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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.

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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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The Oxford Handbook of Qualitative Research

Patricia Leavy Independent Scholar Kennebunk, ME, USA

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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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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

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Muhammad Hassan

Researcher, Academic Writer, Web developer

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Research methods--quantitative, qualitative, and more: overview.

• Quantitative Research
• Qualitative Research
• Data Science Methods (Machine Learning, AI, Big Data)
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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!

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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.
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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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Traditions and innovations in qualitative criminological research methods

• Published: 25 April 2024

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• Rita Faria   ORCID: orcid.org/0000-0003-0093-0550 3  

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In recent years, qualitative research methods in criminology have experienced a notable resurgence. This is evidenced by various scholarly endeavors, including the publication of works such as ‘Qualitative Research in Criminology: Cutting-Edge Methods’ (edited by Faria & Dodge, 2022 ), ‘ Liquid Criminology. Doing imaginative criminological research ’ (edited by Hviid Jacobsen & Walklate, 2016 ), ‘The Routledge Handbook of Qualitative Criminology ’ (edited by Copes & Miller, 2015 ), ‘ Qualitative Research in Criminology’ (Treadwell, 2019 ). The establishment of journals such as Qualitative Criminology and initiatives like the Working Group on Qualitative Research Methodologies and Epistemologies at the European Society of Criminology, or the the Qualitative Research Network in Criminology & Criminal Justice (QRN-CCJ) also signify a renewed recognition of the importance of qualitative approaches in understanding complex criminologically relevant phenomena. More recently, the CrimRxiv Consortium started a curation hub on qualitative criminology aimed at spotlighting studies based on non-numeric data.

Diverse criminological subfields such as global and green criminology, cultural criminology, and narrative criminology, have not only enriched our understanding of the respective topics but have also paved the way for innovative qualitative methodologies. Creative, reflexive and interventionist epistemologies and methodologies proved to be prerequisite, in order to imaginatively (Mills, 1959 ; Young, 2011 ) understand the contemporary social harms of dislocation, surveillance, incarceration, impoverishment, mind-numbing consumerism, experiences of uprooting and existential uncertainty, environmental degradation, global pandemics, the dynamics of social movements, and polarization. Moreover, research into the ever more present online world and online identities, the call for new approaches to data collection and analysis, the use of sensory methods, co-creation strategies, appeals to sensitivity to diversity and reflexivity from researchers - all of this has influenced greatly the panorama in qualitative research, particularly so in the study of crime and deviance, victimization and harm, crime control and related topics.

However, despite many innovations, qualitative researchers continue to grapple with numerous challenges. This includes navigating ethical considerations and the relatively recent data protection regulations, accessing and recruiting participants for studies on sensitive topics, and overcoming difficulties in publishing (Dodge & Parker, 2023 ). Qualitative research remains labor-intensive and requires tailor-made approaches. Numbers still push policy, the field of criminology still suffers from ‘methodological fetisjism’ and is easily seduced by actuarial tendencies, in which dominant research methods contribute to mystification of social realities and the politics of everyday life (Ferrell, 2009 ; Young, 2011 ). To complement knowledge produced employing rather detached methods of criminological inquiry, the aim of qualitative approaches is to foreground meaning, performance, unpredictability, engagement, reflexivity, creativity and, eventually, progressive transformations. Of course, such approaches exhibit great variation across different subfields, epistemological traditions, and geographical contexts. This diversity highlights the need to critically interrogate familiar epistemological frameworks and research agendas shaped by Global-North perspectives. Therefore, this special issue of Crime Law and Social Change focuses on qualitative research ‘from the periphery.’

By periphery, we refer not only to marginalized topics and populations within criminological discourse but also to innovative methodological approaches and underrepresented geographic traditions. The collection of papers featured in this special issue embodies this commitment to exploring the ‘periphery’ of qualitative criminological research, explicitly offering broadly relevant methodological insights, drawing on authors’ research experiences. More subtly, it also intends to red flag the peripheric interest that scientific journals have in qualitative research.

The first paper, A farewell to the lone hero researcher: Team research and writing , Sveinung Sandberg and Lucero Ibarra Rojas challenge the archetype of the lone hero researcher and advocate for collaborative approaches to qualitative research. Drawing upon their experiences in Mexico and Norway, the authors argue for the importance of team research and writing, as a means of addressing power differentials and promoting diversity.

In Rich scholar, poor scholar: inequalities in research capacity, “knowledge” abysses, and the value of unconventional approaches to research David Rodriguez Goyes and May-Len Skilbrei examine material inequalities in research capacity and propose unconventional approaches to data collection. Their paper highlights the global disparities in knowledge production and advocates for innovative methods that democratize access to meaningful data, using examples from their research in Colombia and Russia.

Janeille Zorina Matthews’ contribution titled Creating the Demand for Better Crime Policy: Qualitative Frame Analysis as a Vehicle for Social Transformation explores the potential of Qualitative Frame Analysis (QFA) as a tool for shaping crime discourse and informing policy. By analyzing framing strategies in Antigua and Barbuda, Matthews demonstrates the transformative power of qualitative methodologies in challenging dominant narratives.

In Ethnographic semantics and documentary method in criminology. A combination of reconstructive approaches using the example of Municipal Law Enforcement Services Ina Hennen introduces the documentary method and ethnographic semantics as two complementary approaches, based on her research with German Municipal Law Enforcement Services. Through an ethnomethodological design, Hennen illustrates how these methodologies deepen our understanding of security practices in public spaces.

Next, in their Mapmaking as visual storytelling: The movement and emotion of managing sex work in the urban landscape , Sara Jordenö and Amber Horning-Ruf foreground visual storytelling methods. Their interdisciplinary approach combines psychogeography and mapmaking to elucidate the emotional and spatial dynamics of sex work in urban landscapes, offering insights into the lived experiences and social relations of sex workers.

Finally, an original approach is presented in Lorenzo Natali’s The social perception of environmental victimization. A visual and sensory methodological proposal . Natali proposes a visual and sensory methodology for studying environmental victimization, highlighting the perspectives of those affected by environmental harm and employs photo elicitation and itinerant soliloquy to deepen our understanding and challenge familiar perspectives.

