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Qualitative Research – Methods, Analysis Types and Guide

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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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• 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 Research : Definition

Qualitative research is the naturalistic study of social meanings and processes, using interviews, observations, and the analysis of texts and images.  In contrast to quantitative researchers, whose statistical methods enable broad generalizations about populations (for example, comparisons of the percentages of U.S. demographic groups who vote in particular ways), qualitative researchers use in-depth studies of the social world to analyze how and why groups think and act in particular ways (for instance, case studies of the experiences that shape political views).   

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The Oxford Handbook of Qualitative Research

Patricia Leavy Independent Scholar Kennebunk, ME, USA

A newer edition of this book is available.

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This handbook provides a broad introduction to qualitative research to those with little to no background in the subject while simultaneously providing substantive contributions to the field that will be of interest to even the most experienced researchers. The first two sections explore the history of qualitative research, ethical perspectives, and philosophical/theoretical approaches. The next three sections focus on the major methods of qualitative practice, as well as on newer approaches (such as arts-based research and internet research); area studies often excluded (such as museum studies and disaster studies); and mixed methods and participatory methods (such as community-based research). The next section covers key issues including data analysis, interpretation, writing, and assessment. The final section offers a commentary about politics and research and the move toward public scholarship. The Oxford Handbook of Qualitative Research is intended for students of all levels, faculty, and researchers across the social sciences.

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Research Methodologies

• Quantitative Research Methodologies

Qualitative Research Methodologies

• Systematic Reviews
• Finding Articles by Methodology
• Design Your Research Project

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What is qualitative research.

Qualitative research methodologies seek to capture information that often can't be expressed numerically. These methodologies often include some level of interpretation from researchers as they collect information via observation, coded survey or interview responses, and so on. Researchers may use multiple qualitative methods in one study, as well as a theoretical or critical framework to help them interpret their data.

Qualitative research methods can be used to study:

• How are political and social attitudes formed? 
• How do people make decisions?
• What teaching or training methods are most effective?  

Qualitative Research Approaches

Action research.

In this type of study, researchers will actively pursue some kind of intervention, resolve a problem, or affect some kind of change. They will not only analyze the results but will also examine the challenges encountered through the process. 

Ethnography

Ethnographies are an in-depth, holistic type of research used to capture cultural practices, beliefs, traditions, and so on. Here, the researcher observes and interviews members of a culture — an ethnic group, a clique, members of a religion, etc. — and then analyzes their findings. 

Grounded Theory

Researchers will create and test a hypothesis using qualitative data. Often, researchers use grounded theory to understand decision-making, problem-solving, and other types of behavior.

Narrative Research

Researchers use this type of framework to understand different aspects of the human experience and how their subjects assign meaning to their experiences. Researchers use interviews to collect data from a small group of subjects, then discuss those results in the form of a narrative or story.

Phenomenology

This type of research attempts to understand the lived experiences of a group and/or how members of that group find meaning in their experiences. Researchers use interviews, observation, and other qualitative methods to collect data. 

Often used to share novel or unique information, case studies consist of a detailed, in-depth description of a single subject, pilot project, specific events, and so on. 

• Hossain, M.S., Runa, F., & Al Mosabbir, A. (2021). Impact of COVID-19 pandemic on rare diseases: A case study on thalassaemia patients in Bangladesh. Public Health in Practice, 2(100150), 1-3.
• Nožina, M. (2021). The Czech Rhino connection: A case study of Vietnamese wildlife trafficking networks’ operations across central Europe. European Journal on Criminal Policy and Research, 27(2), 265-283.

Focus Groups

Researchers will recruit people to answer questions in small group settings. Focus group members may share similar demographics or be diverse, depending on the researchers' needs. Group members will then be asked a series of questions and have their responses recorded. While these responses may be coded and discussed numerically (e.g., 50% of group members responded negatively to a question), researchers will also use responses to provide context, nuance, and other details. 

• Dichabeng, P., Merat, N., & Markkula, G. (2021). Factors that influence the acceptance of future shared automated vehicles – A focus group study with United Kingdom drivers. Transportation Research: Part F, 82, 121–140.
• Maynard, E., Barton, S., Rivett, K., Maynard, O., & Davies, W. (2021). Because ‘grown-ups don’t always get it right’: Allyship with children in research—From research question to authorship. Qualitative Research in Psychology, 18(4), 518–536.

Observational Study

Researchers will arrange to observe (usually in an unobtrusive way) a set of subjects in specific conditions. For example, researchers might visit a school cafeteria to learn about the food choices students make or set up trail cameras to collect information about animal behavior in the area. 

• He, J. Y., Chan, P. W., Li, Q. S., Li, L., Zhang, L., & Yang, H. L. (2022). Observations of wind and turbulence structures of Super Typhoons Hato and Mangkhut over land from a 356 m high meteorological tower. Atmospheric Research, 265(105910), 1-18.
• Zerovnik Spela, Kos Mitja, & Locatelli Igor. (2022). Initiation of insulin therapy in patients with type 2 diabetes: An observational study. Acta Pharmaceutica, 72(1), 147–157.

Open-Ended Surveys

Unlike quantitative surveys, open-ended surveys require respondents to answer the questions in their own words. 

• Mujcic, A., Blankers, M., Yildirim, D., Boon, B., & Engels, R. (2021). Cancer survivors’ views on digital support for smoking cessation and alcohol moderation: a survey and qualitative study. BMC Public Health, 21(1), 1-13.
• Smith, S. D., Hall, J. P., & Kurth, N. K. (2021). Perspectives on health policy from people with disabilities. Journal of Disability Policy Studies, 32(3), 224–232.

Structured or Semi-Structured Interviews

Researchers will recruit a small number of people who fit pre-determined criteria (e.g., people in a certain profession) and ask each the same set of questions, one-on-one. Semi-structured interviews will include opportunities for the interviewee to provide additional information they weren't asked about by the researcher.

• Gibbs, D., Haven-Tang, C., & Ritchie, C. (2021). Harmless flirtations or co-creation? Exploring flirtatious encounters in hospitable experiences. Tourism & Hospitality Research, 21(4), 473–486.
• Hongying Dai, Ramos, A., Tamrakar, N., Cheney, M., Samson, K., & Grimm, B. (2021). School personnel’s responses to school-based vaping prevention program: A qualitative study. Health Behavior & Policy Review, 8(2), 130–147.
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Qualitative Research: An Overview

• First Online: 24 April 2019

Cite this chapter

• Yanto Chandra 3 &
• Liang Shang 4  

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Qualitative research is one of the most commonly used types of research and methodology in the social sciences. Unfortunately, qualitative research is commonly misunderstood. In this chapter, we describe and explain the misconceptions surrounding qualitative research enterprise, why researchers need to care about when using qualitative research, the characteristics of qualitative research, and review the paradigms in qualitative research.

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Qualitative research is defined as the practice used to study things –– individuals and organizations and their reasons, opinions, and motivations, beliefs in their natural settings. It involves an observer (a researcher) who is located in the field , who transforms the world into a series of representations such as fieldnotes, interviews, conversations, photographs, recordings and memos (Denzin and Lincoln 2011 ). Many researchers employ qualitative research for exploratory purpose while others use it for ‘quasi’ theory testing approach. Qualitative research is a broad umbrella of research methodologies that encompasses grounded theory (Glaser and Strauss 2017 ; Strauss and Corbin 1990 ), case study (Flyvbjerg 2006 ; Yin 2003 ), phenomenology (Sanders 1982 ), discourse analysis (Fairclough 2003 ; Wodak and Meyer 2009 ), ethnography (Geertz 1973 ; Garfinkel 1967 ), and netnography (Kozinets 2002 ), among others. Qualitative research is often synonymous with ‘case study research’ because ‘case study’ primarily uses (but not always) qualitative data.

The quality standards or evaluation criteria of qualitative research comprises: (1) credibility (that a researcher can provide confidence in his/her findings), (2) transferability (that results are more plausible when transported to a highly similar contexts), (3) dependability (that errors have been minimized, proper documentation is provided), and (4) confirmability (that conclusions are internally consistent and supported by data) (see Lincoln and Guba 1985 ).

We classify research into a continuum of theory building — >   theory elaboration — >   theory testing . Theory building is also known as theory exploration. Theory elaboration refers to the use of qualitative data and a method to seek “confirmation” of the relationships among variables or processes or mechanisms of a social reality (Bartunek and Rynes 2015 ).

In the context of qualitative research, theory/ies usually refer(s) to conceptual model(s) or framework(s) that explain the relationships among a set of variables or processes that explain a social phenomenon. Theory or theories could also refer to general ideas or frameworks (e.g., institutional theory, emancipation theory, or identity theory) that are reviewed as background knowledge prior to the commencement of a qualitative research project.

For example, a qualitative research can ask the following question: “How can institutional change succeed in social contexts that are dominated by organized crime?” (Vaccaro and Palazzo 2015 ).

We have witnessed numerous cases in which committed positivist methodologists were asked to review qualitative papers, and they used a survey approach to assess the quality of an interpretivist work. This reviewers’ fallacy is dangerous and hampers the progress of a field of research. Editors must be cognizant of such fallacy and avoid it.

A social enterprises (SE) is an organization that combines social welfare and commercial logics (Doherty et al. 2014 ), or that uses business principles to address social problems (Mair and Marti 2006 ); thus, qualitative research that reports that ‘social impact’ is important for SEs is too descriptive and, arguably, tautological. It is not uncommon to see authors submitting purely descriptive papers to scholarly journals.

Some qualitative researchers have conducted qualitative work using primarily a checklist (ticking the boxes) to show the presence or absence of variables, as if it were a survey-based study. This is utterly inappropriate for a qualitative work. A qualitative work needs to show the richness and depth of qualitative findings. Nevertheless, it is acceptable to use such checklists as supplementary data if a study involves too many informants or variables of interest, or the data is too complex due to its longitudinal nature (e.g., a study that involves 15 cases observed and involving 59 interviews with 33 informants within a 7-year fieldwork used an excel sheet to tabulate the number of events that occurred as supplementary data to the main analysis; see Chandra 2017a , b ).

As mentioned earlier, there are different types of qualitative research. Thus, a qualitative researcher will customize the data collection process to fit the type of research being conducted. For example, for researchers using ethnography, the primary data will be in the form of photos and/or videos and interviews; for those using netnography, the primary data will be internet-based textual data. Interview data is perhaps the most common type of data used across all types of qualitative research designs and is often synonymous with qualitative research.

