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Types of Interviews in Research | Guide & Examples

Published on March 10, 2022 by Tegan George . Revised on June 22, 2023.

An interview is a qualitative research method that relies on asking questions in order to collect data . Interviews involve two or more people, one of whom is the interviewer asking the questions.

There are several types of interviews, often differentiated by their level of structure.

  • Structured interviews have predetermined questions asked in a predetermined order.
  • Unstructured interviews are more free-flowing.
  • Semi-structured interviews fall in between.

Interviews are commonly used in market research, social science, and ethnographic research .

Table of contents

What is a structured interview, what is a semi-structured interview, what is an unstructured interview, what is a focus group, examples of interview questions, advantages and disadvantages of interviews, other interesting articles, frequently asked questions about types of interviews.

Structured interviews have predetermined questions in a set order. They are often closed-ended, featuring dichotomous (yes/no) or multiple-choice questions. While open-ended structured interviews exist, they are much less common. The types of questions asked make structured interviews a predominantly quantitative tool.

Asking set questions in a set order can help you see patterns among responses, and it allows you to easily compare responses between participants while keeping other factors constant. This can mitigate   research biases and lead to higher reliability and validity. However, structured interviews can be overly formal, as well as limited in scope and flexibility.

  • You feel very comfortable with your topic. This will help you formulate your questions most effectively.
  • You have limited time or resources. Structured interviews are a bit more straightforward to analyze because of their closed-ended nature, and can be a doable undertaking for an individual.
  • Your research question depends on holding environmental conditions between participants constant.

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Semi-structured interviews are a blend of structured and unstructured interviews. While the interviewer has a general plan for what they want to ask, the questions do not have to follow a particular phrasing or order.

Semi-structured interviews are often open-ended, allowing for flexibility, but follow a predetermined thematic framework, giving a sense of order. For this reason, they are often considered “the best of both worlds.”

However, if the questions differ substantially between participants, it can be challenging to look for patterns, lessening the generalizability and validity of your results.

  • You have prior interview experience. It’s easier than you think to accidentally ask a leading question when coming up with questions on the fly. Overall, spontaneous questions are much more difficult than they may seem.
  • Your research question is exploratory in nature. The answers you receive can help guide your future research.

An unstructured interview is the most flexible type of interview. The questions and the order in which they are asked are not set. Instead, the interview can proceed more spontaneously, based on the participant’s previous answers.

Unstructured interviews are by definition open-ended. This flexibility can help you gather detailed information on your topic, while still allowing you to observe patterns between participants.

However, so much flexibility means that they can be very challenging to conduct properly. You must be very careful not to ask leading questions, as biased responses can lead to lower reliability or even invalidate your research.

  • You have a solid background in your research topic and have conducted interviews before.
  • Your research question is exploratory in nature, and you are seeking descriptive data that will deepen and contextualize your initial hypotheses.
  • Your research necessitates forming a deeper connection with your participants, encouraging them to feel comfortable revealing their true opinions and emotions.

A focus group brings together a group of participants to answer questions on a topic of interest in a moderated setting. Focus groups are qualitative in nature and often study the group’s dynamic and body language in addition to their answers. Responses can guide future research on consumer products and services, human behavior, or controversial topics.

Focus groups can provide more nuanced and unfiltered feedback than individual interviews and are easier to organize than experiments or large surveys . However, their small size leads to low external validity and the temptation as a researcher to “cherry-pick” responses that fit your hypotheses.

  • Your research focuses on the dynamics of group discussion or real-time responses to your topic.
  • Your questions are complex and rooted in feelings, opinions, and perceptions that cannot be answered with a “yes” or “no.”
  • Your topic is exploratory in nature, and you are seeking information that will help you uncover new questions or future research ideas.

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using interview in qualitative research

Depending on the type of interview you are conducting, your questions will differ in style, phrasing, and intention. Structured interview questions are set and precise, while the other types of interviews allow for more open-endedness and flexibility.

Here are some examples.

  • Semi-structured
  • Unstructured
  • Focus group
  • Do you like dogs? Yes/No
  • Do you associate dogs with feeling: happy; somewhat happy; neutral; somewhat unhappy; unhappy
  • If yes, name one attribute of dogs that you like.
  • If no, name one attribute of dogs that you don’t like.
  • What feelings do dogs bring out in you?
  • When you think more deeply about this, what experiences would you say your feelings are rooted in?

Interviews are a great research tool. They allow you to gather rich information and draw more detailed conclusions than other research methods, taking into consideration nonverbal cues, off-the-cuff reactions, and emotional responses.

However, they can also be time-consuming and deceptively challenging to conduct properly. Smaller sample sizes can cause their validity and reliability to suffer, and there is an inherent risk of interviewer effect arising from accidentally leading questions.

Here are some advantages and disadvantages of each type of interview that can help you decide if you’d like to utilize this research method.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Student’s  t -distribution
  • Normal distribution
  • Null and Alternative Hypotheses
  • Chi square tests
  • Confidence interval
  • Quartiles & Quantiles
  • Cluster sampling
  • Stratified sampling
  • Data cleansing
  • Reproducibility vs Replicability
  • Peer review
  • Prospective cohort study

Research bias

  • Implicit bias
  • Cognitive bias
  • Placebo effect
  • Hawthorne effect
  • Hindsight bias
  • Affect heuristic
  • Social desirability bias

The four most common types of interviews are:

  • Structured interviews : The questions are predetermined in both topic and order. 
  • Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
  • Unstructured interviews : None of the questions are predetermined.
  • Focus group interviews : The questions are presented to a group instead of one individual.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

A focus group is a research method that brings together a small group of people to answer questions in a moderated setting. The group is chosen due to predefined demographic traits, and the questions are designed to shed light on a topic of interest. It is one of 4 types of interviews .

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

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

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  • Harvard Library
  • Research Guides
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Library Support for Qualitative Research

  • Interview Research
  • Resources for Methodology
  • Remote Research & Virtual Fieldwork

Resources for Research Interviewing

Nih-funded qualitative research.

  • Oral History
  • Data Management & Repositories
  • Campus Access

Types of Interviews

  • Engaging Participants

Interview Questions

  • Conducting Interviews
  • Transcription
  • Coding and Analysis
  • Managing & Finding Interview Data
  • UX & Market Research Interviews

Textbooks, Guidebooks, and Handbooks  

  • The Ethnographic Interview by James P. Spradley  “Spradley wrote this book for the professional and student who have never done ethnographic fieldwork (p. 231) and for the professional ethnographer who is interested in adapting the author’s procedures (p. iv). Part 1 outlines in 3 chapters Spradley’s version of ethnographic research, and it provides the background for Part 2 which consists of 12 guided steps (chapters) ranging from locating and interviewing an informant to writing an ethnography. Most of the examples come from the author’s own fieldwork among U.S. subcultures . . . Steps 6 and 8 explain lucidly how to construct a domain and a taxonomic analysis” (excerpted from book review by James D. Sexton, 1980).  
  • Fundamentals of Qualitative Research by Johnny Saldana (Series edited by Patricia Leavy)  Provides a soup-to-nuts overview of the qualitative data collection process, including interviewing, participant observation, and other methods.  
  • InterViews by Steinar Kvale  Interviewing is an essential tool in qualitative research and this introduction to interviewing outlines both the theoretical underpinnings and the practical aspects of the process. After examining the role of the interview in the research process, Steinar Kvale considers some of the key philosophical issues relating to interviewing: the interview as conversation, hermeneutics, phenomenology, concerns about ethics as well as validity, and postmodernism. Having established this framework, the author then analyzes the seven stages of the interview process - from designing a study to writing it up.  
  • Practical Evaluation by Michael Quinn Patton  Surveys different interviewing strategies, from, a) informal/conversational, to b) interview guide approach, to c) standardized and open-ended, to d) closed/quantitative. Also discusses strategies for wording questions that are open-ended, clear, sensitive, and neutral, while supporting the speaker. Provides suggestions for probing and maintaining control of the interview process, as well as suggestions for recording and transcription.  
  • The SAGE Handbook of Interview Research by Amir B. Marvasti (Editor); James A. Holstein (Editor); Jaber F. Gubrium (Editor); Karyn D. McKinney (Editor)  The new edition of this landmark volume emphasizes the dynamic, interactional, and reflexive dimensions of the research interview. Contributors highlight the myriad dimensions of complexity that are emerging as researchers increasingly frame the interview as a communicative opportunity as much as a data-gathering format. The book begins with the history and conceptual transformations of the interview, which is followed by chapters that discuss the main components of interview practice. Taken together, the contributions to The SAGE Handbook of Interview Research: The Complexity of the Craft encourage readers simultaneously to learn the frameworks and technologies of interviewing and to reflect on the epistemological foundations of the interview craft.  
  • The SAGE Handbook of Online Research Methods by Nigel G. Fielding, Raymond M. Lee and Grant Blank (Editors) Bringing together the leading names in both qualitative and quantitative online research, this new edition is organised into nine sections: 1. Online Research Methods 2. Designing Online Research 3. Online Data Capture and Data Collection 4. The Online Survey 5. Digital Quantitative Analysis 6. Digital Text Analysis 7. Virtual Ethnography 8. Online Secondary Analysis: Resources and Methods 9. The Future of Online Social Research

ONLINE RESOURCES, COMMUNITIES, AND DATABASES  

  • Interviews as a Method for Qualitative Research (video) This short video summarizes why interviews can serve as useful data in qualitative research.  
  • Companion website to Bloomberg and Volpe's  Completing Your Qualitative Dissertation: A Road Map from Beginning to End,  4th ed Provides helpful templates and appendices featured in the book, as well as links to other useful dissertation resources.
  • International Congress of Qualitative Inquiry Annual conference hosted by the International Center for Qualitative Inquiry at the University of Illinois at Urbana-Champaign, which aims to facilitate the development of qualitative research methods across a wide variety of academic disciplines, among other initiatives.  
  • METHODSPACE ​​​​​​​​An online home of the research methods community, where practicing researchers share how to make research easier.  
  • SAGE researchmethods ​​​​​​​Researchers can explore methods concepts to help them design research projects, understand particular methods or identify a new method, conduct their research, and write up their findings. A "methods map" facilitates finding content on methods.

The decision to conduct interviews, and the type of interviewing to use, should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Structured:

  • Structured Interview. Entry in The SAGE Encyclopedia of Social Science Research Methodsby Floyd J. Fowler Jr., Editors: Michael S. Lewis-Beck; Alan E. Bryman; Tim Futing Liao (Editor)  A concise article noting standards, procedures, and recommendations for developing and testing structured interviews. For an example of structured interview questions, you may view the Current Population Survey, May 2008: Public Participation in the Arts Supplement (ICPSR 29641), Apr 15, 2011 at https://doi.org/10.3886/ICPSR29641.v1 (To see the survey questions, preview the user guide, which can be found under the "Data and Documentation" tab. Then, look for page 177 (attachment 8).

Semi-Structured:

  • Semi-Structured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Lioness Ayres; Editor: Lisa M. Given  The semi-structured interview is a qualitative data collection strategy in which the researcher asks informants a series of predetermined but open-ended questions. The researcher has more control over the topics of the interview than in unstructured interviews, but in contrast to structured interviews or questionnaires that use closed questions, there is no fixed range of responses to each question.

Unstructured:

  • Unstructured Interview. Entry in The SAGE Encyclopedia of Qualitative Research Methodsby Michael W. Firmin; Editor: Lisa M. Given  Unstructured interviews in qualitative research involve asking relatively open-ended questions of research participants in order to discover their percepts on the topic of interest. Interviews, in general, are a foundational means of collecting data when using qualitative research methods. They are designed to draw from the interviewee constructs embedded in his or her thinking and rationale for decision making. The researcher uses an inductive method in data gathering, regardless of whether the interview method is open, structured, or semi-structured. That is, the researcher does not wish to superimpose his or her own viewpoints onto the person being interviewed. Rather, inductively, the researcher wishes to understand the participant's perceptions, helping him or her to articulate percepts such that they will be understood clearly by the journal reader.

