory , ethnographic and case study designs.
• When choosing a research design, you need to consider a variety of factors, including the type of data you’ll be working with, your research aims and questions, your time and the resources available to you.

If you need a helping hand with your research design (or any other aspect of your research), check out our private coaching services .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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10 Comments

Is there any blog article explaining more on Case study research design? Is there a Case study write-up template? Thank you.

Thanks this was quite valuable to clarify such an important concept.

Thanks for this simplified explanations. it is quite very helpful.

This was really helpful. thanks

Thank you for your explanation. I think case study research design and the use of secondary data in researches needs to be talked about more in your videos and articles because there a lot of case studies research design tailored projects out there.

Please is there any template for a case study research design whose data type is a secondary data on your repository?

This post is very clear, comprehensive and has been very helpful to me. It has cleared the confusion I had in regard to research design and methodology.

This post is helpful, easy to understand, and deconstructs what a research design is. Thanks

how to cite this page

Thank you very much for the post. It is wonderful and has cleared many worries in my mind regarding research designs. I really appreciate .

how can I put this blog as my reference(APA style) in bibliography part?

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Qualitative study design: Phenomenology

• Qualitative study design

Phenomenology

• Grounded theory
• Ethnography
• Narrative inquiry
• Action research
• Case Studies
• Field research
• Focus groups
• Observation
• Surveys & questionnaires
• Study Designs Home

Used to describe the lived experience of individuals.

• Now called Descriptive Phenomenology, this study design is one of the most commonly used methodologies in qualitative research within the social and health sciences.
• Used to describe how human beings experience a certain phenomenon. The researcher asks, “What is this experience like?’, ‘What does this experience mean?’ or ‘How does this ‘lived experience’ present itself to the participant?’
• Attempts to set aside biases and preconceived assumptions about human experiences, feelings, and responses to a particular situation.
• Experience may involve perception, thought, memory, imagination, and emotion or feeling.
• Usually (but not always) involves a small sample of participants (approx. 10-15).
• Analysis includes an attempt to identify themes or, if possible, make generalizations in relation to how a particular phenomenon is perceived or experienced.

Methods used include:

• participant observation
• in-depth interviews with open-ended questions
• conversations and focus workshops. 

Researchers may also examine written records of experiences such as diaries, journals, art, poetry and music.

Descriptive phenomenology is a powerful way to understand subjective experience and to gain insights around people’s actions and motivations, cutting through long-held assumptions and challenging conventional wisdom.  It may contribute to the development of new theories, changes in policies, or changes in responses.

Limitations

• Does not suit all health research questions.  For example, an evaluation of a health service may be better carried out by means of a descriptive qualitative design, where highly structured questions aim to garner participant’s views, rather than their lived experience.
• Participants may not be able to express themselves articulately enough due to language barriers, cognition, age, or other factors.
• Gathering data and data analysis may be time consuming and laborious.
• Results require interpretation without researcher bias.
• Does not produce easily generalisable data.

Example questions

• How do cancer patients cope with a terminal diagnosis?
• What is it like to survive a plane crash?
• What are the experiences of long-term carers of family members with a serious illness or disability?
• What is it like to be trapped in a natural disaster, such as a flood or earthquake? 

Example studies

• The patient-body relationship and the "lived experience" of a facial burn injury: a phenomenological inquiry of early psychosocial adjustment . Individual interviews were carried out for this study.
• The use of group descriptive phenomenology within a mixed methods study to understand the experience of music therapy for women with breast cancer . Example of a study in which focus group interviews were carried out.
• Understanding the experience of midlife women taking part in a work-life balance career coaching programme: An interpretative phenomenological analysis . Example of a study using action research.
• Holloway, I. & Galvin, K. (2017). Qualitative research in nursing and healthcare (Fourth ed.): John Wiley & Sons Inc.
• Rodriguez, A., & Smith, J. (2018). Phenomenology as a healthcare research method . Journal of Evidence Based Nursing , 21(4), 96-98. doi: 10.1136/eb-2018-102990
• << Previous: Methodologies
• Next: Grounded theory >>
• Last Updated: Apr 8, 2024 11:12 AM
• URL: https://deakin.libguides.com/qualitative-study-designs

From John W. Creswell \(2016\). 30 Essential Skills for the Qualitative Researcher \ . Thousand Oaks, CA: Sage.

Qualitative Research Methods

• Gumberg Library and CIQR
• Qualitative Methods Overview

Phenomenology

• Case Studies
• Grounded Theory
• Narrative Inquiry
• Oral History
• Feminist Approaches
• Action Research
• Finding Books
• Getting Help

Phenomenology helps us to understand the meaning of people's lived experience.  A phenomenological study explores what people experienced and focuses on their experience of a phenomenon.  As phenomenology has a strong foundation in philosophy, it is recommended that you explore the writings of key thinkers such as Husserl, Heidegger, Sartre and Merleau-Ponty before embarking on your research. Duquesne's Simon Silverman Phenomenology Center maintains a collection of resources connected to phenomenology as well as hosting lectures, and is a good place to start your exploration.