The purpose of qualitative research is to provide an explanation , not merely a description and certainly not a prediction (which is the realm of quantitative research). However, description is needed to illustrate qualitative data collected, and usually researchers describe their qualitative data by inserting a number of important “informant quotes” in the body of a qualitative research report.

We advise qualitative researchers to adhere to one approach to avoid any epistemological and ontological mismatch that may arise among different camps in qualitative research. For instance, mixing a positivist with a constructivist approach in qualitative research frequently leads to unnecessary criticism and even rejection from journal editors and reviewers; it shows a lack of methodological competence or awareness of one’s epistemological position.

Analytical generalization is not generalization to some defined population that has been sampled, but to a “theory” of the phenomenon being studied, a theory that may have much wider applicability than the particular case studied (Yin 2003 ).

There are different types of contributions. Typically, a researcher is expected to clearly articulate the theoretical contributions for a qualitative work submitted to a scholarly journal. Other types of contributions are practical (or managerial ), common for business/management journals, and policy , common for policy related journals.

There is ongoing debate on whether a template for qualitative research is desirable or necessary, with one camp of scholars (the pluralistic critical realists) that advocates a pluralistic approaches to qualitative research (“qualitative research should not follow a particular template or be prescriptive in its process”) and the other camps are advocating for some form of consensus via the use of particular approaches (e.g., the Eisenhardt or Gioia Approach, etc.). However, as shown in Table 1.1 , even the pluralistic critical realism in itself is a template and advocates an alternative form of consensus through the use of diverse and pluralistic approaches in doing qualitative research.

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Chandra, Y., Shang, L. (2019). Qualitative Research: An Overview. In: Qualitative Research Using R: A Systematic Approach. Springer, Singapore. https://doi.org/10.1007/978-981-13-3170-1_1

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How to use and assess qualitative research methods

• Loraine Busetto   ORCID: orcid.org/0000-0002-9228-7875 1 ,
• Wolfgang Wick 1 , 2 &
• Christoph Gumbinger 1  

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 , 10 , 11 , 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.

How to conduct qualitative research?

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

Iterative research process

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

Data collection

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

Document study

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

Observations

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

Semi-structured interviews

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

Focus groups

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

Choosing the “right” method

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

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

Possible combination of data collection methods

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

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

Data analysis

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

From data collection to data analysis

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 , 25 , 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig.  4 .

Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 , 38 , 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

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

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Not applicable.

Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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Busetto, L., Wick, W. & Gumbinger, C. How to use and assess qualitative research methods. Neurol. Res. Pract. 2 , 14 (2020). https://doi.org/10.1186/s42466-020-00059-z

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The word qualitative implies an emphasis on the qualities of entities and on processes and meanings that are not experimentally examined or measured [if measured at all] in terms of quantity, amount, intensity, or frequency. Qualitative researchers stress the socially constructed nature of reality, the intimate relationship between the researcher and what is studied, and the situational constraints that shape inquiry. Such researchers emphasize the value-laden nature of inquiry. They seek answers to questions that stress how social experience is created and given meaning. In contrast, quantitative studies emphasize the measurement and analysis of causal relationships between variables, not processes. Qualitative forms of inquiry are considered by many social and behavioral scientists to be as much a perspective on how to approach investigating a research problem as it is a method.

Denzin, Norman. K. and Yvonna S. Lincoln. “Introduction: The Discipline and Practice of Qualitative Research.” In The Sage Handbook of Qualitative Research . Norman. K. Denzin and Yvonna S. Lincoln, eds. 3 rd edition. (Thousand Oaks, CA: Sage, 2005), p. 10.

Characteristics of Qualitative Research

Below are the three key elements that define a qualitative research study and the applied forms each take in the investigation of a research problem.

• Naturalistic -- refers to studying real-world situations as they unfold naturally; non-manipulative and non-controlling; the researcher is open to whatever emerges [i.e., there is a lack of predetermined constraints on findings].
• Emergent -- acceptance of adapting inquiry as understanding deepens and/or situations change; the researcher avoids rigid designs that eliminate responding to opportunities to pursue new paths of discovery as they emerge.
• Purposeful -- cases for study [e.g., people, organizations, communities, cultures, events, critical incidences] are selected because they are “information rich” and illuminative. That is, they offer useful manifestations of the phenomenon of interest; sampling is aimed at insight about the phenomenon, not empirical generalization derived from a sample and applied to a population.

The Collection of Data

• Data -- observations yield a detailed, "thick description" [in-depth understanding]; interviews capture direct quotations about people’s personal perspectives and lived experiences; often derived from carefully conducted case studies and review of material culture.
• Personal experience and engagement -- researcher has direct contact with and gets close to the people, situation, and phenomenon under investigation; the researcher’s personal experiences and insights are an important part of the inquiry and critical to understanding the phenomenon.
• Empathic neutrality -- an empathic stance in working with study respondents seeks vicarious understanding without judgment [neutrality] by showing openness, sensitivity, respect, awareness, and responsiveness; in observation, it means being fully present [mindfulness].
• Dynamic systems -- there is attention to process; assumes change is ongoing, whether the focus is on an individual, an organization, a community, or an entire culture, therefore, the researcher is mindful of and attentive to system and situational dynamics.

The Analysis

• Unique case orientation -- assumes that each case is special and unique; the first level of analysis is being true to, respecting, and capturing the details of the individual cases being studied; cross-case analysis follows from and depends upon the quality of individual case studies.
• Inductive analysis -- immersion in the details and specifics of the data to discover important patterns, themes, and inter-relationships; begins by exploring, then confirming findings, guided by analytical principles rather than rules.
• Holistic perspective -- the whole phenomenon under study is understood as a complex system that is more than the sum of its parts; the focus is on complex interdependencies and system dynamics that cannot be reduced in any meaningful way to linear, cause and effect relationships and/or a few discrete variables.
• Context sensitive -- places findings in a social, historical, and temporal context; researcher is careful about [even dubious of] the possibility or meaningfulness of generalizations across time and space; emphasizes careful comparative case study analysis and extrapolating patterns for possible transferability and adaptation in new settings.
• Voice, perspective, and reflexivity -- the qualitative methodologist owns and is reflective about her or his own voice and perspective; a credible voice conveys authenticity and trustworthiness; complete objectivity being impossible and pure subjectivity undermining credibility, the researcher's focus reflects a balance between understanding and depicting the world authentically in all its complexity and of being self-analytical, politically aware, and reflexive in consciousness.

Berg, Bruce Lawrence. Qualitative Research Methods for the Social Sciences . 8th edition. Boston, MA: Allyn and Bacon, 2012; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 2nd ed. Thousand Oaks, CA: Sage Publications, 1995; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Basic Research Design for Qualitative Studies

Unlike positivist or experimental research that utilizes a linear and one-directional sequence of design steps, there is considerable variation in how a qualitative research study is organized. In general, qualitative researchers attempt to describe and interpret human behavior based primarily on the words of selected individuals [a.k.a., “informants” or “respondents”] and/or through the interpretation of their material culture or occupied space. There is a reflexive process underpinning every stage of a qualitative study to ensure that researcher biases, presuppositions, and interpretations are clearly evident, thus ensuring that the reader is better able to interpret the overall validity of the research. According to Maxwell (2009), there are five, not necessarily ordered or sequential, components in qualitative research designs. How they are presented depends upon the research philosophy and theoretical framework of the study, the methods chosen, and the general assumptions underpinning the study. Goals Describe the central research problem being addressed but avoid describing any anticipated outcomes. Questions to ask yourself are: Why is your study worth doing? What issues do you want to clarify, and what practices and policies do you want it to influence? Why do you want to conduct this study, and why should the reader care about the results? Conceptual Framework Questions to ask yourself are: What do you think is going on with the issues, settings, or people you plan to study? What theories, beliefs, and prior research findings will guide or inform your research, and what literature, preliminary studies, and personal experiences will you draw upon for understanding the people or issues you are studying? Note to not only report the results of other studies in your review of the literature, but note the methods used as well. If appropriate, describe why earlier studies using quantitative methods were inadequate in addressing the research problem. Research Questions Usually there is a research problem that frames your qualitative study and that influences your decision about what methods to use, but qualitative designs generally lack an accompanying hypothesis or set of assumptions because the findings are emergent and unpredictable. In this context, more specific research questions are generally the result of an interactive design process rather than the starting point for that process. Questions to ask yourself are: What do you specifically want to learn or understand by conducting this study? What do you not know about the things you are studying that you want to learn? What questions will your research attempt to answer, and how are these questions related to one another? Methods Structured approaches to applying a method or methods to your study help to ensure that there is comparability of data across sources and researchers and, thus, they can be useful in answering questions that deal with differences between phenomena and the explanation for these differences [variance questions]. An unstructured approach allows the researcher to focus on the particular phenomena studied. This facilitates an understanding of the processes that led to specific outcomes, trading generalizability and comparability for internal validity and contextual and evaluative understanding. Questions to ask yourself are: What will you actually do in conducting this study? What approaches and techniques will you use to collect and analyze your data, and how do these constitute an integrated strategy? Validity In contrast to quantitative studies where the goal is to design, in advance, “controls” such as formal comparisons, sampling strategies, or statistical manipulations to address anticipated and unanticipated threats to validity, qualitative researchers must attempt to rule out most threats to validity after the research has begun by relying on evidence collected during the research process itself in order to effectively argue that any alternative explanations for a phenomenon are implausible. Questions to ask yourself are: How might your results and conclusions be wrong? What are the plausible alternative interpretations and validity threats to these, and how will you deal with these? How can the data that you have, or that you could potentially collect, support or challenge your ideas about what’s going on? Why should we believe your results? Conclusion Although Maxwell does not mention a conclusion as one of the components of a qualitative research design, you should formally conclude your study. Briefly reiterate the goals of your study and the ways in which your research addressed them. Discuss the benefits of your study and how stakeholders can use your results. Also, note the limitations of your study and, if appropriate, place them in the context of areas in need of further research.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Heath, A. W. The Proposal in Qualitative Research. The Qualitative Report 3 (March 1997); Marshall, Catherine and Gretchen B. Rossman. Designing Qualitative Research . 3rd edition. Thousand Oaks, CA: Sage, 1999; Maxwell, Joseph A. "Designing a Qualitative Study." In The SAGE Handbook of Applied Social Research Methods . Leonard Bickman and Debra J. Rog, eds. 2nd ed. (Thousand Oaks, CA: Sage, 2009), p. 214-253; Qualitative Research Methods. Writing@CSU. Colorado State University; Yin, Robert K. Qualitative Research from Start to Finish . 2nd edition. New York: Guilford, 2015.