Genres and Uses

Focus groups:.

  • "Focus Groups." Annual Review of Sociology 22 (1996): 129-1524.by David L. Morgan  Discusses the use of focus groups and group interviews as methods for gathering qualitative data used by sociologists and other academic and applied researchers. Focus groups are recommended for giving voice to marginalized groups and revealing the group effect on opinion formation.  
  • Qualitative Research Methods: A Data Collector's Field Guide (See Module 4: "Focus Groups")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

In-Depth (typically One-on-One):

  • A Practical Introduction to in-Depth Interviewingby Alan Morris  Are you new to qualitative research or a bit rusty and in need of some inspiration? Are you doing a research project involving in-depth interviews? Are you nervous about carrying out your interviews? This book will help you complete your qualitative research project by providing a nuts and bolts introduction to interviewing. With coverage of ethics, preparation strategies and advice for handling the unexpected in the field, this handy guide will help you get to grips with the basics of interviewing before embarking on your research. While recognising that your research question and the context of your research will drive your approach to interviewing, this book provides practical advice often skipped in traditional methods textbooks.  
  • Qualitative Research Methods: A Data Collector's Field Guide (See Module 3: "In-Depth Interviews")by Mack, N., et al.  This field guide is based on an approach to doing team-based, collaborative qualitative research that has repeatedly proven successful in research projects sponsored by Family Health International (FHI) throughout the developing world. With its straightforward delivery of information on the main qualitative methods being used in public health research today, the guide speaks to the need for simple yet effective instruction on how to do systematic and ethically sound qualitative research. The aim of the guide is thus practical. In bypassing extensive discussion on the theoretical underpinnings of qualitative research, it distinguishes itself as a how-to guide to be used in the field.

Folklore Research and Oral Histories:

In addition to the following resource, see the  Oral History   page of this guide for helpful resources on Oral History interviewing.

American Folklife Center at the Library of Congress. Folklife and Fieldwork: A Layman’s Introduction to Field Techniques Interviews gathered for purposes of folklore research are similar to standard social science interviews in some ways, but also have a good deal in common with oral history approaches to interviewing. The focus in a folklore research interview is on documenting and trying to understand the interviewee's way of life relative to a culture or subculture you are studying. This guide includes helpful advice and tips for conducting fieldwork in folklore, such as tips for planning, conducting, recording, and archiving interviews.

An interdisciplinary scientific program within the Institute for Quantitative Social Science which encourages and facilitates research and instruction in the theory and practice of survey research. The primary mission of PSR is to provide survey research resources to enhance the quality of teaching and research at Harvard.

  • Internet, Phone, Mail, and Mixed-Mode Surveysby Don A. Dillman; Jolene D. Smyth; Leah Melani Christian  The classic survey design reference, updated for the digital age. The new edition is thoroughly updated and revised, and covers all aspects of survey research. It features expanded coverage of mobile phones, tablets, and the use of do-it-yourself surveys, and Dillman's unique Tailored Design Method is also thoroughly explained. This new edition is complemented by copious examples within the text and accompanying website. It includes: Strategies and tactics for determining the needs of a given survey, how to design it, and how to effectively administer it. How and when to use mail, telephone, and Internet surveys to maximum advantage. Proven techniques to increase response rates. Guidance on how to obtain high-quality feedback from mail, electronic, and other self-administered surveys. Direction on how to construct effective questionnaires, including considerations of layout. The effects of sponsorship on the response rates of surveys. Use of capabilities provided by newly mass-used media: interactivity, presentation of aural and visual stimuli. The Fourth Edition reintroduces the telephone--including coordinating land and mobile.

User Experience (UX) and Marketing:

  • See the  "UX & Market Research Interviews"  tab on this guide, above. May include  Focus Groups,  above.

Screening for Research Site Selection:

  • Research interviews are used not only to furnish research data for theoretical analysis in the social sciences, but also to plan other kinds of studies. For example, interviews may allow researchers to screen appropriate research sites to conduct empirical studies (such as randomized controlled trials) in a variety of fields, from medicine to law. In contrast to interviews conducted in the course of social research, such interviews do not typically serve as the data for final analysis and publication.

ENGAGING PARTICIPANTS

Research ethics  .

  • Human Subjects (IRB) The Committee on the Use of Human Subjects (CUHS) serves as the Institutional Review Board for the University area which includes the Cambridge and Allston campuses at Harvard. Find your IRB  contact person , or learn about  required ethics training.  You may also find the  IRB Lifecycle Guide  helpful. This is the preferred IRB portal for Harvard graduate students and other researchers. IRB forms can be downloaded via the  ESTR Library  (click on the "Templates and Forms" tab, then navigate to pages 2 and 3 to find the documents labelled with “HUA” for the Harvard University Area IRB. Nota bene: You may use these forms only if you submit your study to the Harvard University IRB). The IRB office can be reached through email at [email protected] or by telephone at (617) 496-2847.  
  • Undergraduate Research Training Program (URTP) Portal The URTP at Harvard University is a comprehensive platform to create better prepared undergraduate researchers. The URTP is comprised of research ethics training sessions, a student-focused curriculum, and an online decision form that will assist students in determining whether their project requires IRB review. Students should examine the  URTP's guide for student researchers: Introduction to Human Subjects Research Protection.  
  • Ethics reports From the Association of Internet Researchers (AoIR)  
  • Respect, Beneficence, and Justice: QDR General Guidance for Human Participants If you are hoping to share your qualitative interview data in a repository after it has been collected, you will need to plan accordingly via informed consent, careful de-identification procedures, and data access controls. Consider  consulting with the Qualitative Research Support Group at Harvard Library  and consulting with  Harvard's Dataverse contacts  to help you think through all of the contingencies and processes.  
  • "Conducting a Qualitative Child Interview: Methodological Considerations." Journal of Advanced Nursing 42/5 (2003): 434-441 by Kortesluoma, R., et al.  The purpose of this article is to illustrate the theoretical premises of child interviewing, as well as to describe some practical methodological solutions used during interviews. Factors that influence data gathered from children and strategies for taking these factors into consideration during the interview are also described.  
  • "Crossing Cultural Barriers in Research Interviewing." Qualitative Social Work 63/3 (2007): 353-372 by Sands, R., et al.  This article critically examines a qualitative research interview in which cultural barriers between a white non-Muslim female interviewer and an African American Muslim interviewee, both from the USA, became evident and were overcome within the same interview.  
  • Decolonizing Methodologies: Research and Indigenous Peoples by Linda Tuhiwai Smith  This essential volume explores intersections of imperialism and research - specifically, the ways in which imperialism is embedded in disciplines of knowledge and tradition as 'regimes of truth.' Concepts such as 'discovery' and 'claiming' are discussed and an argument presented that the decolonization of research methods will help to reclaim control over indigenous ways of knowing and being. The text includes case-studies and examples, and sections on new indigenous literature and the role of research in indigenous struggles for social justice.  

This resource, sponsored by University of Oregon Libraries, exemplifies the use of interviewing methodologies in research that foregrounds traditional knowledge. The methodology page summarizes the approach.

  • Ethics: The Need to Tread Carefully. Chapter in A Practical Introduction to in-Depth Interviewing by Alan Morris  Pay special attention to the sections in chapter 2 on "How to prevent and respond to ethical issues arising in the course of the interview," "Ethics in the writing up of your interviews," and "The Ethics of Care."  
  • Handbook on Ethical Issues in Anthropology by Joan Cassell (Editor); Sue-Ellen Jacobs (Editor)  This publication of the American Anthropological Association presents and discusses issues and sources on ethics in anthropology, as well as realistic case studies of ethical dilemmas. It is meant to help social science faculty introduce discussions of ethics in their courses. Some of the topics are relevant to interviews, or at least to studies of which interviews are a part. See chapters 3 and 4 for cases, with solutions and commentary, respectively.  
  • Research Ethics from the Chanie Wenjack School for Indigenous Studies, Trent University  (Open Access) An overview of Indigenous research ethics and protocols from the across the globe.  
  • Resources for Equity in Research Consult these resources for guidance on creating and incorporating equitable materials into public health research studies that entail community engagement.

The SAGE Handbook of Qualitative Research Ethics by Ron Iphofen (Editor); Martin Tolich (Editor)  This handbook is a much-needed and in-depth review of the distinctive set of ethical considerations which accompanies qualitative research. This is particularly crucial given the emergent, dynamic and interactional nature of most qualitative research, which too often allows little time for reflection on the important ethical responsibilities and obligations. Contributions from leading international researchers have been carefully organized into six key thematic sections: Part One: Thick Descriptions Of Qualitative Research Ethics; Part Two: Qualitative Research Ethics By Technique; Part Three: Ethics As Politics; Part Four: Qualitative Research Ethics With Vulnerable Groups; Part Five: Relational Research Ethics; Part Six: Researching Digitally. This Handbook is a one-stop resource on qualitative research ethics across the social sciences that draws on the lessons learned and the successful methods for surmounting problems - the tried and true, and the new.

RESEARCH COMPLIANCE AND PRIVACY LAWS

Research Compliance Program for FAS/SEAS at Harvard : The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

  • Harvard Global Support Services (GSS) is for students, faculty, staff, and researchers who are studying, researching, or working abroad. Their services span safety and security, health, culture, outbound immigration, employment, financial and legal matters, and research center operations. These include travel briefings and registration, emergency response, guidance on international projects, and managing in-country operations.

Generative AI: Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.

Privacy Laws: Be mindful of any potential privacy laws that may apply wherever you conduct your interviews. The General Data Protection Regulation is a high-profile example (see below):

  • General Data Protection Regulation (GDPR) This Regulation lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data. It protects fundamental rights and freedoms of natural persons and in particular their right to the protection of personal data. The free movement of personal data within the Union shall be neither restricted nor prohibited for reasons connected with the protection of natural persons with regard to the processing of personal data. For a nice summary of what the GDPR requires, check out the GDPR "crash course" here .

SEEKING CONSENT  

If you would like to see examples of consent forms, ask your local IRB, or take a look at these resources:

  • Model consent forms for oral history, suggested by the Centre for Oral History and Digital Storytelling at Concordia University  
  • For NIH-funded research, see this  resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use.

POPULATION SAMPLING

If you wish to assemble resources to aid in sampling, such as the USPS Delivery Sequence File, telephone books, or directories of organizations and listservs, please contact our  data librarian  or write to  [email protected] .

  • Research Randomizer   A free web-based service that permits instant random sampling and random assignment. It also contains an interactive tutorial perfect for students taking courses in research methods.  
  • Practical Tools for Designing and Weighting Survey Samples by Richard Valliant; Jill A. Dever; Frauke Kreuter  Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least three audiences: (1) Students seeking a more in-depth understanding of applied sampling either through a second semester-long course or by way of a supplementary reference; (2) Survey statisticians searching for practical guidance on how to apply concepts learned in theoretical or applied sampling courses; and (3) Social scientists and other survey practitioners who desire insight into the statistical thinking and steps taken to design, select, and weight random survey samples. Several survey data sets are used to illustrate how to design samples, to make estimates from complex surveys for use in optimizing the sample allocation, and to calculate weights. Realistic survey projects are used to demonstrate the challenges and provide a context for the solutions. The book covers several topics that either are not included or are dealt with in a limited way in other texts. These areas include: sample size computations for multistage designs; power calculations related to surveys; mathematical programming for sample allocation in a multi-criteria optimization setting; nuts and bolts of area probability sampling; multiphase designs; quality control of survey operations; and statistical software for survey sampling and estimation. An associated R package, PracTools, contains a number of specialized functions for sample size and other calculations. The data sets used in the book are also available in PracTools, so that the reader may replicate the examples or perform further analyses.  
  • Sampling: Design and Analysis by Sharon L. Lohr  Provides a modern introduction to the field of sampling. With a multitude of applications from a variety of disciplines, the book concentrates on the statistical aspects of taking and analyzing a sample. Overall, the book gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys.  
  • Sampling Techniques by William G. Cochran  Clearly demonstrates a wide range of sampling methods now in use by governments, in business, market and operations research, social science, medicine, public health, agriculture, and accounting. Gives proofs of all the theoretical results used in modern sampling practice. New topics in this edition include the approximate methods developed for the problem of attaching standard errors or confidence limits to nonlinear estimates made from the results of surveys with complex plans.  
  • "Understanding the Process of Qualitative Data Collection" in Chapter 13 (pp. 103–1162) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
  • Survey Methodology by Robert M. Groves; Floyd J. Fowler; Mick P. Couper; James M. Lepkowski; Eleanor Singer; Roger Tourangeau; Floyd J. Fowler  coverage includes sampling frame evaluation, sample design, development of questionnaires, evaluation of questions, alternative modes of data collection, interviewing, nonresponse, post-collection processing of survey data, and practices for maintaining scientific integrity.