The reality in which we set up our inquiries is ever evolving and so does the need to understand and respond to the current complexities of crime, control, conflicts, and threats. From the specter of totalitarianism to the existential threat of global warming, radicalization, and the challenges of artificial intelligence, the current sociopolitical landscape underscores the urgency of mobilizing engaged qualitative research to understand and address pressing issues. The ever-shifting nature of current social, political, and technological phenomena needs to be addressed by qualitative methods which, by their nature, are especially well-suited to offer new theories and explanations based on detailed and nuanced accounts of complex phenomena. In that sense, discussions of critical and creative qualitative methodologies such as the ones presented in this special issue serve, in the first place, as meeting spaces for researchers working on seemingly distant topics, as fora for addressing epistemological and ethical questions and reimagining the boundaries of qualitative criminological research. Only last and least as mere methodological-technical discussions.

Data availability

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Copes, H., & Miller, J. M. (Eds.). (2015). The Routledge handbook of qualitative criminology . Routledge.

Dodge, M., & Parker, J. (2023). What now and how? Publishing the qualitative journal article. In R. Faria, & M. Dodge (Eds.), Qualitative Research in Criminology. Cutting-edge methods (pp. 241–253). Springer.

Faria, R., & Dodge, M. (Eds.). (2022). Qualitative Research in Criminology. Cutting-edge methods . Springer.

Ferrell, J. (2009). Kill method. A provocation. Journal of Theoretical and Philosophical Criminology , 1 (1), 1–22.

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Hviid Jacobsen, M., & Walklate, S. (Eds.). (2016). Liquid Criminology. Doing imaginative criminological research . Routledge.

Mills, C. W. (1959). The sociological imagination . Oxford University Press.

Treadwell, J. (2019). Qualitative Research in Criminology, In P. Atkinson, S. Delamont, A. Cernat, J.W. Sakshaug, & R.A. Williams (Eds.), SAGE Research Methods Foundations https://doi.org/10.4135/9781526421036847209 .

Young, J. (2011). Criminological imagination . Polity.

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Authors and affiliations.

Vrije Universiteit Brussel, CRiS (Crime in Society Research Group), Brussels, Belgium

Olga Petintseva

National Institute for Criminology and Criminalistics, Brussels, Belgium

CIJ – Center for Interdisciplinary Research on Justice, University of Porto, Porto, Portugal

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Petintseva, O., Faria, R. Traditions and innovations in qualitative criminological research methods. Crime Law Soc Change (2024). https://doi.org/10.1007/s10611-024-10153-x

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Implementation and early effects of medicaid policy interventions to promote racial equity in pregnancy and early childhood outcomes in Pennsylvania: protocol for a mixed methods study

• Marian Jarlenski 1 ,
• Evan Cole 1 ,
• Christine McClure 1 ,
• Sarah Sanders 2 ,
• Marquita Smalls 2 &
• Dara D Méndez 2  

BMC Health Services Research volume  24 , Article number:  498 ( 2024 ) Cite this article

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There are large racial inequities in pregnancy and early childhood health within state Medicaid programs in the United States. To date, few Medicaid policy interventions have explicitly focused on improving health in Black populations. Pennsylvania Medicaid has adopted two policy interventions to incentivize racial health equity in managed care (equity payment program) and obstetric service delivery (equity focused obstetric bundle). Our research team will conduct a mixed-methods study to investigate the implementation and early effects of these two policy interventions on pregnancy and infant health equity.

Qualitative interviews will be conducted with Medicaid managed care administrators and obstetric and pediatric providers, and focus groups will be conducted among Medicaid beneficiaries. Quantitative data on healthcare utilization, healthcare quality, and health outcomes among pregnant and parenting people will be extracted from administrative Medicaid healthcare data. Primary outcomes are stakeholder perspectives on policy intervention implementation (qualitative) and timely prenatal care, pregnancy and birth outcomes, and well-child visits (quantitative). Template analysis methods will be applied to qualitative data. Quantitative analyses will use an interrupted time series design to examine changes over time in outcomes among Black people, relative to people of other races, before and after adoption of the Pennsylvania Medicaid equity-focused policy interventions.

Findings from this study are expected to advance knowledge about how Medicaid programs can best implement policy interventions to promote racial equity in pregnancy and early childhood health.

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Rates of maternal and infant morbidity and mortality in the United States far exceed those of comparable nations [ 1 ]. The burdens of racist policies have produced vastly worse outcomes for Black and Native, relative to White, populations [ 2 ]. For example, Black and Native birthing people are more than three times as likely to experience pregnancy-related mortality compared to white birthing people [ 3 ]. For every pregnancy-related death, there are thousands of birthing people who experience severe morbidity; including stark racial disparities where Black populations are more likely to experience stroke or serious cardiovascular events sending them on a trajectory of adverse health outcomes beyond pregnancy [ 4 , 5 ]. We also see similar racial inequities for infant mortality and morbidity. These racial inequities are not adequately explained by individual behaviors or other socio-economic factors, but are a complex intersection of factors shaped by structural and social determinants [ 2 , 6 ], policies and institutions carrying out such policies [ 7 ]. There is a long history of structural racism that has resulted in practices and policies that have had a detrimental impact on Black and Indigenous populations in the United States [ 8 ].

State Medicaid programs are the largest single payer for pregnancy and birth in the US, covering 68% of births to Black people [ 9 ]. As such, Medicaid programs have great potential to implement structural interventions to advance racial equity in healthcare and health outcomes during pregnancy and postpartum [ 10 ]. Historically, Medicaid policies have promoted equality, that is, providing equal benefits to all regardless of the distribution of need [ 11 ]. An equity-focused policy approach, however, will direct resources toward improving health and well-being among those with the greatest need [ 12 ]. Unfortunately, a vast body of research conducted among Medicaid-enrolled populations shows that healthcare systems do not provide the same quality of obstetric care to Black people and other people of color, relative to white people [ 13 , 14 , 15 , 16 , 17 , 18 ].

Pennsylvania’s Medicaid program is the fourth-largest in the United States, with 3.5 million people enrolled and expenditures of $35.1 billion [ 19 , 20 ]. Past research in the Pennsylvania Medicaid program has demonstrated Black people were less able to access prenatal and postpartum care relative to those in other race groups [ 15 ]. Reporting from the Pennsylvania Maternal Mortality Commission shows that in more than half of the cases of pregnancy-associated deaths, the decadents were enrolled in Medicaid [ 21 ]. Similar to national figures, pregnancy-associated death was far more common among Black people vs. those of other races ( [ 21 ].

