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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.

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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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

Qualitative research is a type of research methodology that focuses on exploring and understanding people’s beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.

Qualitative research aims to uncover the meaning and significance of social phenomena, and it typically involves a more flexible and iterative approach to data collection and analysis compared to quantitative research. Qualitative research is often used in fields such as sociology, anthropology, psychology, and education.

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

This method involves conducting an interview with a single participant to gain a detailed understanding of their experiences, attitudes, and beliefs. One-to-one interviews can be conducted in-person, over the phone, or through video conferencing. The interviewer typically uses open-ended questions to encourage the participant to share their thoughts and feelings. One-to-one interviews are useful for gaining detailed insights into individual experiences.

Focus Groups

This method involves bringing together a group of people to discuss a specific topic in a structured setting. The focus group is led by a moderator who guides the discussion and encourages participants to share their thoughts and opinions. Focus groups are useful for generating ideas and insights, exploring social norms and attitudes, and understanding group dynamics.

Ethnographic Studies

This method involves immersing oneself in a culture or community to gain a deep understanding of its norms, beliefs, and practices. Ethnographic studies typically involve long-term fieldwork and observation, as well as interviews and document analysis. Ethnographic studies are useful for understanding the cultural context of social phenomena and for gaining a holistic understanding of complex social processes.

Text Analysis

This method involves analyzing written or spoken language to identify patterns and themes. Text analysis can be quantitative or qualitative. Qualitative text analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Text analysis is useful for understanding media messages, public discourse, and cultural trends.

This method involves an in-depth examination of a single person, group, or event to gain an understanding of complex phenomena. Case studies typically involve a combination of data collection methods, such as interviews, observations, and document analysis, to provide a comprehensive understanding of the case. Case studies are useful for exploring unique or rare cases, and for generating hypotheses for further research.

Process of Observation

This method involves systematically observing and recording behaviors and interactions in natural settings. The observer may take notes, use audio or video recordings, or use other methods to document what they see. Process of observation is useful for understanding social interactions, cultural practices, and the context in which behaviors occur.

Record Keeping

This method involves keeping detailed records of observations, interviews, and other data collected during the research process. Record keeping is essential for ensuring the accuracy and reliability of the data, and for providing a basis for analysis and interpretation.

This method involves collecting data from a large sample of participants through a structured questionnaire. Surveys can be conducted in person, over the phone, through mail, or online. Surveys are useful for collecting data on attitudes, beliefs, and behaviors, and for identifying patterns and trends in a population.

Qualitative data analysis is a process of turning unstructured data into meaningful insights. It involves extracting and organizing information from sources like interviews, focus groups, and surveys. The goal is to understand people’s attitudes, behaviors, and motivations

Qualitative Research Analysis Methods

Qualitative Research analysis methods involve a systematic approach to interpreting and making sense of the data collected in qualitative research. Here are some common qualitative data analysis methods:

Thematic Analysis

This method involves identifying patterns or themes in the data that are relevant to the research question. The researcher reviews the data, identifies keywords or phrases, and groups them into categories or themes. Thematic analysis is useful for identifying patterns across multiple data sources and for generating new insights into the research topic.

Content Analysis

This method involves analyzing the content of written or spoken language to identify key themes or concepts. Content analysis can be quantitative or qualitative. Qualitative content analysis involves close reading and interpretation of texts to identify recurring themes, concepts, and patterns. Content analysis is useful for identifying patterns in media messages, public discourse, and cultural trends.

Discourse Analysis

This method involves analyzing language to understand how it constructs meaning and shapes social interactions. Discourse analysis can involve a variety of methods, such as conversation analysis, critical discourse analysis, and narrative analysis. Discourse analysis is useful for understanding how language shapes social interactions, cultural norms, and power relationships.

Grounded Theory Analysis

This method involves developing a theory or explanation based on the data collected. Grounded theory analysis starts with the data and uses an iterative process of coding and analysis to identify patterns and themes in the data. The theory or explanation that emerges is grounded in the data, rather than preconceived hypotheses. Grounded theory analysis is useful for understanding complex social phenomena and for generating new theoretical insights.

Narrative Analysis

This method involves analyzing the stories or narratives that participants share to gain insights into their experiences, attitudes, and beliefs. Narrative analysis can involve a variety of methods, such as structural analysis, thematic analysis, and discourse analysis. Narrative analysis is useful for understanding how individuals construct their identities, make sense of their experiences, and communicate their values and beliefs.

Phenomenological Analysis

This method involves analyzing how individuals make sense of their experiences and the meanings they attach to them. Phenomenological analysis typically involves in-depth interviews with participants to explore their experiences in detail. Phenomenological analysis is useful for understanding subjective experiences and for developing a rich understanding of human consciousness.

Comparative Analysis

This method involves comparing and contrasting data across different cases or groups to identify similarities and differences. Comparative analysis can be used to identify patterns or themes that are common across multiple cases, as well as to identify unique or distinctive features of individual cases. Comparative analysis is useful for understanding how social phenomena vary across different contexts and groups.

Applications of Qualitative Research

Qualitative research has many applications across different fields and industries. Here are some examples of how qualitative research is used:

• Market Research: Qualitative research is often used in market research to understand consumer attitudes, behaviors, and preferences. Researchers conduct focus groups and one-on-one interviews with consumers to gather insights into their experiences and perceptions of products and services.
• Health Care: Qualitative research is used in health care to explore patient experiences and perspectives on health and illness. Researchers conduct in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education: Qualitative research is used in education to understand student experiences and to develop effective teaching strategies. Researchers conduct classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work : Qualitative research is used in social work to explore social problems and to develop interventions to address them. Researchers conduct in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : Qualitative research is used in anthropology to understand different cultures and societies. Researchers conduct ethnographic studies and observe and interview members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : Qualitative research is used in psychology to understand human behavior and mental processes. Researchers conduct in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy : Qualitative research is used in public policy to explore public attitudes and to inform policy decisions. Researchers conduct focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

• Identify your research question: Qualitative research starts with a research question or set of questions that you want to explore. This question should be focused and specific, but also broad enough to allow for exploration and discovery.
• Select your research design: There are different types of qualitative research designs, including ethnography, case study, grounded theory, and phenomenology. You should select a design that aligns with your research question and that will allow you to gather the data you need to answer your research question.
• Recruit participants: Once you have your research question and design, you need to recruit participants. The number of participants you need will depend on your research design and the scope of your research. You can recruit participants through advertisements, social media, or through personal networks.
• Collect data: There are different methods for collecting qualitative data, including interviews, focus groups, observation, and document analysis. You should select the method or methods that align with your research design and that will allow you to gather the data you need to answer your research question.
• Analyze data: Once you have collected your data, you need to analyze it. This involves reviewing your data, identifying patterns and themes, and developing codes to organize your data. You can use different software programs to help you analyze your data, or you can do it manually.
• Interpret data: Once you have analyzed your data, you need to interpret it. This involves making sense of the patterns and themes you have identified, and developing insights and conclusions that answer your research question. You should be guided by your research question and use your data to support your conclusions.
• Communicate results: Once you have interpreted your data, you need to communicate your results. This can be done through academic papers, presentations, or reports. You should be clear and concise in your communication, and use examples and quotes from your data to support your findings.

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

• Customer Feedback: A company may conduct qualitative research to understand the feedback and experiences of its customers. This may involve conducting focus groups or one-on-one interviews with customers to gather insights into their attitudes, behaviors, and preferences.
• Healthcare : A healthcare provider may conduct qualitative research to explore patient experiences and perspectives on health and illness. This may involve conducting in-depth interviews with patients and their families to gather information on their experiences with different health care providers and treatments.
• Education : An educational institution may conduct qualitative research to understand student experiences and to develop effective teaching strategies. This may involve conducting classroom observations and interviews with students and teachers to gather insights into classroom dynamics and instructional practices.
• Social Work: A social worker may conduct qualitative research to explore social problems and to develop interventions to address them. This may involve conducting in-depth interviews with individuals and families to understand their experiences with poverty, discrimination, and other social problems.
• Anthropology : An anthropologist may conduct qualitative research to understand different cultures and societies. This may involve conducting ethnographic studies and observing and interviewing members of different cultural groups to gain insights into their beliefs, practices, and social structures.
• Psychology : A psychologist may conduct qualitative research to understand human behavior and mental processes. This may involve conducting in-depth interviews with individuals to explore their thoughts, feelings, and experiences.
• Public Policy: A government agency or non-profit organization may conduct qualitative research to explore public attitudes and to inform policy decisions. This may involve conducting focus groups and one-on-one interviews with members of the public to gather insights into their perspectives on different policy issues.

Purpose of Qualitative Research

The purpose of qualitative research is to explore and understand the subjective experiences, behaviors, and perspectives of individuals or groups in a particular context. Unlike quantitative research, which focuses on numerical data and statistical analysis, qualitative research aims to provide in-depth, descriptive information that can help researchers develop insights and theories about complex social phenomena.

Qualitative research can serve multiple purposes, including:

• Exploring new or emerging phenomena : Qualitative research can be useful for exploring new or emerging phenomena, such as new technologies or social trends. This type of research can help researchers develop a deeper understanding of these phenomena and identify potential areas for further study.
• Understanding complex social phenomena : Qualitative research can be useful for exploring complex social phenomena, such as cultural beliefs, social norms, or political processes. This type of research can help researchers develop a more nuanced understanding of these phenomena and identify factors that may influence them.
• Generating new theories or hypotheses: Qualitative research can be useful for generating new theories or hypotheses about social phenomena. By gathering rich, detailed data about individuals’ experiences and perspectives, researchers can develop insights that may challenge existing theories or lead to new lines of inquiry.
• Providing context for quantitative data: Qualitative research can be useful for providing context for quantitative data. By gathering qualitative data alongside quantitative data, researchers can develop a more complete understanding of complex social phenomena and identify potential explanations for quantitative findings.

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

• Exploring a new area: If little is known about a particular topic, qualitative research can help to identify key issues, generate hypotheses, and develop new theories.
• Understanding complex phenomena: Qualitative research can be used to investigate complex social, cultural, or organizational phenomena that are difficult to measure quantitatively.
• Investigating subjective experiences: Qualitative research is particularly useful for investigating the subjective experiences of individuals or groups, such as their attitudes, beliefs, values, or emotions.
• Conducting formative research: Qualitative research can be used in the early stages of a research project to develop research questions, identify potential research participants, and refine research methods.
• Evaluating interventions or programs: Qualitative research can be used to evaluate the effectiveness of interventions or programs by collecting data on participants’ experiences, attitudes, and behaviors.

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

• Focus on subjective experience: Qualitative research is concerned with understanding the subjective experiences, beliefs, and perspectives of individuals or groups in a particular context. Researchers aim to explore the meanings that people attach to their experiences and to understand the social and cultural factors that shape these meanings.
• Use of open-ended questions: Qualitative research relies on open-ended questions that allow participants to provide detailed, in-depth responses. Researchers seek to elicit rich, descriptive data that can provide insights into participants’ experiences and perspectives.
• Sampling-based on purpose and diversity: Qualitative research often involves purposive sampling, in which participants are selected based on specific criteria related to the research question. Researchers may also seek to include participants with diverse experiences and perspectives to capture a range of viewpoints.
• Data collection through multiple methods: Qualitative research typically involves the use of multiple data collection methods, such as in-depth interviews, focus groups, and observation. This allows researchers to gather rich, detailed data from multiple sources, which can provide a more complete picture of participants’ experiences and perspectives.
• Inductive data analysis: Qualitative research relies on inductive data analysis, in which researchers develop theories and insights based on the data rather than testing pre-existing hypotheses. Researchers use coding and thematic analysis to identify patterns and themes in the data and to develop theories and explanations based on these patterns.
• Emphasis on researcher reflexivity: Qualitative research recognizes the importance of the researcher’s role in shaping the research process and outcomes. Researchers are encouraged to reflect on their own biases and assumptions and to be transparent about their role in the research process.

Advantages of Qualitative Research

Qualitative research offers several advantages over other research methods, including:

• Depth and detail: Qualitative research allows researchers to gather rich, detailed data that provides a deeper understanding of complex social phenomena. Through in-depth interviews, focus groups, and observation, researchers can gather detailed information about participants’ experiences and perspectives that may be missed by other research methods.
• Flexibility : Qualitative research is a flexible approach that allows researchers to adapt their methods to the research question and context. Researchers can adjust their research methods in real-time to gather more information or explore unexpected findings.
• Contextual understanding: Qualitative research is well-suited to exploring the social and cultural context in which individuals or groups are situated. Researchers can gather information about cultural norms, social structures, and historical events that may influence participants’ experiences and perspectives.
• Participant perspective : Qualitative research prioritizes the perspective of participants, allowing researchers to explore subjective experiences and understand the meanings that participants attach to their experiences.
• Theory development: Qualitative research can contribute to the development of new theories and insights about complex social phenomena. By gathering rich, detailed data and using inductive data analysis, researchers can develop new theories and explanations that may challenge existing understandings.
• Validity : Qualitative research can offer high validity by using multiple data collection methods, purposive and diverse sampling, and researcher reflexivity. This can help ensure that findings are credible and trustworthy.

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

• Subjectivity : Qualitative research relies on the subjective interpretation of researchers, which can introduce bias into the research process. The researcher’s perspective, beliefs, and experiences can influence the way data is collected, analyzed, and interpreted.
• Limited generalizability: Qualitative research typically involves small, purposive samples that may not be representative of larger populations. This limits the generalizability of findings to other contexts or populations.
• Time-consuming: Qualitative research can be a time-consuming process, requiring significant resources for data collection, analysis, and interpretation.
• Resource-intensive: Qualitative research may require more resources than other research methods, including specialized training for researchers, specialized software for data analysis, and transcription services.
• Limited reliability: Qualitative research may be less reliable than quantitative research, as it relies on the subjective interpretation of researchers. This can make it difficult to replicate findings or compare results across different studies.
• Ethics and confidentiality: Qualitative research involves collecting sensitive information from participants, which raises ethical concerns about confidentiality and informed consent. Researchers must take care to protect the privacy and confidentiality of participants and obtain informed consent.

Also see Research Methods

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Qualitative Research Methods

Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

• Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
• Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
• Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
• Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
• Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
• Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
• Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
• Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
• Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
• And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
• We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
• Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
• Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
• Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

Educational resources and simple solutions for your research journey

What is Qualitative Research? Methods, Types, Approaches and Examples

Qualitative research is a type of method that researchers use depending on their study requirements. Research can be conducted using several methods, but before starting the process, researchers should understand the different methods available to decide the best one for their study type. The type of research method needed depends on a few important criteria, such as the research question, study type, time, costs, data availability, and availability of respondents. The two main types of methods are qualitative research and quantitative research. Sometimes, researchers may find it difficult to decide which type of method is most suitable for their study. Keeping in mind a simple rule of thumb could help you make the correct decision. Quantitative research should be used to validate or test a theory or hypothesis and qualitative research should be used to understand a subject or event or identify reasons for observed patterns.  

Qualitative research methods are based on principles of social sciences from several disciplines like psychology, sociology, and anthropology. In this method, researchers try to understand the feelings and motivation of their respondents, which would have prompted them to select or give a particular response to a question. Here are two qualitative research examples :  

• Two brands (A & B) of the same medicine are available at a pharmacy. However, Brand A is more popular and has higher sales. In qualitative research , the interviewers would ideally visit a few stores in different areas and ask customers their reason for selecting either brand. Respondents may have different reasons that motivate them to select one brand over the other, such as brand loyalty, cost, feedback from friends, doctor’s suggestion, etc. Once the reasons are known, companies could then address challenges in that specific area to increase their product’s sales.  
• A company organizes a focus group meeting with a random sample of its product’s consumers to understand their opinion on a new product being launched.  

Table of Contents

What is qualitative research? 1

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data. The findings of qualitative research are expressed in words and help in understanding individuals’ subjective perceptions about an event, condition, or subject. This type of research is exploratory and is used to generate hypotheses or theories from data. Qualitative data are usually in the form of text, videos, photographs, and audio recordings. There are multiple qualitative research types , which will be discussed later.  