Strengths of Using Qualitative Methods

The advantage of using qualitative methods is that they generate rich, detailed data that leave the participants' perspectives intact and provide multiple contexts for understanding the phenomenon under study. In this way, qualitative research can be used to vividly demonstrate phenomena or to conduct cross-case comparisons and analysis of individuals or groups.

Among the specific strengths of using qualitative methods to study social science research problems is the ability to:

• Obtain a more realistic view of the lived world that cannot be understood or experienced in numerical data and statistical analysis;
• Provide the researcher with the perspective of the participants of the study through immersion in a culture or situation and as a result of direct interaction with them;
• Allow the researcher to describe existing phenomena and current situations;
• Develop flexible ways to perform data collection, subsequent analysis, and interpretation of collected information;
• Yield results that can be helpful in pioneering new ways of understanding;
• Respond to changes that occur while conducting the study ]e.g., extended fieldwork or observation] and offer the flexibility to shift the focus of the research as a result;
• Provide a holistic view of the phenomena under investigation;
• Respond to local situations, conditions, and needs of participants;
• Interact with the research subjects in their own language and on their own terms; and,
• Create a descriptive capability based on primary and unstructured data.

Anderson, Claire. “Presenting and Evaluating Qualitative Research.” American Journal of Pharmaceutical Education 74 (2010): 1-7; Denzin, Norman. K. and Yvonna S. Lincoln. Handbook of Qualitative Research . 2nd edition. Thousand Oaks, CA: Sage, 2000; Merriam, Sharan B. Qualitative Research: A Guide to Design and Implementation . San Francisco, CA: Jossey-Bass, 2009.

Limitations of Using Qualitative Methods

It is very much true that most of the limitations you find in using qualitative research techniques also reflect their inherent strengths . For example, small sample sizes help you investigate research problems in a comprehensive and in-depth manner. However, small sample sizes undermine opportunities to draw useful generalizations from, or to make broad policy recommendations based upon, the findings. Additionally, as the primary instrument of investigation, qualitative researchers are often embedded in the cultures and experiences of others. However, cultural embeddedness increases the opportunity for bias generated from conscious or unconscious assumptions about the study setting to enter into how data is gathered, interpreted, and reported.

Some specific limitations associated with using qualitative methods to study research problems in the social sciences include the following:

• Drifting away from the original objectives of the study in response to the changing nature of the context under which the research is conducted;
• Arriving at different conclusions based on the same information depending on the personal characteristics of the researcher;
• Replication of a study is very difficult;
• Research using human subjects increases the chance of ethical dilemmas that undermine the overall validity of the study;
• An inability to investigate causality between different research phenomena;
• Difficulty in explaining differences in the quality and quantity of information obtained from different respondents and arriving at different, non-consistent conclusions;
• Data gathering and analysis is often time consuming and/or expensive;
• Requires a high level of experience from the researcher to obtain the targeted information from the respondent;
• May lack consistency and reliability because the researcher can employ different probing techniques and the respondent can choose to tell some particular stories and ignore others; and,
• Generation of a significant amount of data that cannot be randomized into manageable parts for analysis.

Research Tip

Human Subject Research and Institutional Review Board Approval

Almost every socio-behavioral study requires you to submit your proposed research plan to an Institutional Review Board. The role of the Board is to evaluate your research proposal and determine whether it will be conducted ethically and under the regulations, institutional polices, and Code of Ethics set forth by the university. The purpose of the review is to protect the rights and welfare of individuals participating in your study. The review is intended to ensure equitable selection of respondents, that you have met the requirements for obtaining informed consent , that there is clear assessment and minimization of risks to participants and to the university [read: no lawsuits!], and that privacy and confidentiality are maintained throughout the research process and beyond. Go to the USC IRB website for detailed information and templates of forms you need to submit before you can proceed. If you are  unsure whether your study is subject to IRB review, consult with your professor or academic advisor.

Chenail, Ronald J. Introduction to Qualitative Research Design. Nova Southeastern University; Labaree, Robert V. "Working Successfully with Your Institutional Review Board: Practical Advice for Academic Librarians." College and Research Libraries News 71 (April 2010): 190-193.

Another Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

NOTE :  For a list of online communities, research centers, indispensable learning resources, and personal websites of leading qualitative researchers, GO HERE .

For a list of scholarly journals devoted to the study and application of qualitative research methods, GO HERE .

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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

Suggestions for changes and additions to this guide are welcome! 

START HERE: SAGE Research Methods

Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

• SAGE Research Methods
• Little Green Books  (Quantitative Methods)
• Little Blue Books  (Qualitative Methods)
• Dictionaries and Encyclopedias  
• Case studies of real research projects
• Sample datasets for hands-on practice
• Streaming video--see methods come to life
• Methodspace- -a community for researchers
• SAGE Research Methods Course Mapping

Library Data Services at UC Berkeley

Library Data Services Program and Digital Scholarship Services

The LDSP offers a variety of services and tools !  From this link, check out pages for each of the following topics:  discovering data, managing data, collecting data, GIS data, text data mining, publishing data, digital scholarship, open science, and the Research Data Management Program.

Be sure also to check out the visual guide to where to seek assistance on campus with any research question you may have!

Library GIS Services

Other Data Services at Berkeley

D-Lab Supports Berkeley faculty, staff, and graduate students with research in data intensive social science, including a wide range of training and workshop offerings Dryad Dryad is a simple self-service tool for researchers to use in publishing their datasets. It provides tools for the effective publication of and access to research data. Geospatial Innovation Facility (GIF) Provides leadership and training across a broad array of integrated mapping technologies on campu Research Data Management A UC Berkeley guide and consulting service for research data management issues

General Research Methods Resources

Here are some general resources for assistance:

• Assistance from ICPSR (must create an account to access): Getting Help with Data , and Resources for Students
• Wiley Stats Ref for background information on statistics topics
• Survey Documentation and Analysis (SDA) .  Program for easy web-based analysis of survey data.

Consultants

• D-Lab/Data Science Discovery Consultants Request help with your research project from peer consultants.
• Research data (RDM) consulting Meet with RDM consultants before designing the data security, storage, and sharing aspects of your qualitative project.
• Statistics Department Consulting Services A service in which advanced graduate students, under faculty supervision, are available to consult during specified hours in the Fall and Spring semesters.

Related Resourcex

• IRB / CPHS Qualitative research projects with human subjects often require that you go through an ethics review.
• OURS (Office of Undergraduate Research and Scholarships) OURS supports undergraduates who want to embark on research projects and assistantships. In particular, check out their "Getting Started in Research" workshops
• Sponsored Projects Sponsored projects works with researchers applying for major external grants.
• Next: Quantitative Research >>
• Last Updated: Apr 25, 2024 11:09 AM
• URL: https://guides.lib.berkeley.edu/researchmethods

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Home Market Research

Qualitative Research Methods: Types, Analysis + Examples

Qualitative research is based on the disciplines of social sciences like psychology, sociology, and anthropology. Therefore, the qualitative research methods allow for in-depth and further probing and questioning of respondents based on their responses. The interviewer/researcher also tries to understand their motivation and feelings. Understanding how your audience makes decisions can help derive conclusions in market research.

What is qualitative research?

Qualitative research is defined as a market research method that focuses on obtaining data through open-ended and conversational communication .

This method is about “what” people think and “why” they think so. For example, consider a convenience store looking to improve its patronage. A systematic observation concludes that more men are visiting this store. One good method to determine why women were not visiting the store is conducting an in-depth interview method with potential customers.

For example, after successfully interviewing female customers and visiting nearby stores and malls, the researchers selected participants through random sampling . As a result, it was discovered that the store didn’t have enough items for women.

So fewer women were visiting the store, which was understood only by personally interacting with them and understanding why they didn’t visit the store because there were more male products than female ones.

Gather research insights

Types of qualitative research methods with examples

Qualitative research methods are designed in a manner that helps reveal the behavior and perception of a target audience with reference to a particular topic. There are different types of qualitative research methods, such as in-depth interviews, focus groups, ethnographic research, content analysis, and case study research that are usually used.

The results of qualitative methods are more descriptive, and the inferences can be drawn quite easily from the obtained data .

Qualitative research methods originated in the social and behavioral research sciences. Today, our world is more complicated, and it is difficult to understand what people think and perceive. Online research methods make it easier to understand that as it is a more communicative and descriptive analysis .

The following are the qualitative research methods that are frequently used. Also, read about qualitative research examples :

1. One-on-one interview

Conducting in-depth interviews is one of the most common qualitative research methods. It is a personal interview that is carried out with one respondent at a time. This is purely a conversational method and invites opportunities to get details in depth from the respondent.

One of the advantages of this method is that it provides a great opportunity to gather precise data about what people believe and their motivations . If the researcher is well experienced, asking the right questions can help him/her collect meaningful data. If they should need more information, the researchers should ask such follow-up questions that will help them collect more information.

These interviews can be performed face-to-face or on the phone and usually can last between half an hour to two hours or even more. When the in-depth interview is conducted face to face, it gives a better opportunity to read the respondents’ body language and match the responses.

2. Focus groups

A focus group is also a commonly used qualitative research method used in data collection. A focus group usually includes a limited number of respondents (6-10) from within your target market.

The main aim of the focus group is to find answers to the “why, ” “what,” and “how” questions. One advantage of focus groups is you don’t necessarily need to interact with the group in person. Nowadays, focus groups can be sent an online survey on various devices, and responses can be collected at the click of a button.

Focus groups are an expensive method as compared to other online qualitative research methods. Typically, they are used to explain complex processes. This method is very useful for market research on new products and testing new concepts.

3. Ethnographic research

Ethnographic research is the most in-depth observational research method that studies people in their naturally occurring environment.

This method requires the researchers to adapt to the target audiences’ environments, which could be anywhere from an organization to a city or any remote location. Here, geographical constraints can be an issue while collecting data.

This research design aims to understand the cultures, challenges, motivations, and settings that occur. Instead of relying on interviews and discussions, you experience the natural settings firsthand.

This type of research method can last from a few days to a few years, as it involves in-depth observation and collecting data on those grounds. It’s a challenging and time-consuming method and solely depends on the researcher’s expertise to analyze, observe, and infer the data.

4. Case study research

T he case study method has evolved over the past few years and developed into a valuable quality research method. As the name suggests, it is used for explaining an organization or an entity.

This type of research method is used within a number of areas like education, social sciences, and similar. This method may look difficult to operate; however , it is one of the simplest ways of conducting research as it involves a deep dive and thorough understanding of the data collection methods and inferring the data.

5. Record keeping

This method makes use of the already existing reliable documents and similar sources of information as the data source. This data can be used in new research. This is similar to going to a library. There, one can go over books and other reference material to collect relevant data that can likely be used in the research.