• Simon Silverman Phenomenology Center
• Husserl, Edmund, 1859–1938
• Heidegger, Martin, 1889–1976
• Sartre, Jean Paul, 1905–1980
• Merleau-Ponty, Maurice, 1908–1961

Books and eBooks

Online Resources

• Phenomenology Stanford Encyclopedia of Philosophy entry.

• << Previous: Qualitative Methods Overview
• Next: Case Studies >>
• Last Updated: Aug 18, 2023 11:56 AM
• URL: https://guides.library.duq.edu/qualitative_research

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Chapter 6: Phenomenology

Darshini Ayton

Learning outcomes

Upon completion of this chapter, you should be able to:

• Identify the key terms, concepts and approaches used in phenomenology.
• Explain the data collection methods and analysis for phenomenology.
• Discuss the advantages and disadvantages of phenomenological research.

What is phenomenology ?

The key concept in phenomenological studies is the individual .

Phenomenology is a method and a philosophical approach, influenced by different paradigms and disciplines. 1

Phenomenology is the everyday world from the viewpoint of the person. In this viewpoint, the emphasis is on how the individual constructs their lifeworld and seeks to understand the ‘taken for granted-ness’ of life and experiences. 2,3 Phenomenology is a practice that seeks to understand, describe and interpret human behaviour and the meaning individuals make of their experiences; it focuses on what was experienced and how it was experienced. 4 Phenomenology deals with perceptions or meanings, attitudes and beliefs, as well as feelings and emotions. The emphasis is on the lived experience and the sense an individual makes of those experiences. Since the primary source of data is the experience of the individual being studied, in-depth interviews are the most common means of data collection (see Chapter 13). Depending on the aim and research questions of the study, the method of analysis is either thematic or interpretive phenomenological analysis (Section 4).

Types of phenomenology

Descriptive phenomenology (also known as ‘transcendental phenomenology’) was founded by Edmund Husserl (1859–1938). It focuses on phenomena as perceived by the individual. 4 When reflecting on the recent phenomenon of the COVID-19 pandemic, it is clear that there is a collective experience of the pandemic and an individual experience, in which each person’s experience is influenced by their life circumstances, such as their living situation, employment, education, prior experiences with infectious diseases and health status. In addition, an individual’s life circumstances, personality, coping skills, culture, family of origin, where they live in the world and the politics of their society also influence their experience of the pandemic. Hence, the objectiveness of the pandemic is intertwined with the subjectiveness of the individual living in the pandemic.

Husserl states that descriptive phenomenological inquiry should be free of assumption and theory, to enable phenomenological reduction (or phenomenological intuiting). 1 Phenomenological reduction means putting aside all judgements or beliefs about the external world and taking nothing for granted in everyday reality. 5 This concept gave rise to a practice called ‘bracketing’ — a method of acknowledging the researcher’s preconceptions, assumptions, experiences and ‘knowing’ of a phenomenon. Bracketing is an attempt by the researcher to encounter the phenomenon in as ‘free and as unprejudiced way as possible so that it can be precisely described and understood’. 1(p132) While there is not much guidance on how to bracket, the advice provided to researchers is to record in detail the process undertaken, to provide transparency for others. Bracketing starts with reflection: a helpful practice is for the researcher to ask the following questions and write their answers as they occur, without overthinking their responses (see Box 1). This is a practice that ideally should be done multiple times during the research process: at the conception of the research idea and during design, data collection, analysis and reporting.

Box 6.1 Example s of bracketing prompts

How does my education, family background (culture), religion, politics and job relate to this topic or phenomenon?

What is my previous experience of this topic or phenomenon? Do I have negative and/or positive reactions to this topic or phenomenon? What has led to this reaction?

What have I read or understood about this topic or phenomenon?

What are my beliefs and attitudes about this topic or phenomenon? What assumptions am I making?

Interpretive or hermeneutic phenomenology was founded by Martin Heidegger (1889–1976), a junior colleague of Husserl. It focuses on the nature of being and the relationship between an individual and their lifeworld. While Heidegger’s initial work and thinking aligned with Husserl’s, he later challenged several elements of descriptive phenomenology, leading to a philosophical separation in ideas. Husserl’s descriptive phenomenology takes an epistemological (knowledge) focus while Heidegger’s interest was in ontology 4 (the nature of reality), with the key phrase ‘being-in-the-world’ referencing how humans exist, act or participate in the world. 1 In descriptive phenomenology, the practice of bracketing is endorsed and experience is stripped from context to examine and understand it.