Qualitative research methods 2

Researchers can choose from several qualitative research methods depending on the study type, research question, the researcher’s role, data to be collected, etc.  

The following table lists the common qualitative research approaches with their purpose and examples, although there may be an overlap between some.  

Types of qualitative research 3,4

The data collection methods in qualitative research are designed to assess and understand the perceptions, motivations, and feelings of the respondents about the subject being studied. The different qualitative research types include the following:  

• In-depth or one-on-one interviews : This is one of the most common qualitative research methods and helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event. These interviews are usually conversational and encourage the respondents to express their opinions freely. Semi-structured interviews, which have open-ended questions (where the respondents can answer more than just “yes” or “no”), are commonly used. Such interviews can be either face-to-face or telephonic, and the duration can vary depending on the subject or the interviewer. Asking the right questions is essential in this method so that the interview can be led in the suitable direction. Face-to-face interviews also help interviewers observe the respondents’ body language, which could help in confirming whether the responses match.  
• Document study/Literature review/Record keeping : Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.  
• Focus groups : Usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic. Focus groups ensure constructive discussions to understand the why, what, and, how about the topic. These group meetings need not always be in-person. In recent times, online meetings are also encouraged, and online surveys could also be administered with the option to “write” subjective answers as well. However, this method is expensive and is mostly used for new products and ideas.  
• Qualitative observation : In this method, researchers collect data using their five senses—sight, smell, touch, taste, and hearing. This method doesn’t include any measurements but only the subjective observation. For example, “The dessert served at the bakery was creamy with sweet buttercream frosting”; this observation is based on the taste perception.  

Qualitative research : Data collection and analysis

• Qualitative data collection is the process by which observations or measurements are gathered in research.  
• The data collected are usually non-numeric and subjective and could be recorded in various methods, for instance, in case of one-to-one interviews, the responses may be recorded using handwritten notes, and audio and video recordings, depending on the interviewer and the setting or duration.  
• Once the data are collected, they should be transcribed into meaningful or useful interpretations. An experienced researcher could take about 8-10 hours to transcribe an interview’s recordings. All such notes and recordings should be maintained properly for later reference.  
• Some interviewers make use of “field notes.” These are not exactly the respondents’ answers but rather some observations the interviewer may have made while asking questions and may include non-verbal cues or any information about the setting or the environment. These notes are usually informal and help verify respondents’ answers.  

2. Qualitative data analysis 

• This process involves analyzing all the data obtained from the qualitative research methods in the form of text (notes), audio-video recordings, and pictures.  
• Text analysis is a common form of qualitative data analysis in which researchers examine the social lives of the participants and analyze their words, actions, etc. in specific contexts. Social media platforms are now playing an important role in this method with researchers analyzing all information shared online.   

There are usually five steps in the qualitative data analysis process: 5

• Prepare and organize the data  
• Transcribe interviews  
• Collect and document field notes and other material  
• Review and explore the data  
• Examine the data for patterns or important observations  
• Develop a data coding system  
• Create codes to categorize and connect the data  
• Assign these codes to the data or responses  
• Review the codes  
• Identify recurring themes, opinions, patterns, etc.  
• Present the findings  
• Use the best possible method to present your observations  

The following table 6 lists some common qualitative data analysis methods used by companies to make important decisions, with examples and when to use each. The methods may be similar and can overlap.  

Characteristics of qualitative research methods 4

• Unstructured raw data : Qualitative research methods use unstructured, non-numerical data , which are analyzed to generate subjective conclusions about specific subjects, usually presented descriptively, instead of using statistical data.  
• Site-specific data collection : In qualitative research methods , data are collected at specific areas where the respondents or researchers are either facing a challenge or have a need to explore. The process is conducted in a real-world setting and participants do not need to leave their original geographical setting to be able to participate.  
• Researchers’ importance : Researchers play an instrumental role because, in qualitative research , communication with respondents is an essential part of data collection and analysis. In addition, researchers need to rely on their own observation and listening skills during an interaction and use and interpret that data appropriately.  
• Multiple methods : Researchers collect data through various methods, as listed earlier, instead of relying on a single source. Although there may be some overlap between the qualitative research methods , each method has its own significance.  
• Solving complex issues : These methods help in breaking down complex problems into more useful and interpretable inferences, which can be easily understood by everyone.  
• Unbiased responses : Qualitative research methods rely on open communication where the participants are allowed to freely express their views. In such cases, the participants trust the interviewer, resulting in unbiased and truthful responses.  
• Flexible : The qualitative research method can be changed at any stage of the research. The data analysis is not confined to being done at the end of the research but can be done in tandem with data collection. Consequently, based on preliminary analysis and new ideas, researchers have the liberty to change the method to suit their objective.  

When to use qualitative research   4

The following points will give you an idea about when to use qualitative research .  

• When the objective of a research study is to understand behaviors and patterns of respondents, then qualitative research is the most suitable method because it gives a clear insight into the reasons for the occurrence of an event.  
• A few use cases for qualitative research methods include:  
• New product development or idea generation  
• Strengthening a product’s marketing strategy  
• Conducting a SWOT analysis of product or services portfolios to help take important strategic decisions  
• Understanding purchasing behavior of consumers  
• Understanding reactions of target market to ad campaigns  
• Understanding market demographics and conducting competitor analysis  
• Understanding the effectiveness of a new treatment method in a particular section of society  

A qualitative research method case study to understand when to use qualitative research 7

Context : A high school in the US underwent a turnaround or conservatorship process and consequently experienced a below average teacher retention rate. Researchers conducted qualitative research to understand teachers’ experiences and perceptions of how the turnaround may have influenced the teachers’ morale and how this, in turn, would have affected teachers’ retention.  

Method : Purposive sampling was used to select eight teachers who were employed with the school before the conservatorship process and who were subsequently retained. One-on-one semi-structured interviews were conducted with these teachers. The questions addressed teachers’ perspectives of morale and their views on the conservatorship process.  

Results : The study generated six factors that may have been influencing teachers’ perspectives: powerlessness, excessive visitations, loss of confidence, ineffective instructional practices, stress and burnout, and ineffective professional development opportunities. Based on these factors, four recommendations were made to increase teacher retention by boosting their morale.  

Advantages of qualitative research 1

• Reflects real-world settings , and therefore allows for ambiguities in data, as well as the flexibility to change the method based on new developments.  
• Helps in understanding the feelings or beliefs of the respondents rather than relying only on quantitative data.  
• Uses a descriptive and narrative style of presentation, which may be easier to understand for people from all backgrounds.  
• Some topics involving sensitive or controversial content could be difficult to quantify and so qualitative research helps in analyzing such content.  
• The availability of multiple data sources and research methods helps give a holistic picture.  
• There’s more involvement of participants, which gives them an assurance that their opinion matters, possibly leading to unbiased responses.   

Disadvantages of qualitative research 1

• Large-scale data sets cannot be included because of time and cost constraints.  
• Ensuring validity and reliability may be a challenge because of the subjective nature of the data, so drawing definite conclusions could be difficult.  
• Replication by other researchers may be difficult for the same contexts or situations.  
• Generalization to a wider context or to other populations or settings is not possible.  
• Data collection and analysis may be time consuming.  
• Researcher’s interpretation may alter the results causing an unintended bias.  

Differences between qualitative research and quantitative research 1

Frequently asked questions on qualitative research  

Q: how do i know if qualitative research is appropriate for my study  .

A: Here’s a simple checklist you could use:  

• Not much is known about the subject being studied.  
• There is a need to understand or simplify a complex problem or situation.  
• Participants’ experiences/beliefs/feelings are required for analysis.  
• There’s no existing hypothesis to begin with, rather a theory would need to be created after analysis.  
• You need to gather in-depth understanding of an event or subject, which may not need to be supported by numeric data.  

Q: How do I ensure the reliability and validity of my qualitative research findings?  

A: To ensure the validity of your qualitative research findings you should explicitly state your objective and describe clearly why you have interpreted the data in a particular way. Another method could be to connect your data in different ways or from different perspectives to see if you reach a similar, unbiased conclusion.   

To ensure reliability, always create an audit trail of your qualitative research by describing your steps and reasons for every interpretation, so that if required, another researcher could trace your steps to corroborate your (or their own) findings. In addition, always look for patterns or consistencies in the data collected through different methods.  

Q: Are there any sampling strategies or techniques for qualitative research ?   

A: Yes, the following are few common sampling strategies used in qualitative research :  

1. Convenience sampling  

Selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.  

2. Purposive sampling  

Participants are grouped according to predefined criteria based on a specific research question. Sample sizes are often determined based on theoretical saturation (when new data no longer provide additional insights).  

3. Snowball sampling  

Already selected participants use their social networks to refer the researcher to other potential participants.  

4. Quota sampling  

While designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.  

Q: What ethical standards need to be followed with qualitative research ?  

A: The following ethical standards should be considered in qualitative research:  

• Anonymity : The participants should never be identified in the study and researchers should ensure that no identifying information is mentioned even indirectly.  
• Confidentiality : To protect participants’ confidentiality, ensure that all related documents, transcripts, notes are stored safely.  
• Informed consent : Researchers should clearly communicate the objective of the study and how the participants’ responses will be used prior to engaging with the participants.  

Q: How do I address bias in my qualitative research ?  

  A: You could use the following points to ensure an unbiased approach to your qualitative research :  

• Check your interpretations of the findings with others’ interpretations to identify consistencies.  
• If possible, you could ask your participants if your interpretations convey their beliefs to a significant extent.  
• Data triangulation is a way of using multiple data sources to see if all methods consistently support your interpretations.  
• Contemplate other possible explanations for your findings or interpretations and try ruling them out if possible.  
• Conduct a peer review of your findings to identify any gaps that may not have been visible to you.  
• Frame context-appropriate questions to ensure there is no researcher or participant bias.

We hope this article has given you answers to the question “ what is qualitative research ” and given you an in-depth understanding of the various aspects of qualitative research , including the definition, types, and approaches, when to use this method, and advantages and disadvantages, so that the next time you undertake a study you would know which type of research design to adopt.  

References:  

• McLeod, S. A. Qualitative vs. quantitative research. Simply Psychology [Accessed January 17, 2023]. www.simplypsychology.org/qualitative-quantitative.html    
• Omniconvert website [Accessed January 18, 2023]. https://www.omniconvert.com/blog/qualitative-research-definition-methodology-limitation-examples/  
• Busetto L., Wick W., Gumbinger C. How to use and assess qualitative research methods. Neurological Research and Practice [Accessed January 19, 2023] https://neurolrespract.biomedcentral.com/articles/10.1186/s42466-020-00059  
• QuestionPro website. Qualitative research methods: Types & examples [Accessed January 16, 2023]. https://www.questionpro.com/blog/qualitative-research-methods/  
• Campuslabs website. How to analyze qualitative data [Accessed January 18, 2023]. https://baselinesupport.campuslabs.com/hc/en-us/articles/204305675-How-to-analyze-qualitative-data  
• Thematic website. Qualitative data analysis: Step-by-guide [Accessed January 20, 2023]. https://getthematic.com/insights/qualitative-data-analysis/  
• Lane L. J., Jones D., Penny G. R. Qualitative case study of teachers’ morale in a turnaround school. Research in Higher Education Journal . https://files.eric.ed.gov/fulltext/EJ1233111.pdf  
• Meetingsnet website. 7 FAQs about qualitative research and CME [Accessed January 21, 2023]. https://www.meetingsnet.com/cme-design/7-faqs-about-qualitative-research-and-cme     
• Qualitative research methods: A data collector’s field guide. Khoury College of Computer Sciences. Northeastern University. https://course.ccs.neu.edu/is4800sp12/resources/qualmethods.pdf  

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Research Paper Appendix: Format and Examples

The qualitative research process, end-to-end

.css-1nrevy2{position:relative;display:inline-block;} The qualitative research process: step by step guide

Although research processes may vary by methodology or project team, some fundamentals exist across research projects. Below outlines the collective experience that qualitative researchers undertake to conduct research.

Step 1: Determine what to research

Once a researcher has determined a list of potential projects to tackle, they will prioritize projects based on the business's impact, available resourcing, timelines & dependencies to create a research roadmap. For each project, they will also identify the key questions they need to answer in the research.

The researcher should identify the participants they plan to research, and any key attributes that are a 'must-have' or 'nice to have' as these can be influential in determining the research approach (e.g. a niche group may require a longer timeline to recruit).

Researchers will generally aim for a mix of project types. Some may be more tactical or requests from stakeholders, and some will be projects that the researcher has proactively identified as opportunities for strategic research.

Step 2: Identify how to research it

Once the researcher has finalized the research project, they will need to figure out how they will do the work.

Firstly, the researcher will look through secondary data and research (e.g. analytics, previous research reports). Secondary analysis will help determine if there are existing answers to any of the open questions, ensuring that any net-new study doesn't duplicate current work (unless previous research is out of date).

After scoping the research, researchers will determine if the research input needs to be  attitudinal  (i.e. what someone says) or  behavioral  (i.e. what someone does); as well as if they need to  explore  a problem space or  evaluate  a product – these help determine the methodology to use. There are many methodologies out there, but the main ones you generally will find from a qualitative perspective are:

Interviews [Attitudinal / Exploratory]  – semi-structured conversation with a participant focused on a small set of topics. Runs for 30-60 minutes.

Contextual Inquiry [Behavioral / Exploratory]  – observation of a participant in their environment. Probing questions may be asked during the observation. Runs for 2-3 hours.

Survey [Attitudinal / Evaluative]  – gathering structured information from a sample of people, traditionally to generalize the results to a larger population. Surveys should generally not take participants more than 10 minutes to complete.

Usability Test [Behavioral / Evaluative]  – evaluating how representative users are, or are not, able to achieve critical tasks within an experience.

Check out these articles for more information about different methodologies:

When to Use Which User-Experience Research Methods

UX Research Cheat Sheet

Usability.gov

Design Research Kit

Step 3: Get buy-in and alignment from others

Once a researcher has determined what they will be researching and how they will research it, they will generally write up a research plan that includes additional information about the research goals, participant scope, timelines, and dependencies. The plan is typically either a document or presentation shared with stakeholders depending on the company and how they work.

After the research plan is complete, researchers will share the plan for feedback and input from their stakeholders to ensure that the stakeholders have the right expectations going into the research. Stakeholders may ask for additional question topics to be added, ensure that research will be executed against specific timelines, or provide recommendations on how the study will help make product decisions.

At organizations where there is a research team, researchers may also share their plan with other researchers informally or through a 'crit' process. Generally, researchers will provide feedback on the research craft, such as methodologies, participant mixes, and the research goals or questions.

Once the researcher feels confident in their plan, they will either begin to plan the research, or in the case of more junior researchers, get approval from their manager to begin the study.

Step 4: Prepare research

This step is where the researcher will get all of their ducks in a row to execute the research. Preparation activities include:

Equipment: Booking venues, labs, observation rooms, and procuring any appropriate equipment needed to run the study (e.g. cameras, mobile devices).

Participants: Sourcing participants from internal / external databases, reaching out/scheduling participants, managing schedule changes.

Incentives: Find budget, identify incentive type (e.g. Amazon gift card? customer credit? gift baskets), and purchasing.

Assets: Building relevant designs / prototypes (with design or design technologists), creating interview / observation guides and other research tools needed for sessions (e.g. physical cards for in-person card sorts).

Legal & Procurement: Participant waivers or NDAs preparation to ensure they are sent in advance of the research session to participants, vendor procurement, and management.

If Research Operations exists within an organization, they will generally take on most of the load in this area. The researcher will focus on assets required for executing research, such as interview guides.

In some cases, vendors may be engaged for some of these requirements (e.g. labs, participants, and incentive management) if resourcing is not available internally or if a researcher wants a blinded study (i.e. the participant doesn't know what company is running the research). In this case, additional time is incorporated to brief, onboard, and get approvals to work with the vendor.

Step 5: Execute research

Now the researcher gets to research!

Researchers will generally aim to execute research activities for 1–2 weeks, depending on the methodology to ensure they can be efficient in execution. In some more longitudinal methods (e.g., diary studies), or if a participant type is harder to recruit, it may take longer.