To ameliorate these racial disparities, Pennsylvania Medicaid is currently implementing two novel policies with the goal to advance racial equity in pregnancy and child health. The first, the equity incentive payment program, was initiated in 2020. The equity incentive payment program makes available approximately $26 million in Medicaid managed care organization (MCO) payments each year to plans that improve access to timely prenatal care and well-child visits among Black beneficiaries. The second is the maternity care bundled payment model, initiated in 2021, designed to provide incentives to obstetric providers across a wide range of pregnancy health outcomes and specifically incentivizes improvements among Black beneficiaries.

Although these policy approaches are unique, it is possible that other state Medicaid programs or other health insurers could learn from the policies and adapt or expand these approaches. Our research team will conduct a mixed-methods study to investigate the implementation and early effects of the two aforementioned policy changes on pregnancy and infant health equity. Our research aims are to: (1) evaluate implementation and early effects of the equity incentive payment program prenatal and early childhood healthcare outcomes and experiences among Black Medicaid beneficiaries; and (2) determine the extent to which an equity-focused maternity care bundled payment model affects racial equity in obstetric care and pregnancy health outcomes. To achieve these aims, we will draw on established partnerships between university researchers, community organizations, and policymakers to collect and analyze data. First, we will collect qualitative data with diverse stakeholders including Medicaid beneficiaries, MCO plan representatives, and pediatric and obstetric care clinicians to study implementation of these equity-focused policy changes. Second, we will use a community-partnered approach to develop a quantitative analysis plan of Medicaid administrative data for an estimated 167,000 birthing person-child dyads to estimate early effects of these policies. Our cross-disciplinary, community-engaged partnerships will enable us to triangulate how the healthcare policy structures of state Medicaid programs can be changed to promote racial equity in health.

Theoretical framework

The proposed research seeks to advance knowledge about the causes of, and structural interventions to improve, health and well-being among Black pregnant and parenting persons and their children in Medicaid. The theoretical model underlying this work is informed by foundational literature from a range of disciplines. First, it incorporates Critical Race Theory and Public Health Critical Race Praxis, which posit structural determinants, such as racism and other forms of oppression (e.g., sexism, classism, poverty), as fundamental causes of adverse social environments that interact to make certain populations more susceptible to illness and resulting in suboptimal health [ 22 , 23 , 24 , 25 , 26 ]. Second, it incorporates political science theory that dominant social definitions of populations shape group empowerment and resulting health policies and material benefits [ 27 ]. Third, it draws on new scholarship suggesting the necessity of studying social welfare policies with a critical race lens centering the beneficiaries’ lived experiences [ 11 , 28 , 29 ].

As depicted in Fig.  1 , our research project identifies both the Medicaid policy environment as well as the beneficiary experiences of the policy environment as upstream factors that influence healthcare organization and beneficiaries’ interaction with healthcare systems. In particular, we aim to facilitate and further enhance the connection between beneficiaries’ lived experiences and policy decision-makers through our collaboration with community partners. This connection can influence the policymaking process that shapes how care is delivered both at the managed care and healthcare provider levels. Healthcare utilization and quality are conceptualized as intermediate outcomes which may influence pregnancy and birth outcomes.

Conceptual model of the evaluation of structural interventions in Medicaid to promote racial equity in pregnancy and child health

Medicaid policy interventions

Nearly all Medicaid beneficiaries in Pennsylvania are enrolled in 1 of 8 Medicaid managed care plans, which manage the physical health care of enrollees and are subject to pay-for-performance requirements for healthcare quality measures. Currently, the Pennsylvania Medicaid program makes available 2% of total payments to MCO plans, contingent on MCO plan performance on 13 different healthcare quality metrics. An equity incentive payment program was added to this reimbursement scheme for two metrics in 2020: timely prenatal care and well-child visit utilization in the first 15 months of life (Fig.  2 ). Specifically, 2/13 (or 0.15%) of total payments are withheld for these two equity-focused metrics. MCO plans are assessed on overall performance and subsequently on the annual improvement on these measures among Black beneficiaries. MCO plans can be penalized (up to -0.12% of total payments) or rewarded (up to + 0.35% of total payments) for their performance on each of these two metrics.

Pennsylvania Medicaid’s health equity incentive payment program will condition payments to managed care organizations based on overall performance as well as improvement among Black beneficiaries

Second, Pennsylvania Medicaid implemented a maternity care bundled payment model in 2021 that considers outcomes among Black beneficiaries (Fig.  3 ). Under maternity care bundled payment models, obstetric providers are incentivized to meet a total cost threshold and quality metrics for prenatal and delivery care [ 30 ]. Specifically, providers and payers agree on a target cost for low- or average-risk perinatal care, including pregnancy, delivery, and postpartum care. If total payments to providers are lower than the target cost while maintaining certain quality metrics, providers and payers share those savings. Under Pennsylvania’s new model, providers are able to achieve shared savings based on quality metric performance, as well as a health equity score reflecting performance on those metrics among Black beneficiaries.

Pennsylvania Medicaid’s equity-focused maternity bundled payment model will allow for shared savings between obstetric care providers and managed care organizations, allowing for extra shared savings among providers whose Black patients experience better outcomes

Qualitative data Collection

To understand the interventions and responses to these policies, as well as related implementation barriers and facilitators, we will conduct interviews with each at least two representatives from each MCO ( n  = 18). We will partner with colleagues from the Department of Human Services (DHS) to identify relevant MCO representatives. Interviews will elucidate MCOs’ perspectives, processes used by MCOs to design their interventions (e.g., review of existing evidence, input from community members or providers who serve them), anticipated effects, and sustainability of these payment policy changes. The goal is for some of the results of these interviews to inform our understanding of the implementation process which will be further explored in the interviews and focus groups with clinicians and Medicaid recipients.

In collaboration with the Community Health Advocates (CHA) program led by Healthy Start Pittsburgh, as well as other community and organizational partners across the state, we will recruit current and former Medicaid beneficiaries for focus group participation. We aim to recruit  ∼  50 community participants and will purposively oversample Black participants and will aim to recruit people of all ethnicities who identify as Black and multi-racial in order to achieve our aims of elucidating the experiences of Black parenting and pregnant people in Medicaid. Inclusion criteria are: current pregnancy or pregnant within the past 2 years; current or former enrollment in Pennsylvania Medicaid and/or Healthy Start; and ability to complete the interview in English.