The way a qualitative researcher constructs and approaches interview questions should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

Constructing Your Questions

Helpful texts:.

  • "Developing Questions" in Chapter 4 (pp. 98–108) of Becoming Qualitative Researchers by Corrine Glesne  Ideal for introducing the novice researcher to the theory and practice of qualitative research, this text opens students to the diverse possibilities within this inquiry approach, while helping them understand how to design and implement specific research methods.  
  • "Learning to Interview in the Social Sciences" Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659 - 660.  
  • Qualitative Research Interviewing: Biographic Narrative and Semi-Structured Methods (See sections on “Lightly and Heavily Structured Depth Interviewing: Theory-Questions and Interviewer-Questions” and “Preparing for any Interviewing Sequence") by Tom Wengraf  Unique in its conceptual coherence and the level of practical detail, this book provides a comprehensive resource for those concerned with the practice of semi-structured interviewing, the most commonly used interview approach in social research, and in particular for in-depth, biographic narrative interviewing. It covers the full range of practices from the identification of topics through to strategies for writing up research findings in diverse ways.  
  • "Scripting a Qualitative Purpose Statement and Research Questions" in Chapter 12 (pp. 93–102) of 30 Essential Skills for the Qualitative Researcher by John W. Creswell  Provides practical "how-to" information for beginning researchers in the social, behavioral, and health sciences with many applied examples from research design, qualitative inquiry, and mixed methods.The skills presented in this book are crucial for a new qualitative researcher starting a qualitative project.  
  • Some Strategies for Developing Interview Guides for Qualitative Interviews by Sociology Department, Harvard University Includes general advice for conducting qualitative interviews, pros and cons of recording and transcription, guidelines for success, and tips for developing and phrasing effective interview questions.  
  • Tip Sheet on Question Wording by Harvard University Program on Survey Research

Let Theory Guide You:

The quality of your questions depends on how you situate them within a wider body of knowledge. Consider the following advice:

A good literature review has many obvious virtues. It enables the investigator to define problems and assess data. It provides the concepts on which percepts depend. But the literature review has a special importance for the qualitative researcher. This consists of its ability to sharpen his or her capacity for surprise (Lazarsfeld, 1972b). The investigator who is well versed in the literature now has a set of expectations the data can defy. Counterexpectational data are conspicuous, readable, and highly provocative data. They signal the existence of unfulfilled theoretical assumptions, and these are, as Kuhn (1962) has noted, the very origins of intellectual innovation. A thorough review of the literature is, to this extent, a way to manufacture distance. It is a way to let the data of one's research project take issue with the theory of one's field.

McCracken, G. (1988), The Long Interview, Sage: Newbury Park, CA, p. 31

When drafting your interview questions, remember that everything follows from your central research question. Also, on the way to writing your "operationalized" interview questions, it's  helpful to draft broader, intermediate questions, couched in theory. Nota bene:  While it is important to know the literature well before conducting your interview(s), be careful not to present yourself to your research participant(s) as "the expert," which would be presumptuous and could be intimidating. Rather, the purpose of your knowledge is to make you a better, keener listener.

If you'd like to supplement what you learned about relevant theories through your coursework and literature review, try these sources:

  • Annual Reviews   Review articles sum up the latest research in many fields, including social sciences, biomedicine, life sciences, and physical sciences. These are timely collections of critical reviews written by leading scientists.  
  • HOLLIS - search for resources on theories in your field   Modify this example search by entering the name of your field in place of "your discipline," then hit search.  
  • Oxford Bibliographies   Written and reviewed by academic experts, every article in this database is an authoritative guide to the current scholarship in a variety of fields, containing original commentary and annotations.  
  • ProQuest Dissertations & Theses (PQDT)   Indexes dissertations and masters' theses from most North American graduate schools as well as some European universities. Provides full text for most indexed dissertations from 1990-present.  
  • Very Short Introductions   Launched by Oxford University Press in 1995, Very Short Introductions offer concise introductions to a diverse range of subjects from Climate to Consciousness, Game Theory to Ancient Warfare, Privacy to Islamic History, Economics to Literary Theory.

CONDUCTING INTERVIEWS

Equipment and software:  .

  • Lamont Library  loans microphones and podcast starter kits, which will allow you to capture audio (and you may record with software, such as Garage Band). 
  • Cabot Library  loans digital recording devices, as well as USB microphones.

If you prefer to use your own device, you may purchase a small handheld audio recorder, or use your cell phone.

  • Audio Capture Basics (PDF)  - Helpful instructions, courtesy of the Lamont Library Multimedia Lab.
  • Getting Started with Podcasting/Audio:  Guidelines from Harvard Library's Virtual Media Lab for preparing your interviewee for a web-based recording (e.g., podcast, interview)
  • ​ Camtasia Screen Recorder and Video Editor
  • Zoom: Video Conferencing, Web Conferencing
  • Visit the Multimedia Production Resources guide! Consult it to find and learn how to use audiovisual production tools, including: cameras, microphones, studio spaces, and other equipment at Cabot Science Library and Lamont Library.
  • Try the virtual office hours offered by the Lamont Multimedia Lab!

TIPS FOR CONDUCTING INTERVIEWS

Quick handout:  .

  • Research Interviewing Tips (Courtesy of Dr. Suzanne Spreadbury)

Remote Interviews:  

  • For Online or Distant Interviews, See "Remote Research & Virtual Fieldwork" on this guide .  
  • Deborah Lupton's Bibliography: Doing Fieldwork in a Pandemic

Seeking Consent:

Books and articles:  .

  • "App-Based Textual Interviews: Interacting With Younger Generations in a Digitalized Social Reallity."International Journal of Social Research Methodology (12 June 2022). Discusses the use of texting platforms as a means to reach young people. Recommends useful question formulations for this medium.  
  • "Learning to Interview in the Social Sciences." Qualitative Inquiry, 9(4) 2003, 643–668 by Roulston, K., deMarrais, K., & Lewis, J. B. See especially the section on "Phrasing and Negotiating Questions" on pages 653-655 and common problems with framing questions noted on pages 659-660.  
  • "Slowing Down and Digging Deep: Teaching Students to Examine Interview Interaction in Depth." LEARNing Landscapes, Spring 2021 14(1) 153-169 by Herron, Brigette A. and Kathryn Roulston. Suggests analysis of videorecorded interviews as a precursor to formulating one's own questions. Includes helpful types of probes.  
  • Using Interviews in a Research Project by Nigel Joseph Mathers; Nicholas J Fox; Amanda Hunn; Trent Focus Group.  A work pack to guide researchers in developing interviews in the healthcare field. Describes interview structures, compares face-to-face and telephone interviews. Outlines the ways in which different types of interview data can be analysed.  
  • “Working through Challenges in Doing Interview Research.” International Journal of Qualitative Methods, (December 2011), 348–66 by Roulston, Kathryn.  The article explores (1) how problematic interactions identified in the analysis of focus group data can lead to modifications in research design, (2) an approach to dealing with reported data in representations of findings, and (3) how data analysis can inform question formulation in successive rounds of data generation. Findings from these types of examinations of interview data generation and analysis are valuable for informing both interview practice as well as research design.

Videos:  

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The way a qualitative researcher transcribes interviews should flow from, or align with, the methodological paradigm chosen for the study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these).

TRANSCRIPTION

Before embarking on a transcription project, it's worthwhile to invest in the time and effort necessary to capture good audio, which will make the transcription process much easier. If you haven't already done so, check out the  audio capture guidelines from Harvard Library's Virtual Media Lab , or  contact a media staff member  for customized recommendations. First and foremost, be mindful of common pitfalls by watching this short video that identifies  the most common errors to avoid!

SOFTWARE:  

  • Adobe Premiere Pro Speech-To-Text  automatically generates transcripts and adds captions to your videos. Harvard affiliates can download Adobe Premiere in the Creative Cloud Suite.  
  • GoTranscript  provides cost-effective human-generated transcriptions.  
  • pyTranscriber  is an app for generating automatic transcription and/or subtitles for audio and video files. It uses the Google Cloud Speech-to-Text service, has a friendly graphical user interface, and is purported to work nicely with Chinese.   
  • Otter  provides a new way to capture, store, search and share voice conversations, lectures, presentations, meetings, and interviews. The startup is based in Silicon Valley with a team of experienced Ph.Ds and engineers from Google, Facebook, Yahoo and Nuance (à la Dragon). Free accounts available. This is the software that  Zoom  uses to generate automated transcripts, so if you have access to a Zoom subscription, you have access to Otter transcriptions with it (applicable in several  languages ). As with any automated approach, be prepared to correct any errors after the fact, by hand.  
  • Panopto  is available to Harvard affiliates and generates  ASR (automated speech recognition) captions . You may upload compatible audio files into it. As with any automatically generated transcription, you will need to make manual revisions. ASR captioning is available in several  languages . Panopto maintains robust security practices, including strong authentication measures and end-to-end encryption, ensuring your content remains private and protected.  
  • REV.Com  allows you to record and transcribe any calls on the iPhone, both outgoing and incoming. It may be useful for recording phone interviews. Rev lets you choose whether you want an AI- or human-generated transcription, with a fast turnaround. Rev has Service Organization Controls Type II (SOC2) certification (a SOC2 cert looks at and verifies an organization’s processing integrity, privacy practices, and security safeguards).   
  • Scribie Audio/Video Transcription  provides automated or manual transcriptions for a small fee. As with any transcription service, some revisions will be necessary after the fact, particularly for its automated transcripts.  
  • Sonix  automatically transcribes, translates, and helps to organize audio and video files in over 40 languages. It's fast and affordable, with good accuracy. The free trial includes 30 minutes of free transcription.  
  • TranscriptionWing  uses a human touch process to clean up machine-generated transcripts so that the content will far more accurately reflect your audio recording.   
  • Whisper is a tool from OpenAI that facilitates transcription of sensitive audiovisual recordings (e.g., of research interviews) on your own device. Installation and use depends on your operating system and which version you install. Important Note: The Whisper API, where audio is sent to OpenAI to be processed by them and then sent back (usually through a programming language like Python) is NOT appropriate for sensitive data. The model should be downloaded with tools such as those described in this FAQ , so that audio is kept to your local machine. For assistance, contact James Capobianco .

EQUIPMENT:  

  • Transcription pedals  are in circulation and available to borrow from the Circulation desk at Lamont, or use at Lamont Library's Media Lab on level B. For hand-transcribing your interviews, they work in conjunction with software such as  Express Scribe , which is loaded on Media Lab computers, or you may download for free on your own machine (Mac or PC versions; scroll down the downloads page for the latter). The pedals are plug-and-play USB, allow a wide range of playback speeds, and have 3 programmable buttons, which are typically set to rewind/play/fast-forward. Instructions are included in the bag that covers installation and set-up of the software, and basic use of the pedals.

NEED HELP?  