Interpretive or hermeneutic phenomenology embraces the intertwining of an individual’s subjective experience with their social, cultural and political contexts, regardless of whether they are conscious of this influence. 4 Interpretive or hermeneutic phenomenology moves beyond description to the interpretation of the phenomenon and the study of meanings through the lifeworld of the individual. While the researcher’s knowledge, experience, assumptions and beliefs are valued, they do need to be acknowledged as part of the process of analysis. 4

For example, Singh and colleagues wanted to understand the experiences of managers involved in the implementation of quality improvement projects in an assisted living facility, and thus they conducted a hermeneutic phenomenology study. 6 The objective was to ‘understand how managers define the quality of patient care and administrative processes’, alongside an exploration of the participant’s perspectives of leadership and challenges to the implementation of quality improvement strategies. (p3) Semi-structured interviews (60–75 minutes in duration) were conducted with six managers and data was analysed using inductive thematic techniques.

New phenomenology , or American phenomenology , has initiated a transition in the focus of phenomenology from the nature and understanding of the phenomenon to the lived experience of individuals experiencing the phenomenon. This transition may seem subtle but fundamentally is related to a shift away from the philosophical approaches of Husserl and Heidegger to an applied approach to research. 1 New phenomenology does not undergo the phenomenological reductionist approach outlined by Husserl to examine and understand the essence of the phenomenon. Dowling 1 emphasises that this phenomenological reduction, which leads to an attempt to disengage the researcher from the participant, is not desired or practical in applied research such as in nursing studies. Hence, new phenomenology is aligned with interpretive phenomenology, embracing the intersubjectivity (shared subjective experiences between two or more people) of the research approach. 1

Another feature of new phenomenology is the positioning of culture in the analysis of an individual’s experience. This is not the case for the traditional phenomenological approaches 1 ;  hence, philosophical approaches by European philosophers Husserl and Heidegger can be used if the objective is to explore or understand the phenomenon itself or the object of the participant’s experience. The methods of new phenomenology, or American phenomenology, should be applied if the researcher seeks to understand a person’s experience(s) of the phenomenon. 1

See Table 6.1. for two different examples of phenomenological research.

Advantages and disadvantages of phenomenological research

Phenomenology has many advantages, including that it can present authentic accounts of complex phenomena; it is a humanistic style of research that demonstrates respect for the whole individual; and the descriptions of experiences can tell an interesting story about the phenomenon and the individuals experiencing it. 7 Criticisms of phenomenology tend to focus on the individuality of the results, which makes them non-generalisable, considered too subjective and therefore invalid. However, the reason a researcher may choose a phenomenological approach is to understand the individual, subjective experiences of an individual; thus, as with many qualitative research designs, the findings will not be generalisable to a larger population. 7,8

Table 6.1. Examples of phenomenological studies

Phenomenology focuses on understanding a phenomenon from the perspective of individual experience (descriptive and interpretive phenomenology) or from the lived experience of the phenomenon by individuals (new phenomenology). This individualised focus lends itself to in-depth interviews and small scale research projects.

• Dowling M. From Husserl to van Manen. A review of different phenomenological approaches. Int J Nurs Stud . 2007;44(1):131-42. doi:10.1016/j.ijnurstu.2005.11.026
• Creswell J, Hanson W, Clark Plano V, Morales A. Qualitative research designs: selection and implementation. Couns Psychol . 2007;35(2):236-264. doi:10.1177/0011000006287390
• Morse JM, Field PA. Qualitative Research Methods for Health Professionals. 2nd ed. SAGE; 1995.
• Neubauer BE, Witkop CT, Varpio L. How phenomenology can help us learn from the experiences of others. Perspect Med Educ . 2019;8(2):90-97. doi:10.1007/s40037-019-0509-2
• Merleau-Ponty M, Landes D, Carman T, Lefort C. Phenomenology of Perception . 1st ed. Routledge; 2011.
• Singh J, Wiese A, Sillerud B. Using phenomenological hermeneutics to understand the experiences of managers working with quality improvement strategies in an assisted living facility. Healthcare (Basel) . 2019;7(3):87. doi:10.3390/healthcare7030087
• Liamputtong P, Ezzy D. Qualitative Research Methods: A Health Focus . Oxford University Press; 1999.
• Liamputtong P. Qualitative Research Methods . 5th ed. Oxford University Press; 2020.
• Abbaspour Z, Vasel G, Khojastehmehr R. Investigating the lived experiences of abused mothers: a phenomenological study. Journal of Qualitative Research in Health Sciences . 2021;10(2)2:108-114. doi:10.22062/JQR.2021.193653.0
• Engberink AO, Mailly M, Marco V, et al. A phenomenological study of nurses experience about their palliative approach and their use of mobile palliative care teams in medical and surgical care units in France. BMC Palliat Care . 2020;19:34. doi:10.1186/s12904-020-0536-0

Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Darshini Ayton is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Research MethodologyOverview of Qualitative Research

Qualitative research methods are a robust tool for chaplaincy research questions. Similar to much of chaplaincy clinical care, qualitative research generally works with written texts, often transcriptions of individual interviews or focus group conversations and seeks to understand the meaning of experience in a study sample. This article describes three common methodologies: ethnography, grounded theory, and phenomenology. Issues to consider relating to the study sample, design, and analysis are discussed. Enhancing the validity of the data, as well reliability and ethical issues in qualitative research are described. Qualitative research is an accessible way for chaplains to contribute new knowledge about the sacred dimension of people's lived experience.