In consumer research, there will usually be back up participants available in case of no shows. However, in business or enterprise research, researchers will engage will all recruited participants as participants will generally have relationships with other parts of the company (e.g. sales). It is essential to maintain those relationships post-research.

During sessions, in a perfect world, there is one facilitator (principal researcher). In some cases, a secondary attendee who takes notes – this can be a stakeholder or a more junior researcher who can then learn soft skills from the primary researcher. By delegating note-taking, the principal researcher can focus on driving and managing the participant's conversation.

However, in most cases (especially if there is a "research team of one"), researchers will try to have to do both facilitation and documentation – this can lead to a clunkier conversation as the facilitator attempts to quickly write notes between trying to think of the next question. If a researcher decides to record a session instead, they will have to spend additional time after the research listening to the full recordings and writing notes.

In qualitative research, researchers may begin to  see patterns in the findings after five sessions . They may start to tailor the research questions to be more specific to gaps in their understanding.

Researchers may also set up an observation room for stakeholders (or share links to remote sessions) to attend live. Generally, researchers will have a backchannel (e.g., slack, chat, or SMS), so if a stakeholder has a follow-up question to an answer, the researcher can dig deeper. In some cases, researchers will give stakeholders an input form to take their notes that can be shared with the researcher afterward - this can be useful for the researcher to understand how the stakeholder views the research and what the stakeholder perceives as necessary to the research insights.

Step 6: Synthesize and find insights

Once the research capture is complete, the researcher will then aggregate findings to begin to look for common themes (in exploratory) or success rates (in evaluative). Both of these will then lead to insight generation that researchers will then look to tie back to the project's original research goals.

As analysis can be one of the most high-effort tasks in research, researchers will lean towards how to be efficient in their study, generally using digital tools, hacks, or workarounds. Researchers will usually create the analysis process they refine throughout their careers to help them become more efficient.

In cases where researchers are looking to get buy-in for research or capture stakeholder input, they may seem to more visual approaches (e.g. post-it affinity analysis) in war rooms. This process can take longer to process (especially if there is a high volume of data). Still, there can be a higher impact on analyzing research in this way – especially if the researcher is looking to get buy-in for future projects.

Step 7: Create research outputs

After a researcher identifies the key themes and insights, the researcher will reframe these findings to a relevant research output to ensure that stakeholders understand and buy-in to the outcomes. Outputs may include:

Report: Outlines vital findings from research in a document or presentation format. Will most likely include an executive summary, insight themes, and supporting evidence.

Videos: A highlight reel of supporting evidence from crucial findings. Generally seen as more useful and engaging compared to just a report. In most cases, the video will help the research report.

Personas : A written representation of a product's intended users to understand different types of user goals, needs, and behaviors. Also used to help stakeholders build empathy for the end-user of the product.

Journey Map : A visualization of the process that a person goes through to accomplish a goal. Generally created in conjunction with a persona.

Concepts / Wireframes / Designs: If research is evaluative, designs can visualize recommendations.

Storyboarding

Before a researcher makes the output, researchers will spend time planning the structure and storyboarding. Storyboarding is incredibly essential to help researchers define information requirements and ensure they present their findings in the most impactful way to stakeholders.

Having a point of view in outputs

Historically, researchers have tried to stay neutral to the data and not try to have a strong opinion or perspective to let the data speak. However, as researchers become more embedded in the industry, this has shifted to stakeholders wanting a strong point of view or recommendations from researchers that can help other stakeholders (especially product managers and designers) decide the knowledge captured as part of the research.

Having a strong perspective helps researchers have a seat at the table and appear as a trusted advisor/partner in cross-functional settings.

Step 8: Share and follow up on findings

After the research outputs are complete, some researchers will do a "pre-share" or walkthrough with key stakeholders or potential detractors to the research. The purpose of these meetings is to align with stakeholders' expectations and find potential 'watch-outs' (things that may derail a presentation).

Researchers will generally have to share their findings out multiple times to different stakeholder groups and tailor them for each audience. For example, executive meetings will be more higher level than a meeting with a product manager.

After sharing, researchers will follow up with key stakeholders (especially those who provided input to the research) to confirm they understand the findings and identify next steps. Next steps may include incorporating results in product strategy documents, proposals / PRDs, or user stories to ensure that the recommendations or findings have been reflected or sourced.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.

Qualitative research involves collecting and analysing 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 analysing 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, and history.

• 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 organisation?
• 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, 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 emphasise different aims and perspectives.

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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 analysing 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 organise 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 categorise 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 analysing qualitative data. Although these methods share similar processes, they emphasise 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.

Researchers must consider practical and theoretical limitations in analysing 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 analysing 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 generalisability

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

• Labour-intensive

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

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

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 organisation 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 organisations.

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

• Prepare and organise 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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Qualitative vs Quantitative Research Methods & Data Analysis

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The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

• Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

On This Page:

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography .

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis .

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Mixed methods research
• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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How to Do Qualitative Research

Last Updated: October 26, 2022 Fact Checked

This article was co-authored by Jeremiah Kaplan . Jeremiah Kaplan is a Research and Training Specialist at the Center for Applied Behavioral Health Policy at Arizona State University. He has extensive knowledge and experience in motivational interviewing. In addition, Jeremiah has worked in the mental health, youth engagement, and trauma-informed care fields. Using his expertise, Jeremiah supervises Arizona State University’s Motivational Interviewing Coding Lab. Jeremiah has also been internationally selected to participate in the Motivational Interviewing International Network of Trainers sponsored Train the Trainer event. Jeremiah holds a BS in Human Services with a concentration in Family and Children from The University of Phoenix. There are 10 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 751,258 times.

Qualitative research is a broad field of inquiry that uses unstructured data collections methods, such as observations, interviews, surveys and documents, to find themes and meanings to inform our understanding of the world. [1] X Trustworthy Source PubMed Central Journal archive from the U.S. National Institutes of Health Go to source Qualitative research tends to try to cover the reasons for behaviors, attitudes and motivations, instead of just the details of what, where and when. Qualitative research can be done across many disciplines, such as social sciences, healthcare and businesses, and it is a common feature of nearly every single workplace and educational environment.

Preparing Your Research

• The research questions is one of the most important pieces of your research design. It determines what you want to learn or understand and also helps to focus the study, since you can't investigate everything at once. Your research question will also shape how you conduct your study since different questions require different methods of inquiry.
• You should start with a burning question and then narrow it down more to make it manageable enough to be researched effectively. For example, "what is the meaning of teachers' work to teachers" is too broad for a single research endeavor, but if that's what you're interested you could narrow it by limiting the type of teacher or focusing on one level of education. For example, "what is the meaning of teachers' work to second career teachers?" or "what is the meaning of teachers' work to junior high teachers?"

Tip: Find the balance between a burning question and a researchable question. The former is something you really want to know about and is often quite broad. The latter is one that can be directly investigated using available research methods and tools.

• For example, if your research question focuses on how second career teachers attribute meaning to their work, you would want to examine the literature on second career teaching - what motivates people to turn to teaching as a second career? How many teachers are in their second career? Where do most second career teachers work? Doing this reading and review of existing literature and research will help you refine your question and give you the base you need for your own research. It will also give you a sense of the variables that might impact your research (e.g., age, gender, class, etc.) and that you will need to take into consideration in your own study.
• A literature review will also help you to determine whether you are really interested and committed to the topic and research question and that there is a gap in the existing research that you want to fill by conducting your own investigation.

For example, if your research question is "what is the meaning of teachers' work to second career teachers?" , that is not a question that can be answered with a 'yes' or 'no'. Nor is there likely to be a single overarching answer. This means that qualitative research is the best route.

• Consider the possible outcomes. Because qualitative methodologies are generally quite broad, there is almost always the possibility that some useful data will come out of the research. This is different than in a quantitative experiment, where an unproven hypothesis can mean that a lot of time has been wasted.
• Your research budget and available financial resources should also be considered. Qualitative research is often cheaper and easier to plan and execute. For example, it is usually easier and cost-saving to gather a small number of people for interviews than it is to purchase a computer program that can do statistical analysis and hire the appropriate statisticians.

• Action Research – Action research focuses on solving an immediate problem or working with others to solve problem and address particular issues. [7] X Research source
• Ethnography – Ethnography is the study of human interaction in communities through direct participation and observation within the community you wish to study. Ethnographic research comes from the discipline of social and cultural anthropology but is now becoming more widely used. [8] X Research source
• Phenomenology – Phenomenology is the study of the subjective experiences of others. It researches the world through the eyes of another person by discovering how they interpret their experiences. [9] X Research source
• Grounded Theory – The purpose of grounded theory is to develop theory based on the data systematically collected and analyzed. It looks at specific information and derives theories and reasons for the phenomena.
• Case Study Research – This method of qualitative study is an in-depth study of a specific individual or phenomena in its existing context. [10] X Research source

Collecting and Analyzing Your Data

• Direct observation – Direct observation of a situation or your research subjects can occur through video tape playback or through live observation. In direct observation, you are making specific observations of a situation without influencing or participating in any way. [12] X Research source For example, perhaps you want to see how second career teachers go about their routines in and outside the classrooms and so you decide to observe them for a few days, being sure to get the requisite permission from the school, students and the teacher and taking careful notes along the way.
• Participant observation – Participant observation is the immersion of the researcher in the community or situation being studied. This form of data collection tends to be more time consuming, as you need to participate fully in the community in order to know whether your observations are valid. [13] X Research source
• Interviews – Qualitative interviewing is basically the process of gathering data by asking people questions. Interviewing can be very flexible - they can be on-on-one, but can also take place over the phone or Internet or in small groups called "focus groups". There are also different types of interviews. Structured interviews use pre-set questions, whereas unstructured interviews are more free-flowing conversations where the interviewer can probe and explore topics as they come up. Interviews are particularly useful if you want to know how people feel or react to something. For example, it would be very useful to sit down with second career teachers in either a structured or unstructured interview to gain information about how they represent and discuss their teaching careers.
• Surveys – Written questionnaires and open ended surveys about ideas, perceptions, and thoughts are other ways by which you can collect data for your qualitative research. For example, in your study of second career schoolteachers, perhaps you decide to do an anonymous survey of 100 teachers in the area because you're concerned that they may be less forthright in an interview situation than in a survey where their identity was anonymous.
• "Document analysis" – This involves examining written, visual, and audio documents that exist without any involvement of or instigation by the researcher. There are lots of different kinds of documents, including "official" documents produced by institutions and personal documents, like letters, memoirs, diaries and, in the 21st century, social media accounts and online blogs. For example, if studying education, institutions like public schools produce many different kinds of documents, including reports, flyers, handbooks, websites, curricula, etc. Maybe you can also see if any second career teachers have an online meet group or blog. Document analysis can often be useful to use in conjunction with another method, like interviewing.

• Coding – In coding, you assign a word, phrase, or number to each category. Start out with a pre-set list of codes that you derived from your prior knowledge of the subject. For example, "financial issues" or "community involvement" might be two codes you think of after having done your literature review of second career teachers. You then go through all of your data in a systematic way and "code" ideas, concepts and themes as they fit categories. You will also develop another set of codes that emerge from reading and analyzing the data. For example, you may see while coding your interviews, that "divorce" comes up frequently. You can add a code for this. Coding helps you organize your data and identify patterns and commonalities. [15] X Research source tobaccoeval.ucdavis.edu/analysis-reporting/.../CodingQualitativeData.pdf
• Descriptive Statistics – You can analyze your data using statistics. Descriptive statistics help describe, show or summarize the data to highlight patterns. For example, if you had 100 principal evaluations of teachers, you might be interested in the overall performance of those students. Descriptive statistics allow you to do that. Keep in mind, however, that descriptive statistics cannot be used to make conclusions and confirm/disprove hypotheses. [16] X Research source
• Narrative analysis – Narrative analysis focuses on speech and content, such as grammar, word usage, metaphors, story themes, meanings of situations, the social, cultural and political context of the narrative. [17] X Research source
• Hermeneutic Analysis – Hermeneutic analysis focuses on the meaning of a written or oral text. Essentially, you are trying to make sense of the object of study and bring to light some sort of underlying coherence. [18] X Research source
• Content analysis / Semiotic analysis – Content or semiotic analysis looks at texts or series of texts and looks for themes and meanings by looking at frequencies of words. Put differently, you try to identify structures and patterned regularities in the verbal or written text and then make inferences on the basis of these regularities. [19] X Research source For example, maybe you find the same words or phrases, like "second chance" or "make a difference," coming up in different interviews with second career teachers and decide to explore what this frequency might signify.

Community Q&A

• Qualitative research is often regarded as a precursor to quantitative research, which is a more logical and data-led approach which statistical, mathematical and/or computational techniques. Qualitative research is often used to generate possible leads and formulate a workable hypothesis that is then tested with quantitative methods. [20] X Research source Thanks Helpful 0 Not Helpful 0
• Try to remember the difference between qualitative and quantitative as each will give different data. Thanks Helpful 4 Not Helpful 0

You Might Also Like

• ↑ https://www.ncbi.nlm.nih.gov/books/NBK470395/
• ↑ https://owl.purdue.edu/owl/research_and_citation/conducting_research/writing_a_literature_review.html
• ↑ https://academic.oup.com/humrep/article/31/3/498/2384737?login=false
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4275140/
• ↑ http://www.qual.auckland.ac.nz/
• ↑ http://www.socialresearchmethods.net/kb/qualapp.php
• ↑ http://www.socialresearchmethods.net/kb/qualdata.php
• ↑ tobaccoeval.ucdavis.edu/analysis-reporting/.../CodingQualitativeData.pdf
• ↑ https://statistics.laerd.com/statistical-guides/descriptive-inferential-statistics.php
• ↑ https://explorable.com/qualitative-research-design

About This Article

To do qualitative research, start by deciding on a clear, specific question that you want to answer. Then, do a literature review to see what other experts are saying about the topic, and evaluate how you will best be able to answer your question. Choose an appropriate qualitative research method, such as action research, ethnology, phenomenology, grounded theory, or case study research. Collect and analyze data according to your chosen method, determine the answer to your question. For tips on performing a literature review and picking a method for collecting data, read on! Did this summary help you? Yes No

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Qualitative Research for Intervention Development and Evaluation:

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Speaker 1: In this video, we're going to dive into the topic of qualitative coding, which you'll need to understand if you plan to undertake qualitative analysis for any dissertation, thesis, or research project. We'll explain what exactly qualitative coding is, the different coding approaches and methods, and how to go about coding your data step by step. So go ahead, grab a cup of coffee, grab a cup of tea, whatever works for you, and let's jump into it. Hey, welcome to Grad Coach TV, where we demystify and simplify the oftentimes intimidating world of academic research. My name's Emma, and today we're going to explore qualitative coding, an essential first step in qualitative analysis. If you'd like to learn more about qualitative analysis or research methodology in general, we've also got videos covering those topics, so be sure to check them out. I'll include the links below. If you're new to Grad Coach TV, hit that subscribe button for more videos covering all things research related. Also, if you're looking for hands-on help with your qualitative coding, check out our one-on-one coaching services, where we hold your hand through the coding process step by step. Alternatively, if you're looking to fast track your coding, we also offer a professional coding service, where our seasoned qualitative experts code your data for you, ensuring high-quality initial coding. If that sounds interesting to you, you can learn more and book a free consultation at gradcoach.com. All right, with that out of the way, let's get into it. To kick things off, let's start by understanding what a code is. At the simplest level, a code is a label that describes a piece of content. For example, in the sentence, pigeons attacked me and stole my sandwich, you could use pigeons as a code. This code would simply describe that the sentence involves pigeons. Of course, there are many ways you could code this, and this is just one approach. We'll explore the different ways in which you can code later in this video. So, qualitative coding is simply the process of creating and assigning codes to categorize data extracts. You'll then use these codes later down the road to derive themes and patterns for your actual qualitative analysis. For example, thematic analysis or content analysis. It's worth It's worth noting that coding and analysis can take place simultaneously. In fact, it's pretty much expected that you'll notice some themes emerge while you code. That said, it's important to note that coding does not necessarily involve identifying themes. Instead, it refers to the process of labeling and grouping similar types of data, which in turn will make generating themes and analyzing the data more manageable. You might be wondering then, why should I bother with coding at all? Why not just look for themes from the outset? Well, coding is a way of making sure your data is valid. In other words, it helps ensure that your analysis is undertaken systematically, and that other researchers can review it. In the world of research, we call this transparency. In other words, coding is the foundation of high quality analysis, which makes it an essential first step. Right, now that we've got a plain language definition of coding on the table, the next step is to understand what types of coding exist. Let's start with the two main approaches, deductive and inductive coding. With deductive coding, you as the researcher begin with a set of pre-established codes and apply them to your data set, for example, a set of interview transcripts. Inductive coding, on the other hand, works in reverse, as you start with a blank canvas and create your set of codes based on the data itself. In other words, the codes emerge from the data. Let's take a closer look at both of these approaches. With deductive coding, you'll make use of predetermined codes, also called a priori codes, which are developed before you interact with the present data. This usually involves drawing up a set of codes based on a research question or previous research from your literature review. You could also use an existing code set from the codebook of a previous study. For example, if you were studying the eating habits of college students, you might have a research question along the lines of, what foods do college students eat the most? As a result of this research question, you might develop a code set that includes codes such as sushi, pizza, and burgers. You'd then code your data set using only these codes, regardless of what you find in the data. On the upside, the deductive approach allows you to undertake your analysis with a very tightly focused lens and quickly identify relevant data, avoiding distractions and detours. The downside, of course, is that you could miss out on some very valuable insights as a result of this tight predetermined focus. Now let's look at the opposite approach, inductive coding. As I mentioned earlier, this type of coding involves jumping right into the data without predetermined codes and developing the codes based on what you find within the data. For example, if you were to analyze a set of open-ended interview question responses, you wouldn't necessarily know which direction the conversation would flow. If a conversation begins with a discussion of cats, it might go on to include other animals too. And so, you'd add these codes as you progress with your analysis. Simply put, with inductive coding, you go with the flow of the data. Inductive coding is great when you're researching something that isn't yet well understood because the coding derived from the data helps you explore the subject. Therefore, this approach to coding is usually adopted when researchers want to investigate new ideas or concepts or when they want to create new theories. So, as you can see, the inductive and deductive approaches represent two ends of a spectrum, but this doesn't mean that they're mutually exclusive. You can also take a hybrid approach where you utilize a mix of both. For example, if you've got a set of codes you've derived from a literature review or a previous study, in other words, a deductive approach, but you still don't have a rich enough code set to capture the depth of your qualitative data, you can combine deductive and inductive approaches, which we call a hybrid approach. To adopt a hybrid approach, you'll begin your analysis with a set of a priori codes, in other words, a deductive approach, and then add new codes, in other words, an inductive approach, as you work your way through the data. Essentially, the hybrid coding approach provides the best of both worlds, which is why it's pretty common to see this in research. All right, now that we've covered what qualitative coding is and the overarching approaches, let's dive into the actual coding process and look at how to undertake the coding. So, let's take a look at the actual coding process step by step. Whether you adopt an inductive or deductive approach, your coding will consist of two stages, initial coding and line-by-line coding. In the initial coding stage, the objective is to get a general overview of the data by reading through and understanding it. If you're using an inductive approach, this is also where you'll develop an initial set of codes. Then in the second stage, line-by-line coding, you'll delve deeper into the data and organize it into a formalized set of codes. Let's take a look at these stages of qualitative coding in more detail. Stage one, initial coding. The first step of the coding process is to identify the essence of the text and code it accordingly. While there are many qualitative analysis software options available, you can just as easily code text-based data using Microsoft Word's comments feature. In fact, if it's your first time coding, it's oftentimes best to just stick with Word as this eliminates the additional need to learn new software. Importantly, you should avoid the temptation of any sort of automated coding software or service. No matter what promises they make, automated software simply cannot compare to human-based coding as it can't understand the subtleties of language and context. Don't waste your time with this. In all likelihood, you'll just end up having to recode everything yourself anyway. Okay, so let's take a look at a practical example of the coding process. Assume you had the following interview data from two interviewees. In the initial stage of coding, you could assign the code of pets or animals. These are just initial fairly broad codes that you can and will develop and refine later. In the initial stage, broad rough codes are fine. They're just a starting point which you will build onto later when you undertake line-by-line coding. So, at this stage, you're probably wondering how to decide what codes to use, especially when there are so many ways to read and interpret any given sentence. Well, there are a few different coding methods you can adopt and the right method will depend on your research aims and research questions. In other words, the way you code will depend on what you're trying to achieve with your research. Five common methods utilized in the initial coding stage include in vivo coding, process coding, descriptive coding, structural coding, and value coding. These are not the only methods available, but they're a useful starting point. Let's take a look at each of them to understand how and when each method could be useful. Method number one, in vivo coding. When you use in vivo coding, you make use of a participant's own words rather than your interpretation of the data. In other words, you use direct quotes from participants as your codes. By doing this, you'll avoid trying to infer meaning by staying as close to the original phrases and words as possible. In vivo coding is particularly useful when your data are derived from participants who speak different languages or come from different cultures. In cases like these, it's often difficult to accurately infer meaning thanks to linguistic and or cultural differences. For example, English speakers typically view the future as in front of them and the past as behind them. However, this isn't the same in all cultures. Speakers of Aymara view the past as in front of them and the future as behind them. Why? Because the future is unknown. It must be out of sight or behind them. They know what happened in the past so their perspective is that it's positioned in front of them where they can see it. In a scenario like this one, it's not possible to derive the reason for viewing the past as in front and the future as behind without knowing the Aymara culture's perception of time. Therefore, in vivo coding is particularly useful as it avoids interpretation errors. While this case is a unique one, it illustrates the point that different languages and cultures can view the same things very differently, which would have major impacts on your data. Method number two, process coding. Next up, there's process coding, which makes use of action-based codes. Action-based codes are codes that indicate a movement or procedure. These actions are often indicated by gerunds, that is words ending in ing. For example, running, jumping, or singing. Process coding is useful as it allows you to code parts of data that aren't necessarily spoken but that are still important to understand the meaning of the text. For example, you may have action codes such as describing a panda, singing a song, or arguing with a relative. Another example would be if a participant were to say something like, I have no idea where she is. A sentence like this could be interpreted in many different ways depending on the context and movements of the participant. The participant could, for example, shrug their shoulders, which would indicate that they genuinely don't know where the girl is. Alternatively, they could wink, suggesting that they do actually know where the girl is. Simply put, process coding is useful as it allows you to, in a concise manner, identify occurrences in a set of data that are not necessarily spoken and to provide a dynamic account of events. Method number three, descriptive coding. Descriptive coding is a popular coding method that aims to summarize extracts by using a single word that encapsulates the general idea of the data. These words will typically describe the data in a highly condensed manner, which allows you as the researcher to quickly refer to the content. For example, a descriptive code could be food, when coding a video clip that involves a group of people discussing what they ate throughout the day, or cooking, when coding an image showing the steps of a recipe. Descriptive coding is very useful when dealing with data that appear in forms other than text. For example, video clips, sound recordings, or images. It's also particularly useful when you want to organize a large data set by topic area. This makes descriptive coding a popular choice for many research projects. Method number four, structural coding. True to its name, structural coding involves labeling and describing specific structural attributes of the data. Generally, it includes coding according to answers of the questions of who, what, where, and how, rather than the actual topics expressed in the data. For example, if you were coding a collection of dissertations, which would be quite a large data set, structural coding might be useful as you could code according to different sections within each of these documents. Coding what centric labels, such as hypotheses, literature review, and methodology, would help you to efficiently refer to sections and navigate without having to work through sections of data all over again. So, structural coding is useful when you want to access segments of data quickly, and it can help tremendously when you're dealing with large data sets. Structural coding can also be useful for data from open-ended survey questions. This data may initially be difficult to code as they lack the set structure of other forms of data, such as an interview with a strict closed set of questions to be answered. In this case, it would be useful to code sections of data that answer certain questions, such as who, what, where, and how. Method number five, values coding. Last but not least, values-based coding involves coding excerpts that relate to the participant's worldviews. Typically, this type of coding focuses on excerpts that provide insight regarding the values, attitudes, and beliefs of the participants. In practical terms, this means you'd be looking for instances where your participants say things like, I feel, I think that, I need, and it's important that, as these sorts of statements often provide insight into their values, attitudes, and beliefs. Values coding is therefore very useful when your research aims and research questions seek to explore cultural values and interpersonal experiences and actions, or when you're looking to learn about the human experience. All right, so we've looked at five popular methods that can be used in the initial coding stage. As I mentioned, this is not a comprehensive list, so if none of these sound relevant to your project, be sure to look up alternative coding methods to find the right fit for your research aims. The five methods we've discussed allow you to arrange your data so that it's easier to navigate during the next stage, line-by-line coding. While these methods can all be used individually, it's important to know that it's possible, and quite often beneficial, to combine them. For example, when conducting initial coding with interview data, you could begin by using structural coding to indicate who speaks when. Then, as a next step, you could apply descriptive coding so that you can navigate to and between conversation topics easily. As with all design choices, the right method or combination of methods depends on your research aims and research questions, so think carefully about what you're trying to achieve with your research. Then, select the method or methods that make sense in light of that. So, to recap, the aim of initial coding is to understand and familiarize yourself with your data, to develop an initial code set, if you're taking an inductive approach, and to take the first shot at coding your data. Once that's done, you can move on to the next stage, line-by-line coding. Let's do it. Line-by-line coding is pretty much exactly what it sounds like, reviewing your data line-by-line, digging deeper, refining your codes, and assigning additional codes to each line. With line-by-line coding, the objective is to pay close attention to your data, to refine and expand upon your coding, especially when it comes to adopting an inductive approach. For example, if you have a discussion of beverages and you previously just coded this as beverages, you could now go deeper and code more specifically, such as coffee, tea, and orange juice. The aim here is to scratch below the surface. This is the time to get detailed and specific so that you can capture as much richness from the data as possible. In the line-by-line coding process, it's useful to code as much data as possible, even if you don't think you're going to use it. As you go through this process, your coding will become more thorough and detailed, and you'll have a much better understanding of your data as a result of this. This will be incredibly valuable in the analysis phase, so don't cut corners here. Take your time to work through your data line-by-line and apply your mind to see how you refine your coding as much as possible. Keep in mind that coding is an iterative process, which means that you'll move back and forth between interviews or documents to apply the codes consistently throughout your data set. Be careful to clearly define each code and update previously coded excerpts if you adjust or update the definition of any code, or if you split any code into narrower codes. Line-by-line coding takes time, so don't rush it. Be patient and work through your data meticulously to ensure you develop a high-quality code set. Stage three, moving from coding to analysis. Once you've completed your initial and line-by-line coding, the next step is to start your actual qualitative analysis. Of course, the coding process itself will get you in analysis mode, and you'll probably already have some insights and ideas as a result of it, so you should always keep notes of your thoughts as you work through the coding process. When it comes to qualitative data analysis, there are many different methods you can use, including content analysis, thematic analysis, and discourse analysis. The analysis method you adopt will depend heavily on your research aims and research questions. We cover qualitative analysis methods on the Grad Coach blog, so we're not going to go down that rabbit hole here, but we'll discuss the important first steps that build the bridge from qualitative coding to qualitative analysis. So, how do you get started with your analysis? Well, each analysis will be different, but it's useful to ask yourself the following more general questions to get the wheels turning. What actions and interactions are shown in the data? What are the aims of these interactions and excerpts? How do participants interpret what is happening, and how do they speak about it? What does their language reveal? What are the assumptions made by the participants? What are the participants doing? Why do I want to learn about this? What am I trying to find out? As with initial coding and line-by-line coding, your qualitative analysis can follow certain steps. The first two steps will typically be code categorization and theme identification. Let's look at these two steps. Code categorization, which is the first step, is simply the process of reviewing everything you've coded and then creating categories that can be used to guide your future analysis. In other words, it's about bundling similar or related codes into categories to help organize your data effectively. Let's look at a practical example. If you were discussing different types of animals, your codes may include dogs, llamas, and lions. In the process of code categorization, you could label, in other words, categorize these three animals as mammals, whereas you could categorize flies, crickets, and beetles as insects. By creating these code categories, you will be making your data more organized, as well as enriching it so that you can see new connections between different groups of codes. Once you've categorized your codes, you can move on to the next step, which is to identify the themes in your data. Let's look at the theme identification step. From the coding and categorization processes, you'll naturally start noticing themes. Therefore, the next logical step is to identify and clearly articulate the themes in your data set. When you determine themes, you'll take what you've learned from the coding and categorization stages and synthesize it to develop themes. This is the part of the analysis process where you'll begin to draw meaning from your data and produce a narrative. The nature of this narrative will, of course, depend on your research aims, your research questions, and the analysis method you've chosen. For example, content analysis or thematic analysis. So, keep these factors front of mind as you scan for themes, as they'll help you stay aligned with the big picture. All right, now that we've covered both the what and the how of qualitative coding, I want to quickly share some general tips and suggestions to help you optimize your coding process. Let's rapid fire. One, before you begin coding, plan out the steps you'll take and the coding approach and method or methods you'll follow to avoid inconsistencies. Two, when adopting a deductive approach, it's best to use a codebook with detailed descriptions of each code right from the start of the coding process. This will ensure that you apply codes consistently based on their descriptions and will help you keep your work organized. Three, whether you adopt an inductive or deductive approach, keep track of the meanings of your codes and remember to revisit these as you go along. Four, while coding, keep your research aims, research questions, coding methods, and analysis method front of mind. This will help you to avoid directional drift, which happens when coding is not kept consistent. Five, if you're working in a research team with multiple coders, make sure that everyone has been trained and clearly understands how codes need to be assigned. If multiple coders are pulling in even slightly different directions, you will end up with a mess that needs to be redone. You don't want that. So keep these five tips in mind and you'll be on the fast track to coding success. And there you have it, qualitative coding in a nutshell. Remember, as with every design choice in your dissertation, thesis, or research project, your research aims and research questions will have a major influence on how you approach the coding. So keep these two elements front of mind every step of the way and make sure your coding approach and methods align well. If you enjoyed the video, hit the like button and leave a comment if you have any questions. Also, be sure to subscribe to the channel for more research-related content. If you need a helping hand with your qualitative coding or any part of your research project, remember to check out our private coaching service where we work with you on a one-on-one basis, chapter by chapter, to help you craft a winning piece of research. If that sounds interesting to you, book a free consultation with a friendly coach at gradcoach.com. As always, I'll include a link below. That's all for this episode of Grad Coach TV. Until next time, good luck.

• Open access
• Published: 26 August 2024

Candidacy 2.0 (CC) – an enhanced theory of access to healthcare for chronic conditions: lessons from a critical interpretive synthesis on access to rheumatoid arthritis care

• Sharon Koehn 1 ,
• C Allyson Jones 2 ,
• Claire Barber 3 ,
• Lisa Jasper 2 ,
• Anh Pham 1 ,
• Cliff Lindeman 4 &
• Neil Drummond 5  

BMC Health Services Research volume  24 , Article number:  986 ( 2024 ) Cite this article

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Metrics details

The Dixon-Woods et al. Candidacy Framework, a valuable tool since its 2006 introduction, has been widely utilized to analyze access to various services in diverse contexts, including healthcare. This social constructionist approach examines micro, meso, and macro influences on access, offering concrete explanations for access challenges rooted in socially patterned influences. This study employed the Candidacy Framework to explore the experiences of individuals living with rheumatoid arthritis (RA) and their formal care providers. The investigation extended to assessing supports and innovations in RA diagnosis and management, particularly in primary care.

This systematic review is a Critical Interpretive Synthesis (CIS) of qualitative and mixed methods literature. The CIS aimed to generate theory from identified constructs across the reviewed literature. The study found alignment between the seven dimensions of the Candidacy Framework and key themes emerging from the data. Notably absent from the framework was an eighth dimension, identified as the “embodied relational self.” This dimension, central to the model, prompted the proposal of a revised framework specific to healthcare for chronic conditions.