  • Try the virtual office hours offered by the Lamont Multimedia Lab!    
  • If you're creating podcasts, login to  Canvas  and check out the  Podcasting/Audio guide . 

Helpful Texts:  

  • "Transcription as a Crucial Step of Data Analysis" in Chapter 5 of The SAGE Handbook of Qualitative Data Analysisby Uwe Flick (Editor)  Covers basic terminology for transcription, shares caveats for transcribers, and identifies components of vocal behavior. Provides notation systems for transcription, suggestions for transcribing turn-taking, and discusses new technologies and perspectives. Includes a bibliography for further reading.  
  • "Transcribing the Oral Interview: Part Art, Part Science " on p. 10 of the Centre for Community Knowledge (CCK) newsletter: TIMESTAMPby Mishika Chauhan and Saransh Srivastav

QUALITATIVE DATA ANALYSIS

Software  .

  • Free download available for Harvard Faculty of Arts and Sciences (FAS) affiliates
  • Desktop access at Lamont Library Media Lab, 3rd floor
  • Desktop access at Harvard Kennedy School Library (with HKS ID)
  • Remote desktop access for Harvard affiliates from  IQSS Computer Labs . Email them at  [email protected] and ask for a new lab account and remote desktop access to NVivo.
  • Virtual Desktop Infrastructure (VDI) access available to Harvard T.H. Chan School of Public Health affiliates

CODING AND THEMEING YOUR DATA

Data analysis methods should flow from, or align with, the methodological paradigm chosen for your study, whether that paradigm is interpretivist, critical, positivist, or participative in nature (or a combination of these). Some established methods include Content Analysis, Critical Analysis, Discourse Analysis, Gestalt Analysis, Grounded Theory Analysis, Interpretive Analysis, Narrative Analysis, Normative Analysis, Phenomenological Analysis, Rhetorical Analysis, and Semiotic Analysis, among others. The following resources should help you navigate your methodological options and put into practice methods for coding, themeing, interpreting, and presenting your data.

  • Users can browse content by topic, discipline, or format type (reference works, book chapters, definitions, etc.). SRM offers several research tools as well: a methods map, user-created reading lists, a project planner, and advice on choosing statistical tests.  
  • Abductive Coding: Theory Building and Qualitative (Re)Analysis by Vila-Henninger, et al.  The authors recommend an abductive approach to guide qualitative researchers who are oriented towards theory-building. They outline a set of tactics for abductive analysis, including the generation of an abductive codebook, abductive data reduction through code equations, and in-depth abductive qualitative analysis.  
  • Analyzing and Interpreting Qualitative Research: After the Interview by Charles F. Vanover, Paul A. Mihas, and Johnny Saldana (Editors)   Providing insight into the wide range of approaches available to the qualitative researcher and covering all steps in the research process, the authors utilize a consistent chapter structure that provides novice and seasoned researchers with pragmatic, "how-to" strategies. Each chapter author introduces the method, uses one of their own research projects as a case study of the method described, shows how the specific analytic method can be used in other types of studies, and concludes with three questions/activities to prompt class discussion or personal study.   
  • "Analyzing Qualitative Data." Theory Into Practice 39, no. 3 (2000): 146-54 by Margaret D. LeCompte   This article walks readers though rules for unbiased data analysis and provides guidance for getting organized, finding items, creating stable sets of items, creating patterns, assembling structures, and conducting data validity checks.  
  • "Coding is Not a Dirty Word" in Chapter 1 (pp. 1–30) of Enhancing Qualitative and Mixed Methods Research with Technology by Shalin Hai-Jew (Editor)   Current discourses in qualitative research, especially those situated in postmodernism, represent coding and the technology that assists with coding as reductive, lacking complexity, and detached from theory. In this chapter, the author presents a counter-narrative to this dominant discourse in qualitative research. The author argues that coding is not necessarily devoid of theory, nor does the use of software for data management and analysis automatically render scholarship theoretically lightweight or barren. A lack of deep analytical insight is a consequence not of software but of epistemology. Using examples informed by interpretive and critical approaches, the author demonstrates how NVivo can provide an effective tool for data management and analysis. The author also highlights ideas for critical and deconstructive approaches in qualitative inquiry while using NVivo. By troubling the positivist discourse of coding, the author seeks to create dialogic spaces that integrate theory with technology-driven data management and analysis, while maintaining the depth and rigor of qualitative research.   
  • The Coding Manual for Qualitative Researchers by Johnny Saldana   An in-depth guide to the multiple approaches available for coding qualitative data. Clear, practical and authoritative, the book profiles 32 coding methods that can be applied to a range of research genres from grounded theory to phenomenology to narrative inquiry. For each approach, Saldaña discusses the methods, origins, a description of the method, practical applications, and a clearly illustrated example with analytic follow-up. Essential reading across the social sciences.  
  • Flexible Coding of In-depth Interviews: A Twenty-first-century Approach by Nicole M. Deterding and Mary C. Waters The authors suggest steps in data organization and analysis to better utilize qualitative data analysis technologies and support rigorous, transparent, and flexible analysis of in-depth interview data.  
  • From the Editors: What Grounded Theory is Not by Roy Suddaby Walks readers through common misconceptions that hinder grounded theory studies, reinforcing the two key concepts of the grounded theory approach: (1) constant comparison of data gathered throughout the data collection process and (2) the determination of which kinds of data to sample in succession based on emergent themes (i.e., "theoretical sampling").  
  • “Good enough” methods for life-story analysis, by Wendy Luttrell. In Quinn N. (Ed.), Finding culture in talk (pp. 243–268). Demonstrates for researchers of culture and consciousness who use narrative how to concretely document reflexive processes in terms of where, how and why particular decisions are made at particular stages of the research process.   
  • Presentation slides on coding and themeing your data, derived from Saldana, Spradley, and LeCompte Click to request access.  
  • Qualitative Data Analysis by Matthew B. Miles; A. Michael Huberman   A practical sourcebook for researchers who make use of qualitative data, presenting the current state of the craft in the design, testing, and use of qualitative analysis methods. Strong emphasis is placed on data displays matrices and networks that go beyond ordinary narrative text. Each method of data display and analysis is described and illustrated.  
  • "A Survey of Qualitative Data Analytic Methods" in Chapter 4 (pp. 89–138) of Fundamentals of Qualitative Research by Johnny Saldana   Provides an in-depth introduction to coding as a heuristic, particularly focusing on process coding, in vivo coding, descriptive coding, values coding, dramaturgical coding, and versus coding. Includes advice on writing analytic memos, developing categories, and themeing data.   
  • "Thematic Networks: An Analytic Tool for Qualitative Research." Qualitative Research : QR, 1(3), 385–405 by Jennifer Attride-Stirling Details a technique for conducting thematic analysis of qualitative material, presenting a step-by-step guide of the analytic process, with the aid of an empirical example. The analytic method presented employs established, well-known techniques; the article proposes that thematic analyses can be usefully aided by and presented as thematic networks.  
  • Using Thematic Analysis in Psychology by Virginia Braun and Victoria Clark Walks readers through the process of reflexive thematic analysis, step by step. The method may be adapted in fields outside of psychology as relevant. Pair this with One Size Fits All? What Counts as Quality Practice in Reflexive Thematic Analysis? by Virginia Braun and Victoria Clark

TESTING OR GENERATING THEORIES

The quality of your data analysis depends on how you situate what you learn within a wider body of knowledge. Consider the following advice:

Once you have coalesced around a theory, realize that a theory should  reveal  rather than  color  your discoveries. Allow your data to guide you to what's most suitable. Grounded theory  researchers may develop their own theory where current theories fail to provide insight.  This guide on Theoretical Models  from Alfaisal University Library provides a helpful overview on using theory.

MANAGING & FINDING INTERVIEW DATA

Managing your elicited interview data, general guidance:  .

  • Research Data Management @ Harvard A reference guide with information and resources to help you manage your research data. See also: Harvard Research Data Security Policy , on the Harvard University Research Data Management website.  
  • Data Management For Researchers: Organize, Maintain and Share Your Data for Research Success by Kristin Briney. A comprehensive guide for scientific researchers providing everything they need to know about data management and how to organize, document, use and reuse their data.  
  • Open Science Framework (OSF) An open-source project management tool that makes it easy to collaborate within and beyond Harvard throughout a project's lifecycle. With OSF you can manage, store, and share documents, datasets, and other information with your research team. You can also publish your work to share it with a wider audience. Although data can be stored privately, because this platform is hosted on the Internet and designed with open access in mind, it is not a good choice for highly sensitive data.  
  • Free cloud storage solutions for Harvard affiliates to consider include:  Google Drive ,  DropBox , or  OneDrive ( up to DSL3 )  

Data Confidentiality and Secure Handling:  

  • Data Security Levels at Harvard - Research Data Examples This resource provided by Harvard Data Security helps you determine what level of access is appropriate for your data. Determine whether it should be made available for public use, limited to the Harvard community, or be protected as either "confidential and sensitive," "high risk," or "extremely sensitive." See also:  Harvard Data Classification Table  
  • Harvard's Best Practices for Protecting Privacy and  Harvard Information Security Collaboration Tools Matrix Follow the nuts-and-bolts advice for privacy best practices at Harvard. The latter resource reveals the level of security that can be relied upon for a large number of technological tools and platforms used at Harvard to conduct business, such as email, Slack, Accellion Kiteworks, OneDrive/SharePoint, etc.  
  • “Protecting Participant Privacy While Maintaining Content and Context: Challenges in Qualitative Data De‐identification and Sharing.” Proceedings of the ASIST Annual Meeting 57 (1) (2020): e415-420 by Myers, Long, and Polasek Presents an informed and tested protocol, based on the De-Identification guidelines published by the Qualitative Data Repository (QDR) at Syracuse University. Qualitative researchers may consult it to guide their data de-identification efforts.  
  • QDS Qualitative Data Sharing Toolkit The Qualitative Data Sharing (QDS) project and its toolkit was funded by the NIH National Human Genome Research Institute (R01HG009351). It provides tools and resources to help researchers, especially those in the health sciences, share qualitative research data while protecting privacy and confidentiality. It offers guidance on preparing data for sharing through de-identification and access control. These health sciences research datasets in ICPSR's Qualitative Data Sharing (QDS) Project Series were de-identified using the QuaDS Software and the project’s QDS guidelines.  
  • Table of De-Identification Techniques  
  • Generative AI Harvard-affiliated researchers should not enter data classified as confidential ( Level 2 and above ), including non-public research data, into publicly-available generative AI tools, in accordance with the University’s Information Security Policy. Information shared with generative AI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.  
  • Harvard Information Security Quick Reference Guide Storage guidelines, based on the data's security classification level (according to its IRB classification) is displayed on page 2, under "handling."  
  • Email Encryption Harvard Microsoft 365 users can now send encrypted messages and files directly from the Outlook web or desktop apps. Encrypting an email adds an extra layer of security to the message and its attachments (up to 150MB), and means only the intended recipient (and their inbox delegates with full access) can view it. Message encryption in Outlook is approved for sending high risk ( level 4 ) data and below.  

Sharing Qualitative Data:  

  • Repositories for Qualitative Data If you have cleared this intention with your IRB, secured consent from participants, and properly de-identified your data, consider sharing your interviews in one of the data repositories included in the link above. Depending on the nature of your research and the level of risk it may present to participants, sharing your interview data may not be appropriate. If there is any chance that sharing such data will be desirable, you will be much better off if you build this expectation into your plans from the beginning.  
  • Guide for Sharing Qualitative Data at ICPSR The Inter-university Consortium for Political and Social Research (ICPSR) has created this resource for investigators planning to share qualitative data at ICPSR. This guide provides an overview of elements and considerations for archiving qualitative data, identifies steps for investigators to follow during the research life cycle to ensure that others can share and reuse qualitative data, and provides information about exemplars of qualitative data  

International Projects:

  • Research Compliance Program for FAS/SEAS at Harvard The Faculty of Arts and Sciences (FAS), including the School of Engineering and Applied Sciences (SEAS), and the Office of the Vice Provost for Research (OVPR) have established a shared Research Compliance Program (RCP). An area of common concern for interview studies is international projects and collaboration . RCP is a resource to provide guidance on which international activities may be impacted by US sanctions on countries, individuals, or entities and whether licenses or other disclosure are required to ship or otherwise share items, technology, or data with foreign collaborators.