INTRODUCTION

Qualitative research is, “the systematic collection, organization, and interpretation of textual material derived from talk or conversation. It is used in the exploration of meanings of social phenomena as experienced by individuals themselves, in their natural context” ( Malterud, 2001 , p. 483). It can be the most accessible means of entry for chaplains into the world of research because, like clinical conversations, it focuses on eliciting people's stories. The stories can actually be expressed in almost any medium: conversations (interviews or focus groups), written texts (journal, prayers, or letters), or visual forms (drawings, photographs). Qualitative research may involve presenting data collected from a single person, as in a case study ( Risk, 2013 ), or from a group of people, as in one of my studies of parents of children with cystic fibrosis (CF) ( Grossoehme et al., 2013 ). Whole books are devoted to qualitative research methodology and, indeed, to the individual methods themselves. This article is intended to present, in rather broad brushstrokes, some of the “methods of choice” and to suggest some issues to consider before embarking on a qualitative research project. Helpful texts are cited to provide resources for more complete information.

Although virtually anything may be data, spoken mediums are the most common forms of collecting data in health research, so the focus of this article will mainly be on interviews and to a lesser extent, focus groups. Interviews explore experiences of individuals, and through a series of questions and answers, the meaning individuals give to their experiences ( Tong, Sainsbury, & Craig, 2007 ). They may be “structured” interviews, in which an interview guide is used with pre-determined questions from which no deviation is permitted by the interviewer, or semi-structured interviews, in which an interview guide is used with pre-determined questions and potential follow-up questions. The latter allows the interviewer to pursue topics that arise during the interview that seem relevant ( Cohen & Crabtree, 2006 ). Writing good questions is harder than it appears! In my first unit of CPE, the supervisor returned verbatims, especially our early efforts, with “DCFQ” written in the margin, for “direct, closed, factual question.” We quickly learned to avoid DCFQs in our clinical conversations because they did not create the space for reflection on illness and the sacred the way open-ended questions did. To some extent, writing good open-ended questions that elicit stories can come more readily to chaplains, due perhaps to our training, than to investigators from other disciplines. This is not to say writing an interview guide is easy or an aspect of research that can be taken lightly, as the quality of the data you collect, and hence the quality of your study, depends on the quality of your interview questions.

Data may also be collected using focus groups. Focus groups are normally built around a specific topic. They almost always follow a semi-structured format and include open discussion of responses among participants, which may range from four to twelve people ( Tong et al., 2007 ). They provide an excellent means to gather data on an entire range of responses to a topic, or on the social interactions between participants, or to clarify a process. Once the data are collected, the analytic approach is typically similar to that of interview data.

Qualitative investigators are not disinterested outsiders who merely observe without interacting with participants, but affect and are affected by their data. The investigator's emotions as they read participants' narratives are data to be included in the study. Simply asking “research” questions can itself be a chaplaincy intervention: what we ask affects the other person and can lead them to reflect and change ( Grossoehme, 2011 ). It is important to articulate our biases and understand how they influence us when we collect and analyze data. Qualitative research is often done by a small group of researchers, especially the data coding. This minimizes the bias of an individual investigator. Inevitably, two or more people will code passages differently at times. It is important to establish at the outset how such discrepancies will be handled.

Ensuring Rigor, Validity, and Reliability

Some people do not think qualitative research is not very robust or significant. This attitude is due, in part, to the poor quality of some early efforts. Increasingly, however, qualitative studies have improved in rigor, and reviewers of qualitative manuscripts expect investigators to have addressed problematic issues from the start of the project. Two important areas are validity and reliability. Validity refers to whether or not the final product (usually referred to a “model”) truly portrays what it claims to portray. If you think of a scale on which you weigh yourself, you want a valid reading so that you know your correct weight. Reliability refers to the extent to which the results are repeatable; if someone else repeated this study, would they obtain the same result? To continue the scale analogy, a reliable scale gives the same weight every time I step on it. A scale can be reliable without being valid. The scale could reliably read 72 pounds every time I step on it, but that value is hardly correct, so the measure is not valid.

Swinton and Mowat (2006) discussed ensuring the “trustworthiness” of the data. N narrative data which are “rich” in their use of metaphor and description, and which express deeper levels of meaning and nuance compared to everyday language are likely to yield a trustworthy final model because the investigators have done a credible job of completely describing and understanding the topic that is under study. Validity is also enhanced by some methodologies, such as grounded theory, which use participants' own words to name categories and themes, instead of using labels given by the investigator. The concept of “member checking” also enhances validity. Once the analyses are complete and a final model has been developed, these findings are shown to all or some of the participants (the members) who are invited to check the findings and give feedback. Do they see themselves in the words or conceptual model that is presented? Do they offer participants a new insight, or do they nod agreement without really reengaging the findings?