6. Process of observation

Qualitative Observation is a process of research that uses subjective methodologies to gather systematic information or data. Since the focus on qualitative observation is the research process of using subjective methodologies to gather information or data. Qualitative observation is primarily used to equate quality differences.

Qualitative observation deals with the 5 major sensory organs and their functioning – sight, smell, touch, taste, and hearing. This doesn’t involve measurements or numbers but instead characteristics.

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

Qualitative data collection allows collecting data that is non-numeric and helps us to explore how decisions are made and provide us with detailed insight. For reaching such conclusions the data that is collected should be holistic, rich, and nuanced and findings to emerge through careful analysis.

• Whatever method a researcher chooses for collecting qualitative data, one aspect is very clear the process will generate a large amount of data. In addition to the variety of methods available, there are also different methods of collecting and recording the data.

For example, if the qualitative data is collected through a focus group or one-to-one discussion, there will be handwritten notes or video recorded tapes. If there are recording they should be transcribed and before the process of data analysis can begin.

• As a rough guide, it can take a seasoned researcher 8-10 hours to transcribe the recordings of an interview, which can generate roughly 20-30 pages of dialogues. Many researchers also like to maintain separate folders to maintain the recording collected from the different focus group. This helps them compartmentalize the data collected.
• In case there are running notes taken, which are also known as field notes, they are helpful in maintaining comments, environmental contexts, environmental analysis , nonverbal cues etc. These filed notes are helpful and can be compared while transcribing audio recorded data. Such notes are usually informal but should be secured in a similar manner as the video recordings or the audio tapes.

B. Qualitative data analysis

Qualitative data analysis such as notes, videos, audio recordings images, and text documents. One of the most used methods for qualitative data analysis is text analysis.

Text analysis is a  data analysis method that is distinctly different from all other qualitative research methods, where researchers analyze the social life of the participants in the research study and decode the words, actions, etc. 

There are images also that are used in this research study and the researchers analyze the context in which the images are used and draw inferences from them. In the last decade, text analysis through what is shared on social media platforms has gained supreme popularity.

Characteristics of qualitative research methods

• Qualitative research methods usually collect data at the sight, where the participants are experiencing issues or research problems . These are real-time data and rarely bring the participants out of the geographic locations to collect information.
• Qualitative researchers typically gather multiple forms of data, such as interviews, observations, and documents, rather than rely on a single data source .
• This type of research method works towards solving complex issues by breaking down into meaningful inferences, that is easily readable and understood by all.
• Since it’s a more communicative method, people can build their trust on the researcher and the information thus obtained is raw and unadulterated.

Qualitative research method case study

Let’s take the example of a bookstore owner who is looking for ways to improve their sales and customer outreach. An online community of members who were loyal patrons of the bookstore were interviewed and related questions were asked and the questions were answered by them.

At the end of the interview, it was realized that most of the books in the stores were suitable for adults and there were not enough options for children or teenagers.

By conducting this qualitative research the bookstore owner realized what the shortcomings were and what were the feelings of the readers. Through this research now the bookstore owner can now keep books for different age categories and can improve his sales and customer outreach.

Such qualitative research method examples can serve as the basis to indulge in further quantitative research , which provides remedies.

When to use qualitative research

Researchers make use of qualitative research techniques when they need to capture accurate, in-depth insights. It is very useful to capture “factual data”. Here are some examples of when to use qualitative research.

• Developing a new product or generating an idea.
• Studying your product/brand or service to strengthen your marketing strategy.
• To understand your strengths and weaknesses.
• Understanding purchase behavior.
• To study the reactions of your audience to marketing campaigns and other communications.
• Exploring market demographics, segments, and customer care groups.
• Gathering perception data of a brand, company, or product.

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

The basic differences between qualitative research methods and quantitative research methods are simple and straightforward. They differ in:

• Their analytical objectives
• Types of questions asked
• Types of data collection instruments
• Forms of data they produce
• Degree of flexibility

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Understanding Q-Methodology: Bridging the Gap Between Qualitative and Quantitative Research

By  Stella Smith, Ph.D.

Introduction

Among the myriad of methodologies, Q-methodology stands out as a unique approach that offers a nuanced understanding of subjectivity while maintaining the rigor of quantitative analysis (Damio, 2016; Herrington & Coogan, 2011). On April 2nd, the Research Methodology Group hosted a webinar focused on Q-methodology Essentials. In this blog post, we delve into the essence of Q-methodology, exploring its principles, applications, and significance in contemporary research. We will end with some suggestions for how to learn more about Q-methodology.

Q-methodology

Seeks to uncover subjective viewpoints or perspectives on a particular topic by systematically analyzing individuals' rankings of statements or items

What is Q-Methodology?

Q-methodology, developed by British physicist and psychologist William Stephenson, is a research technique that combines elements of both qualitative and quantitative methodologies (Stephenson,1953). At its core, Q-methodology seeks to uncover subjective viewpoints or perspectives on a particular topic by systematically analyzing individuals' rankings of statements or items (Sandling, 2022; Van Exel & De Graaf, 2005). Unlike traditional surveys or interviews, which aim to capture consensus or frequency of responses, Q-methodology focuses on understanding the diversity of opinions within a given population.

Principles of Q-Methodology

Central to Q-methodology is the notion of "subjectivity" – recognizing that individuals interpret the world differently based on their unique experiences, beliefs, and values. The process typically involves three main steps:

Statement Generation: Researchers compile a set of statements or items relevant to the topic under study. These statements should cover a wide range of viewpoints and perspectives to capture the diversity within the population.

Q-Sorting: Participants are presented with the statements and asked to rank them according to their level of agreement or preference. This process, known as Q-sorting, requires participants to make subjective judgments about the statements based on their personal viewpoints.

Factor Analysis: The Q-sort data from multiple participants are then subjected to factor analysis, a statistical technique that identifies patterns or "factors" representing clusters of similar viewpoints. Through factor analysis, researchers can uncover underlying dimensions of opinion within the dataset.

Applications of Q-Methodology

Q-methodology has found applications across various disciplines, including psychology, sociology, political science, and market research. Some common areas of application include exploring subjective perceptions, understanding stakeholder perspectives and market segmentation.

Significance of Q-Methodology

What distinguishes Q-methodology is its ability to reconcile the richness of qualitative data with the rigor of quantitative analysis. By acknowledging the subjective nature of human perception while employing robust statistical techniques, Q-methodology offers a holistic approach to understanding complex social phenomena (Herrington & Coogan, 2011).

Moreover, Q-methodology provides a platform for amplifying marginalized voices and uncovering minority viewpoints that may be overlooked in traditional research approaches. By embracing diversity and embracing subjectivity, Q-methodology fosters a more inclusive and comprehensive understanding of the world around us.

Want to know more?

Check out the full webinar on Q-methodology which is uploaded to the  Research and Methodology Group Teams  site. 

Schedule an  office hours appointment  with a methodologist to discuss your Q-methodology design.

Review the  Qmethod  website and  Operant Subjectivity - The International Journal of Q Methodology

Damio, S. M. (2016). Q Methodology: An Overview and Steps to Implementation. Asian Journal of  University Education, 12(1), 105.

Herrington, N., &, Coogan, J. (2011). Q methodology: an overview. Research in Teacher   Education, 1(2), 24-28.

Sandling, J. (2022). Q Methodology: Complete Beginner’s Guide. Available at   https://jonathansandling.com/q-methodology-complete-beginners-guide/

Stephenson W. The study of behavior: Q-technique and its methodology. Chicago: University of Chicago Press. 1953

Van Exel, J., & De Graaf, G. (2005). Q methodology: A sneak preview. Available at https://www.betterevaluation.org/tools-resources/q-methodology-sneak-preview

Stella Smith, Ph.D.

ABOUT THE AUTHOR

Dr. Stella Smith serves as the Associate University Research Chair for Center for Educational and Instructional Technology Research (CEITR).  She is also an Assistant Professor of Qualitative Research at Prairie View A&M University. A qualitative researcher, Dr. Stella Smith's scholarly interests focus on the experiences of  African American females in leadership in higher education; diversity, equity and inclusion of underserved populations in higher education, and P–20 educational pipeline alignment.  Dr. Smith is a strong advocate for social justice and passionate about creating asset based pathways of success for underserved students.

Dr. Smith was recognized with a 2014 Dissertation Award from the American Association of Blacks in Higher Education and as part of the 2019 class of 35 Outstanding Women Leaders in Higher Education by Diverse Issues in Higher Education. Dr. Smith earned her PhD in Educational Administration with a portfolio in Women and Gender Studies from The University of Texas at Austin.

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Choosing a Qualitative Research Approach

Associated data.

Editor's Note: The online version of this article contains a list of further reading resources and the authors' professional information .

The Challenge

Educators often pose questions about qualitative research. For example, a program director might say: “I collect data from my residents about their learning experiences in a new longitudinal clinical rotation. If I want to know about their learning experiences, should I use qualitative methods? I have been told that there are many approaches from which to choose. Someone suggested that I use grounded theory, but how do I know this is the best approach? Are there others?”

What Is Known

Qualitative research is the systematic inquiry into social phenomena in natural settings. These phenomena can include, but are not limited to, how people experience aspects of their lives, how individuals and/or groups behave, how organizations function, and how interactions shape relationships. In qualitative research, the researcher is the main data collection instrument. The researcher examines why events occur, what happens, and what those events mean to the participants studied. 1 , 2

Qualitative research starts from a fundamentally different set of beliefs—or paradigms—than those that underpin quantitative research. Quantitative research is based on positivist beliefs that there is a singular reality that can be discovered with the appropriate experimental methods. Post-positivist researchers agree with the positivist paradigm, but believe that environmental and individual differences, such as the learning culture or the learners' capacity to learn, influence this reality, and that these differences are important. Constructivist researchers believe that there is no single reality, but that the researcher elicits participants' views of reality. 3 Qualitative research generally draws on post-positivist or constructivist beliefs.

Qualitative scholars develop their work from these beliefs—usually post-positivist or constructivist—using different approaches to conduct their research. In this Rip Out, we describe 3 different qualitative research approaches commonly used in medical education: grounded theory, ethnography, and phenomenology. Each acts as a pivotal frame that shapes the research question(s), the method(s) of data collection, and how data are analyzed. 4 , 5

Choosing a Qualitative Approach

Before engaging in any qualitative study, consider how your views about what is possible to study will affect your approach. Then select an appropriate approach within which to work. Alignment between the belief system underpinning the research approach, the research question, and the research approach itself is a prerequisite for rigorous qualitative research. To enhance the understanding of how different approaches frame qualitative research, we use this introductory challenge as an illustrative example.