Finding Extant Interview Data

Finding journalistic interviews:  .

  • Academic Search Premier This all-purpose database is great for finding articles from magazines and newspapers. In the Advanced Search, it allows you to specify "Document Type":  Interview.  
  • Guide to Newspapers and Newspaper Indexes Use this guide created to Harvard Librarians to identify newspapers collections you'd like to search. To locate interviews, try adding the term  "interview"  to your search, or explore a database's search interface for options to  limit your search to interviews.  Nexis Uni  and  Factiva  are the two main databases for current news.   
  • Listen Notes Search for podcast episodes at this podcast aggregator, and look for podcasts that include interviews. Make sure to vet the podcaster for accuracy and quality! (Listen Notes does not do much vetting.)  
  • NPR  and  ProPublica  are two sites that offer high-quality long-form reporting, including journalistic interviews, for free.

Finding Oral History and Social Research Interviews:  

  • To find oral histories, see the Oral History   page of this guide for helpful resources on Oral History interviewing.  
  • Repositories for Qualitative Data It has not been a customary practice among qualitative researchers in the social sciences to share raw interview data, but some have made this data available in repositories, such as the ones listed on the page linked above. You may find published data from structured interview surveys (e.g., questionnaire-based computer-assisted telephone interview data), as well as some semi-structured and unstructured interviews.  
  • If you are merely interested in studies interpreting data collected using interviews, rather than finding raw interview data, try databases like  PsycInfo ,  Sociological Abstracts , or  Anthropology Plus , among others. 

Finding Interviews in Archival Collections at Harvard Library:

In addition to the databases and search strategies mentioned under the  "Finding Oral History and Social Research Interviews" category above,  you may search for interviews and oral histories (whether in textual or audiovisual formats) held in archival collections at Harvard Library.

  • HOLLIS searches all documented collections at Harvard, whereas HOLLIS for Archival Discovery searches only those with finding aids. Although HOLLIS for Archival Discovery covers less material, you may find it easier to parse your search results, especially when you wish to view results at the item level (within collections). Try these approaches:

Search in  HOLLIS :  

  • To retrieve items available online, do an Advanced Search for  interview* OR "oral histor*" (in Subject), with Resource Type "Archives/Manuscripts," then refine your search by selecting "Online" under "Show Only" on the right of your initial result list.  Revise the search above by adding your topic in the Keywords or Subject field (for example:  African Americans ) and resubmitting the search.  
  •  To enlarge your results set, you may also leave out the "Online" refinement; if you'd like to limit your search to a specific repository, try the technique of searching for  Code: Library + Collection on the "Advanced Search" page .   

Search in  HOLLIS for Archival Discovery :  

  • To retrieve items available online, search for   interview* OR "oral histor*" limited to digital materials . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +).  
  • To preview results by collection, search for  interview* OR "oral histor*" limited to collections . Revise the search above by adding your topic (for example:  artist* ) in the second search box (if you don't see the box, click +). Although this method does not allow you to isolate digitized content, you may find the refinement options on the right side of the screen (refine by repository, subject or names) helpful.  Once your select a given collection, you may search within it  (e.g., for your topic or the term interview).

UX & MARKET RESEARCH INTERVIEWS

Ux at harvard library  .

  • User Experience and Market Research interviews can inform the design of tangible products and services through responsive, outcome-driven insights. The  User Research Center  at Harvard Library specializes in this kind of user-centered design, digital accessibility, and testing. They also offer guidance and  resources  to members of the Harvard Community who are interested in learning more about UX methods. Contact [email protected] or consult the URC website for more information.

Websites  

  • User Interviews: The Beginner’s Guide (Chris Mears)  
  • Interviewing Users (Jakob Nielsen)

Books  

  • Interviewing Users: How to Uncover Compelling Insights by Steve Portigal; Grant McCracken (Foreword by)  Interviewing is a foundational user research tool that people assume they already possess. Everyone can ask questions, right? Unfortunately, that's not the case. Interviewing Users provides invaluable interviewing techniques and tools that enable you to conduct informative interviews with anyone. You'll move from simply gathering data to uncovering powerful insights about people.  
  • Rapid Contextual Design by Jessamyn Wendell; Karen Holtzblatt; Shelley Wood  This handbook introduces Rapid CD, a fast-paced, adaptive form of Contextual Design. Rapid CD is a hands-on guide for anyone who needs practical guidance on how to use the Contextual Design process and adapt it to tactical projects with tight timelines and resources. Rapid Contextual Design provides detailed suggestions on structuring the project and customer interviews, conducting interviews, and running interpretation sessions. The handbook walks you step-by-step through organizing the data so you can see your key issues, along with visioning new solutions, storyboarding to work out the details, and paper prototype interviewing to iterate the design all with as little as a two-person team with only a few weeks to spare *Includes real project examples with actual customer data that illustrate how a CD project actually works.

Videos  

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Instructional Presentations on Interview Skills  

  • Interview/Oral History Research for RSRA 298B: Master's Thesis Reading and Research (Spring 2023) Slideshow covers: Why Interviews?, Getting Context, Engaging Participants, Conducting the Interview, The Interview Guide, Note Taking, Transcription, File management, and Data Analysis.  
  • Interview Skills From an online class on February 13, 2023:  Get set up for interview research. You will leave prepared to choose among the three types of interviewing methods, equipped to develop an interview schedule, aware of data management options and their ethical implications, and knowledgeable of technologies you can use to record and transcribe your interviews. This workshop complements Intro to NVivo, a qualitative data analysis tool useful for coding interview data.

NIH Data Management & Sharing Policy (DMSP) This policy, effective January 25, 2023, applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of  scientific data , including NIH-funded qualitative research. Click here to see some examples of how the DMSP policy has been applied in qualitative research studies featured in the 2021 Qualitative Data Management Plan (DMP) Competition . As a resource for the community, NIH has developed a resource for developing informed consent language in research studies where data and/or biospecimens will be stored and shared for future use. It is important to note that the DMS Policy does NOT require that informed consent obtained from research participants must allow for broad sharing and the future use of data (either with or without identifiable private information). See the FAQ for more information.

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Book cover

Qualitative Methodologies in Organization Studies pp 75–96 Cite as

Interviewing in Qualitative Research

  • Svetlana Gudkova 4  
  • First Online: 14 December 2017

6177 Accesses

4 Citations

The interview is one of the basic methods of data collection employed in the social sciences. It is worth noting that this method is not restricted solely to the qualitative research. Interviews have been actively taken advantage of by representatives of various scientific traditions. Both the supporters of the positivist paradigm and the interpretivist one use the technique of the interview to collect data even though the expectations and assumptions of researchers as well as the process of preparing the interview and the conclusion sphere differ fundamentally. The chapter presents different types of interviews employed by the researchers to collect the data in a qualitative research and discusses the process of preparation and conducting the interviews.

  • Group and individual interviews
  • Structured vs unstructured interviews
  • conducting an interview

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Svetlana Gudkova

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Gudkova, S. (2018). Interviewing in Qualitative Research. In: Ciesielska, M., Jemielniak, D. (eds) Qualitative Methodologies in Organization Studies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-65442-3_4

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How to carry out great interviews in qualitative research.

11 min read An interview is one of the most versatile methods used in qualitative research. Here’s what you need to know about conducting great qualitative interviews.

What is a qualitative research interview?

Qualitative research interviews are a mainstay among q ualitative research techniques, and have been in use for decades either as a primary data collection method or as an adjunct to a wider research process. A qualitative research interview is a one-to-one data collection session between a researcher and a participant. Interviews may be carried out face-to-face, over the phone or via video call using a service like Skype or Zoom.

There are three main types of qualitative research interview – structured, unstructured or semi-structured.

  • Structured interviews Structured interviews are based around a schedule of predetermined questions and talking points that the researcher has developed. At their most rigid, structured interviews may have a precise wording and question order, meaning that they can be replicated across many different interviewers and participants with relatively consistent results.
  • Unstructured interviews Unstructured interviews have no predetermined format, although that doesn’t mean they’re ad hoc or unplanned. An unstructured interview may outwardly resemble a normal conversation, but the interviewer will in fact be working carefully to make sure the right topics are addressed during the interaction while putting the participant at ease with a natural manner.
  • Semi-structured interviews Semi-structured interviews are the most common type of qualitative research interview, combining the informality and rapport of an unstructured interview with the consistency and replicability of a structured interview. The researcher will come prepared with questions and topics, but will not need to stick to precise wording. This blended approach can work well for in-depth interviews.

Free eBook: The qualitative research design handbook

What are the pros and cons of interviews in qualitative research?

As a qualitative research method interviewing is hard to beat, with applications in social research, market research, and even basic and clinical pharmacy. But like any aspect of the research process, it’s not without its limitations. Before choosing qualitative interviewing as your research method, it’s worth weighing up the pros and cons.

Pros of qualitative interviews:

  • provide in-depth information and context
  • can be used effectively when their are low numbers of participants
  • provide an opportunity to discuss and explain questions
  • useful for complex topics
  • rich in data – in the case of in-person or video interviews , the researcher can observe body language and facial expression as well as the answers to questions

Cons of qualitative interviews:

  • can be time-consuming to carry out
  • costly when compared to some other research methods
  • because of time and cost constraints, they often limit you to a small number of participants
  • difficult to standardize your data across different researchers and participants unless the interviews are very tightly structured
  • As the Open University of Hong Kong notes, qualitative interviews may take an emotional toll on interviewers

Qualitative interview guides

Semi-structured interviews are based on a qualitative interview guide, which acts as a road map for the researcher. While conducting interviews, the researcher can use the interview guide to help them stay focused on their research questions and make sure they cover all the topics they intend to.

An interview guide may include a list of questions written out in full, or it may be a set of bullet points grouped around particular topics. It can prompt the interviewer to dig deeper and ask probing questions during the interview if appropriate.

Consider writing out the project’s research question at the top of your interview guide, ahead of the interview questions. This may help you steer the interview in the right direction if it threatens to head off on a tangent.

using interview in qualitative research

Avoid bias in qualitative research interviews

According to Duke University , bias can create significant problems in your qualitative interview.

  • Acquiescence bias is common to many qualitative methods, including focus groups. It occurs when the participant feels obliged to say what they think the researcher wants to hear. This can be especially problematic when there is a perceived power imbalance between participant and interviewer. To counteract this, Duke University’s experts recommend emphasizing the participant’s expertise in the subject being discussed, and the value of their contributions.
  • Interviewer bias is when the interviewer’s own feelings about the topic come to light through hand gestures, facial expressions or turns of phrase. Duke’s recommendation is to stick to scripted phrases where this is an issue, and to make sure researchers become very familiar with the interview guide or script before conducting interviews, so that they can hone their delivery.

What kinds of questions should you ask in a qualitative interview?

The interview questions you ask need to be carefully considered both before and during the data collection process. As well as considering the topics you’ll cover, you will need to think carefully about the way you ask questions.

Open-ended interview questions – which cannot be answered with a ‘yes’ ‘no’ or ‘maybe’ – are recommended by many researchers as a way to pursue in depth information.

An example of an open-ended question is “What made you want to move to the East Coast?” This will prompt the participant to consider different factors and select at least one. Having thought about it carefully, they may give you more detailed information about their reasoning.

A closed-ended question , such as “Would you recommend your neighborhood to a friend?” can be answered without too much deliberation, and without giving much information about personal thoughts, opinions and feelings.

Follow-up questions can be used to delve deeper into the research topic and to get more detail from open-ended questions. Examples of follow-up questions include:

  • What makes you say that?
  • What do you mean by that?
  • Can you tell me more about X?
  • What did/does that mean to you?