Finally, we will partner with colleagues from DHS to identify pediatric and obstetric health professionals for interviews regarding the maternity bundled payment program and key outcomes related to the equity incentive payment. We will also use Medicaid administrative data to identify providers who serve Black beneficiaries and invite them to participate. We will aim to interview at least 20 obstetric and pediatric healthcare professionals to elucidate their perspectives on how structural racism in medicine affects patient outcomes, and the types of Medicaid policy changes that should be implemented.

We developed separate focus group/interview guides for community members, MCO leaders, and healthcare professionals. Each interview guide consists of open-ended questions to elucidate participants’ experiences with Medicaid; desired policy changes in Medicaid (among beneficiary participants); perceived steps that would be useful to combat anti-Black racism in healthcare and social services (especially among Black participants); and perspectives about the new Medicaid policies. Additionally, the interview guides ask demographic questions regarding gender identity, race, and ethnicity. We will first pilot-test the guide with our research partners and Healthy Start CHAs for clarity of question wording. All interviews will take place in-person in a private office space, or over the phone or videoconference, according to participants’ preferences and COVID-19 protocols. The interviewer will describe study objectives to each participant, obtain consent, and each interview will be audio-recorded and the interviewer will take notes throughout. Interview audio recordings will be transcribed verbatim, and transcripts spot-checked against the audio recordings for accuracy. The audio recording files will then be deleted to protect confidentiality of participants.

Qualitative data analysis

Study data will be analyzed and reported using the Consolidated Criteria for Reporting Qualitative Research (COREQ) Framework [ 31 ]. To analyze data, we will use template analysis, which combines features of deductive content analysis and inductive grounded theory, thereby allowing us to obtain specific information while also capturing any new or unanticipated themes [ 32 ]. Two coders will separately code the first 3 interview transcripts, meet to compare codes, discuss inconsistency in coding approaches, and then alter or add codes. This iterative process will be repeated until the coding scheme is fully developed. The coders will independently code all transcripts, and any coding discrepancies will be resolved via discussion. Once coding is complete, synthesis of content will begin by organizing codes under broader domains (meta-codes) as well as sub-codes. The primary analysis will be to convey qualitative data, including the use of illustrative quotes.

Quantitative healthcare data and analysis

Administrative healthcare data from the Pennsylvania Medicaid program, with linked birthing person-child dyads, will be used to create our quantitative analytic data. Medicaid data include a census of enrollment, hospital, outpatient/professional, pharmaceutical, and provider data for all beneficiaries in the Pennsylvania Medicaid program. Importantly, data contain self-reported race and ethnicity that is provided at the time of Medicaid enrollment (< 2% missing); as well as time-varying data on 9-digit ZIP code of residence. Data also include the amounts paid from Medicaid MCOs to healthcare providers for all medical services. Table  1 shows baseline data from Pennsylvania Medicaid-enrolled persons with a livebirth delivery in 2019, overall and stratified by race of the birthing person. We will also conduct sensitivity analyses to examine dyads that are multi-racial.

We will employ a comparative interrupted time series (ITS) analyses with a nonequivalent comparison group to estimate policy effects. Specifically, we will evaluate: (1) the extent to which the equity incentive payment program improved timely prenatal care and well-child visits among Black beneficiaries, relative to those of other races; and (2) the extent to which healthcare provider participation in the equity-focused maternity bundled payment model improved healthcare and health outcomes among Black beneficiaries, relative to those of other races.

For Aim 1, outcomes include binary measures of initiating prenatal care in the first trimester, and children receiving at least 6 well-child visits in the first six months of life. We will compare outcomes among Black beneficiaries relative to those of other racial groups, post- relative to pre- implementation of the equity incentive payment program. For Aim 2, outcomes include a composite of prenatal care quality measures (social determinants of health screening, prenatal and postpartum depression screening and follow-up, immunization, screening and treatment for substance use disorders, postpartum visit attendance), gestational age and birthweight, and severe maternal morbidity [ 33 ]. For both aims, multivariable regression models will control for maternal age, ethnicity, parity, ZIP code of residence, MCO plan enrollment, Medicaid eligibility category (expansion, pregnancy, disability, or others), and indices of obstetric and pediatric clinical comorbidities [ 34 , 35 ].

Sensitivity analyses

Analyses are designed to estimate early effects of the policies and should be interpreted alongside the qualitative results regarding policy implementation and beneficiary experiences. One assumption of ITS analyses is that our comparison groups approximate a counterfactual scenario for the intervention groups [ 36 , 37 , 38 ]. Although trends in Black-White inequities in pregnancy and child outcomes have, unfortunately, persisted over time [ 39 ], the COVID-19 pandemic has differentially burdened Black and Latina/x people relative to other race and ethnic groups [ 40 , 41 ]. Effects of the pandemic on pregnancy outcomes are only just beginning of what is to be explored [ 42 ]. It is therefore possible that we will not be able to disentangle policy effects from effects of COVID-19. To address this limitation, we will employ area-level rates of COVID-19 infection as control variables and for Aim 1 (equity incentive payment) we will conduct a sub-analysis investigating trends in 2021 vs. 2020. We chose to evaluate outcomes for Aim 2 (maternity care bundled payment) only in 2021, comparing the statistical intervention of race*provider. Finally, our qualitative analyses will provide context on differential impacts of COVID-19, which will inform interpretation of the quantitative results.

This study was approved by the University of Pittsburgh Institutional Review Board (Study # 23090108).

This mixed-methods research will investigate the extent to which changes in the Pennsylvania Medicaid program are associated with improvements in access to medical care and health outcomes among Black pregnant and birthing persons and their children. Our past research found that Black childbearing people in Pennsylvania Medicaid consistently experienced worse healthcare and health outcomes, compared to those of other racial and ethnic groups [ 43 , 44 ]. Racism in healthcare and other systems manifests in systematically worse access to and quality of care and other services for Black childbearing people [ 8 ]. In addition to suboptimal healthcare experiences, historical policies and practices such as residential redlining and segregation have resulted in lower wealth attainment in Black communities resulting in inequities in neighborhood factors and perinatal health [ 45 , 46 , 47 ].