The CIS revealed that the eight dimensions, including the embodied relational self, provided a comprehensive understanding of the experiences and perspectives of individuals with RA and their care providers. The proposed Candidacy 2.0 (Chronic Condition (CC)) model demonstrated how integrating approaches like Intersectionality, concordance, and recursivity enhanced the framework when the embodied self was central.

Conclusions

The study concludes that while the original Candidacy Framework serves as a robust foundation, a revised version, Candidacy 2.0 (CC), is warranted for chronic conditions. The addition of the embodied relational self dimension enriches the model, accommodating the complexities of accessing healthcare for chronic conditions.

Trial Registration

This study did not involve a health care intervention on human participants, and as such, trial registration is not applicable. However, our review is registered with the Open Science Framework at https://doi.org/10.17605/OSF.IO/ASX5C .

Peer Review reports

Introduction

Access barriers for people with chronic conditions can result in delays in diagnosis, treatment, and management. These barriers can directly impact a patient’s ability to receive timely and appropriate care and increase healthcare costs [ 1 , 2 ]. Although theoretical frameworks exist to guide health and community care for chronic conditions (e.g., [ 3 ]), the process of attaining a diagnosis and ongoing care for chronic conditions across the micro-to macro continuum is less well understood. The Candidacy Framework is a theoretical model that has the potential to deepen our understanding of the process of gaining access to diverse health and social services needed by people living with chronic conditions. Our study applied the Candidacy Framework to systematically examine the experiences of people living with Rheumatoid Arthritis (RA), a common chronic autoimmune disease, to comprehensively analyze barriers and facilitators in accessing a diagnosis and healthcare services [ 4 ].

Dixon-Woods et al. [ 4 ] developed the framework from an extensive scoping review and a Critical Interpretive Synthesis (CIS) of the literature on access to care by marginalized populations. O’Brien et al. [ 5 ] have since demonstrated that the framework is applicable to a wider population base of people with chronic conditions. We argue, however, that while the Candidacy Framework is an excellent starting point, a more comprehensive theory of access must also incorporate an intersectional lens and a phenomenological understanding of identity and its influences on access.

The Candidacy Framework conceptualizes healthcare access as a dynamic process wherein candidacy for care is constructed between those needing and providing services [ 4 , 6 ]. This multi-level approach includes individual (patient, practitioner), interpersonal, institutional, and infrastructural factors [ 7 ], operationalized as seven distinct yet overlapping dimensions with which individuals are likely to engage in an iterative manner [ 6 , 8 ].

According to Dixon-Woods et al. [ 4 ], and depicted in Fig.  1 , establishing access is a fluid process that entails [ 1 ] identification of the need for care, [ 2 ] finding a way to it, (3&4) presenting a claim for it to service providers who judge its credibility, and [ 5 ] accepting or rejecting resultant offers. The ‘openness’ and compatibility of the system [ 6 ] and local operating conditions [ 7 ] are also salient, reflecting the broader organizational and socio-political or environmental conditions that influence claims to candidacy throughout a process of negotiation [ 7 ]. Application of Candidacy dimensions generates concrete and testable explanations of access challenges, which can reveal socially patterned influences underlying seemingly individual behaviours [ 7 , 9 , 10 ].

Seven dimensions of Candidacy to achieve access to healthcare

The Candidacy Framework has been used to analyze access to a broad range of medical and non-medical services, including those for chronic conditions such as dementia [ 11 ], fibromyalgia [ 12 ], comorbid obesity [ 7 ], diabetes [ 13 , 14 ], coronary heart disease [ 13 ], multiple sclerosis [ 15 ], mental health problems [ 16 , 17 ], osteoarthritis [ 5 ], and asthma and other ‘long-term conditions’ [ 14 ]. Collectively, these works have demonstrated that gaining access to a diagnosis and receiving appropriate ongoing care for chronic conditions, comorbidities and adverse effects of treatment is key to achieving positive health and social outcomes. These studies also underscore the explanatory power of the original Candidacy Framework but have inevitably suggested refinements that are not always acknowledged in subsequent applications of the framework, although some trends are apparent.

Using RA as an exemplar for an augmented Candidacy framework, we discuss the implications of our findings for an interdisciplinary understanding of access to chronic conditions, particularly those that are complex and difficult to diagnose. Drawing upon prior applications of the Candidacy Framework to analyses of primary data and systematic reviews, we propose an expanded version that seeks to capture these additional dimensions: Candidacy 2.0 (Chronic Conditions [CC]).

RA affects approximately 0.5% of the world’s population, and its prevalence is increasing globally [ 18 ]. Prevalence rates are higher in industrialized countries (e.g., Canada: 0.65–0.78%) and among women [ 18 ]. RA affects multiple joints, causing pain, swelling, stiffness, warmth, redness, fatigue, weakness, and loss of range of motion. Rheumatoid nodules may develop under the skin near the affected joints and may cause functional and/or cosmetic concerns. Systematic inflammation associated with RA may affect other organs, including nerves, eyes, skin, lungs, or heart. Symptoms vary from person to person and can come and go, with periods of more active disease commonly referred to as flare-ups. The target of treatment is disease remission; however, treatment is often complex and needs frequent reassessment to achieve this goal [ 19 ]. RA can thus have a significant impact on patients’ quality of life due to pain, stiffness, and swelling, as well as fatigue, reduced mobility, and functional disability, reduced ability to work and premature mortality, yet many gaps in care remain due in part to inconsistencies with current treatment guidelines [ 20 ].

Methodology: critical interpretive synthesis (CIS)

Our study aimed to explore healthcare access experiences of people living with Rheumatoid Arthritis (PlwRA) through the Candidacy Framework [ 4 ]. Despite qualitative studies offering valuable insights into complex issues, they comprise only 1% of research in top-tier rheumatology journals [ 21 ]. To address this gap, we conducted a systematic review using Critical Interpretive Synthesis methodology [ 4 ], focusing on qualitative and mixed-methods literature on RA care access. This approach allowed us to capture in-depth perspectives of both RA patients and their care providers, offering insights that quantitative studies alone might miss. Qualitative methods, such as interviews and focus groups, are uniquely suited to explore the nuanced, contextual aspects of patient experiences [ 22 ]. Our review also examined supports and innovations in RA diagnosis and management, particularly in primary care settings.

A CIS differs from a conventional systematic review by emphasizing the inclusion of diverse study types, beyond randomized controlled trials, to capture a broader range of evidence [ 4 ]. CIS incorporates a more interpretive and reflexive approach, encouraging researchers to critically engage with the context and complexities of the included studies. Unlike traditional systematic reviews that focus on aggregating quantitative data, CIS prioritizes the synthesis of qualitative and quantitative evidence, allowing for a more nuanced understanding of the research topic. Additionally, CIS places a greater emphasis on exploring underlying mechanisms and contextual factors, promoting a deeper and more holistic analysis of the subject matter.

A CIS improves on the meta-ethnographic approach [ 23 , 24 ] typically employed in reviews of qualitative literature (1) by utilizing systematic review search strategies, and (2) by seeking to produce more generalizable theoretical conclusions, rather than a simple synopsis of the literature reviewed [ 4 , 25 ]. This is achieved by an inductive approach to analysis that integrates different theoretical categories to achieve deeper understanding of the topic of interest [ 25 ]. Thus, while the review focuses on the literature on RA access, this informs a more general theory of access to care for multiple chronic conditions.

Search and sampling process

Within a CIS, question formulation, source search and selection, and analysis are dynamic and iterative processes [ 25 ]. The search and sampling process involves selecting a set of guided topics, iteratively identifying ‘probably relevant articles’ through a range of searching strategies that are ‘fit for purpose’, and sampling purposively relative to an emerging theory [ 4 ].

Articles reporting qualitative and mixed method studies were identified from multiple database searches in Medline (OVID) and CINAHL by a health sciences librarian using the terms detailed in Appendix A: Search Terms (see supplementary file 1) and based on our inclusion criteria (Table 1 ). The data bases were searched from their date of inception to search dates ranging from April 12, 2020, to June 13, 2022. Dixon-Woods et al. [ 4 ] advocate for refining database searches in critical interpretive synthesis to ensure relevance to guiding questions. This iterative approach aligns with CIS’s flexible nature, allowing researchers to adapt their strategy as understanding evolves and focus on obtaining the most pertinent literature for theoretical development. Thus, searches were added and refined to better reflect the breadth of articles needed to comprehensively understand all dimensions of access, e.g., to address a paucity of references to allied health professionals.

A total of 1244 articles were identified through database searches (see Fig.  2 ). An additional five articles were identified by experts on our team, after their review of our list of articles to be screened in full. Team members include PlwRA, primary care physicians, and rheumatologists as well as researchers with backgrounds in physiotherapy, social epidemiology, health services research, and medical anthropology. Database-identified references were imported into Covidence [ 26 ] and reviewed by two investigators (AP and SK) until all conflicts in classification (i.e., include or exclude for full-text screening) were resolved. Following Dixon-Woods and colleagues [ 4 ], we prioritized papers based on relevance rather than specific study types or strict methodological standards, aiming to include a wide variety of papers at the conceptual level. While our priority was to review the qualitative literature that focuses on patient experience we chose to include three highly relevant review articles [ 27 , 28 , 29 ] and four quantitative studies [ 30 , 31 , 32 , 33 ] that addressed, to a degree, gaps in understanding in the qualitative record. We set a low inclusion threshold, excluding only fatally flawed papers. The concept of “fatally flawed” as a criterion for excluding articles in a CIS refers to studies with severe methodological deficiencies. These include lacking clear aims, having an inappropriate research design, failing to explain its process clearly, providing insufficient data to support conclusions, or using an inadequate or poorly explained analysis method [ 4 ]. Such flaws significantly undermine a study’s credibility and contribution to the synthesis. In our study, this judgement occurred primarily at the abstract screening stage, although 20 articles were excluded for this reason at the full article screening phase (denoted as ‘wrong study design’ in Fig.  2 ).

Of the 1093 abstracts reviewed, 307 articles were deemed eligible for full-text screening (by SK) of which 10 could not be retrieved. 111 articles were subsequently excluded, as detailed in Fig.  2 . The exclusion process was in fact iterative since nine of the articles excluded were withdrawn during the analysis phase within NVivo, when their lack of fit with our guiding questions and inclusion criteria became apparent. Ultimately, any study deemed unlikely to contribute to our development of a theory that answers the guiding questions was excluded. In accordance with PRISMA guidelines, these articles were subcategorized in the flow chart as wrong population, language, setting, outcomes, etc.). ‘Wrong setting’ refers to contexts outside of the scope of enquiry relevant to a North American context (e.g., a discussion of patient experiences of Traditional Chinese Medicine care for RA in China). ‘Wrong outcomes’ indicates that the study did not specifically report on either the health and health care experiences of people with RA. One article was a protected PDF that did not allow for text selection and coding in NVivo. Since it was a marginally relevant study, we chose to exclude it. Studies with mixed populations were included if patients with RA were part of the study sample. Another 76 articles were demoted to a secondary list because their focus was not on experience. Ultimately, our sample included 110 multidisciplinary articles employing diverse theoretical approaches (see Appendix C in supplementary file 2, a framework summation of methodological features of sampled literature).

Selection flow chart

Through the process of familiarization with the materials and consultation with our advisory panel (five people living with RA across Canada) Footnote 1 and RA experts on our team, we refined our overarching question into the five guiding topics that ultimately determined the selection of articles included in the review (Table 2 ). Our topics were further informed by the Candidacy Framework for understanding access to healthcare services.

Data analysis

The inductive approach of a CIS consists of several phases. The first phase of the analysis is the development of a synthesizing argument through reciprocal translational analysis , which involves the translation of different concepts into each other [ 4 ]. Two studies often discuss the same construct using different terms or use a common term to which each study ascribes a different meaning. Thematically coding all sources of evidence using qualitative data management software, QSR NVivo 12 ® , facilitated this process. SK led the analytic phase but met regularly with the research team’s CIS subcommittee comprised of the remaining authors. Emergent codes and interpretations were discussed with and contextualized by this group and were refined accordingly.

All categories and the nodes within them are listed and described in a codebook (Appendix B, supplementary file 1). The analysis employed both deductive and inductive coding methods. Deductive coding was guided by the Candidacy Framework, which provided a structured lens for examining access to healthcare services. Inductive coding emerged organically from the interview data, allowing new themes and insights to surface. The inductive nodes were ultimately grouped as subnodes of each of the Guiding Topics. Two additional node families—‘healthcare provider roles’ and ‘treatment effects’—were created to accommodate relevant topics that did not fit comfortably within any of the Guiding Topics. Most extracts of pertinent text were coded at multiple nodes, which allows for explorations of associations among them using the Matrix feature of NVivo 12 ® . For example, the Guiding Questions nodes are often coded as well with Candidacy Framework nodes which allows us to discern which dimensions of Candidacy are most salient for each of the Guiding Questions.

Our reciprocal translational analysis generated an aggregative synthesis of the reviewed literature, although it is distinct from most aggregative reviews in that each article is viewed more as a “repository of concepts” than a source of data per se [ 34 ]. We provide both a condensed review of the dominant themes in tabular form as well as a detailed and cited account of these themes in supplementary file 1.

The next phase of CIS analysis— refutational synthesis —involves characterizing and explaining the contradictions between constructs in different studies (e.g., in terms of different study approaches, conceptual assumptions). To facilitate ready access to study details that could explain such discrepancies we created a ‘Methodology’ code category that included the subnodes data collection method , limitations , location of study , sample size , study question or purpose , target population of study , and theory or framework . Using the “framework” feature in NVivo 12 ® , we generated a tabular summary of these details for each study that could be readily checked to potentially explain anomalies in our findings or as a resource for others (supplementary file 2).

The final phase is the lines-of-argument synthesis , which aims to create a comprehensive explanatory proposition suggested by the data [ 4 ]. This final interpretation is grounded in the constructs included in the reviewed materials, and seeks to identify and reconcile the most influential themes that represent the combined data [ 35 ]. This process ensures a robust and well-supported understanding of the phenomenon under study. Coding text at both Candidacy nodes and Guiding Questions subnodes systematically connected the ideas more specific to the RA experience represented by the Guiding Questions to the dimensions of access described by the Candidacy Framework and identified what was missing in this framework.

Results: making sense of access to RA care through a candidacy lens and beyond

The Candidacy Framework offered a relatively inclusive ecological approach that served as a useful starting point for the development of lines of argument that broke down the process of access to RA care into seven dimensions of access. All seven dimensions could be identified in the literature, but some were more thoroughly explored than others, pointing to opportunities for additional inquiry into these areas. Our interpretations were derived from text coded in NVivo 12 ® at different dimensions of Candidacy, many of which were co-coded with the themes emerging as important in association with each of the Guiding Questions (presented as Findings in supplementary document 1).

However, the explanations associated with the different dimensions of Candidacy for limitations to access did not suffice to explain findings that linked the bilateral relationship between illness and identity to access challenges. We recognized the need to augment the Candidacy Framework dimensions with insights from phenomenological and intersectional theories. The following interpretation of the CIS analysis will include a consideration of the intersectional, relational and embodied self to enhance the explanatory power of Candidacy as a theory of access.

Identification of RA

The first step in securing access to care is recognition of the need to seek out medical attention. A common pattern emerged in all studies that focused on initial help seeking whereby symptoms were rationalized in relation to preceding events or current conditions, such as an accident, pregnancy, too much or too little exercise, exposure to heat or cold, consuming certain foods, comorbidities, changes in medication, and so on [ 29 , 36 , 37 , 38 , 39 , 40 ]. At some point, however, these explanations no longer accounted for the persistence or evolution of symptoms, and medical advice was sought [ 40 ]. Alternatively, some explanations of symptoms, such as a curse, were culture-specific and could prompt consultation of non-medical (e.g., religious) practitioners, or remedial actions such as prayer or a change in diet that further delayed consultation [ 29 , 39 , 41 ]. Importantly, family members could be instrumental in either advising recourse to alternative explanations and remedies or persuading the afflicted person to seek medical advice [ 42 , 43 , 44 ].