The clinic rotation in a program director's training program was recently redesigned as a longitudinal clinical experience. Resident satisfaction with this rotation improved significantly following implementation of the new longitudinal experience. The program director wants to understand how the changes made in the clinic rotation translated into changes in learning experiences for the residents.

Qualitative research can support this program director's efforts. Qualitative research focuses on the events that transpire and on outcomes of those events from the perspectives of those involved. In this case, the program director can use qualitative research to understand the impact of the new clinic rotation on the learning experiences of residents. The next step is to decide which approach to use as a frame for the study.

The table lists the purpose of 3 commonly used approaches to frame qualitative research. For each frame, we provide an example of a research question that could direct the study and delineate what outcomes might be gained by using that particular approach.

Methodology Overview

How You Can Start TODAY

• 1 Examine the foundations of the existing literature: As part of the literature review, make note of what is known about the topic and which approaches have been used in prior studies. A decision should be made to determine the extent to which the new study is exploratory and the extent to which findings will advance what is already known about the topic.
• 2 Find a qualitatively skilled collaborator: If you are interested in doing qualitative research, you should consult with a qualitative expert. Be prepared to talk to the qualitative scholar about what you would like to study and why . Furthermore, be ready to describe the literature to date on the topic (remember, you are asking for this person's expertise regarding qualitative approaches—he or she won't necessarily have content expertise). Qualitative research must be designed and conducted with rigor (rigor will be discussed in Rip Out No. 8 of this series). Input from a qualitative expert will ensure that rigor is employed from the study's inception.
• 3 Consider the approach: With a literature review completed and a qualitatively skilled collaborator secured, it is time to decide which approach would be best suited to answering the research question. Questions to consider when weighing approaches might include the following:
• • Will my findings contribute to the creation of a theoretical model to better understand the area of study? ( grounded theory )
• • Will I need to spend an extended amount of time trying to understand the culture and process of a particular group of learners in their natural context? ( ethnography )
• • Is there a particular phenomenon I want to better understand/describe? ( phenomenology )

What You Can Do LONG TERM

• 1 Develop your qualitative research knowledge and skills : A basic qualitative research textbook is a valuable investment to learn about qualitative research (further reading is provided as online supplemental material). A novice qualitative researcher will also benefit from participating in a massive online open course or a mini-course (often offered by professional organizations or conferences) that provides an introduction to qualitative research. Most of all, collaborating with a qualitative researcher can provide the support necessary to design, execute, and report on the study.
• 2 Undertake a pilot study: After learning about qualitative methodology, the next best way to gain expertise in qualitative research is to try it in a small scale pilot study with the support of a qualitative expert. Such application provides an appreciation for the thought processes that go into designing a study, analyzing the data, and reporting on the findings. Alternatively, if you have the opportunity to work on a study led by a qualitative expert, take it! The experience will provide invaluable opportunities for learning how to engage in qualitative research.

Supplementary Material

The views expressed in this article are those of the authors and do not necessarily reflect the official policy or position of the Uniformed Services University of the Health Sciences, the Department of the Navy, the Department of Defense, or the US government.

References and Resources for Further Reading

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

Published on 26.4.2024 in Vol 26 (2024)

Understanding Symptom Self-Monitoring Needs Among Postpartum Black Patients: Qualitative Interview Study

Authors of this article:

Original Paper

• Natalie Benda 1 , PhD   ; 
• Sydney Woode 2 , BSc   ; 
• Stephanie Niño de Rivera 1 , BS   ; 
• Robin B Kalish 3 , MD   ; 
• Laura E Riley 3 , MD   ; 
• Alison Hermann 4 , MD   ; 
• Ruth Masterson Creber 1 , MSc, PhD, RN   ; 
• Eric Costa Pimentel 5 , MS   ; 
• Jessica S Ancker 6 , MPH, PhD  

1 School of Nursing, Columbia University, New York, NY, United States

2 Department of Radiology, Early Lung and Cardiac Action Program, The Mount Sinai Health System, New York, NY, United States

3 Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, United States

4 Department of Psychiatry, Weill Cornell Medicine, New York, NY, United States

5 Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States

6 Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States

Corresponding Author:

Natalie Benda, PhD

School of Nursing

Columbia University

560 West 168th Street

New York, NY, 10032

United States

Phone: 1 212 305 9547

Email: [email protected]

Background: Pregnancy-related death is on the rise in the United States, and there are significant disparities in outcomes for Black patients. Most solutions that address pregnancy-related death are hospital based, which rely on patients recognizing symptoms and seeking care from a health system, an area where many Black patients have reported experiencing bias. There is a need for patient-centered solutions that support and encourage postpartum people to seek care for severe symptoms.

Objective: We aimed to determine the design needs for a mobile health (mHealth) patient-reported outcomes and decision-support system to assist Black patients in assessing when to seek medical care for severe postpartum symptoms. These findings may also support different perinatal populations and minoritized groups in other clinical settings.

Methods: We conducted semistructured interviews with 36 participants—15 (42%) obstetric health professionals, 10 (28%) mental health professionals, and 11 (31%) postpartum Black patients. The interview questions included the following: current practices for symptom monitoring, barriers to and facilitators of effective monitoring, and design requirements for an mHealth system that supports monitoring for severe symptoms. Interviews were audio recorded and transcribed. We analyzed transcripts using directed content analysis and the constant comparative process. We adopted a thematic analysis approach, eliciting themes deductively using conceptual frameworks from health behavior and human information processing, while also allowing new themes to inductively arise from the data. Our team involved multiple coders to promote reliability through a consensus process.

Results: Our findings revealed considerations related to relevant symptom inputs for postpartum support, the drivers that may affect symptom processing, and the design needs for symptom self-monitoring and patient decision-support interventions. First, participants viewed both somatic and psychological symptom inputs as important to capture. Second, self-perception; previous experience; sociocultural, financial, environmental, and health systems–level factors were all perceived to impact how patients processed, made decisions about, and acted upon their symptoms. Third, participants provided recommendations for system design that involved allowing for user control and freedom. They also stressed the importance of careful wording of decision-support messages, such that messages that recommend them to seek care convey urgency but do not provoke anxiety. Alternatively, messages that recommend they may not need care should make the patient feel heard and reassured.

Conclusions: Future solutions for postpartum symptom monitoring should include both somatic and psychological symptoms, which may require combining existing measures to elicit symptoms in a nuanced manner. Solutions should allow for varied, safe interactions to suit individual needs. While mHealth or other apps may not be able to address all the social or financial needs of a person, they may at least provide information, so that patients can easily access other supportive resources.

Introduction

This study focused on designing a culturally congruent mobile health (mHealth) app to support postpartum symptom monitoring, as the current practice does not adequately support patients in identifying the warning signs of pregnancy-related death (PRD). First, we describe the public health case for symptom monitoring and decision support for PRD, specifically among US-based, Black patients, a group that faces severe disparities [ 1 , 2 ]. Next, we discuss why the current mechanisms for symptom monitoring and decision support are insufficient. We then outline the existing solutions while also emphasizing the need for new interventions, particularly why those using a combination of mHealth and patient-reported outcomes (PROs) may be appropriate. Finally, we introduce a conceptual model used to accomplish our study objectives.

PRD and Associated Health Disparities

The pregnancy-related mortality ratio has increased by >200% in the United States in the past 2 decades, and in a recent review of PRDs, experts estimated that 80% of the deaths were preventable [ 3 ]. The Centers for Disease Control and Prevention (CDC) defines PRD as “the death of a woman while pregnant or within 1 year of the end of pregnancy from any cause related to or aggravated by the pregnancy” [ 4 , 5 ]. Mental health conditions (22.7%), hemorrhage (13.7%), cardiac and coronary conditions (12.8%), infection (9.2%), thrombotic embolism (8.7%), and cardiomyopathy (8.5%) have been cited as the most common causes for PRD [ 3 ]. Although the global maternal mortality rate has declined, the global rates are still high with 287,000 people dying following childbirth in 2020. There are significant disparities in maternal mortality based on a country’s income, with almost 95% of the cases occurring in low- and middle-income countries [ 6 ]. Stark disparities in pregnancy-related outcomes in the United States, such as PRD, exist based on race. Specifically, Black or African American (henceforth, referred to as “Black”) perinatal patients experience PRD 3 times more than White perinatal patients [ 1 , 2 , 7 - 10 ].

The disparities in maternal health outcomes experienced by Black patients in the United States are based on inequitable access to care, biased treatment, and inadequate communication, driven by systemic racism and all the cascading effects it creates. Black perinatal patients are significantly more likely to be uninsured and significantly less likely to have a usual source of medical care (eg, a primary care clinician) than White patients [ 7 , 10 ]. When Black patients seek care, they face implicit biases that negatively affect care quality and health outcomes [ 1 , 7 , 10 - 12 ]. Unsurprisingly, these biases have led to reduced trust in the health care system among Black patients [ 13 - 17 ]. Black patients also receive less patient-centered communication and feel that they have poorer access to communication with their medical team [ 10 , 18 , 19 ]. Our study aimed to improve the patient centeredness of information and support for Black patients in the postpartum period through a participatory design, an approach by which representative end users are involved throughout the design process [ 20 - 23 ]. While this study focused on Black postpartum patients in the United States, we believe that our findings may provide insights for improving perinatal support for patients from minority groups globally.

Challenges to Supporting Symptom Recognition and Treatment Seeking Post Partum

Patients encounter several challenges recognizing concerning postpartum symptoms. First, the initial postpartum visit occurs 6 weeks after birth, and 86% of PRD cases occur within the first 6 weeks post partum [ 24 , 25 ]. Second, most strategies for improving postpartum outcomes focus on hospital-based solutions, which rely on people recognizing symptoms and contacting a health professional [ 7 ]. Most counseling regarding the warning signs of PRD occurs during the discharge process following delivery, when people are physically exhausted from childbirth and primarily focused on infant care [ 24 ]. As such, this is a suboptimal time for patient education about postpartum risk factors. Discharge nurses report spending <10 minutes on the warning signs of postpartum issues, and most nurses could not correctly identify the leading causes of PRD, making it unlikely that their patients could recognize the warning signs [ 26 ]. There are many measures for postpartum symptom reporting, but the most common instruments focus narrowly on specific mental health issues, many of which are not specific to postpartum mental health or postpartum health–related quality of life [ 27 ]. While these are helpful measures to use in a clinic or hospital setting, they do not provide real-time decision support regarding the full spectrum of severe symptoms that may be indicative of PRD.