Reliability

One means of demonstrating reliability is to document the research decisions made along the way, as they were made, perhaps in a research diary ( Swinton & Mowat, 2006 ). Qualitative methodologies accept that the investigator is part of what is being studied and will influence it, and that this does not devalue a study but, in fact, enhances it. Simply deciding what questions to ask or not ask, and who you ask them to (and not) reflect certain decisions that should be consciously made and documented. Another researcher should be able to understand what was done and why from reading the research diary.

ETHNOGRAPHIC RESEARCH

Elisa Sobo (2009) defines ethnography as the presentation of, “… a given group's conceptual world, seen and experienced from the inside” (p. 297). Ethnography answers the question, “what's it like to be this person?” One example of this kind of study comes from the work of Fore and colleagues ( Fore, Goldenhar, Margolis, & Seid, 2013 ). In order to design tools that would enable clinicians and persons with pediatric inflammatory bowel disease (IDB) to work together more efficiently, an ethnographic study was undertaken to learn what it was like for a family when a child had IDB. After 36 interviews, the study team was able to create three parent-child dyad personas: archetypes of parents and children with IDB based directly on the data they gathered. These personas were used by the design team to think about how different types of parents and children adapted to the disease and to think what tools should be developed to help different types of parents and children with IDB. An ethnographic study is the method of choice when the goal is to understand a culture, and to present, or explain, its spoken and unspoken nature to people who are not part of the culture, as in the example above of IDB. Before “outsiders” could think about the needs of people with IDB, it was necessary to learn what it is like to live with this disease.

Determining the sample in ethnographic studies typically means using what is called a purposive sample ( Newfield, Sells, Smith, Newfield, & Newfield, 1996 ). Purposive samples are based on criteria that the investigator establishes at the outset, which describe participant characteristics. In the aforementioned IDB example, the criteria were: (1) being a person with IDB who was between 12 and 22 years old or the parent of such a child; (2) being or having a child whose IDB care was provided at one of a particular group of treatment centers; (3) being a pediatric gastrointestinal nurse at one of the centers; or (4) a physician/researcher at one of five treatment centers. Having a sample that is representative of the larger population, always the goal in quantitative research, is not the point in ethnographic studies. Here, the goal is to recruit participants who have the experience to respond to the questions. Out of their intimate knowledge of their culture, the investigator can build a theory, or conceptual model, which could later be tested for generalizability in an entire population.

Ethnographic study designs typically involve a combination of data collection methods. Whenever possible, observing the participants in the midst of whatever experience is the study's focus is desirable. In the process of an ethnographic project on CF, for instance, two students spent a twelve-hour period at the home of a family with a child who had CF, taking notes about what they saw and heard. Interviews with participants are frequently employed to learn more about the experience of interest. An example of this is the work of Sobo and colleagues, who interviewed parents of pediatric patients in a clinic to ask about the barriers they experienced obtaining health care for their child ( Seid, Sobo, Gelhard, & Varni, 2004 ). Diaries and journals detailing people's lived experience may also be used, alone, or in combination with other methods.

Analysis of ethnographic data is variable, depending on the study's goal. One common analytic approach is to begin analysis after the first few interviews have been completed, and to read them to get a sense of their content. The next step is to name the seemingly important words or phrases. At this point, one might begin to see how the names relate to each other; this is the beginning of theory development. This process continues until all the data are collected. At that point, the data are sorted by the names, with data from multiple participants clustered under each topic name ( Boyle, 1994 ). Similar names may be grouped together, or placed under a larger label name (i.e., category). In a sense, what happens is that each interviewer's voice is broken into individual fragments, and everyone's fragments that have the same name are put together. From individual voices speaking on multiple topics, there is now one topic with multiple voices speaking to it.

GROUNDED THEORY RESEARCH

Grounded theory is “grounded” in its data; this inductive approach collects data while simultaneously analyzing it and using the emerging theory to inform data collection ( Rafuls & Moon, 1996 ). This cycle continues until the categories are said to be “saturated,” which typically means the point when no new information is being learned ( Morse, 1995 ). This methodology is generally credited to Glaser and Strauss, who wanted to create a means of developing theoretical models from empirical data ( Charmaz, 2005 ). Perhaps, more than in any other qualitative methodology, the person of the investigator is the key. The extent to which the investigator notices subtle nuances in the data and responds to them with new questions for future participants, or revises an emerging theory, is the extent to which a grounded theory research truly presents a theory capturing the fullness of the data from which it was built. It is also the extent to which the theory is capable of being used to guide future research or alter clinical practice. Grounded theory is the method of choice when there is no existing hypothesis to test. For instance, there was no published data on how parents use faith to cope after their child's diagnosis with CF. Using grounded theory allowed us to develop a theory, or a conceptual model, of how parents used faith to cope ( Grossoehme, Ragsdale, Wooldridge, Cotton, & Seid, 2010 ). An excellent discussion of this method is provided by Charmaz (2006) .