Regardless, delays in consultation due to failure to recognize the symptoms of RA were attributed in retrospect to a lack of knowledge: “had they known when they developed their symptoms what they knew once they had been diagnosed with RA, they would have consulted much earlier” (43, see also 29). Numerous studies reported that laypeople have little if any knowledge of RA and are unaware that it is a serious degenerative disorder requiring aggressive treatment to prevent irreparable damage [ 29 , 40 , 45 , 46 , 47 , 48 ]. Similarly, failure to recognize the symptoms of foot problems associated with RA, as well as confusion around who to consult or how to access podiatry services resulted in delayed access and potential damage [ 49 , 50 , 51 ]. Ultimately, the evidence pointed to the inadequacy of information available to the public about RA, its expression, and treatment [ 43 , 46 , 48 , 50 , 52 ]. Primary care practitioners who were asked to comment on the viability of campaigns to promote rapid help-seeking behaviour at the onset of RA were nonetheless wary of the impact of a poorly designed campaign on their workload and the possibility that false presentations would “‘clog up’ the referral pathway for genuine cases of RA” [ 53 ].

Navigation to services

Navigation through a Candidacy lens refers to the process of finding appropriate services and physically navigating to them. Navigation challenges were rarely and only superficially addressed in the reviewed literature. Once they had identified the need for medical attention, participants in most studies consulted their primary care physicians, with variable success in securing a referral to a rheumatologist [ 29 , 36 , 54 , 55 ]. Of note were reports of “proactive” patients who had been able to find information on the internet and self-advocate for referrals or shorter wait-times, sometimes through recourse to private care [ 36 , 39 , 55 , 56 , 57 ]. While not explicitly explored in these studies, the ability of some to more effectively navigate the system invokes Bourdieu’s notion of social capital whereby symbolic power is gained by some actors due to their access to higher levels of economic, cultural and symbolic capital (e.g., income, education, familiarity with the healthcare system) in different social spaces [ 58 ]. Navigating to other specialists identified by PlwRA as important to their care, such as podiatrists and psychologists, was just as challenging [ 59 ]. Barriers identified were a lack of information about their roles, the lack of clear pathways to care, and the limited availability of RA-informed specialists [ 51 , 60 ]. Barber et al. [ 61 ] recommended the development of a peer navigation system to expedite information gathering about the disease or the healthcare system.

Appearances and adjudications (the patient-care provider interaction)

Once a PlwRA has successfully navigated to a care provider they need to present their symptoms in a manner that precipitates some kind of offer, such as a referral, screening, or treatment. These ‘appearances’ are often difficult to identify without reference to the adjudications or decisions made by the care provider positioned to make such offers. Adjudications are based in part on the clarity of the claim to care made by the PlwRA, but the provider’s own training and biases also play a role.

Appearances or presentation of RA symptoms

Evidence on appearances of people seeking diagnosis or care from gatekeepers such as primary care physicians underscored the relevance of considerations of social capital and reflected the importance of considering sampling bias. In some studies, participants saw themselves as team members engaged in a bilateral relationship with their physicians in which the PlwRA’s expertise of their own bodies was on a par with the physician’s professional expertise [ 47 , 62 ]. Confident ‘expert’ patients were more likely to access information on the internet and request blood tests for RA and hence secured a diagnosis or referral to a rheumatologist more expediently [ 36 , 55 ]. The confidence needed to assume the role of expert patient sometimes derived from prior familiarity with RA [ 36 ]. Firth et al. [ 51 ] maintained, however, that patient education could also build self-efficacy to develop PlwRAs’ confidence to proactively seek solutions. Given the common expectation that the ‘Expert Patient’ can self-manage their disease, Townsend et al. [ 52 ] suggested that the failure to adequately inform patients about RA is ethically problematic; without adequate knowledge or support, the potential for benefits is limited, whereas the likelihood of harm is increased.

Subsequent to diagnosis, Laires et al. [ 46 ] found that many PlwRA had limited awareness of treatment options and typically had a passive relationship with their physicians characterized by unilateral decision making. PlwRA, healthcare professionals, and decision-makers participating in a focus group identified those with lower SES as being less assertive in their relationships with physicians and therefore less likely to gain a prompt referral [ 45 ]. More passive patients hesitated to raise their concerns about sources of pain or discomfort needing treatment for fear of being ‘a nuisance’ or because they viewed themselves as a ‘coper’ or ‘stoic’ and preferred not to ‘complain’ [ 42 , 50 , 63 , 64 ]. Flurey et al’s [ 63 ] study of British men with RA highlighted the gendered nature of stoicism among them. However, the culturally-mediated and cohort-specific nature of this orientation is also salient [ 65 , 66 ]. Some studies found that past experiences of sexist or racist treatment by healthcare providers influenced the presentation and healthcare preferences of PlwRA [ 64 , 67 ]. To address such constraints, studies recommended that healthcare providers afford their patients sufficient time to express themselves, pay attention to patient context and increase patients’ health literacy [ 68 , 69 ].

Adjudications

Access to RA care may be influenced by the biases of primary care providers, or patients’ anticipation of such biases based on prior experience. Some biases were widely shared by providers and patients alike. For example, several studies found that primary care providers were less likely to suspect RA, an inflammatory arthritis, as a possible diagnosis among younger patients because ‘arthritis’ is perceived as a normal part of aging and is not associated with the young; this view also prevented them from taking a proactive approach to the symptoms of RA in older patients [ 45 , 54 , 55 ]. The scarcity of or distant location from specialists and other resources also inhibited some primary care practitioners from referring patients to them [ 45 , 70 , 71 ]. Patients who were overweight or consumed excessive alcohol delayed medical consultations in anticipation of the physician’s attribution of their symptoms to their behaviours, which triggered feelings of guilt [ 29 , 40 ].

Thurston et al. [ 67 ] reported that healthcare providers who did not regularly work with Indigenous patients attributed their perceived lack of buy-in to medical treatment of their RA to a lack of education about the value of specialists and their services. However, the evidence pointed instead to the historical treatment of Indigenous peoples that has undermined their trust in Western institutions, and cultural constraints such as family obligations that prevented Indigenous PlwRA from attending appointments or establishing concordance with treatment plans [ 67 , 69 , 72 ].

The most frequently reported cause of treatment delays, according to PlwRA, was a gatekeeper—usually a primary care provider—who lacked the expertise, time or consideration to recognize their signs and symptoms of RA [ 36 , 39 , 46 , 50 , 64 , 70 , 73 , 74 , 75 , 76 , 77 ]. Lopatina et al. [ 78 ] have advocated for improved access to information and resources on RA for primary care practitioners to this end. Some studies emphasized that delays occurred because primary care physicians viewed themselves as gatekeepers to scarce secondary services and, hence, to integrated care [ 71 , 73 ]. Some authors advocated for the greater availability or awareness of diagnostic tools [ 46 , 73 , 76 ]. More commonly, though, patients identified the importance of physicians who took a person-centred approach that resulted in better health outcomes. This entailed the affordance of mutual respect through bilateral communication and inclusion in treatment decisions; such physicians saw them in the context of their whole lives, not just in terms of their disease [ 42 , 52 , 61 , 62 , 64 , 67 , 69 , 71 , 75 , 79 , 80 , 81 ].

Acceptance and resistance of offers (diagnosis, screening, treatment)

So far, we have seen ample evidence of the Candidacy Framework premise that “accomplishing access to healthcare requires considerable work on the part of users, and the amount, difficulty, and complexity of that work may operate as barriers to receipt of care” [ 4 ]. Ultimately, people seeking care aim to secure an offer of some kind. This may be a prescription, a treatment plan, a referral to a specialist or for screening. Yet receipt of an offer does not guarantee access because the ability or willingness to accept the offer may depend on a great many factors such as proximity, affordability, and cultural congruence. This dimension of Candidacy was by far the most densely coded. Of the nodes cross-coded with this dimension, ‘medications’ and ‘exercise and physiotherapy programs’ were most populated.

Medications

The pain and disability experienced by PlwRA, especially during flares, was reported as extreme to the extent that some had contemplated suicide [ 59 , 60 , 76 ], and the relief that the appropriate prescription of DMARDS and/or biologics can bring was described as ‘dramatic’ and life-changing’ across multiple studies [ 80 , 82 , 83 , 84 , 85 , 86 ]. Thus, the offer of therapeutic drugs for RA is typically accepted, albeit with some reservations: “Most felt or had been told that they had no choice other than to take potentially toxic drugs to alleviate their symptoms or to slow down the deterioration of their chronic condition” [ 64 ].

Yet arriving at the point of relief was often a long and painful process of trial and error to find the right combination of medications ([ 75 ],e.g., [ 87 ])—there was no ‘one size fits all’—which, in turn, took a toll on the PlwRA’s mental health [ 60 ]. PlwRA for whom effective medication had all but eradicated their symptoms hesitated to taper or temporarily discontinue it to resolve an infection, for fear that the intensity of the flares could increase and the drug would no longer be as effective upon resumption [ 49 , 88 , 89 , 90 ], although in principle, they were willing to try. While some temporarily opted out of taking DMARDS and biologics due to their incompatibility with their reproductive goals [ 91 ], others had relinquished the possibility of conceiving because they felt unable to cope without these medications [ 60 ].

Adherence to pharmaceutical treatment for RA was highly variable, ranging from 30 to 80% [ 33 , 92 ]. Multiple studies explained non-adherence in terms of the burden of administration and monitoring DMARD/biologic treatment, which required a considerable commitment from PlwRA [ 44 , 71 , 91 , 93 , 94 , 95 ]. Side effects of the drugs were also found to negatively the PlwRA’s wellbeing and add another level of healthcare complication [ 44 , 68 , 84 ], (e.g., [ 91 , 96 , 97 ]). Ultimately, the extent to which PlwRA perceived their medications to be helpful or harmful exerted the greatest influence on their acceptance or resistance to treatment [ 92 , 93 ]. Some had tried multiple medications with limited or no relief or recovery of their prior capacity and quality of life [ 54 , 84 , 86 , 94 , 96 , 97 ], or the effectiveness of any treatment was short-lived [ 44 ]. It should be noted, however, that the introduction of new more efficacious treatments has decreased the risk of negative outcomes such as joint arthroplasty, excess mortality or adverse pregnancy outcomes following parental exposure to DMARDs [ 98 , 99 , 100 ].

Considerable evidence points to resistance as partial rather than absolute. Most commonly, PlwRA decided to ‘take control’ of their disease by varying the dose according to their perceived need, periodically abstaining from certain medications [ 38 , 63 , 64 , 92 ], or utilizing complementary and alternative medicine or over-the-counter drugs [ 29 , 38 , 43 , 44 , 54 , 59 , 64 , 67 , 92 , 93 , 97 , 101 , 102 , 103 ]. Studies found that the understanding of the mechanism of action of DMARDs and biologics, was often poorly understood by PlwRA; in particular, they did not understand the preventive value of the medications [ 38 , 93 ]. Moreover, they did not understand the harms of long-term use of glucocorticoids like Prednisone [ 38 , 91 ]. A patient-initiated self‐monitoring service for PlwRA on methotrexate was well received in the UK, in large part because the training they received to prepare them to monitor and initiate the drug themselves “increased their knowledge of arthritis, their treatment, the reasons for regular testing and the meaning of test results” and thus “enabled them to gain a sense of control and ownership over their arthritis” [ 95 ]. This speaks to the importance of the provision of person-centred information and education to address harmful misconceptions.

Exercise and physiotherapy programs

Engagement in exercise programs benefitted PlwRA physically and psychologically and contributed to participants’ empowerment and their ability to manage RA [ 104 , 105 ]. However, exercise programs tailored to the needs of PlwRA were reportedly scarce [ 61 ] and many home exercise programs were viewed as boring and difficult to prioritize [ 106 ].

Studies of RA-tailored exercise programs have identified some key components that increase uptake and maintenance of an exercise routine. These include expert person-centred guidance, flexibility, and sensitivity to and accommodation of RA-specific limitations.

Successful programs were typically moderated by a physiotherapist or other exercise professional with the expertise to guide participants through the challenges of pain or fatigue, even when the program was largely participant-led [ 104 , 107 ]. This guidance was especially important for those unfamiliar with exercise [ 108 ], but was also valued for broad-based feedback and back-up, particularly when participants needed to adjust their routines or increase their exercise load [ 105 , 109 , 110 ]. Professionals who took a person-centred approach, recognized the need for PlwRA to feel heard, and adopted a holistic approach to symptom management were especially valued [ 108 , 109 , 110 , 111 ].

Flexibility in programming was appreciated by PlwRA and took many forms. Some programs were customized so PlwRA could exercise at home and fit the exercises into their normal routines [ 104 , 108 ]; being able to modify exercises to their own pace, limitations, and goals (which may vary on a daily basis contingent on disease activity), was also important (104, 108, 110, 111). PlwRA were often afraid to participate in exercise if they believed it would cause pain or they may not be able to get in and out of exercise positions, and adherence to exercise programs often waned as participants experienced flares, fluctuating symptoms or medication changes [ 104 , 105 , 111 ]. Programming must therefore be sensitive to these fears and adapted accordingly.

Permeability of the healthcare system

Permeability invokes the metaphor of the passage of fluid through material, with slower transmission representing the more stringent qualifications of candidacy (e.g., the need for a referral, lack of cultural alignment) needed to gain access to the healthcare system, and rapid transmission representing easier processes of access [ 4 ]. In our sample, evidence of healthcare system impermeability was primarily found in accounts of untimely delivery of care that disrupted continuity. New models of care were proposed to increase system permeability.

The benefits and challenges of different approaches aimed at increasing system permeability according to the reviewed literature are summarized in Table  3 . These characteristics were often reported in combination.

Local operating conditions

The final dimension of Candidacy considers local influences on the ability of the person needing access to services that may extend beyond the healthcare system [ 4 ]. There is ample evidence in the reviewed literature that access to care for RA is especially compromised for those living in rural and remote areas, in which people who are low-income and Indigenous populations in Canada are disproportionately represented [ 61 , 72 ].

Primarily, access in remote areas was found to be limited because of the absence or low representation of all types of healthcare providers from primary care providers to rheumatologists as well as other specialists and allied health professionals to whom access is needed for optimal care of RA [ 32 , 45 , 46 , 61 ]. As a result, PlwRA faced long drives to access these services. For example, more than half the PlwRA in rural and northern Saskatchewan (a Canadian prairie province) had to drive an hour or more to access primary care providers, Physical Therapy (PT) and Occupational Therapy (OT), pharmacies, labs and medical imaging facilities, and > 25% travelled 4 + hours to see a rheumatologist [ 32 ]. In addition to distance, factors such as weather, road conditions and maintenance, a lack of transportation and the need to arrange childcare compromised PlwRAs’ ability to access care [ 32 ].

PlwRA also had to absorb multiple out-of-pocket costs for fuel or other transportation, childcare, overnight accommodation, etc. Some PT and OT services external to hospitals or outpatient services were also not covered by medical insurance for many, hence affordability of care was a barrier despite Canada’s universal healthcare coverage [ 32 , 75 ]. Also missing in these communities are resources such as community pools or rehabilitation centres needed for optimal RA care [ 45 ]. The availability of potential solutions to address access limitations in these communities, such as traveling clinics, telehealth, and patient travel grants was found to vary by province. The viability of each was hampered by lack of available staff, lack of patient buy-in, and low cost-effectiveness, respectively [ 61 ].

Even outside of rural and remote areas, local influences can affect access to care. Hand et al. [ 27 ] noted that access to services could be compromised for low-income seniors when cost-saving policies resulted in housing that was poorly situated (e.g., on a hill, near a highway, far from services). These authors also reported that despite protective policies, employers did not always cooperate with accommodations for modified working arrangements to facilitate a PlwRA’s ability to return to work.