The policies under study involve modifying common Medicaid reimbursement arrangements– namely, pay-for-performance programs and maternity care bundled payments. The policies are modified to embed financial incentives for Medicaid health plans and healthcare providers to improve the quality of care and health outcomes for Black pregnant and parenting persons and their children. These are the first such payment policies, to our knowledge, that explicitly aim to promote racial health equity with an explicit focus on addressing inequities that affect Black and Indigenous populations in Pennsylvania.

Interest from policymakers in payment reforms to improve health equity has increased recently; however, information on the implementation and effects of such models is sparse [ 48 , 49 ]. Although several state Medicaid programs have adopted maternity care bundled payment models, prior models have not considered racial inequities in pregnancy outcomes [ 30 , 50 ]. In 2012, Oregon adopted regional health equity coalitions as part of the state Medicaid program’s transition to Coordinated Care Organizations (CCOs). CCOs were required and given support to develop strategies that would address racial health disparities within the Medicaid population, and the regional health equity coalitions included underrepresented stakeholders to guide CCOs in the development of these interventions. While CCOs did reduce Black-white differences in primary care utilization and access to care within 3 years of policy implementation, it did not impact disparities in emergency department utilization [ 51 ]. The current research project will add to the extant evidence on how Medicaid programs can use policy to promote racial health equity.

Our study is limited in investigating the direct effects of the pandemic on racial inequities in perinatal and infant health and the intersections between the effects of the pandemic and the effects of the aforementioned Medicaid policies. However, we will have the ability to look at changes in outcomes over time. Additionally, these payment reform interventions focus largely on transforming the financing and delivery of healthcare, drawing attention to the structural and social determinants of health in the healthcare system. It is estimated that medical care contributes 10–20% to health outcomes; health and well-being are also shaped by factors such as environmental and socioeconomic conditions [ 52 ].

This study will contribute to the current body of knowledge about the recent interventions in Medicaid focused on racial equity. Specifically, findings will shed light on how the equity-focused obstetric care policies are being implemented and provide an evaluation of effects on health outcomes. These results can be used for future adaptions of the policy interventions or to inform the adoption of such equity-focused policies in different geographic regions of the United States.

Data availability

No datasets were generated or analysed during the current protocol study.

Abbreviations

Managed Care Organization

Community Health Advocate

Coordinated Care Organization

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This study received funding from the National Institute of Nursing Research under award R01NR020670. The funder had no role in the study design, data collection or analysis, or decision to publish the study.

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Department of Health Policy and Management, University of Pittsburgh School of Public Health, 130 DeSoto St, A619, 15261, Pittsburgh, PA, USA

Marian Jarlenski, Evan Cole & Christine McClure

Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA

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Contributions

Jarlenski: Conceptualization; funding acquisition; investigation; methodology; supervision; writing-original draftCole: Conceptualization; data curation; investigation; resources; writing-reviewing and editingMcClure: Investigation; project administration; supervision; writing-reviewing and editingSanders: Investigation; methodology; visualization; writing-reviewing and editingSmalls: Investigation; project administration; visualization; writing-reviewing and editingMendez: Conceptualization; funding acquisition; investigation; validation; supervision; writing-original draft.

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Jarlenski, M., Cole, E., McClure, C. et al. Implementation and early effects of medicaid policy interventions to promote racial equity in pregnancy and early childhood outcomes in Pennsylvania: protocol for a mixed methods study. BMC Health Serv Res 24 , 498 (2024). https://doi.org/10.1186/s12913-024-10982-5

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Qualitative Methods in Health Care Research

Vishnu renjith.

School of Nursing and Midwifery, Royal College of Surgeons Ireland - Bahrain (RCSI Bahrain), Al Sayh Muharraq Governorate, Bahrain

Renjulal Yesodharan

1 Department of Mental Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Judith A. Noronha

2 Department of OBG Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Elissa Ladd

3 School of Nursing, MGH Institute of Health Professions, Boston, USA

Anice George

4 Department of Child Health Nursing, Manipal College of Nursing Manipal, Manipal Academy of Higher Education, Manipal, Karnataka, India

Healthcare research is a systematic inquiry intended to generate robust evidence about important issues in the fields of medicine and healthcare. Qualitative research has ample possibilities within the arena of healthcare research. This article aims to inform healthcare professionals regarding qualitative research, its significance, and applicability in the field of healthcare. A wide variety of phenomena that cannot be explained using the quantitative approach can be explored and conveyed using a qualitative method. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research. The greatest strength of the qualitative research approach lies in the richness and depth of the healthcare exploration and description it makes. In health research, these methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

Introduction

Healthcare research is a systematic inquiry intended to generate trustworthy evidence about issues in the field of medicine and healthcare. The three principal approaches to health research are the quantitative, the qualitative, and the mixed methods approach. The quantitative research method uses data, which are measures of values and counts and are often described using statistical methods which in turn aids the researcher to draw inferences. Qualitative research incorporates the recording, interpreting, and analyzing of non-numeric data with an attempt to uncover the deeper meanings of human experiences and behaviors. Mixed methods research, the third methodological approach, involves collection and analysis of both qualitative and quantitative information with an objective to solve different but related questions, or at times the same questions.[ 1 , 2 ]

In healthcare, qualitative research is widely used to understand patterns of health behaviors, describe lived experiences, develop behavioral theories, explore healthcare needs, and design interventions.[ 1 , 2 , 3 ] Because of its ample applications in healthcare, there has been a tremendous increase in the number of health research studies undertaken using qualitative methodology.[ 4 , 5 ] This article discusses qualitative research methods, their significance, and applicability in the arena of healthcare.

Qualitative Research

Diverse academic and non-academic disciplines utilize qualitative research as a method of inquiry to understand human behavior and experiences.[ 6 , 7 ] According to Munhall, “Qualitative research involves broadly stated questions about human experiences and realities, studied through sustained contact with the individual in their natural environments and producing rich, descriptive data that will help us to understand those individual's experiences.”[ 8 ]

Significance of Qualitative Research

The qualitative method of inquiry examines the 'how' and 'why' of decision making, rather than the 'when,' 'what,' and 'where.'[ 7 ] Unlike quantitative methods, the objective of qualitative inquiry is to explore, narrate, and explain the phenomena and make sense of the complex reality. Health interventions, explanatory health models, and medical-social theories could be developed as an outcome of qualitative research.[ 9 ] Understanding the richness and complexity of human behavior is the crux of qualitative research.