The nature of the research question should dictate the sample description, which should be defined before beginning the data collection. In some cases, the incidence of the phenomena may set some limits on the sample. For example, a study of religious coping by adults who were diagnosed with CF after age 18 years began with a low incidence: this question immediately limited the number of eligible adults in a four-state area to approximately 25 ( Grossoehme et al., 2012 ). Knowing that between 12 and 20 participants might be required in order to have sufficient data to convince ourselves that our categories were indeed saturated, limiting our sample in other ways: for example, selecting representative individuals spread across the number of years since diagnosis would not have made sense. In some studies, the goal is to learn what makes a particular subset of a larger sample special; these subsets are known as “positive deviants” ( Bradley et al., 2009 ).

Once the sample is defined and data collection begins, the analytic process begins shortly thereafter. As will be described in the following paragraphs, interviews and other forms of spoken communication are nearly always transcribed, typically verbatim. Unlike most other qualitative methods, grounded theory uses an iterative design. Sometime around the third or fourth interview has been completed and transcribed and before proceeding with further interviews, it is time to begin analyzing the transcripts. There are two aspects to this. The first is to code the data that you have. Grounded theory prefers to use the participants' own words as the code, rather than having the investigator name it. For example, in the following transcript excerpt, we coded part of the following except:

• INTERVIEWER: OK. Have your beliefs or perhaps relationship with God changed at all because of what you've gone through the last nine and 10 months with N.?
• INTERVIEWEE: Yeah, I mean, I feel that I'm stronger than I was before actually.
• INTERVIEWER: Hmm-hmm. How so? Can you put that into words? I know some of these could be hard to talk about but …
• INTERVIEWEE: I don't know, I feel like I'm putting his life more in God's hands than I ever was before.

We labeled, or coded, these data as, “I'm putting his life more in God's hands,” whereas in a different methodology we might have simply named it “Trusting God.” Focus on the action in the narrative. Although it can be difficult, you as a researcher must try very hard to set your own ideas aside. Remember you are doing this because there is no pre-existing theory about what you are studying, so you should not be guided by a theory you have in your mind. You must let the data speak for themselves.

The second point is to reflect on the codes and what they are already telling you. What questions are eliciting the narrative data you want? Which ones are not? Questions that are not leading you to the data you want probably need to be changed. Interesting, novel ideas may emerge from the data, or topics that you want to know more about that you did not anticipate and so the interviewer did not' follow up on them. What are the data not telling you that you are seeking? All of this information flows back to revising the semi-structured interview guide ( Charmaz, 2006 ). This issue raised mild concern with the IRB reviewer who had not encountered this methodology before. This concern was overcome by showing that this is an accepted method with voluminous literature behind it, and by showing that the types of item revisions were not expected to significantly alter the study's effect on the participants. From this point onward you collect data, code it, and analyze it simultaneously. As you code a new transcript and come across a statement similar to others, you can begin to put them together. If you are using qualitative analysis software such as NVivo ( “NVivo qualitative data analysis software,” 2012 ), you can make these new codes “children” of a “parent” node (the first statement you encountered on this topic). The next step is called “focused coding” and in this phase you combine what seems to you to be the most significant codes ( Charmaz, 2006 ). These may also be the most frequently occurring, or the topic with the most duplicates, but not necessarily. This is not a quantitative approach in which having large amounts of data is important. You combine codes at this stage in such a way that your new, larger, categories begin to give shape to aspects of the theory you think is going to emerge. As you collect and code more data, and revise your categories, your idea of the theory will change.

Axial coding follows, as you look at your emerging themes or categories, and begin to associate coded data that explains that category. Axial coding refers to coding the words or quotations that are around the category's “axis,” or core. For example, in a study of parental faith and coping in the first year after their child's diagnosis with CF ( Grossoehme et al., 2010 ), one of the categories which emerged was, “Our beliefs have changed.” There were five axial codes which explain aspects of this category. The axial codes were, “Unchanged,” “We've learned how fragile life is,” “Our faith has been strengthened,” “We've gotten away from our parents' viewpoints,” and “I'm better in tune with who I am.” Each of these axial codes had multiple explanatory phrases or sentences under them; together they explain the breadth and dimensions of the category, “Our beliefs have changed.”