As well as avoiding closed-ended questions, be wary of leading questions. As with other qualitative research techniques such as surveys or focus groups, these can introduce bias in your data. Leading questions presume a certain point of view shared by the interviewer and participant, and may even suggest a foregone conclusion.

An example of a leading question might be: “You moved to New York in 1990, didn’t you?” In answering the question, the participant is much more likely to agree than disagree. This may be down to acquiescence bias or a belief that the interviewer has checked the information and already knows the correct answer.

Other leading questions involve adjectival phrases or other wording that introduces negative or positive connotations about a particular topic. An example of this kind of leading question is: “Many employees dislike wearing masks to work. How do you feel about this?” It presumes a positive opinion and the participant may be swayed by it, or not want to contradict the interviewer.

Harvard University’s guidelines for qualitative interview research add that you shouldn’t be afraid to ask embarrassing questions – “if you don’t ask, they won’t tell.” Bear in mind though that too much probing around sensitive topics may cause the interview participant to withdraw. The Harvard guidelines recommend leaving sensitive questions til the later stages of the interview when a rapport has been established.

More tips for conducting qualitative interviews

Observing a participant’s body language can give you important data about their thoughts and feelings. It can also help you decide when to broach a topic, and whether to use a follow-up question or return to the subject later in the interview.

Be conscious that the participant may regard you as the expert, not themselves. In order to make sure they express their opinions openly, use active listening skills like verbal encouragement and paraphrasing and clarifying their meaning to show how much you value what they are saying.

Remember that part of the goal is to leave the interview participant feeling good about volunteering their time and their thought process to your research. Aim to make them feel empowered , respected and heard.

Unstructured interviews can demand a lot of a researcher, both cognitively and emotionally. Be sure to leave time in between in-depth interviews when scheduling your data collection to make sure you maintain the quality of your data, as well as your own well-being .

Recording and transcribing interviews

Historically, recording qualitative research interviews and then transcribing the conversation manually would have represented a significant part of the cost and time involved in research projects that collect qualitative data.

Fortunately, researchers now have access to digital recording tools, and even speech-to-text technology that can automatically transcribe interview data using AI and machine learning. This type of tool can also be used to capture qualitative data from qualitative research (focus groups,ect.) making this kind of social research or market research much less time consuming.

using interview in qualitative research

Data analysis

Qualitative interview data is unstructured, rich in content and difficult to analyze without the appropriate tools. Fortunately, machine learning and AI can once again make things faster and easier when you use qualitative methods like the research interview.

Text analysis tools and natural language processing software can ‘read’ your transcripts and voice data and identify patterns and trends across large volumes of text or speech. They can also perform khttps://www.qualtrics.com/experience-management/research/sentiment-analysis/

which assesses overall trends in opinion and provides an unbiased overall summary of how participants are feeling.

using interview in qualitative research

Another feature of text analysis tools is their ability to categorize information by topic, sorting it into groupings that help you organize your data according to the topic discussed.

All in all, interviews are a valuable technique for qualitative research in business, yielding rich and detailed unstructured data. Historically, they have only been limited by the human capacity to interpret and communicate results and conclusions, which demands considerable time and skill.

When you combine this data with AI tools that can interpret it quickly and automatically, it becomes easy to analyze and structure, dovetailing perfectly with your other business data. An additional benefit of natural language analysis tools is that they are free of subjective biases, and can replicate the same approach across as much data as you choose. By combining human research skills with machine analysis, qualitative research methods such as interviews are more valuable than ever to your business.

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How to Conduct Interviews in Qualitative Research: Interview Guidelines for Qualitative Research

using interview in qualitative research

Rev › Blog › Market Research › How to Conduct Interviews in Qualitative Research: Interview Guidelines for Qualitative Research

Qualitative research interviews are depth interviews. They elicit detailed feedback from your leads and customers. Unstructured interviews reveal why people react in a certain way or make certain decisions. According to The Hartford , qualitative research provides an anecdotal look into your business. That provides an important form of data.

Why Your Business Should Use a Qualitative Interview Process

Qualitative research helps business owners:

  • Identify customer needs
  • Clarify marketing messages
  • Generate ideas for improvements of a product
  • Decide to extend a line or brand
  • Gain perspective on how a product fits into a customer’s lifestyle

How Is Conducting Qualitative Research & Quantitative Research Different?

Quantitative research concerns measurable quantities and numbers. It involves close-ended questions. Answer possibilities include yes or no, true or false, or various set choices. Qualitative research is descriptive and concerned with understanding behavior. It invites people to tell their stories in their own words.

Examples of Qualitative Research

Qualitative research helps researchers understand the social reality of individuals, groups and cultures. Qualitative research for businesses involves understanding consumer behavior. It can involve ethnographic techniques, including participant observation and field research. It also includes phenomenology, understanding life experiences using written or recorded narratives. Qualitative research also includes in-depth interviews.

What Is a Qualitative Interview?

A qualitative interview is a more personal form of research compared to questionnaires. The interviewer can probe or ask follow-up research questions of the interview participant. In some cases, subjects may start to interview the interviewer. This fosters deep discussion of the interview topic.

Why Are Interview Techniques in Qualitative Research Effective?

Qualitative research interviews help you explain, understand and explore opinions, behavior and experiences. Qualitative research can provide insights into a phenomenon. Qualitative research discoveries can be further researched and analyzed to influence business decisions.

How Are Interviews in Qualitative Research Formatted?

Qualitative research interviews may take place one-on-one or in focus groups. Learn how to run a successful focus group . Interviews span around 30 to 90 minutes. The interview can take place in person, over the phone or through video chat. The interviewer collects information about opinions, behavior, attitudes, feelings, preferences and knowledge.

How to Conduct Interviews in Qualitative Research

1. determine your goal., 2. target people to interview., 3. design interview questions., 4. prep the interview., 5. conduct the interview., 6. transcribe and analyze the interview., 7. optimize and evolve your interview guide., the first step in qualitative research: determine your goal.

Determine what you want to study:

  • A current or potential product, service or brand positioning
  • Strengths and weaknesses in products
  • Purchasing decisions
  • Reactions to advertising or marketing campaigns
  • Usability of a website or other interactive services
  • Perceptions about the company, brand or product
  • Reactions to packaging and design

How Can You Decide a Goal for a Qualitative Interview?

Have your business team ask the following questions: 

  • What information do you want to get?
  • Why do you want to pursue in-depth information about this research topic?
  • Why is a qualitative interview process the best solution for this research?
  • How will you use qualitative data to improve your business? 

How to Determine the Right Interview Participants

When looking for people to talk to for a qualitative interview, consider your goal. If you want to expand a product line, interview existing customers about their needs. If you’re researching marketing, ask new customers how they found your business. Match interview subjects with the goal of the interview.

How to Design Interview Questions for Qualitative Research

When you’re creating an interview guide, it’s a good idea to: 

  • Plan structured interviews with open ended questions.
  • Avoid leading questions.
  • Create interview questions that are clear and easy to understand.
  • Make research questions focused but flexible.
  • Design questions that align with data collection and data analysis goals.

Tips for Preparing a Qualitative Research Interview

Preparation improves interview effectiveness. Tips to prepare include:

  • Create an interview guide. The guide should include questions, question intent and answer-based paths to take.
  • Choose a setting where the subject feels comfortable.
  • Build rapport with interview participants.
  • Have a reliable way to record the interview.
  • Rehearse the interview first.

Environmental Concerns for Qualitative Interviews

The setting of a qualitative interview also affects the quality of the interview. Consider the needs of the subject. For example, if you’re interviewing a teenager, a formal boardroom may not be the best setting. Some cultures may not value direct eye contact. An interview that’s non-face-to-face may be better.

How to Make Qualitative Interview Subjects Comfortable

For long interviews, offer water and breaks to participants. Be polite and respectful when interacting with interview subjects. Let interview participants know the purpose of the research. Explain exactly how you’ll use their answers. Address terms of confidentiality if necessary. Thank participants after the interview and let them know what to expect next.

What Are Interview Techniques in Qualitative Research?

Qualitative research techniques include:

  • Start interviews with “get-to-know-you” questions to put the interview participant at ease.
  • Pay attention.
  • Use active listening techniques.
  • Watch for body language cues.
  • Pivot questions as needed.
  • Acknowledge emotions.
  • Avoid interrogation.
  • Ending interviews, ask subjects if they have anything to add.

What Is Active Listening in Interviews in Qualitative Research?

Active listening techniques include: 

  • Make eye contact.
  • Lean in and use body language to show you’re listening.
  • Don’t get distracted by devices.
  • Use verbal affirmation.
  • Paraphrase answers for reflection.
  • Reference earlier answers.
  • Avoid interrupting.
  • Embrace pauses.
  • Ask for clarification.
  • Pay attention in the moment.

Tips for Transcribing a Qualitative Interview

It’s best to transcribe and analyze a qualitative research interview right away. This helps you optimize future interviews. Transcribe the interview word for word. Note non-verbal interactions in your transcription. Interactions like pauses and laughter can provide deeper insights into responses.

How to Analyze a Qualitative Interview

Analyze your qualitative research data early. That way, you can identify emerging themes to shape future interviews. Consider adding these to each interview report:

  • The goal of the interview
  • Details about the interview participant
  • Questions asked, summarized responses and key findings
  • Recommendations

Relate the analysis to the goal of the qualitative research interview.

Optimize the Interview Guide for Qualitative Research

Each interview can help you improve the efficiency and effectiveness of future ones. Adjust your interview guide based on insights from each previous interview. Keep all versions of your transcriptions and interview guides with notes on them. You can reference these for future qualitative research.

Get Reliable Transcription Services for Qualitative Research Interviews

As mentioned, you should transcribe qualitative research interviews as soon as possible. There are several reasons for this.

  • You can gain insights that help you shape your interview guide. You might identify questions to add or questions to clarify.
  • Your interview participants may not be appropriate for this type of qualitative research. Finding more targeted interview subjects may be better.
  • Answers may evolve the qualitative research goal and/or data analysis.
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How to use and assess qualitative research methods

Loraine busetto.

1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany

Wolfgang Wick

2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany

Christoph Gumbinger

Associated data.

Not applicable.

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig1_HTML.jpg

Iterative research process

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

Data collection

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

Document study

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

Observations

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

Semi-structured interviews

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

Focus groups

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

Choosing the “right” method

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

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

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Possible combination of data collection methods

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

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

Data analysis

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

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From data collection to data analysis

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

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

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Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

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

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

The main take-away points of this paper are summarised in Table ​ Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.

Take-away-points

Acknowledgements

Abbreviations, authors’ contributions.

LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.

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  • Published: 22 March 2008

Methods of data collection in qualitative research: interviews and focus groups

  • P. Gill 1 ,
  • K. Stewart 2 ,
  • E. Treasure 3 &
  • B. Chadwick 4  

British Dental Journal volume  204 ,  pages 291–295 ( 2008 ) Cite this article

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Interviews and focus groups are the most common methods of data collection used in qualitative healthcare research

Interviews can be used to explore the views, experiences, beliefs and motivations of individual participants

Focus group use group dynamics to generate qualitative data

Qualitative research in dentistry

Conducting qualitative interviews with school children in dental research

Analysing and presenting qualitative data

This paper explores the most common methods of data collection used in qualitative research: interviews and focus groups. The paper examines each method in detail, focusing on how they work in practice, when their use is appropriate and what they can offer dentistry. Examples of empirical studies that have used interviews or focus groups are also provided.

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Introduction

Having explored the nature and purpose of qualitative research in the previous paper, this paper explores methods of data collection used in qualitative research. There are a variety of methods of data collection in qualitative research, including observations, textual or visual analysis (eg from books or videos) and interviews (individual or group). 1 However, the most common methods used, particularly in healthcare research, are interviews and focus groups. 2 , 3

The purpose of this paper is to explore these two methods in more detail, in particular how they work in practice, the purpose of each, when their use is appropriate and what they can offer dental research.