Suitability of Different Solutions for Supporting Symptom Monitoring

mHealth can address the need for tailored, dynamic symptom monitoring and support. The Association of Women’s Health, Obstetric, and Neonatal Nurses and the CDC have developed 1-page summaries to help patients identify the warning signs of PRD, such as the Urgent Maternal Warning Signs (UWS) [ 28 , 29 ]. These tools represent a positive step toward improving symptom management, but these solutions do not provide real-time, tailored support. Telephone-based support staffed by health professionals has been demonstrated to decrease postpartum depression and improve maternal self-efficacy [ 30 - 33 ]. However, 24-hour hotlines can be resource intensive, and people may still experience bias when accessing these services. The goal of this study was to conduct a qualitative needs assessment for the Maternal Outcome Monitoring and Support app, an mHealth system using PROs to provide decision support for postpartum symptom monitoring.

Mobile phones offer a viable, inclusive option for intervention delivery for Black people of childbearing age. In 2020, data from the Pew Research Center indicate that 83% of Black people owned smartphones, which is comparable to smartphone ownership among White people (85%). Smartphone ownership is also higher among people aged <50 years (96%), which encompasses most postpartum patients [ 34 ]. However, Black people are twice as likely as White people to be dependent on smartphones for internet access [ 35 ]. mHealth-based apps for blood pressure and weight tracking during pregnancy have demonstrated success among diverse groups, providing evidence that mHealth may be an acceptable means for symptom reporting in the target population [ 36 - 38 ].

Symptom education and PRO-based interventions have demonstrated success in improving knowledge, self-efficacy, and outcomes. Use of PROs has improved symptom knowledge, health awareness, communication with health care professionals, and prioritization of symptoms in patients with chronic disease and cancer [ 39 - 44 ]. Multiple studies have also demonstrated that educational interventions regarding expected symptoms in the postpartum period can improve self-efficacy, resourcefulness, breastfeeding practices, and mental health [ 12 , 38 , 45 - 47 ]. However, given the issues related to trust and disparities in patient-centered communication, it is critical to understand Black patients’ perspectives about how such a system should be designed and implemented.

Conceptual Model

To study the issue of supporting symptom monitoring, we combined 2 theoretical frameworks ( Figure 1 ): the common sense model of self-regulation (health behavior) by Diefenbach and Leventhal [ 48 ] and the model of human information processing (human factors engineering) by Wickens [ 49 ]. The model by Diefenbach and Leventhal [ 48 ] depicts patients as active problem solvers with a mental model of their conditions. Patients process their symptoms, both cognitively and emotionally, and then evaluate whether action is needed [ 48 ]. The patient’s mental model of their condition, personal experiences, and sociocultural factors impact processing, evaluation, and action. In the information processing model by Wickens [ 49 ], action occurs in 2 steps—selection and execution [ 48 ]. Environmental or organizational factors also affect patients’ selection of actions and whether they can execute an action. For example, a patient may suspect that they should visit the emergency room but may not go because they do not have insurance, transportation, or childcare. Our qualitative inquiry investigated how to better support symptom processing and appropriate response selection, while also uncovering the barriers to action that may need to be mitigated.

The goal of this study was to identify the design and implementation needs of an mHealth-based symptom self-monitoring and decision-support system to support Black patients in determining when to seek care from a health professional for signs of PRD in the postpartum period. This tool will support both somatic and psychological symptoms given their complex, critical, and connected presentation. We used the described conceptual model in qualitative inquiry and pragmatic intervention design to provide contributions regarding the following: (1) relevant symptom inputs for postpartum support, (2) drivers that may affect symptom processing, and (3) how the previous 2 aspects highlight the design needs for symptom self-monitoring and patient decision support. To address our study objective, we conducted semistructured interviews with postpartum Black patients, obstetrics health professionals, and mental health professionals.

The study was conducted in 3 tertiary care hospitals and affiliated clinics within the same health system in New York City. The 3 hospitals, taken together, are involved in the delivery of >14,000 babies annually. All participants were either patients who received obstetric care in the included sites or health professionals affiliated with the sites.

Eligible patients were identified by the institutions’ research informatics team using electronic health record data. First, the patients’ providers consented to their patients being contacted, and patients’ charts were reviewed by the primary obstetrician or designate to ensure that the patient was eligible for the study and that they had a delivery experience that would allow them to participate in the interview without undue stress. Next, the patients were sent an invitation to participate via the email address listed in their record. We also posted fliers in 2 high-risk, outpatient obstetric clinics.

Obstetric and mental health professionals were eligible if they were affiliated with one of the institutions in the obstetrics or mental health department. Brief presentations were given at relevant faculty meetings, and participants were contacted individually via email or through departmental listserves.

Interested participants from all groups used a link to schedule a time to speak with a researcher.

Ethical Considerations

The study was approved by the affiliated medical schools’ institutional review board (protocol number 20-08022582). All participants provided written informed consent. Study data were coded (ie, all identifying information was removed) to protect participant privacy. Each participant was compensated US $50 for their time via a physical or electronic gift card.

Study Design and Sample

The study used semistructured interviews with 3 key stakeholder groups: recent postpartum Black patients, obstetric health professionals, and mental health professionals. Eligible patients were within 12 months post partum of a live birth, self-identified their race as Black or African American, and had at least 1 somatic or psychological high-risk feature associated with their pregnancy. High-risk features included attendance at a high-risk clinic for prenatal or postnatal care, inpatient hospitalization within 12 months post partum, a prescription of an antidepressant or benzodiazepine within 12 months of the pregnancy, or a new diagnosis of depression or anxiety within 12 months of the pregnancy. High-risk clinics treated various conditions, but the most common conditions were gestational hypertension and gestational diabetes.

We adopted an interpretivist qualitative research paradigm to study patient and health professionals’ perspectives of how symptom recognition and care seeking may be better supported [ 50 ]. Our methodological orientation involved directed content analysis, adopting an abductive reasoning approach. First, we used the previously specified conceptual model to construct questions and thematically categorize responses [ 48 ]. Then, we allowed unique subthemes to inductively emerge from the data collected [ 51 ].

Interview Guide Development

Interview guides were iteratively developed by our team of researchers with expertise in obstetrics, perinatal mental health, nursing, consumer informatics, inclusive design, and qualitative methods. The guide for each stakeholder group was reviewed and piloted before enrollment of the first participant. Interview guides were tailored for patients or health professionals but followed a similar structure, based on our conceptual model ( Figure 1 ), such that participants were first asked about barriers to and facilitators of processing symptoms cognitively and emotionally (eg, Do they notice the symptom or realize its severity?), making decisions about symptoms they are experiencing (ie, When to seek help from a health professional?), and taking action on problematic symptoms. Probing questions encouraged participants to elaborate on experiential, educational, sociocultural, organizational, environmental, or health systems–level drivers of patients’ symptom management. Then, participants were asked a series of questions related to their thoughts regarding the design of the mHealth system, including how to best report symptoms, the wording of system decision support, the desired level of involvement of the obstetrics health professionals, the means for facilitating outreach to a health professional, additional information resources, and preferences for sharing information included in the system with a trusted friend or family members. During this process, obstetrics and mental health professionals were also shown a handout that outlined the draft of the symptom management algorithm for the system being developed (CDC’s UWS) and asked if they would make any changes, additions, or deletions [ 29 ]. Full interview guides are included in Multimedia Appendix 1 .

Data Collection

All interviewees provided consent electronically before the interview. A PhD-trained qualitative research expert (NB) completing a postdoctoral study in health informatics and population health conducted all the interviews via Zoom (Zoom Video Communications) or telephone. Participants had the option to request an in-person interview, but none of them chose this option. Interviews lasted 30 to 60 minutes and were audio recorded. We explicitly described the study objectives to each participant before the interview. Following the interview, participants completed a demographics survey electronically. All electronic survey information was collected using REDCap (Research Electronic Data Capture; Vanderbilt University).

Data Preparation and Analysis

Audio recordings were converted into transcripts using an electronic software (NVivo Transcription; QSR International) and manually checked for accuracy by a study team member who did not conduct the initial interviews. We completed all data analyses using NVivo (versions 12 and 13), but we manually analyzed the data and did not use computer-aided techniques (eg, computerized emotion detection or autocoding).

Data were analyzed using thematic analysis and the constant comparative process [ 51 - 53 ]. Specifically, each analyst open coded the transcripts, by coding segments that pertained to the research questions, as opposed to coding all words and phrases. We used thematic analysis to detect the common and divergent needs for postpartum symptom monitoring. We chose this method over other approaches such as grounded theory or sentiment analysis because our needs were pragmatic to solution design, and we were not attempting to establish theory, describe phenomena, or represent collective feeling about a topic.

The first deductive analysis was conducted using an initial theoretical model derived from the common sense model by Diefenbach and Leventhal [ 48 ] and the model of human information processing by Wickens [ 49 ] ( Figure 1 ). To promote reliability, 2 coders in addition to the interviewer were involved in the analysis, and each transcript was first analyzed independently by at least 2 people (NB, SW, or SNdR), followed by meetings to resolve discrepancies based on consensus coding. The analysis team created initial codes based on the conceptual model and added new items to the codebook inductively (ie, post hoc instead of a priori, as they arose in the data). The team used NVivo to maintain a working codebook of themes, definitions, and relevant quotes derived from the data. The codebook was periodically presented to coinvestigators with expertise in obstetrics and perinatal psychiatry to improve external validity [ 51 , 52 ]. The sufficiency of sample size was assessed according to the theoretical saturation of themes encountered, specifically based on the need to add additional subthemes to the codebook [ 54 , 55 ]. After all the transcripts had been coded, at least 2 members of the coding team reviewed the data code by code to ensure that meaning remained consistent throughout the analysis and to derive key emerging themes [ 51 ].

Participant Characteristics

This study included 36 participants—15 (42%) obstetrics health professionals, 10 (28%) mental health professionals, and 11 (31%) recent postpartum Black patients. Table 1 presents the self-reported demographic information. As shown, 19% (7/36) of the health professionals and 11% (4/36) of the patients had missing data (ie, did not complete the questionnaire). Participants could also selectively choose not to answer questions. “Other” affiliations were possible for health professionals because those who had a secondary affiliation with one of the included sites but primary affiliation with another organization were eligible.

a N/A: not applicable.

b Health professionals’ self-reported role of resident psychiatrist, chief resident in psychiatry, psychologist, and patient care director was combined into the other category for analysis purposes.