Differences between Quantitative and Qualitative Research

The quantitative and qualitative forms of inquiry vary based on their underlying objectives. They are in no way opposed to each other; instead, these two methods are like two sides of a coin. The critical differences between quantitative and qualitative research are summarized in Table 1 .[ 1 , 10 , 11 ]

Differences between quantitative and qualitative research

Qualitative Research Questions and Purpose Statements

Qualitative questions are exploratory and are open-ended. A well-formulated study question forms the basis for developing a protocol, guides the selection of design, and data collection methods. Qualitative research questions generally involve two parts, a central question and related subquestions. The central question is directed towards the primary phenomenon under study, whereas the subquestions explore the subareas of focus. It is advised not to have more than five to seven subquestions. A commonly used framework for designing a qualitative research question is the 'PCO framework' wherein, P stands for the population under study, C stands for the context of exploration, and O stands for the outcome/s of interest.[ 12 ] The PCO framework guides researchers in crafting a focused study question.

Example: In the question, “What are the experiences of mothers on parenting children with Thalassemia?”, the population is “mothers of children with Thalassemia,” the context is “parenting children with Thalassemia,” and the outcome of interest is “experiences.”

The purpose statement specifies the broad focus of the study, identifies the approach, and provides direction for the overall goal of the study. The major components of a purpose statement include the central phenomenon under investigation, the study design and the population of interest. Qualitative research does not require a-priori hypothesis.[ 13 , 14 , 15 ]

Example: Borimnejad et al . undertook a qualitative research on the lived experiences of women suffering from vitiligo. The purpose of this study was, “to explore lived experiences of women suffering from vitiligo using a hermeneutic phenomenological approach.” [ 16 ]

Review of the Literature

In quantitative research, the researchers do an extensive review of scientific literature prior to the commencement of the study. However, in qualitative research, only a minimal literature search is conducted at the beginning of the study. This is to ensure that the researcher is not influenced by the existing understanding of the phenomenon under the study. The minimal literature review will help the researchers to avoid the conceptual pollution of the phenomenon being studied. Nonetheless, an extensive review of the literature is conducted after data collection and analysis.[ 15 ]

Reflexivity

Reflexivity refers to critical self-appraisal about one's own biases, values, preferences, and preconceptions about the phenomenon under investigation. Maintaining a reflexive diary/journal is a widely recognized way to foster reflexivity. According to Creswell, “Reflexivity increases the credibility of the study by enhancing more neutral interpretations.”[ 7 ]

Types of Qualitative Research Designs

The qualitative research approach encompasses a wide array of research designs. The words such as types, traditions, designs, strategies of inquiry, varieties, and methods are used interchangeably. The major types of qualitative research designs are narrative research, phenomenological research, grounded theory research, ethnographic research, historical research, and case study research.[ 1 , 7 , 10 ]

Narrative research

Narrative research focuses on exploring the life of an individual and is ideally suited to tell the stories of individual experiences.[ 17 ] The purpose of narrative research is to utilize 'story telling' as a method in communicating an individual's experience to a larger audience.[ 18 ] The roots of narrative inquiry extend to humanities including anthropology, literature, psychology, education, history, and sociology. Narrative research encompasses the study of individual experiences and learning the significance of those experiences. The data collection procedures include mainly interviews, field notes, letters, photographs, diaries, and documents collected from one or more individuals. Data analysis involves the analysis of the stories or experiences through “re-storying of stories” and developing themes usually in chronological order of events. Rolls and Payne argued that narrative research is a valuable approach in health care research, to gain deeper insight into patient's experiences.[ 19 ]

Example: Karlsson et al . undertook a narrative inquiry to “explore how people with Alzheimer's disease present their life story.” Data were collected from nine participants. They were asked to describe about their life experiences from childhood to adulthood, then to current life and their views about the future life. [ 20 ]

Phenomenological research

Phenomenology is a philosophical tradition developed by German philosopher Edmond Husserl. His student Martin Heidegger did further developments in this methodology. It defines the 'essence' of individual's experiences regarding a certain phenomenon.[ 1 ] The methodology has its origin from philosophy, psychology, and education. The purpose of qualitative research is to understand the people's everyday life experiences and reduce it into the central meaning or the 'essence of the experience'.[ 21 , 22 ] The unit of analysis of phenomenology is the individuals who have had similar experiences of the phenomenon. Interviews with individuals are mainly considered for the data collection, though, documents and observations are also useful. Data analysis includes identification of significant meaning elements, textural description (what was experienced), structural description (how was it experienced), and description of 'essence' of experience.[ 1 , 7 , 21 ] The phenomenological approach is further divided into descriptive and interpretive phenomenology. Descriptive phenomenology focuses on the understanding of the essence of experiences and is best suited in situations that need to describe the lived phenomenon. Hermeneutic phenomenology or Interpretive phenomenology moves beyond the description to uncover the meanings that are not explicitly evident. The researcher tries to interpret the phenomenon, based on their judgment rather than just describing it.[ 7 , 21 , 22 , 23 , 24 ]

Example: A phenomenological study conducted by Cornelio et al . aimed at describing the lived experiences of mothers in parenting children with leukemia. Data from ten mothers were collected using in-depth semi-structured interviews and were analyzed using Husserl's method of phenomenology. Themes such as “pivotal moment in life”, “the experience of being with a seriously ill child”, “having to keep distance with the relatives”, “overcoming the financial and social commitments”, “responding to challenges”, “experience of faith as being key to survival”, “health concerns of the present and future”, and “optimism” were derived. The researchers reported the essence of the study as “chronic illness such as leukemia in children results in a negative impact on the child and on the mother.” [ 25 ]

Grounded Theory Research

Grounded theory has its base in sociology and propagated by two sociologists, Barney Glaser, and Anselm Strauss.[ 26 ] The primary purpose of grounded theory is to discover or generate theory in the context of the social process being studied. The major difference between grounded theory and other approaches lies in its emphasis on theory generation and development. The name grounded theory comes from its ability to induce a theory grounded in the reality of study participants.[ 7 , 27 ] Data collection in grounded theory research involves recording interviews from many individuals until data saturation. Constant comparative analysis, theoretical sampling, theoretical coding, and theoretical saturation are unique features of grounded theory research.[ 26 , 27 , 28 ] Data analysis includes analyzing data through 'open coding,' 'axial coding,' and 'selective coding.'[ 1 , 7 ] Open coding is the first level of abstraction, and it refers to the creation of a broad initial range of categories, axial coding is the procedure of understanding connections between the open codes, whereas selective coding relates to the process of connecting the axial codes to formulate a theory.[ 1 , 7 ] Results of the grounded theory analysis are supplemented with a visual representation of major constructs usually in the form of flow charts or framework diagrams. Quotations from the participants are used in a supportive capacity to substantiate the findings. Strauss and Corbin highlights that “the value of the grounded theory lies not only in its ability to generate a theory but also to ground that theory in the data.”[ 27 ]