Beyond candidacy – the embodied self

Candidacy focuses on the negotiation of access at micro, meso and macro levels, but none of its dimensions fully capture how the identities of PlwRA are challenged by illness experiences and the ways in which access is consequently compromised. This understanding emerges from our sample, in part, because of the phenomenological/phenomenographic approach adopted by 18 of the reviewed studies, for which the focus was on meaning-making. Yet evidence of the same is found across studies with diverse methodological approaches. These findings speak to Kleinman’s [ 117 ] emphasis on the importance of understanding illness as an embodied experience, rather than just a set of symptoms or diagnostic criteria. Kleinman argued that illness is not just a matter of biological dysfunction but is also shaped by a person’s cultural and social context, as well as their own subjective experiences and meanings. Similarly, Bury [ 118 ], who conducted his research with PlwRA, viewed chronic illness as a biological disruption, in the face of which people were forced to reappraise their selfhood as intimately bound to the body. To this, Goodacre [ 119 ] added the importance of the social interpretation of self. Both Charmaz [ 120 ] and Ratcliffe [ 121 ], influenced by Merleau-Ponty, spoke to the loss of identity and self that could arise from bodily disruptions. A profound sense of loss is apparent in PlwRA’s accounts of flares or the effects of pain, deformity and immobilization caused by RA in which not only the body but the mind and sense of self are profoundly affected by the illness (e.g., [ 28 , 31 , 37 , 49 , 60 , 68 , 83 , 86 , 91 , 94 , 107 , 109 , 122 ]).

Consistent with Martin’s [ 123 ] work on how women’s culturally-informed and gendered identities are affected by illness, and sources of women’s power in the body discussed by Chrisler et al. [ 124 ], women with RA in several studies detailed identity compromises. Illness affected their appearance and sexuality (e.g., [ 49 , 109 , 125 ]). It also hindered gendered roles like housework, food preparation, and childcare [ 76 , 85 , 126 , 127 , 128 , 129 ]. Yet, some studies reported women exhibiting stoicism [ 55 ] and facing peer exclusion [ 87 ], akin to patterns more commonly found among men [ 63 ]. This highlights the importance of adopting an intersectional approach, wherein identities (e.g., age, gender, SES, rural/urban residence) and concomitant experiences of social domination are seen as intertwined with a compounding effect [ 130 , 131 ].

Additionally, the identities of PlwRA could be supported or undermined by members of their social networks. People who understood their challenges and offered necessary support, without undermining the PlwRA’s self-determination, promoted their identity and facilitated coping [ 27 , 37 , 83 , 128 , 129 ]. Others undermined their sense of self and personal value by dismissing their suffering or assuming control over them [ 60 , 83 , 102 , 108 , 128 , 129 , 132 ].

A PlwRA’s selfhood must therefore be understood in relation to their embodiment of illness (RA and comorbidities), their intersections of identity (e.g., gender, SES, age) and the nature of their relationships with close others. In the studies reviewed, the PlwRA’s selfhood primarily undermined access through the effect of identity loss on their mental health, expressed variously as embarrassment, shame, and loss of self-esteem, power and control [ 31 , 60 , 133 ], which in turn led to self-isolation and societal withdrawal [ 37 , 57 , 59 , 68 , 91 , 134 ]. PlwRA were thus impeded from seeking the help they needed, which could further undermine their mental and physical health [ 28 , 63 , 85 , 94 , 109 , 127 ]. Kristiansen and Antoft [ 135 ] reported on a program for PlwRA that overlooked the debilitating effect of RA on self-esteem and thus further undermined it. “Narratives of chaos” created by illness in relation to identity, as theorized by Frank [ 136 ], were also evident in the efforts of some PlwRA to ‘gain control’ of their illness and hence their sense of self by resisting or modifying treatment [ 38 , 63 , 64 , 91 , 132 ]. Some supplemented or replaced biomedical treatments with complementary and alternative medicines (CAM) in ways that were detrimental to their health [ 59 , 97 , 103 ]. While CAM use can indicate patient engagement and a proactive stance to treatment, it sometimes reflected an uninformed approach to medication resistance. Other such examples were suspending medication while on vacation to permit greater alcohol intake [ 63 ] or substituting medication with unconventional remedies (e.g., horse liniment) [ 44 ] that delayed access and compromised health outcomes.

To summarize, we illustrate in Table  4 the seven dimensions of Candidacy plus the embodied self with brief descriptions, based on our CIS, of factors that promote (✔) and limit (✘) candidacy in each.

Discussion: extending a theory of access to care for chronic conditions: candidacy 2.0 (CC)

Previous applications of the Candidacy Framework have suggested the addition of supplementary constructs to enhance the theory. Most notable among them are recursivity [ 137 ] and concordance [ 138 ], the importance of intersectionality theory [ 139 ] and the relational nature of negotiations of candidacy [ 10 ]. Our findings not only support inclusion of these concepts, the centrality of the embodied self in the model facilitates their integration as components rather than adjuncts of candidacy and suggests the need for an enhanced Candidacy 2.0 model.

Selfhood can be challenged by chronic disease, comorbidities and treatments that may have severe side-effects. A person’s identity facilitates their creation of meaning, which is a central tenet of mental health [ 140 ]. The relationship between illness and selfhood can be cyclical when challenges to selfhood due to pain, disability or extreme fatigue, for example, result in deteriorating mental health. This, in turn, has a bidirectional relationship with social isolation and withdrawal [ 141 , 142 ].

Yet the self is not a blank slate: rather it is composed of multiple intersecting identities that are more or less privileged in the societal context in which the person living with a chronic condition is embedded [ 141 , 143 ]. The compounding effect of these identities and societal expectations of and responses to them shapes the extent to which illness-related changes to physical features, sexuality, or the roles that people perform are important to them and the meanings that they ascribe to their illness and its effect on their selfhood [ 144 , 145 ]. In parallel with Mackenzie et al. [ 139 ], we identified the positive or negative influence of intersecting identities on the ability of people to establish candidacy in the articles reviewed for the CIS, especially in the dimensions of navigation and appearances. The addition of an intersectional lens facilitates a more nuanced understanding of help-seeking behaviours and acceptance or rejection of treatment: gender matters in its own right, for example, but it also interacts with other identities and social determinants of health to influence these behaviours [ 143 ]. Intersectional awareness achieved through the integration of candidacy and intersectionality also offers policy makers and practitioners “a means of enhancing knowledge of how the political becomes enacted in the personal” [ 139 ].

Intersecting identities also influence the extent to which a person is likely to reach ‘concordance’ (i.e., agreement with care providers about the problem and best solutions) and engage in shared decision-making with them [ 138 ]. The importance of concordance in the establishment of candidacy has been recognized in multiple studies [ 16 , 17 ] and corresponds well with the original construct of permeability whereby “the service provider’s alignment with service users, including personality, gender, and ethno-linguistic characteristics” facilitates access at the organizational level [ 11 ]. However it is only when intersectionality and candidacy are united that we can fully appreciate how “discordant healthcare encounters are not simply a manifestation of essential cultural differences between the two parties but are shaped by factors that emanate from a complex interplay of historical and contemporary discourses, inequitable structures, multiple intersecting identities and past experiences” [ 146 ]. In the CIS sample, this is illustrated most clearly with reference to experiences of access to RA care by Indigenous people, immigrants and refugees, the frail elderly and people who are low-income or live in rural and remote areas; importantly, people are often marginalized by the intersection of two or more of these identities [ 67 , 69 , 72 ].

Intersections of identity also influence the degree of agency that people can exercise. As Chase et al. [ 6 ] point out, Dixon-Woods et al. [ 4 ] originally conceived of the establishment of candidacy as a ‘negotiation’ between patients and healthcare providers, but this underestimates the power differentials between them that can undermine the agency of people at marginalized intersections of identity, effectively foreclosing any true negotiation and reducing candidacy. For example, asylum seekers who encountered discriminatory and unjust treatment when applying for services were subsequently more likely to pay out of pocket and showed greater reluctance to seek further help or even information [ 6 ]. Similarly, in the articles reviewed for our CIS, we saw multiple examples of curtailed interaction with health professionals due to diminished trust arising from what were seen as biased adjudications rooted in power differentials between healthcare providers and PlwRA at marginalized intersections of identity (e.g., low SES, Indigenous, etc.). This phenomenon is identified as ‘recursivity’ [ 137 ]: “the interdependency between a user’s experiences of health services and her/his future actions in regards [sic.] to health and help seeking” [ 16 ]. Thus “the key determinants of patient choice of healthcare are social and diachronic” [ 14 ]. The outcome of reduced candidacy due to negative recursivity in the CIS data and in Koehn et al’s dementia study [ 11 ] was most apparent in people’s resistance to offers but was also seen in their interactions with healthcare providers (appearances and adjudications). For example, Machin et al. [ 81 ] suggested that PlwRA’s perception of their primary care practitioner as too busy and primarily focused on physical over mental health provoked anxiety and recursively prevented them from discussing mood or seeking assistance to locate mental health resources in subsequent consultations.

The connection of recursivity to the embodied self was illustrated by Flurey et al. [ 63 ] who reported that the selfhood of men living with RA, already diminished by their inability to work and perform other roles central to their masculinity, was further degraded when physicians did not take their medical complaints seriously. In response they sought to recover some sense of control by reducing medications, and engaging in excessive exercise or alcohol consumption, and only consulted the physician as a last resort. The permeability of services is also implicated in recursivity as illustrated by Hunter et al.’s [ 14 ] finding that people with ‘long-term conditions’ are frequent users of emergency care services for illness exacerbations because they provide the most expedient access to needed care and technology. Dixon-Woods et al. [ 4 ] have described emergency care as the most permeable healthcare service which, as a result, tends to be utilized more frequently by the most vulnerable members of society, thus underscoring the importance of the inclusion of an intersectional lens. These examples further emphasize Kovandžić et al.’s [ 17 ] point that recursivity is important because it unites the concepts of access to and utilization of healthcare services. Rather than viewing recursivity and candidacy as separate processes [ 14 , 16 , 17 ], we propose that recursivity be understood as an integral component of the process of establishing candidacy that reflects the relative agency of people living with chronic conditions at different intersections of identity as they attempt to negotiate access across its different dimensions.

Another key element to arise from the articles included in this CIS is the potential for family, friends, and the broader social network of the person with a chronic condition to either promote or undermine their self-determination and personal value. The notion of an interdependent or sociocentric self, whereby the self is viewed “not in terms of one’s independence from others, but rather by one’s connection to them” [ 147 ] is more commonly attributed to non-Eurocentric cultures, yet examples of this interdependence between PlwRA and their social networks abound throughout our CIS sample. The influence of the social network on candidacy is also apparent in other analyses utilizing the framework. For example, family members who may have more social capital than the person with a chronic condition, particularly dementia, are more likely to identify the need to seek medical attention, facilitate navigation to care, and convey observed symptoms to family physicians and other gatekeepers [ 11 , 14 ]. Accordingly, we propose that the embodied self or personhood conceived as central to the Candidacy 2.0 model is necessarily understood as relational.

The centrality of the intersectional relational self in the enhanced model also makes sense in relation to the abundance of evidence that person-centred interactions, information, and service configuration are key to addressing many of the access challenges faced by PlwRA and, we would argue, people living with chronic conditions in general. Candidacy 2.0 provides a strong explanatory framework that maps out why this is the case. Focusing attention on selfhood in the Candidacy model further reinforces the importance of understanding movement through the dimensions of access as iterative, not only because the need for care among people with chronic conditions is ongoing, but because, as Saari [ 140 ] reminds us, “meaning systems must be constantly maintained and amended so that the content will fit with the context and experience of the present. The processes of the self must therefore be active in creating and altering meaning throughout life.” This in turn serves as a reminder to those designing and delivering person-centred systems and care that the ‘person’ is not a static entity, and their values, needs and goals of care may well shift over time.

Figure  3 depicts the movement of the intersectional relational self through each dimension of candidacy. Appearances and adjudications are inextricably linked, while permeability is characterized as a barrier with variable holes through which some of the offers made by gatekeepers (adjudicators) will pass. Offers such as referrals, medications or screening are depicted by the small balls that need to be accepted by the self and be compatible with the organizational framework represented by permeability and wider environment or local conditions. Concordance and recursivity are integral to the framework and are most often salient to the dimensions they touch in the diagram. The outcome is ideally access, but different resources may require an iterative process to obtain and for some, the obstacles represented by the accumulated dimensions may defeat access.

Candidacy 2.0: An enhanced Candidacy Framework to understand access to healthcare for chronic conditions

Limitations

The CIS is a very flexible approach to systematic synthesis, which can be both a strength and a weakness. This critical approach draws on the reviewer’s expertise in the field on the one hand and responds to the knowledge needs of the research team, on the other. In this sense, it is not entirely reproducible [ 35 ]. SK, the first author, was primarily responsible for data analysis for which task she drew on her considerable expertise in access to health care and theoretical approaches to illness experience. She consulted frequently with the remaining authors whose expertise in RA and primary care provision strengthened the validity of her interpretations. To remain accountable, the authors of a CIS must demonstrate both systematicity (soundness of execution) and transparency (explicitness of reporting), for which Depraetere and colleagues (25) have developed seven evaluative criteria that distinguish a CIS. Most important among them are (1) Data-extraction method for identifying themes/concepts, (2) Formulation of a synthesizing argument, (3) Inclusion of qualitative and quantitative research results, and (4) Flexible inclusion criteria. We believe that all criteria in this list have been met. While most sources were qualitative to address the deficit in comprehensive studies of RA access experience, eleven were mixed methods with a quantitative component, four were quantitative, and three were review articles.

Adoption of the CIS methodology using the lens of the Candidacy Framework to review literature focused on the experiences of people living with a chronic condition (specifically RA) has generated a rich analysis of the challenges and complexity of access to care for RA. Perhaps more importantly, this analysis has identified the key phenomenological dimension of embodied selfhood that is missing in the original formulation of Candidacy. The importance of this central concept is reinforced when considered in relation to other applications of Candidacy, particularly those concerned with access to care for chronic conditions. Modifications suggested by these studies underscore the importance of considering the intersectional and relational self as integral to an enhanced version of the framework.

Availability of data and materials

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

Data availability

Data is provided within the manuscript or supplementary information files.

Advisory committee members continue to be involved with the overall programme of RA research but did not feel equipped to contribute to the CIS given their lack of familiarity with academic literature.

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Acknowledgements

The authors would like to express a sincere thank you to Nikoletta Wood for the creation of the graphics for the Candidacy 2.0 framework model, and to all of the members of the advisory committee, composed of people living with RA, who provided support and insight in the development of the research questions.

The authors would also like to convey their gratitude to The Arthritis Society Canada for the support through the Strategic Operating Grant 20 − 0000000018 SOG, and to Mitacs for the.

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Koehn, S., Jones, C.A., Barber, C. et al. Candidacy 2.0 (CC) – an enhanced theory of access to healthcare for chronic conditions: lessons from a critical interpretive synthesis on access to rheumatoid arthritis care. BMC Health Serv Res 24 , 986 (2024). https://doi.org/10.1186/s12913-024-11438-6

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Qualitative Research: Getting Started

Introduction.

As scientifically trained clinicians, pharmacists may be more familiar and comfortable with the concept of quantitative rather than qualitative research. Quantitative research can be defined as “the means for testing objective theories by examining the relationship among variables which in turn can be measured so that numbered data can be analyzed using statistical procedures”. 1 Pharmacists may have used such methods to carry out audits or surveys within their own practice settings; if so, they may have had a sense of “something missing” from their data. What is missing from quantitative research methods is the voice of the participant. In a quantitative study, large amounts of data can be collected about the number of people who hold certain attitudes toward their health and health care, but what qualitative study tells us is why people have thoughts and feelings that might affect the way they respond to that care and how it is given (in this way, qualitative and quantitative data are frequently complementary). Possibly the most important point about qualitative research is that its practitioners do not seek to generalize their findings to a wider population. Rather, they attempt to find examples of behaviour, to clarify the thoughts and feelings of study participants, and to interpret participants’ experiences of the phenomena of interest, in order to find explanations for human behaviour in a given context.