Structure of Themes

Our initial theoretical model, derived from the common sense model by Diefenbach and Leventhal [ 48 ] and the model of human information processing by Wickens [ 49 ] ( Figure 1 ), described that patients experience some inputs (psychological and somatic symptoms of PRD). Then, there is a series of drivers that affect how patients cognitively and emotionally process (eg, notice and realize symptom severity), make decisions about, and act on symptoms they are experiencing. The nature of these symptoms, how they are processed, how decisions are made, and how they are acted upon then drive a conversation regarding the design needs for symptom monitoring and decision support for PRD. The emerging themes were organized into the following categories: (1) symptoms of PRD; (2) drivers of processing, decision-making, and action; and (3) design needs for a symptom-reporting and decision-support system. Quotes are labeled with study-specific identifiers: OB denotes obstetric health professional, MHP denotes mental health professional, and PT denotes patient.

Inputs: Psychological and Somatic Symptoms of PRD

Concerning and routine symptoms were reported both from a psychological and somatic perspective. Sometimes, the distinction between routine and concerning symptoms was clear. Other times, it was more challenging to differentiate routine versus concerning symptoms particularly because they were related to psychological health. Mental health professionals also noted the challenge that routine symptoms can progress to something more serious over time:

In my mind, like normal becomes abnormal, when there is any kind of functioning [loss] that like withstands two to three weeks. [MHP 04]

We really hear a lot about postpartum depression and stuff...A lot of women think...postpartum depression is you just don’t want to. You don’t have it. You go into depression where you can’t take care of your child and you don’t want to hold your child. You don’t feel connected to your child. And I learned...it can be so many different things. [PT 09]

A clear distinction was not always present between psychological and somatic symptoms:

If someone...has pain in their chest or shortness of breath, the first thing you want to think about is it sort of like clots and other kind of physiologic reasons for that. Those are also very implicated and sort of obviously [associated with] panic attacks and anxiety. So, I think though those symptoms are also relevant of physical symptoms, [they] are also relevant for mental health. [MHP 05]

Drivers of Processing, Decision-Making, and Action Based on the Symptoms Experienced

Several drivers were reported to affect symptom processing (ie, whether they noticed the symptom and its severity), patients’ capacity to decide what should be done (ie, make decisions), and whether they were able to act on concerning symptoms ( Table 2 ).

Table 2 presents exemplary quotes for emerging themes under a single driver, but many quotes were coded under multiple drivers in our analysis process. The following passage, for example, highlights how self-perception, sociocultural concerns, and the health system can overlap to present a complex set of factors that may prevent women from receiving the care they need for the symptoms they are experiencing:

A lot of times I think that does get overlooked because people feel like, well, you’re OK, you’re fine. But what research shows us is that especially for Black women, it really doesn’t matter how much money you make or your income level, like our postpartum and perinatal health outcomes are the same across the board, which is really detrimental. So, yeah, I think they get overlooked because of that. I think they get overlooked or we get overlooked in the health care system. But I also think we get overlooked by our family and friends because we’re the strong ones. So, if anybody can deal with this, it’s you. [MHP 10]

a MHP: mental health professional.

b PT: patient.

c OB: obstetric health professional.

Design Needs for a Symptom-Reporting and Decision-Support System

Obstetric health professionals, mental health professionals, and patients discussed multiple needs for improved PRD symptom reporting and decision support. The key design requirements are embedded and italicized in the following text.

Participants generally agreed that although the proposed system focuses on postpartum symptoms, it would be advantageous to introduce the system during pregnancy, particularly in the third trimester :

You have to reach women before they give birth. They might look, they might not look, they might look at it and be concerned. But then they might forget about it and not have time to call. Those first six weeks are really chaotic. [MHP 06]

I think in the third trimester would be great because often we don’t really have anything to talk about in the office. It’s very quick visits like blood pressure and you’re still pregnant and we’re just waiting. And so, I think and they start to have a lot of questions about like, well, when I get home and how’s this going to go? So, I think that time is a good time. We’re all kind of just waiting for labor to happen or full term to get there, and this kind of gives them something to feel like they can prepare for. [OB 08]

Patients were open to reminders regarding entering symptoms they were experiencing, and participants described a desire for just-in-time symptom reporting and decision support, so that they could get quick feedback as they were experiencing the symptoms:

When people get home so much in their life has changed. And it’s probably a very hectic time. So maybe I think that’s a great idea reaching out again, either a few days or a week later to make sure they’re really able to use it and engage with it to the extent that’s helpful to them. [OB 02]

I think it would be a good idea to have like a system where you can report whenever you want. [PT 03]

I think for me, I would say in the moment. But then also having something at the end of every week to just, you know, to check in with yourself. I think that would be good as well. [PT 09]

In addition to considerations about how symptoms would be recorded, participants stressed the importance of the wording of the decision-support messages that patients receive . For messages that inform the patient that their symptom did not seem to require immediate medical attention, it was important to ensure that the patient still felt heard and that they did not leave the interaction feeling stuck with nothing to do regarding a symptom that was concerning to them:

Reframe the message. You know...we apologize that you were experiencing this. We just want to reassure you that this is normal. [PT 01]

[You] don’t want to make anyone feel like their feelings aren’t valid because that’s a horrible thing, especially in health care, especially if a person is convinced that something is wrong with them and you’re telling them that it’s normal and is perfectly fine. So, in that situation, I would just, depending on what the issue is, I would also share information of what to look out for. [PT 05]

The first thing is that it’s normal, but also something that you want to be able to do for comfort. For me, I don’t have to do too much, especially if I’m having anxiety, like if I get a text back that says here are some things you can do in this very moment to handle it. And then also, here are some links or information that you can also look up. [PT 09]

In the events where a concerning symptom was reported and it was recommended that the patient should reach out to a health professional, importance of conveying a sense of urgency without scaring the patient:

You don’t want to scare people, but it’s kind of hard to get around that when something is serious, and you don’t want to dumb it down. [PT 01]

Participants wanted multiple, easy-to-do methods for connecting with their health professional team, including having the number to call pop up, scheduling a time for someone to call them, and being able to start a live web-based chat:

I like all the options, especially that form or chat you can have like, you know, those online chat where like you really chatting with someone for those who like the type. I’m the type of person I just want to make a phone call, right? So, like for me, [it] will be a call. Maybe say maybe if it’s five, five or ten minutes then that will be great. Like especially, it’s going to make me feel like, OK, there’s someone out there that will care about my health. [PT 06]

However, participants noted that they would prefer not to use a symptom-reporting and decision-support tool, but instead reach out directly via phone if they were experiencing issues.

Participants, particularly mental health professionals, described a need for improved nuance or details regarding the different psychological symptoms patients could experience that are indicative of severe mental health issues:

Thoughts of hurting yourself or someone else is a good one...I would say I would add difficulty bonding. It would add something about not being able to sleep, even if you could sleep, you know, like or your anxiety that doesn’t go away, that changes your behavior. So, it changes the way that you interact with the baby or kind of do childcare. I guess I would want to say something about. psychotic thoughts, like fear that someone else may be hurting you or...recurrent worries or anxieties that don’t go away. [MHP 02]

Patients had differing opinions regarding whether the system should be integrated with other health technologies, particularly the patient portal:

I love the patient portal. I was able to be traveling to reach out to my OB, to reach out to all, you know, the nurses and stuff like that and just experience things that I needed. [PT 09]

I feel like...it’s an integral part of my medical history. So, even if it may seem somewhat insignificant for whatever reason, I would still want to have access. [PT 09]

I didn’t find it [the patient portal] very helpful... [PT 03]

On the basis of the feedback from health professionals that it may be challenging for postpartum patients to process and recognize certain symptoms, especially those related to mental health, we explored whether patient participants would be open to sharing educational information about symptoms to expect (rather than sharing the actual symptom reports) with trusted friends or family members. Similar to other design considerations, results were mixed, but it seemed helpful to have a patient-driven option for sharing symptom-related educational information with chosen friends or family members :

I think that there’s so much going on it would help to have someone with a different perspective equipped with this information. [PT 02]

There’s a lot of shame that comes with this. I’m not sure people would actually want other people to know. I can’t speak for the majority, but I didn’t really want people to know because I don’t want the kind of energy that came with people knowing. [PT 05]

We also discovered the competing needs of balancing the patient’s desire for their health professionals to be involved in symptom reporting with the need to avoid significant increases to health professional workload :

I sort of wonder from the health care provider perspective, how involved is the provider in that in the app? Like, do they get like a PDF of all the information? Is that more work for the provider? How does the provider interpret that data? [MHP 03]

I feel like they [the health professional] should be super involved. Especially because I’m not just going off of my experience because, you know, I don’t want to feel like they’re not really like I’m experiencing. And so, it’s scaring me. So, I just want to know that, you know, you’re hands on with everything. [PT 01]

Finally, the participants desired information beyond PRD symptoms to entice them to use the system . They were supportive of including various types of information, such as breastfeeding support resources, milestones and information regarding their child, other websites and apps with trusted maternal and child health information, further support resources for how they feel mentally, and links to social services (eg, food, housing, or other assistance).

Principal Findings

In this qualitative study, we interviewed obstetric health professionals, mental health professionals, and Black postpartum patients. Our findings helped to identify the design and implementation needs of an mHealth-based, symptom self-monitoring and decision-support system designed to support Black patients in determining when to seek care from a health professional for signs of PRD in the postpartum period. We encountered important findings related to (1) inputs, including psychological and somatic symptoms; (2) drivers of processing, decision-making, and action based on the symptoms experienced; and (3) design needs for a symptom-reporting and decision-support system. We have discussed how our findings may be helpful to other postpartum populations as well as the implications of our study for patient decision-support in other clinical settings.

First, our findings related to symptom inputs revealed the challenges caused by the overlapping presentation of somatic and psychological symptoms. This provides support for our approach of including psychological and somatic issues in a single app, particularly given that mental health conditions are a leading cause of PRD. A 2021 review found 15 PRO measures for assessing postpartum recovery. The measures typically focused on mental health or health-related quality of life, but few included both psychological and somatic outcomes, and none were targeted for PRD, such as the system [ 56 ].

Moreover, related to symptom inputs, we found that current tools for pinpointing severe symptoms, such as the CDC’s UWS did not provide sufficient nuance for concerning psychological symptoms. Symptom-reporting tools for PRD will either need to consider incorporating structured assessments, such as the Edinburgh Postnatal Depression Scale (EPDS) [ 56 ], or incorporating additional symptoms. The latter approach may have advantages as the EPDS focuses on depression (while providing subscales for anxiety) and PROs evaluated for use with anxiety disorders have limitations [ 57 ]. Furthermore, the EPDS has been validated in in-person laboratory settings but not in community settings or for web-based entry [ 58 ]. We must also consider how mistrust in the health system may lead to less truthful answers. Issues expressed around stigma related to mental health indicate that the way in which these symptoms are elicited may require further assessment to promote the normalcy of the symptoms and improve candid reporting. Technology-based approaches for supporting perinatal mental health have been described as uniformly positive but having limited evidence for use [ 59 ], suggesting that further exploration is needed in this area, also considering how adding somatic issues may be perceived by patients.