The next step is theoretical coding, and here the categories generated during focused coding are synthesized into a theory. Some grounded theorists, notably one of the two most associated with it (Glaser), do not use axial coding but proceed directly to this step as the means of creating coherence out of the data ( Charmaz, 2006 ). As your emerging theory crystallizes, you may pause to see if it has similarities with other theoretical constructs you encountered in your literature search. Does your emerging theory remind you of anything? It would be appropriate to engage in member-checking at this point. In this phase, you show your theoretical model and its supporting categories to participants and ask for their feedback. Does your model make sense to them? Does it help them see this aspect of their experience differently ( Charmaz, 2005 ). Use their feedback to revise your theory and put it in its final form. At this point, you have generated new knowledge: a theory no one has put forth previously, and one that is ready to be tested.

PHENOMENOLOGY RESEARCH

Perhaps the most chaplain-friendly qualitative research approach is phenomenology, because it is all about the search for meaning. Its roots are in the philosophical work of Husserl, Heidegger and Ricoeur ( Boss, Dahl, & Kaplan, 1996 ; Swinton & Mowat, 2006 ). This approach is based on several assumptions: (1) meaning and knowing are social constructions, always incomplete and developing; (2) the investigator is a part of the experience being studied and the investigator's values play a role in the investigation; (3) bias is inherent in all research and should be articulated at the beginning; (4) participants and investigators share knowledge and are partners; (5) common forms of expression (e.g., words or art) are important; and (6) meanings may not be shared by everyone (Boss et al.). John Swinton and Harriet Mowat (2006) described the process of carrying out a phenomenological study of depression and spirituality in adults and reading their book is an excellent way to gain a sense of the whole process. Phenomenology may be the method of choice when you want to study what an experience means to a particular group of people. May not be the best choice when you want to be able to generalize your findings. An accurate presentation of the experience under study is more important in this approach than the ability to claim that the findings apply to across situations or people (Boss et al.). A study of the devil among predominately Hispanic horse track workers is unlikely to be generalizable to experiences of the devil among persons of Scandinavian descent living in Minnesota. Care must be taken not to overstate the findings from a study and extend the conclusions beyond what the data support.

The emphasis on accurately portraying the phenomenon means that large numbers of participants are not required. In fact, relatively small sample sizes are required compared to most quantitative, clinical studies. The goal is to gather descriptions of their lived experience which are rich in detail and imagery, as well as reflection on its theological or psychological meaning. The likelihood of achieving this goal can be enhanced by using a purposeful sample. That is, decide in the beginning approximately how large and how diverse your sample needs to be. For example, CF can be caused by over 1,000 different genetic mutations; some cause more pulmonary symptoms while others cause more gastrointestinal problems. Some people with CF have diabetes and others do not; some have a functioning pancreas and others need to take replacement enzymes before eating or drinking anything other than water. Some CF adolescents may have lung function that is over 100% of what is expected for healthy adolescents of their age and gender, whereas others, with severe pulmonary disease, may have lung function that is just 30% of what is expected for their age and gender. A study of what it is like for an adolescent to live with a life-shortening genetic disease using this approach might benefit from purposive sampling. For example, lung disease severity in CF is broadly described as mild, moderate or severe. A purposeful sample might call for 18 participants divided into 3 age groups (11–13 years; 14–16 years; and 17–19 years old) and disease severity (mild, moderate, and severe). In each of those nine groups there would be one male and one female. In actual practice, one might want to have more than 18 to allow for attrition, but this breakdown gives the basic idea of defining a purposive sample. One could reasonably expect that having the experience of both genders across the spectrum of disease severity and the developmental range of adolescence would permit an accurate, multi-dimensional understanding to emerge of what living with this life-shortening disease means to adolescents. In fact, such an accurate description is more likely to emerge with this purposeful sample of 18 adolescents than with a convenience sample of the first 18 adolescents who might agree to participate in the study during their outpatient clinic appointment. Defining the sample to be studied requires some forethought about what is likely to be needed to gain the fullest understanding of the topic.

Any research design may be used. The design will be dictated by what data are required to understand the phenomena and its meaning. Interviews are by far the most common means of gathering data, although one might also use written texts, such as prayers written in open prayer books in hospital chapels, for example ( ap Sion, 2013 ; Grossoehme, 1996 ), or drawings ( Pendleton, Cavalli, Pargament, & Nasr, 2002 ), or photographs/videos ( Olausson, Ekebergh, & Lindahl, 2012 ). Although the word “text” appears, it should be with the understanding that any form of data is implied.

The theoretical underpinnings of phenomenology, which are beyond the scope of this article, suggest to users that “a method” is unnecessary or indeed, contrary, to phenomenology. However, one phenomenological researcher did articulate a method ( Giorgi, 1985 ), which consists of the following steps. First, the research team immerses themselves in the data. They do this by reading and re-reading the transcribed interviews and listening to the recorded interviews so that they can hear the tone and timbre of the voices. The goal at this stage is to get a sense of the whole. Second, the texts are coded, in which the words, phrases or sentences that stand out as describing the experience or phenomena under study, or which express outright its meaning for the participant are extracted or highlighted. Each coded bit of data is sometimes referred to as a “meaning unit.” Third, similar meaning units are placed into categories. Fourth, for each meaning unit the meaning of the participants' own words is spelled out. For chaplains, this may mean articulating what the experience means in theological language. Other disciplines might transform the participants' words into psychological, sociological or anthropological language. Here the investigators infer the meaning behind the participants' words and articulate it. Finally, each of the transformed statements of meaning are combined into a few thematic statements that describe the experience ( Bassett, 2004 ; Boss et al., 1996 ). After this, it would be appropriate to do member-checking and a subsequent revision of the final model based on participants' responses and feedback.