Qualitative research interviews

There are three fundamental types of research interviews: structured, semi-structured and unstructured. Structured interviews are, essentially, verbally administered questionnaires, in which a list of predetermined questions are asked, with little or no variation and with no scope for follow-up questions to responses that warrant further elaboration. Consequently, they are relatively quick and easy to administer and may be of particular use if clarification of certain questions are required or if there are likely to be literacy or numeracy problems with the respondents. However, by their very nature, they only allow for limited participant responses and are, therefore, of little use if 'depth' is required.

Conversely, unstructured interviews do not reflect any preconceived theories or ideas and are performed with little or no organisation. 4 Such an interview may simply start with an opening question such as 'Can you tell me about your experience of visiting the dentist?' and will then progress based, primarily, upon the initial response. Unstructured interviews are usually very time-consuming (often lasting several hours) and can be difficult to manage, and to participate in, as the lack of predetermined interview questions provides little guidance on what to talk about (which many participants find confusing and unhelpful). Their use is, therefore, generally only considered where significant 'depth' is required, or where virtually nothing is known about the subject area (or a different perspective of a known subject area is required).

Semi-structured interviews consist of several key questions that help to define the areas to be explored, but also allows the interviewer or interviewee to diverge in order to pursue an idea or response in more detail. 2 This interview format is used most frequently in healthcare, as it provides participants with some guidance on what to talk about, which many find helpful. The flexibility of this approach, particularly compared to structured interviews, also allows for the discovery or elaboration of information that is important to participants but may not have previously been thought of as pertinent by the research team.

For example, in a recent dental public heath study, 5 school children in Cardiff, UK were interviewed about their food choices and preferences. A key finding that emerged from semi-structured interviews, which was not previously thought to be as highly influential as the data subsequently confirmed, was the significance of peer-pressure in influencing children's food choices and preferences. This finding was also established primarily through follow-up questioning (eg probing interesting responses with follow-up questions, such as 'Can you tell me a bit more about that?') and, therefore, may not have emerged in the same way, if at all, if asked as a predetermined question.

The purpose of research interviews

The purpose of the research interview is to explore the views, experiences, beliefs and/or motivations of individuals on specific matters (eg factors that influence their attendance at the dentist). Qualitative methods, such as interviews, are believed to provide a 'deeper' understanding of social phenomena than would be obtained from purely quantitative methods, such as questionnaires. 1 Interviews are, therefore, most appropriate where little is already known about the study phenomenon or where detailed insights are required from individual participants. They are also particularly appropriate for exploring sensitive topics, where participants may not want to talk about such issues in a group environment.

Examples of dental studies that have collected data using interviews are 'Examining the psychosocial process involved in regular dental attendance' 6 and 'Exploring factors governing dentists' treatment philosophies'. 7 Gibson et al . 6 provided an improved understanding of factors that influenced people's regular attendance with their dentist. The study by Kay and Blinkhorn 7 provided a detailed insight into factors that influenced GDPs' decision making in relation to treatment choices. The study found that dentists' clinical decisions about treatments were not necessarily related to pathology or treatment options, as was perhaps initially thought, but also involved discussions with patients, patients' values and dentists' feelings of self esteem and conscience.

There are many similarities between clinical encounters and research interviews, in that both employ similar interpersonal skills, such as questioning, conversing and listening. However, there are also some fundamental differences between the two, such as the purpose of the encounter, reasons for participating, roles of the people involved and how the interview is conducted and recorded. 8

The primary purpose of clinical encounters is for the dentist to ask the patient questions in order to acquire sufficient information to inform decision making and treatment options. However, the constraints of most consultations are such that any open-ended questioning needs to be brought to a conclusion within a fairly short time. 2 In contrast, the fundamental purpose of the research interview is to listen attentively to what respondents have to say, in order to acquire more knowledge about the study topic. 9 Unlike the clinical encounter, it is not to intentionally offer any form of help or advice, which many researchers have neither the training nor the time for. Research interviewing therefore requires a different approach and a different range of skills.

The interview

When designing an interview schedule it is imperative to ask questions that are likely to yield as much information about the study phenomenon as possible and also be able to address the aims and objectives of the research. In a qualitative interview, good questions should be open-ended (ie, require more than a yes/no answer), neutral, sensitive and understandable. 2 It is usually best to start with questions that participants can answer easily and then proceed to more difficult or sensitive topics. 2 This can help put respondents at ease, build up confidence and rapport and often generates rich data that subsequently develops the interview further.

As in any research, it is often wise to first pilot the interview schedule on several respondents prior to data collection proper. 8 This allows the research team to establish if the schedule is clear, understandable and capable of answering the research questions, and if, therefore, any changes to the interview schedule are required.

The length of interviews varies depending on the topic, researcher and participant. However, on average, healthcare interviews last 20-60 minutes. Interviews can be performed on a one-off or, if change over time is of interest, repeated basis, 4 for example exploring the psychosocial impact of oral trauma on participants and their subsequent experiences of cosmetic dental surgery.

Developing the interview

Before an interview takes place, respondents should be informed about the study details and given assurance about ethical principles, such as anonymity and confidentiality. 2 This gives respondents some idea of what to expect from the interview, increases the likelihood of honesty and is also a fundamental aspect of the informed consent process.

Wherever possible, interviews should be conducted in areas free from distractions and at times and locations that are most suitable for participants. For many this may be at their own home in the evenings. Whilst researchers may have less control over the home environment, familiarity may help the respondent to relax and result in a more productive interview. 9 Establishing rapport with participants prior to the interview is also important as this can also have a positive effect on the subsequent development of the interview.

When conducting the actual interview it is prudent for the interviewer to familiarise themselves with the interview schedule, so that the process appears more natural and less rehearsed. However, to ensure that the interview is as productive as possible, researchers must possess a repertoire of skills and techniques to ensure that comprehensive and representative data are collected during the interview. 10 One of the most important skills is the ability to listen attentively to what is being said, so that participants are able to recount their experiences as fully as possible, without unnecessary interruptions.

Other important skills include adopting open and emotionally neutral body language, nodding, smiling, looking interested and making encouraging noises (eg, 'Mmmm') during the interview. 2 The strategic use of silence, if used appropriately, can also be highly effective at getting respondents to contemplate their responses, talk more, elaborate or clarify particular issues. Other techniques that can be used to develop the interview further include reflecting on remarks made by participants (eg, 'Pain?') and probing remarks ('When you said you were afraid of going to the dentist what did you mean?'). 9 Where appropriate, it is also wise to seek clarification from respondents if it is unclear what they mean. The use of 'leading' or 'loaded' questions that may unduly influence responses should always be avoided (eg, 'So you think dental surgery waiting rooms are frightening?' rather than 'How do you find the waiting room at the dentists?').

At the end of the interview it is important to thank participants for their time and ask them if there is anything they would like to add. This gives respondents an opportunity to deal with issues that they have thought about, or think are important but have not been dealt with by the interviewer. 9 This can often lead to the discovery of new, unanticipated information. Respondents should also be debriefed about the study after the interview has finished.

All interviews should be tape recorded and transcribed verbatim afterwards, as this protects against bias and provides a permanent record of what was and was not said. 8 It is often also helpful to make 'field notes' during and immediately after each interview about observations, thoughts and ideas about the interview, as this can help in data analysis process. 4 , 8

Focus groups

Focus groups share many common features with less structured interviews, but there is more to them than merely collecting similar data from many participants at once. A focus group is a group discussion on a particular topic organised for research purposes. This discussion is guided, monitored and recorded by a researcher (sometimes called a moderator or facilitator). 11 , 12

Focus groups were first used as a research method in market research, originating in the 1940s in the work of the Bureau of Applied Social Research at Columbia University. Eventually the success of focus groups as a marketing tool in the private sector resulted in its use in public sector marketing, such as the assessment of the impact of health education campaigns. 13 However, focus group techniques, as used in public and private sectors, have diverged over time. Therefore, in this paper, we seek to describe focus groups as they are used in academic research.

When focus groups are used

Focus groups are used for generating information on collective views, and the meanings that lie behind those views. They are also useful in generating a rich understanding of participants' experiences and beliefs. 12 Suggested criteria for using focus groups include: 13

As a standalone method, for research relating to group norms, meanings and processes

In a multi-method design, to explore a topic or collect group language or narratives to be used in later stages

To clarify, extend, qualify or challenge data collected through other methods

To feedback results to research participants.

Morgan 12 suggests that focus groups should be avoided according to the following criteria:

If listening to participants' views generates expectations for the outcome of the research that can not be fulfilled

If participants are uneasy with each other, and will therefore not discuss their feelings and opinions openly

If the topic of interest to the researcher is not a topic the participants can or wish to discuss

If statistical data is required. Focus groups give depth and insight, but cannot produce useful numerical results.

Conducting focus groups: group composition and size

The composition of a focus group needs great care to get the best quality of discussion. There is no 'best' solution to group composition, and group mix will always impact on the data, according to things such as the mix of ages, sexes and social professional statuses of the participants. What is important is that the researcher gives due consideration to the impact of group mix (eg, how the group may interact with each other) before the focus group proceeds. 14

Interaction is key to a successful focus group. Sometimes this means a pre-existing group interacts best for research purposes, and sometimes stranger groups. Pre-existing groups may be easier to recruit, have shared experiences and enjoy a comfort and familiarity which facilitates discussion or the ability to challenge each other comfortably. In health settings, pre-existing groups can overcome issues relating to disclosure of potentially stigmatising status which people may find uncomfortable in stranger groups (conversely there may be situations where disclosure is more comfortable in stranger groups). In other research projects it may be decided that stranger groups will be able to speak more freely without fear of repercussion, and challenges to other participants may be more challenging and probing, leading to richer data. 13

Group size is an important consideration in focus group research. Stewart and Shamdasani 14 suggest that it is better to slightly over-recruit for a focus group and potentially manage a slightly larger group, than under-recruit and risk having to cancel the session or having an unsatisfactory discussion. They advise that each group will probably have two non-attenders. The optimum size for a focus group is six to eight participants (excluding researchers), but focus groups can work successfully with as few as three and as many as 14 participants. Small groups risk limited discussion occurring, while large groups can be chaotic, hard to manage for the moderator and frustrating for participants who feel they get insufficient opportunities to speak. 13

Preparing an interview schedule

Like research interviews, the interview schedule for focus groups is often no more structured than a loose schedule of topics to be discussed. However, in preparing an interview schedule for focus groups, Stewart and Shamdasani 14 suggest two general principles:

Questions should move from general to more specific questions

Question order should be relative to importance of issues in the research agenda.

There can, however, be some conflict between these two principles, and trade offs are often needed, although often discussions will take on a life of their own, which will influence or determine the order in which issues are covered. Usually, less than a dozen predetermined questions are needed and, as with research interviews, the researcher will also probe and expand on issues according to the discussion.

Moderating a focus group looks easy when done well, but requires a complex set of skills, which are related to the following principles: 15

Participants have valuable views and the ability to respond actively, positively and respectfully. Such an approach is not simply a courtesy, but will encourage fruitful discussions

Moderating without participating: a moderator must guide a discussion rather than join in with it. Expressing one's own views tends to give participants cues as to what to say (introducing bias), rather than the confidence to be open and honest about their own views

Be prepared for views that may be unpalatably critical of a topic which may be important to you

It is important to recognise that researchers' individual characteristics mean that no one person will always be suitable to moderate any kind of group. Sometimes the characteristics that suit a moderator for one group will inhibit discussion in another

Be yourself. If the moderator is comfortable and natural, participants will feel relaxed.