Second, there were several drivers that affected symptom processing, decision-making, and action that cannot typically be solved through a symptom-reporting and decision-support system. Challenges related to self-perception and lack of experience or expectations may be addressed based on the wording for how the symptoms are elicited and by providing concise, easy-to-understand depictions of what should be expected versus what are the causes for concern. However, many of the other issues described related to sociocultural, financial, and environmental factors and the health systems’ systemic racism issues cannot be addressed directly in a simple PRO-based app and decision-support system. Directly addressing these issues will likely require more systematic, multipronged approaches. Therefore, it seems advisable to couple patient decision-support aids with other social support interventions for perinatal health [ 60 , 61 ].

Drivers of processing, decision-making, and action are still important contextual elements to be considered in the design of the system. Another study tailoring an mHealth app for Latina patients to support health during pregnancy also found it important to address issues related to financial barriers, social support, health care accessibility, and cultural differences [ 62 ]. Our best attempt to address these issues may be to promote information transparency and inclusive design. For example, there may be a “frequently asked questions” section of an app, where patients can explore things such as supportive resources for childcare while they seek medical attention or information they may show their friends or family members regarding postpartum symptoms of concern. The system may also use common human-computer interaction principles, such as information filtering [ 63 ] and organizing the suggested resources (eg, for mental health care) based on whether they accept the patient’s insurance. The built environment can also be changed through the system, but it may offer mechanisms for remote monitoring, such as telemedicine-based support or linking the system to a blood pressure cuff, when clinically appropriate [ 64 , 65 ]. As noted, the system obviously cannot address issues related to systematic racism directly [ 66 ]. Instead, we used a participatory design approach, with the hope that the nature of the information presented may be more patient centered, acceptable, and better aligned with the beliefs and values of Black patients [ 67 ]. Issues related to systematic racism have commonly been described in the US health care system, but structural inequities also exist on a global scale. Future studies should investigate how our findings regarding design needs may extend to other minoritized perinatal patient groups.

A systematic review of patient decision aids for socially disadvantaged populations across clinical settings found that such tools can improve knowledge, enhance patient-clinician communication, and reduce decisional conflict [ 68 ]. However, descriptions of patient decision aids focus on the type of tool (eg, paper vs digital), how it was delivered, when it was delivered, and by whom, as opposed to describing the content the aid provides. Therefore, it is challenging to determine how other decision-support tools have addressed information regarding environmental, financial, or health system–level factors that may affect care seeking based on the decision aid. Some tools seem to address sociocultural needs by tailoring to the target population, but the aforementioned systematic review did not find differential effects on outcomes when tools were tailored versus not tailored [ 16 ]. Future studies on patient decision aids may benefit from including non-symptom related information. Providing appropriate informational support may involve a deeper study of the systemic needs that patients may have, even if these needs may not directly be addressed by the decision aid.

Third, descriptions of the design needs for PRD symptom monitoring revealed that there is likely not a one-size-fits-all solution related to reminders, involvement of health professionals, and how the tool is incorporated with other systems (eg, the patient portal). “User control and freedom” and “flexibility of use” are two of the key items in commonly used heuristics for user interface design [ 69 ]; therefore, it is important to include options for customization and varied but safe pathways for interaction with the proposed system. For example, some participants described that they may not be likely to access the symptom-reporting system through the patient portal. Although there may be safety and convenience-related reasons for having the system as part of the patients’ medical record, if the patient chooses, the system could, on the front end, appear more like a stand-alone app than something that must be accessed through the patient portal. Patients also had varying opinions related to how they may want to reach out to a health professional if a problematic symptom was reported. These preferences may differ from instance to instance; therefore, it is helpful to ensure that patients have a choice regarding how to reach out, but system designers must also create workflows with feedback loop, so that patients who are reporting problematic symptoms are not missed (ie, if patients do not reach out themselves, they never receive attention). Patient-level customizations and options for interaction also respects patients as individuals and may promote patient-centered interactions.

Furthermore, related to design needs, participants indicated that the wording of the decision-support messages was critical. Specifically, for reports that did not include currently urgent symptoms, it was important that the message still conveyed support and validation, clarified that the patient could still reach out for help, and provided additional means for managing their symptoms, so the patient did not feel frustrated by their report [ 70 ]. Regarding messages that recommended patients to reach out to their health professional team, it was crucial to note what the symptom meant (eg, what kind of disease it could indicate), encourage the patient to reach out without increasing anxiety, and provide different avenues for easy outreach. Going forward, we plan to incorporate the aforementioned elements into the messages built into the system. We will then complete additional acceptance and comprehension testing with a larger sample of postpartum patients. These findings also indicate that care must be taken in translating such tools, and the translated materials should be reviewed with the target end user groups before implementation. This may mitigate unintended consequences or inadvertent inclusion of language that does not support the needs of minoritized groups.

Strengths and Limitations

Our study highlighted the limitations and areas that would benefit from further exploration. First, our study involved recruitment sites that were within a single health system in New York City. Second, while we achieved thematic saturation of qualitative themes (a means for determining sample sufficiency in qualitative studies) [ 54 , 55 ], our conclusions are based on a sample of 36 participants from 3 stakeholder groups. Third, given the documented disparities, we deliberately focused on the needs of Black postpartum patients, but this may not represent the needs of the postpartum patients of other races. Furthermore, our sample should not be viewed as encompassing the opinions of all Black postpartum patients. Our findings revealed the need for individual customization and varied interaction patterns on a case-by-case basis. Fourth, all interviews were conducted remotely (via Zoom or telephone), which can have effects on the interaction. On the one hand, it may be harder to connect with the interviewee, and on the other hand, people may feel more anonymous and comfortable with sharing information. Finally, although we attempted to promote external validity through the review of the coding scheme by a subject matter expert, we did not have the opportunity to perform triangulation of the findings by returning the results to participants. To address these limitations, it would be beneficial to survey a larger group of postpartum patients, powered to assess the differences based on race and ethnicity. This would allow us to come to a stronger consensus regarding design choices, assess whether there are differences in design needs or preferences, and gain feedback from patients in areas outside New York City. Future studies may also explore how other underserved groups, such as those with limited English proficiency, may benefit from tailored symptom self-monitoring and decision support.

Conclusions

In this qualitative study regarding postpartum symptom monitoring and decision support, we found that the current structured reporting measures do not include the combination of somatic and psychological symptoms that may be indicative of severe outcomes in the postpartum period. While not explicitly related to symptom reporting and decision support, patient decision aids, particularly those focusing on minoritized groups, should consider how the aids may be coupled with other structural support interventions or, at least, information about how other resources may be accessed. As stated in the commonly accepted design heuristics, we also found that user control and freedom unsurprisingly remain important for a patient decision-support aid for Black postpartum patients. Finally, decision aid–related phrases must take care to convey urgency without inducing anxiety when action may be indicated and consider respect and empathy for the patients’ symptoms when action may not be indicated to ensure that they do not feel unheard and are empowered to report new or worsening symptoms.

Acknowledgments

This study was supported by the National Institute on Minority Health and Health Disparities (K99MD015781; principal investigator: NB).

Data Availability

The data sets generated and analyzed during this study are not publicly available due to institutional review board regulations but are available from the corresponding author on reasonable request.

Authors' Contributions

NB conceptualized the study and acquired funding under the advisement of RBK, LER, AH, RMC, and JSA. NB collected the data. NB, SW, and SNdR analyzed the data with input from all other authors. ECP completed the literature review and descriptive analysis of participants’ characteristics. NB drafted the paper and received substantial inputs from all other authors.

Conflicts of Interest

LER is an Up to Date contributor and an advisory board member for the New English Journal of Medicine, and Contemporary OB/GYN. She has also been a speaker for Medscape is an an expert reviewer for Pfizer on the RSV Vaccine. AH is an Up to Date contributor, a co-founder and medical consultant for Iris Ob Health, and a consultant for Progyny.

Semistructured interview guide questions for patients and health professionals.

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Abbreviations

Edited by A Mavragani; submitted 22.03.23; peer-reviewed by C Laranjeira; comments to author 15.01.24; revised version received 20.02.24; accepted 08.03.24; published 26.04.24.

©Natalie Benda, Sydney Woode, Stephanie Niño de Rivera, Robin B Kalish, Laura E Riley, Alison Hermann, Ruth Masterson Creber, Eric Costa Pimentel, Jessica S Ancker. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 26.04.2024.

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

Artificial intelligence in qualitative research methods

A one-day community-building gathering.

• Starts: 09:30, 26 April 2024
• Ends: 16:00, 26 April 2024
• Location: BI - campus Oslo, room: A2-Red 13
• Contact: Renate Kratochvil ([email protected])

The purpose of this event is to bring together qualitative researchers from different parts of Norway, other Nordic countries, and beyond. The main objective is to establish relationships, learn from each other, and build a community. 

During the day, you will hear from some prestigious scholars, learn what others are working on, receive (and give) feedback on work in progress, and socialize with like-minded colleagues. 

This year, our main focus will be on the utilization of AI and machine learning in qualitative research. The recent advancements in these technologies present an array of opportunities and challenges for qualitative researchers and their traditional skills, as they can automate  the processes of data collection, analysis, and presentation of findings. Through this event, we aim to delve deeper into the current hype surrounding AI and its possible implications for qualitative research. 

Established scholars, early career researchers, and PhD students from all parts of Norway, other Nordic countries, and beyond are welcome to attend.

Keynote speakers

Catherine Welch, Katharina Cepa, Heidi Karlsen and David Morgan.

Work in progress

If you want to receive feedback on your work in progress (any management topic),  please share a document of up to 2,000 words by April 16th. We welcome both early-stage ideas and proposals, as well as more developed drafts.

Participation is free, coffee & tea will be served.

The event is organized jointly by BI Qualitative Research Forum (Renate Kratochvil, Davide Nicolini & Victor Renza) and NHH (Inger Stensaker, Vidya Oruganti).

Provisional Programme

Room: A2 - Red 13

• Key notes by Catherine Welch (Trinity), Katharina Cepa (VU), Heidi Karlsen (BI) & David Morgan (Portland, zoom)
• Research speed dating
• Feedback on participants papers (Round  tables, any topic)
• AI Showcasing discussions

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