WHAT IS QUALITATIVE RESEARCH?

Much of the work of clinicians (including pharmacists) takes place within a social, clinical, or interpersonal context where statistical procedures and numeric data may be insufficient to capture how patients and health care professionals feel about patients’ care. Qualitative research involves asking participants about their experiences of things that happen in their lives. It enables researchers to obtain insights into what it feels like to be another person and to understand the world as another experiences it.

Qualitative research was historically employed in fields such as sociology, history, and anthropology. 2 Miles and Huberman 2 said that qualitative data “are a source of well-grounded, rich descriptions and explanations of processes in identifiable local contexts. With qualitative data one can preserve chronological flow, see precisely which events lead to which consequences, and derive fruitful explanations.” Qualitative methods are concerned with how human behaviour can be explained, within the framework of the social structures in which that behaviour takes place. 3 So, in the context of health care, and hospital pharmacy in particular, researchers can, for example, explore how patients feel about their care, about their medicines, or indeed about “being a patient”.

THE IMPORTANCE OF METHODOLOGY

Smith 4 has described methodology as the “explanation of the approach, methods and procedures with some justification for their selection.” It is essential that researchers have robust theories that underpin the way they conduct their research—this is called “methodology”. It is also important for researchers to have a thorough understanding of various methodologies, to ensure alignment between their own positionality (i.e., bias or stance), research questions, and objectives. Clinicians may express reservations about the value or impact of qualitative research, given their perceptions that it is inherently subjective or biased, that it does not seek to be reproducible across different contexts, and that it does not produce generalizable findings. Other clinicians may express nervousness or hesitation about using qualitative methods, claiming that their previous “scientific” training and experience have not prepared them for the ambiguity and interpretative nature of qualitative data analysis. In both cases, these clinicians are depriving themselves of opportunities to understand complex or ambiguous situations, phenomena, or processes in a different way.

Qualitative researchers generally begin their work by recognizing that the position (or world view) of the researcher exerts an enormous influence on the entire research enterprise. Whether explicitly understood and acknowledged or not, this world view shapes the way in which research questions are raised and framed, methods selected, data collected and analyzed, and results reported. 5 A broad range of different methods and methodologies are available within the qualitative tradition, and no single review paper can adequately capture the depth and nuance of these diverse options. Here, given space constraints, we highlight certain options for illustrative purposes only, emphasizing that they are only a sample of what may be available to you as a prospective qualitative researcher. We encourage you to continue your own study of this area to identify methods and methodologies suitable to your questions and needs, beyond those highlighted here.

The following are some of the methodologies commonly used in qualitative research:

• Ethnography generally involves researchers directly observing participants in their natural environments over time. A key feature of ethnography is the fact that natural settings, unadapted for the researchers’ interests, are used. In ethnography, the natural setting or environment is as important as the participants, and such methods have the advantage of explicitly acknowledging that, in the real world, environmental constraints and context influence behaviours and outcomes. 6 An example of ethnographic research in pharmacy might involve observations to determine how pharmacists integrate into family health teams. Such a study would also include collection of documents about participants’ lives from the participants themselves and field notes from the researcher. 7
• Grounded theory, first described by Glaser and Strauss in 1967, 8 is a framework for qualitative research that suggests that theory must derive from data, unlike other forms of research, which suggest that data should be used to test theory. Grounded theory may be particularly valuable when little or nothing is known or understood about a problem, situation, or context, and any attempt to start with a hypothesis or theory would be conjecture at best. 9 An example of the use of grounded theory in hospital pharmacy might be to determine potential roles for pharmacists in a new or underserviced clinical area. As with other qualitative methodologies, grounded theory provides researchers with a process that can be followed to facilitate the conduct of such research. As an example, Thurston and others 10 used constructivist grounded theory to explore the availability of arthritis care among indigenous people of Canada and were able to identify a number of influences on health care for this population.
• Phenomenology attempts to understand problems, ideas, and situations from the perspective of common understanding and experience rather than differences. 10 Phenomenology is about understanding how human beings experience their world. It gives researchers a powerful tool with which to understand subjective experience. In other words, 2 people may have the same diagnosis, with the same treatment prescribed, but the ways in which they experience that diagnosis and treatment will be different, even though they may have some experiences in common. Phenomenology helps researchers to explore those experiences, thoughts, and feelings and helps to elicit the meaning underlying how people behave. As an example, Hancock and others 11 used a phenomenological approach to explore health care professionals’ views of the diagnosis and management of heart failure since publication of an earlier study in 2003. Their findings revealed that barriers to effective treatment for heart failure had not changed in 10 years and provided a new understanding of why this was the case.

ROLE OF THE RESEARCHER

For any researcher, the starting point for research must be articulation of his or her research world view. This core feature of qualitative work is increasingly seen in quantitative research too: the explicit acknowledgement of one’s position, biases, and assumptions, so that readers can better understand the particular researcher. Reflexivity describes the processes whereby the act of engaging in research actually affects the process being studied, calling into question the notion of “detached objectivity”. Here, the researcher’s own subjectivity is as critical to the research process and output as any other variable. Applications of reflexivity may include participant-observer research, where the researcher is actually one of the participants in the process or situation being researched and must then examine it from these divergent perspectives. 12 Some researchers believe that objectivity is a myth and that attempts at impartiality will fail because human beings who happen to be researchers cannot isolate their own backgrounds and interests from the conduct of a study. 5 Rather than aspire to an unachievable goal of “objectivity”, it is better to simply be honest and transparent about one’s own subjectivities, allowing readers to draw their own conclusions about the interpretations that are presented through the research itself. For new (and experienced) qualitative researchers, an important first step is to step back and articulate your own underlying biases and assumptions. The following questions can help to begin this reflection process:

• Why am I interested in this topic? To answer this question, try to identify what is driving your enthusiasm, energy, and interest in researching this subject.
• What do I really think the answer is? Asking this question helps to identify any biases you may have through honest reflection on what you expect to find. You can then “bracket” those assumptions to enable the participants’ voices to be heard.
• What am I getting out of this? In many cases, pressures to publish or “do” research make research nothing more than an employment requirement. How does this affect your interest in the question or its outcomes, or the depth to which you are willing to go to find information?
• What do others in my professional community think of this work—and of me? As a researcher, you will not be operating in a vacuum; you will be part of a complex social and interpersonal world. These external influences will shape your views and expectations of yourself and your work. Acknowledging this influence and its potential effects on personal behaviour will facilitate greater self-scrutiny throughout the research process.

FROM FRAMEWORKS TO METHODS

Qualitative research methodology is not a single method, but instead offers a variety of different choices to researchers, according to specific parameters of topic, research question, participants, and settings. The method is the way you carry out your research within the paradigm of quantitative or qualitative research.

Qualitative research is concerned with participants’ own experiences of a life event, and the aim is to interpret what participants have said in order to explain why they have said it. Thus, methods should be chosen that enable participants to express themselves openly and without constraint. The framework selected by the researcher to conduct the research may direct the project toward specific methods. From among the numerous methods used by qualitative researchers, we outline below the three most frequently encountered.

DATA COLLECTION

Patton 12 has described an interview as “open-ended questions and probes yielding in-depth responses about people’s experiences, perceptions, opinions, feelings, and knowledge. Data consists of verbatim quotations and sufficient content/context to be interpretable”. Researchers may use a structured or unstructured interview approach. Structured interviews rely upon a predetermined list of questions framed algorithmically to guide the interviewer. This approach resists improvisation and following up on hunches, but has the advantage of facilitating consistency between participants. In contrast, unstructured or semistructured interviews may begin with some defined questions, but the interviewer has considerable latitude to adapt questions to the specific direction of responses, in an effort to allow for more intuitive and natural conversations between researchers and participants. Generally, you should continue to interview additional participants until you have saturated your field of interest, i.e., until you are not hearing anything new. The number of participants is therefore dependent on the richness of the data, though Miles and Huberman 2 suggested that more than 15 cases can make analysis complicated and “unwieldy”.

Focus Groups

Patton 12 has described the focus group as a primary means of collecting qualitative data. In essence, focus groups are unstructured interviews with multiple participants, which allow participants and a facilitator to interact freely with one another and to build on ideas and conversation. This method allows for the collection of group-generated data, which can be a challenging experience.

Observations

Patton 12 described observation as a useful tool in both quantitative and qualitative research: “[it involves] descriptions of activities, behaviours, actions, conversations, interpersonal interactions, organization or community processes or any other aspect of observable human experience”. Observation is critical in both interviews and focus groups, as nonalignment between verbal and nonverbal data frequently can be the result of sarcasm, irony, or other conversational techniques that may be confusing or open to interpretation. Observation can also be used as a stand-alone tool for exploring participants’ experiences, whether or not the researcher is a participant in the process.

Selecting the most appropriate and practical method is an important decision and must be taken carefully. Those unfamiliar with qualitative research may assume that “anyone” can interview, observe, or facilitate a focus group; however, it is important to recognize that the quality of data collected through qualitative methods is a direct reflection of the skills and competencies of the researcher. 13 The hardest thing to do during an interview is to sit back and listen to participants. They should be doing most of the talking—it is their perception of their own life-world that the researcher is trying to understand. Sophisticated interpersonal skills are required, in particular the ability to accurately interpret and respond to the nuanced behaviour of participants in various settings. More information about the collection of qualitative data may be found in the “Further Reading” section of this paper.

It is essential that data gathered during interviews, focus groups, and observation sessions are stored in a retrievable format. The most accurate way to do this is by audio-recording (with the participants’ permission). Video-recording may be a useful tool for focus groups, because the body language of group members and how they interact can be missed with audio-recording alone. Recordings should be transcribed verbatim and checked for accuracy against the audio- or video-recording, and all personally identifiable information should be removed from the transcript. You are then ready to start your analysis.

DATA ANALYSIS

Regardless of the research method used, the researcher must try to analyze or make sense of the participants’ narratives. This analysis can be done by coding sections of text, by writing down your thoughts in the margins of transcripts, or by making separate notes about the data collection. Coding is the process by which raw data (e.g., transcripts from interviews and focus groups or field notes from observations) are gradually converted into usable data through the identification of themes, concepts, or ideas that have some connection with each other. It may be that certain words or phrases are used by different participants, and these can be drawn together to allow the researcher an opportunity to focus findings in a more meaningful manner. The researcher will then give the words, phrases, or pieces of text meaningful names that exemplify what the participants are saying. This process is referred to as “theming”. Generating themes in an orderly fashion out of the chaos of transcripts or field notes can be a daunting task, particularly since it may involve many pages of raw data. Fortunately, sophisticated software programs such as NVivo (QSR International Pty Ltd) now exist to support researchers in converting data into themes; familiarization with such software supports is of considerable benefit to researchers and is strongly recommended. Manual coding is possible with small and straightforward data sets, but the management of qualitative data is a complexity unto itself, one that is best addressed through technological and software support.

There is both an art and a science to coding, and the second checking of themes from data is well advised (where feasible) to enhance the face validity of the work and to demonstrate reliability. Further reliability-enhancing mechanisms include “member checking”, where participants are given an opportunity to actually learn about and respond to the researchers’ preliminary analysis and coding of data. Careful documentation of various iterations of “coding trees” is important. These structures allow readers to understand how and why raw data were converted into a theme and what rules the researcher is using to govern inclusion or exclusion of specific data within or from a theme. Coding trees may be produced iteratively: after each interview, the researcher may immediately code and categorize data into themes to facilitate subsequent interviews and allow for probing with subsequent participants as necessary. At the end of the theming process, you will be in a position to tell the participants’ stories illustrated by quotations from your transcripts. For more information on different ways to manage qualitative data, see the “Further Reading” section at the end of this paper.

ETHICAL ISSUES

In most circumstances, qualitative research involves human beings or the things that human beings produce (documents, notes, etc.). As a result, it is essential that such research be undertaken in a manner that places the safety, security, and needs of participants at the forefront. Although interviews, focus groups, and questionnaires may seem innocuous and “less dangerous” than taking blood samples, it is important to recognize that the way participants are represented in research can be significantly damaging. Try to put yourself in the shoes of the potential participants when designing your research and ask yourself these questions:

• Are the requests you are making of potential participants reasonable?
• Are you putting them at unnecessary risk or inconvenience?
• Have you identified and addressed the specific needs of particular groups?

Where possible, attempting anonymization of data is strongly recommended, bearing in mind that true anonymization may be difficult, as participants can sometimes be recognized from their stories. Balancing the responsibility to report findings accurately and honestly with the potential harm to the participants involved can be challenging. Advice on the ethical considerations of research is generally available from research ethics boards and should be actively sought in these challenging situations.

GETTING STARTED

Pharmacists may be hesitant to embark on research involving qualitative methods because of a perceived lack of skills or confidence. Overcoming this barrier is the most important first step, as pharmacists can benefit from inclusion of qualitative methods in their research repertoire. Partnering with others who are more experienced and who can provide mentorship can be a valuable strategy. Reading reports of research studies that have utilized qualitative methods can provide insights and ideas for personal use; such papers are routinely included in traditional databases accessed by pharmacists. Engaging in dialogue with members of a research ethics board who have qualitative expertise can also provide useful assistance, as well as saving time during the ethics review process itself. The references at the end of this paper may provide some additional support to allow you to begin incorporating qualitative methods into your research.

CONCLUSIONS

Qualitative research offers unique opportunities for understanding complex, nuanced situations where interpersonal ambiguity and multiple interpretations exist. Qualitative research may not provide definitive answers to such complex questions, but it can yield a better understanding and a springboard for further focused work. There are multiple frameworks, methods, and considerations involved in shaping effective qualitative research. In most cases, these begin with self-reflection and articulation of positionality by the researcher. For some, qualitative research may appear commonsensical and easy; for others, it may appear daunting, given its high reliance on direct participant– researcher interactions. For yet others, qualitative research may appear subjective, unscientific, and consequently unreliable. All these perspectives reflect a lack of understanding of how effective qualitative research actually occurs. When undertaken in a rigorous manner, qualitative research provides unique opportunities for expanding our understanding of the social and clinical world that we inhabit.

Further Reading

• Breakwell GM, Hammond S, Fife-Schaw C, editors. Research methods in psychology. Thousand Oaks (CA): Sage Publications Ltd; 1995. [ Google Scholar ]
• Strauss A, Corbin J. Basics of qualitative research. Thousand Oaks (CA): Sage Publications Ltd; 1998. [ Google Scholar ]
• Willig C. Introducing qualitative research in psychology. Buckingham (UK): Open University Press; 2001. [ Google Scholar ]
• Guest G, Namey EE, Mitchel ML. Collecting qualitative data: a field manual for applied research. Thousand Oaks (CA): Sage Publications Ltd; 2013. [ Google Scholar ]
• Ogden R. Bias. In: Given LM, editor. The Sage encyclopedia of qualitative research methods. Thousand Oaks (CA): Sage Publications Inc; 2008. pp. 61–2. [ Google Scholar ]

This article is the seventh in the CJHP Research Primer Series, an initiative of the CJHP Editorial Board and the CSHP Research Committee. The planned 2-year series is intended to appeal to relatively inexperienced researchers, with the goal of building research capacity among practising pharmacists. The articles, presenting simple but rigorous guidance to encourage and support novice researchers, are being solicited from authors with appropriate expertise.

Previous article in this series:

Bond CM. The research jigsaw: how to get started. Can J Hosp Pharm . 2014;67(1):28–30.

Tully MP. Research: articulating questions, generating hypotheses, and choosing study designs. Can J Hosp Pharm . 2014;67(1):31–4.

Loewen P. Ethical issues in pharmacy practice research: an introductory guide. Can J Hosp Pharm. 2014;67(2):133–7.

Tsuyuki RT. Designing pharmacy practice research trials. Can J Hosp Pharm . 2014;67(3):226–9.

Bresee LC. An introduction to developing surveys for pharmacy practice research. Can J Hosp Pharm . 2014;67(4):286–91.

Gamble JM. An introduction to the fundamentals of cohort and case–control studies. Can J Hosp Pharm . 2014;67(5):366–72.

Competing interests: None declared.