Example: Williams et al . conducted a grounded theory research to explore the nature of relationship between the sense of self and the eating disorders. Data were collected form 11 women with a lifetime history of Anorexia Nervosa and were analyzed using the grounded theory methodology. Analysis led to the development of a theoretical framework on the nature of the relationship between the self and Anorexia Nervosa. [ 29 ]

Ethnographic research

Ethnography has its base in anthropology, where the anthropologists used it for understanding the culture-specific knowledge and behaviors. In health sciences research, ethnography focuses on narrating and interpreting the health behaviors of a culture-sharing group. 'Culture-sharing group' in an ethnography represents any 'group of people who share common meanings, customs or experiences.' In health research, it could be a group of physicians working in rural care, a group of medical students, or it could be a group of patients who receive home-based rehabilitation. To understand the cultural patterns, researchers primarily observe the individuals or group of individuals for a prolonged period of time.[ 1 , 7 , 30 ] The scope of ethnography can be broad or narrow depending on the aim. The study of more general cultural groups is termed as macro-ethnography, whereas micro-ethnography focuses on more narrowly defined cultures. Ethnography is usually conducted in a single setting. Ethnographers collect data using a variety of methods such as observation, interviews, audio-video records, and document reviews. A written report includes a detailed description of the culture sharing group with emic and etic perspectives. When the researcher reports the views of the participants it is called emic perspectives and when the researcher reports his or her views about the culture, the term is called etic.[ 7 ]

Example: The aim of the ethnographic study by LeBaron et al . was to explore the barriers to opioid availability and cancer pain management in India. The researchers collected data from fifty-nine participants using in-depth semi-structured interviews, participant observation, and document review. The researchers identified significant barriers by open coding and thematic analysis of the formal interview. [ 31 ]

Historical research

Historical research is the “systematic collection, critical evaluation, and interpretation of historical evidence”.[ 1 ] The purpose of historical research is to gain insights from the past and involves interpreting past events in the light of the present. The data for historical research are usually collected from primary and secondary sources. The primary source mainly includes diaries, first hand information, and writings. The secondary sources are textbooks, newspapers, second or third-hand accounts of historical events and medical/legal documents. The data gathered from these various sources are synthesized and reported as biographical narratives or developmental perspectives in chronological order. The ideas are interpreted in terms of the historical context and significance. The written report describes 'what happened', 'how it happened', 'why it happened', and its significance and implications to current clinical practice.[ 1 , 10 ]

Example: Lubold (2019) analyzed the breastfeeding trends in three countries (Sweden, Ireland, and the United States) using a historical qualitative method. Through analysis of historical data, the researcher found that strong family policies, adherence to international recommendations and adoption of baby-friendly hospital initiative could greatly enhance the breastfeeding rates. [ 32 ]

Case study research

Case study research focuses on the description and in-depth analysis of the case(s) or issues illustrated by the case(s). The design has its origin from psychology, law, and medicine. Case studies are best suited for the understanding of case(s), thus reducing the unit of analysis into studying an event, a program, an activity or an illness. Observations, one to one interviews, artifacts, and documents are used for collecting the data, and the analysis is done through the description of the case. From this, themes and cross-case themes are derived. A written case study report includes a detailed description of one or more cases.[ 7 , 10 ]

Example: Perceptions of poststroke sexuality in a woman of childbearing age was explored using a qualitative case study approach by Beal and Millenbrunch. Semi structured interview was conducted with a 36- year mother of two children with a history of Acute ischemic stroke. The data were analyzed using an inductive approach. The authors concluded that “stroke during childbearing years may affect a woman's perception of herself as a sexual being and her ability to carry out gender roles”. [ 33 ]

Sampling in Qualitative Research

Qualitative researchers widely use non-probability sampling techniques such as purposive sampling, convenience sampling, quota sampling, snowball sampling, homogeneous sampling, maximum variation sampling, extreme (deviant) case sampling, typical case sampling, and intensity sampling. The selection of a sampling technique depends on the nature and needs of the study.[ 34 , 35 , 36 , 37 , 38 , 39 , 40 ] The four widely used sampling techniques are convenience sampling, purposive sampling, snowball sampling, and intensity sampling.

Convenience sampling

It is otherwise called accidental sampling, where the researchers collect data from the subjects who are selected based on accessibility, geographical proximity, ease, speed, and or low cost.[ 34 ] Convenience sampling offers a significant benefit of convenience but often accompanies the issues of sample representation.

Purposive sampling

Purposive or purposeful sampling is a widely used sampling technique.[ 35 ] It involves identifying a population based on already established sampling criteria and then selecting subjects who fulfill that criteria to increase the credibility. However, choosing information-rich cases is the key to determine the power and logic of purposive sampling in a qualitative study.[ 1 ]

Snowball sampling

The method is also known as 'chain referral sampling' or 'network sampling.' The sampling starts by having a few initial participants, and the researcher relies on these early participants to identify additional study participants. It is best adopted when the researcher wishes to study the stigmatized group, or in cases, where findings of participants are likely to be difficult by ordinary means. Respondent ridden sampling is an improvised version of snowball sampling used to find out the participant from a hard-to-find or hard-to-study population.[ 37 , 38 ]

Intensity sampling

The process of identifying information-rich cases that manifest the phenomenon of interest is referred to as intensity sampling. It requires prior information, and considerable judgment about the phenomenon of interest and the researcher should do some preliminary investigations to determine the nature of the variation. Intensity sampling will be done once the researcher identifies the variation across the cases (extreme, average and intense) and picks the intense cases from them.[ 40 ]

Deciding the Sample Size

A-priori sample size calculation is not undertaken in the case of qualitative research. Researchers collect the data from as many participants as possible until they reach the point of data saturation. Data saturation or the point of redundancy is the stage where the researcher no longer sees or hears any new information. Data saturation gives the idea that the researcher has captured all possible information about the phenomenon of interest. Since no further information is being uncovered as redundancy is achieved, at this point the data collection can be stopped. The objective here is to get an overall picture of the chronicle of the phenomenon under the study rather than generalization.[ 1 , 7 , 41 ]

Data Collection in Qualitative Research

The various strategies used for data collection in qualitative research includes in-depth interviews (individual or group), focus group discussions (FGDs), participant observation, narrative life history, document analysis, audio materials, videos or video footage, text analysis, and simple observation. Among all these, the three popular methods are the FGDs, one to one in-depth interviews and the participant observation.