PRACTICAL CONCERNS

Just as questionnaires or blood samples contain data, in qualitative research it is the recording of people's words, whether in an audio, video, or paper format which hold the data. Interviews, either in-person or by telephone should be recorded using audio, video or both. It is important to have a device with suitable audio quality and fresh batteries. Experience has shown me the benefit of using two audio recorders so that you do not lose data if one of them fails. There are several small recorders available that have USB connections that allow the audio file to be uploaded to a computer easily. To protect participants' privacy, all data should be anonymized by removing any information that could identify individuals. The Standard Operating Procedure in my research group is to replace all participants' names with an “ N .” During the transcription process, all other individuals are identified by their role in square brackets, “[parent].” Depending on the study's goal and the analytic method you have selected, you may want to include symbols for pauses before participants respond, or non-fluencies (e.g., “ummm. …”, “well … uh …”) or non-verbal gestures (if you are video recording). Decide before beginning whether it is important to capture these as data or not. There are conventional symbols which are inserted into transcriptions which capture these data for you. After the initial transcription, these need to be verified by comparing the written copy against the original recording. Verification should be done by someone other than the transcriptionist. There are several tasks at this stage. Depending on the quality of your recording, the clarity of participants' speech and other factors, some words or phrases may have been unintelligible to the transcriptionist, and this is the time to address them. In my research group our Standard Operating Procedure is to highlight unintelligible text during the transcription phase, and a “verifier” attempts three times to clarify the words on the original recording before leaving them marked “unintelligible” in the transcript. No transcriptionist is perfect and if they are unfamiliar with the topic, they may transcribe the recording inaccurately. I recently verified a transcript where a commercial medical transcriptionist changed the participant's gender from “he” to “she” when the word prior to the pronoun ended with an “s.” If this pattern had not been caught during the verification process, it would have been very difficult during the coding to know whether the pronoun referred to the participant or to their daughter.

ETHICAL ISSUES IN QUALITATIVE RESEARCH

Study design.

The issue of power and the possibility of subtle coercion is the concern here. There is an inherent power differential between a research participant and the investigator, which is exacerbated when the investigator is a chaplain. Despite our attempts to be non-threatening, the very words, "chaplain," or "clergy" connote power. For this reason, the chaplain-investigator should not approach potential participants regarding a study. Potential participants may be informed regarding their eligibility to participate by their physician or a chaplain, but the recruitment and informed consent process should be handled by someone else, perhaps a clinical research coordinator. However, as the chaplain-investigator, you will need to teach them how to talk with potential participants about your study and answer their questions. Choose a data collection method that is best-suited to the level of sensitivity of your research topic. Focus groups can provide data with multiple perspectives, and they are a poor choice when there may be pressure to provide socially correct responses, or when disclosures may be stigmatizing. In such cases, it is better to collect data using individual semi-structured interviews.

Develop a plan for assessing participants' discomfort, anxiety, or even more severe reactions during the study. For instance, what will you do when someone discloses his/her current thoughts of self-harm, or experiences a flashback to a prior traumatic event that was triggered during an interview? How will you handle this if you are collecting data in person? By telephone? You will need to be specific who must be informed and who will make decisions about responding to the risk.

Privacy and Confidentiality

In addition to maintaining privacy and confidentiality of your actual data and other study documents, consider how you will protect participants' privacy when you write the study up for publication. Make sure that people cannot be identified by their quotations that you include as you publish data. The smaller the population you are working with, the more diligently you need to work on this. If the transcriptionist is not an employee of your institution and under the same privacy and confidentiality policies, it is up to you to ensure that an external transcriptionist takes steps to protect and maintain the privacy of participants' data.

Qualitative research is an accessible way for chaplains to contribute new knowledge regarding the sacred dimension of people's lived experience. Chaplains are already sensitive to and familiar with many aspects of qualitative research methodologies. Studies need to be designed to be valid and meaningful, and are best done collaboratively. They provide an excellent opportunity to develop working relationships with physicians, medical anthropologists, nurses, psychologists, and sociologists, all of whom have rich traditions of qualitative research. This article can only provide an overview of some of the issues related to qualitative research and some of its methods. The texts cited, as well as others, provide additional information needed before designing and carrying out a qualitative study. Qualitative research is a tool that chaplains can use to develop new knowledge and contribute to professional chaplaincy's ability to facilitate the healing of brokenness and disease.

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