FGDs are useful in eliciting data from a group of individuals. They are normally built around a specific topic and are considered as the best approach to gather data on an entire range of responses to a topic.[ 42 Group size in an FGD ranges from 6 to 12. Depending upon the nature of participants, FGDs could be homogeneous or heterogeneous.[ 1 , 14 ] One to one in-depth interviews are best suited to obtain individuals' life histories, lived experiences, perceptions, and views, particularly while exporting topics of sensitive nature. In-depth interviews can be structured, unstructured, or semi-structured. However, semi-structured interviews are widely used in qualitative research. Participant observations are suitable for gathering data regarding naturally occurring behaviors.[ 1 ]

Data Analysis in Qualitative Research

Various strategies are employed by researchers to analyze data in qualitative research. Data analytic strategies differ according to the type of inquiry. A general content analysis approach is described herewith. Data analysis begins by transcription of the interview data. The researcher carefully reads data and gets a sense of the whole. Once the researcher is familiarized with the data, the researcher strives to identify small meaning units called the 'codes.' The codes are then grouped based on their shared concepts to form the primary categories. Based on the relationship between the primary categories, they are then clustered into secondary categories. The next step involves the identification of themes and interpretation to make meaning out of data. In the results section of the manuscript, the researcher describes the key findings/themes that emerged. The themes can be supported by participants' quotes. The analytical framework used should be explained in sufficient detail, and the analytic framework must be well referenced. The study findings are usually represented in a schematic form for better conceptualization.[ 1 , 7 ] Even though the overall analytical process remains the same across different qualitative designs, each design such as phenomenology, ethnography, and grounded theory has design specific analytical procedures, the details of which are out of the scope of this article.

Computer-Assisted Qualitative Data Analysis Software (CAQDAS)

Until recently, qualitative analysis was done either manually or with the help of a spreadsheet application. Currently, there are various software programs available which aid researchers to manage qualitative data. CAQDAS is basically data management tools and cannot analyze the qualitative data as it lacks the ability to think, reflect, and conceptualize. Nonetheless, CAQDAS helps researchers to manage, shape, and make sense of unstructured information. Open Code, MAXQDA, NVivo, Atlas.ti, and Hyper Research are some of the widely used qualitative data analysis software.[ 14 , 43 ]

Reporting Guidelines

Consolidated Criteria for Reporting Qualitative Research (COREQ) is the widely used reporting guideline for qualitative research. This 32-item checklist assists researchers in reporting all the major aspects related to the study. The three major domains of COREQ are the 'research team and reflexivity', 'study design', and 'analysis and findings'.[ 44 , 45 ]

Critical Appraisal of Qualitative Research

Various scales are available to critical appraisal of qualitative research. The widely used one is the Critical Appraisal Skills Program (CASP) Qualitative Checklist developed by CASP network, UK. This 10-item checklist evaluates the quality of the study under areas such as aims, methodology, research design, ethical considerations, data collection, data analysis, and findings.[ 46 ]

Ethical Issues in Qualitative Research

A qualitative study must be undertaken by grounding it in the principles of bioethics such as beneficence, non-maleficence, autonomy, and justice. Protecting the participants is of utmost importance, and the greatest care has to be taken while collecting data from a vulnerable research population. The researcher must respect individuals, families, and communities and must make sure that the participants are not identifiable by their quotations that the researchers include when publishing the data. Consent for audio/video recordings must be obtained. Approval to be in FGDs must be obtained from the participants. Researchers must ensure the confidentiality and anonymity of the transcripts/audio-video records/photographs/other data collected as a part of the study. The researchers must confirm their role as advocates and proceed in the best interest of all participants.[ 42 , 47 , 48 ]

Rigor in Qualitative Research

The demonstration of rigor or quality in the conduct of the study is essential for every research method. However, the criteria used to evaluate the rigor of quantitative studies are not be appropriate for qualitative methods. Lincoln and Guba (1985) first outlined the criteria for evaluating the qualitative research often referred to as “standards of trustworthiness of qualitative research”.[ 49 ] The four components of the criteria are credibility, transferability, dependability, and confirmability.

Credibility refers to confidence in the 'truth value' of the data and its interpretation. It is used to establish that the findings are true, credible and believable. Credibility is similar to the internal validity in quantitative research.[ 1 , 50 , 51 ] The second criterion to establish the trustworthiness of the qualitative research is transferability, Transferability refers to the degree to which the qualitative results are applicability to other settings, population or contexts. This is analogous to the external validity in quantitative research.[ 1 , 50 , 51 ] Lincoln and Guba recommend authors provide enough details so that the users will be able to evaluate the applicability of data in other contexts.[ 49 ] The criterion of dependability refers to the assumption of repeatability or replicability of the study findings and is similar to that of reliability in quantitative research. The dependability question is 'Whether the study findings be repeated of the study is replicated with the same (similar) cohort of participants, data coders, and context?'[ 1 , 50 , 51 ] Confirmability, the fourth criteria is analogous to the objectivity of the study and refers the degree to which the study findings could be confirmed or corroborated by others. To ensure confirmability the data should directly reflect the participants' experiences and not the bias, motivations, or imaginations of the inquirer.[ 1 , 50 , 51 ] Qualitative researchers should ensure that the study is conducted with enough rigor and should report the measures undertaken to enhance the trustworthiness of the study.

Conclusions

Qualitative research studies are being widely acknowledged and recognized in health care practice. This overview illustrates various qualitative methods and shows how these methods can be used to generate evidence that informs clinical practice. Qualitative research helps to understand the patterns of health behaviors, describe illness experiences, design health interventions, and develop healthcare theories. The ultimate strength of the qualitative research approach lies in the richness of the data and the descriptions and depth of exploration it makes. Hence, qualitative methods are considered as the most humanistic and person-centered way of discovering and uncovering thoughts and actions of human beings.

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