The moderator should facilitate group discussion, keeping it focussed without leading it. They should also be able to prevent the discussion being dominated by one member (for example, by emphasising at the outset the importance of hearing a range of views), ensure that all participants have ample opportunity to contribute, allow differences of opinions to be discussed fairly and, if required, encourage reticent participants. 13

Other relevant factors

The venue for a focus group is important and should, ideally, be accessible, comfortable, private, quiet and free from distractions. 13 However, while a central location, such as the participants' workplace or school, may encourage attendance, the venue may affect participants' behaviour. For example, in a school setting, pupils may behave like pupils, and in clinical settings, participants may be affected by any anxieties that affect them when they attend in a patient role.

Focus groups are usually recorded, often observed (by a researcher other than the moderator, whose role is to observe the interaction of the group to enhance analysis) and sometimes videotaped. At the start of a focus group, a moderator should acknowledge the presence of the audio recording equipment, assure participants of confidentiality and give people the opportunity to withdraw if they are uncomfortable with being taped. 14

A good quality multi-directional external microphone is recommended for the recording of focus groups, as internal microphones are rarely good enough to cope with the variation in volume of different speakers. 13 If observers are present, they should be introduced to participants as someone who is just there to observe, and sit away from the discussion. 14 Videotaping will require more than one camera to capture the whole group, as well as additional operational personnel in the room. This is, therefore, very obtrusive, which can affect the spontaneity of the group and in a focus group does not usually yield enough additional information that could not be captured by an observer to make videotaping worthwhile. 15

The systematic analysis of focus group transcripts is crucial. However, the transcription of focus groups is more complex and time consuming than in one-to-one interviews, and each hour of audio can take up to eight hours to transcribe and generate approximately 100 pages of text. Recordings should be transcribed verbatim and also speakers should be identified in a way that makes it possible to follow the contributions of each individual. Sometimes observational notes also need to be described in the transcripts in order for them to make sense.

The analysis of qualitative data is explored in the final paper of this series. However, it is important to note that the analysis of focus group data is different from other qualitative data because of their interactive nature, and this needs to be taken into consideration during analysis. The importance of the context of other speakers is essential to the understanding of individual contributions. 13 For example, in a group situation, participants will often challenge each other and justify their remarks because of the group setting, in a way that perhaps they would not in a one-to-one interview. The analysis of focus group data must therefore take account of the group dynamics that have generated remarks.

Focus groups in dental research

Focus groups are used increasingly in dental research, on a diverse range of topics, 16 illuminating a number of areas relating to patients, dental services and the dental profession. Addressing a special needs population difficult to access and sample through quantitative measures, Robinson et al . 17 used focus groups to investigate the oral health-related attitudes of drug users, exploring the priorities, understandings and barriers to care they encounter. Newton et al . 18 used focus groups to explore barriers to services among minority ethnic groups, highlighting for the first time differences between minority ethnic groups. Demonstrating the use of the method with professional groups as subjects in dental research, Gussy et al . 19 explored the barriers to and possible strategies for developing a shared approach in prevention of caries among pre-schoolers. This mixed method study was very important as the qualitative element was able to explain why the clinical trial failed, and this understanding may help researchers improve on the quantitative aspect of future studies, as well as making a valuable academic contribution in its own right.

Interviews and focus groups remain the most common methods of data collection in qualitative research, and are now being used with increasing frequency in dental research, particularly to access areas not amendable to quantitative methods and/or where depth, insight and understanding of particular phenomena are required. The examples of dental studies that have employed these methods also help to demonstrate the range of research contexts to which interview and focus group research can make a useful contribution. The continued employment of these methods can further strengthen many areas of dentally related work.

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Gill, P., Stewart, K., Treasure, E. et al. Methods of data collection in qualitative research: interviews and focus groups. Br Dent J 204 , 291–295 (2008). https://doi.org/10.1038/bdj.2008.192

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Interview as a Method for Qualitative Research

using interview in qualitative research

Goals of Interview Research

  • Preferences
  • They help you explain, better understand, and explore research subjects' opinions, behavior, experiences, phenomenon, etc.
  • Interview questions are usually open-ended questions so that in-depth information will be collected.

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There are several types of interviews, including:

  • Face-to-Face
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FAQ: Conducting Interview Research

What are the important steps involved in interviews?

  • Think about who you will interview
  • Think about what kind of information you want to obtain from interviews
  • Think about why you want to pursue in-depth information around your research topic
  • Introduce yourself and explain the aim of the interview
  • Devise your questions so interviewees can help answer your research question
  • Have a sequence to your questions / topics by grouping them in themes
  • Make sure you can easily move back and forth between questions / topics
  • Make sure your questions are clear and easy to understand
  • Do not ask leading questions
  • Do you want to bring a second interviewer with you?
  • Do you want to bring a notetaker?
  • Do you want to record interviews? If so, do you have time to transcribe interview recordings?
  • Where will you interview people? Where is the setting with the least distraction?
  • How long will each interview take?
  • Do you need to address terms of confidentiality?

Do I have to choose either a survey or interviewing method?

No.  In fact, many researchers use a mixed method - interviews can be useful as follow-up to certain respondents to surveys, e.g., to further investigate their responses.

Is training an interviewer important?

Yes, since the interviewer can control the quality of the result, training the interviewer becomes crucial.  If more than one interviewers are involved in your study, it is important to have every interviewer understand the interviewing procedure and rehearse the interviewing process before beginning the formal study.

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Interviews in qualitative research

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  • PMID: 25783145
  • DOI: 10.7748/nr.22.4.6.s2

Interviews are a common method of data collection in nursing research. They are frequently used alone in a qualitative study or combined with other data collection methods in mixed or multi-method research. Semi-structured interviews, where the researcher has some predefined questions or topics but then probes further as the participant responds, can produce powerful data that provide insights into the participants' experiences, perceptions or opinions.

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Original research article, patients' experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation: a qualitative interview study.

using interview in qualitative research

  • 1 Faculty of Medicine, Paracelsus Medical University, Salzburg, Austria
  • 2 Ludwig Boltzmann Institute for Digital Health and Prevention, Salzburg, Austria
  • 3 University Institute of Sports Medicine, Prevention and Rehabilitation and Research Institute of Molecular Sports Medicine and Rehabilitation, Paracelsus Medical University, Salzburg, Austria
  • 4 Department of Health Promotion, Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands

Introduction: Despite the well-known benefits of exercise-based cardiac rehabilitation for the secondary prevention of cardiovascular disease, participation in cardiac rehabilitation programmes and adherence to secondary prevention recommendations remain limited. Digital technologies have the potential to address low participation and adherence but attempts at implementing digital health interventions in real-life clinical practice frequently encounter various barriers. Studies about patients' experiences and perspectives regarding the use of digital technology can assist developers, researchers and clinicians in addressing or pre-empting patient-related barriers. This study was therefore conducted to investigate the experiences and perspectives of cardiac rehabilitation patients in Austria with regard to using digital technology for physical activity and exercise.

Methods: Twenty-five current and former cardiac rehabilitation patients (18 men and 7 women, age range 39 to 83) with various cardiac conditions were recruited from a clinical site in Salzburg, Austria. Semi-structured qualitative interviews were audio-recorded and transcribed verbatim. The analysis followed a descriptive phenomenological approach, applying the framework analysis method.

Results: The sample was diverse, including interviewees who readily used digital devices to support their physical activity, exercise and health monitoring, and interviewees who did not. Simplicity, convenience and accessibility were highlighted as important facilitators for the use of digital technology, while annoyance with digital devices, concerns about becoming dependent on them, or simply a preference to not use digital technology were commonly stated reasons for non-use. Interviewees' views on data protection, data sharing and artificial intelligence revealed wide variations in individuals' prior knowledge and experience about these topics, and a need for greater accessibility and transparency of data protection regulation and data sharing arrangements.

Discussion: These findings support the importance that is attributed to user-centred design methodologies in the conceptualisation and design of digital health interventions, and the imperative to develop solutions that are simple, accessible and that can be personalised according to the preferences and capabilities of the individual patient. Regarding data protection, data sharing and artificial intelligence, the findings indicate opportunity for information and education, as well as the need to offer patients transparency and accountability in order to build trust in digital technology and digital health interventions.

1 Introduction

The growing prevalence of cardiovascular disease (CVD) presents an increasing global challenge. Accounting for 18.6 million deaths per year in 2019, CVD remains the leading cause of death worldwide ( 1 ). Patients suffering from CVD and its sequelae such as myocardial infarction, heart failure and stroke face severe burden, including reduced quality of life, reduced exercise tolerance and a higher risk of hospital admissions and mortality ( 2 ). In Austria in 2019, the age-standardised CVD incidence was 654 per 100,000, the age-standardised mortality attributed to CVD was 151 per 100,000, and CVD accounted for 5,105 disability-adjusted life-years per 100,000 across all ages in both sexes ( 1 ). Prevention is of utmost importance to reduce morbidity and mortality caused by CVD ( 3 ).

Exercise-based cardiac rehabilitation is an evidence-based secondary prevention model that has been proven to prolong life and improve functional capacity, well-being and quality of life for individuals with CVD ( 4 , 5 ). Exercise-based cardiac rehabilitation is a multidisciplinary intervention comprising clinical assessments, patient education, pharmacological therapy, exercise training, physical activity counselling, psychological support and support to address CVD risk factors and lifestyle modifications. In the setting of this study in Austria, cardiac rehabilitation provision is standardised according to national guidelines and organised in four phases: phase I refers to the acute hospital admission; phase II refers to a structured programme under medical supervision in an inpatient (3 to 4 weeks) or outpatient (up to 6 weeks) setting, with the main focus on improving physical performance; phase III refers to a 6 to 12 months outpatient programme, with the aim of supporting sustainability of lifestyle modifications; and phase IV refers to patients' independent lifelong secondary prevention by continuing the CVD preventive behaviour from the previous phases ( 6 , 7 ). Notably, the structure and organisation of cardiac rehabilitation programmes can differ between countries ( 8 ).

Despite the well-known benefits of exercise-based cardiac rehabilitation, many patients who qualify for it based on their medical history do not participate in cardiac rehabilitation programmes, with reported participation rates among eligible CVD patients in Austria of 30% and 20% for phases II and III, respectively ( 9 ), and 30%–50% in other European countries ( 8 ). Moreover, there is limited adherence and carry-over from the well-supervised cardiac rehabilitation phases to patients' independent secondary prevention behaviour. The maintenance of regular heart-healthy physical activity and exercise, for example, constitutes a crucial secondary prevention behaviour, but the effectiveness of cardiac rehabilitation programmes for establishing long-tern physical activity habits is variable ( 10 , 11 ).

Low participation in cardiac rehabilitation programmes and poor long-term adherence to CVD secondary prevention behaviours are important contributing factors for re-hospitalisation and high rates of morbidity and mortality. The underlying reasons for low participation and poor adherence are many and multi-faceted ( 12 , 13 ), including patients' employment and family responsibilities, location of cardiac rehabilitation centres and resulting travel times for patients, lack of social support from family and friends, and lack of knowledge and low health literacy (i.e., an individual's ability to access, understand and act on health information; 14 ) of individuals with CVD.

Digital technologies have the potential to address or at least alleviate some of these reasons. The term “digital health” describes the implementation of digital technology in the context of healthcare, encompassing “electronic health” (i.e., the use of information and communications technology in the health domain), “mobile health” (i.e., the use of wireless technologies for the purpose of health), “telemedicine” (i.e., the provision of health services at a distance), and emerging areas such as the use of advanced computing sciences in big data and artificial intelligence ( 15 ). Numerous scientific publications describe the vast potential of digital health interventions to advance the care of individuals with CVD, for example by enabling home-based and technology-based cardiac rehabilitation across phases II, III and IV ( 16 ), by supporting regular physical activity and other heart-healthy lifestyle modifications through text-messaging programmes, smartphone applications and wearable devices ( 17 ), or by enhancing clinical decision-making through artificial intelligence-supported analysis of large volumes of patient data ( 18 ). Moreover, systematic reviews provide good evidence of patient safety of digital health interventions for cardiac rehabilitation, with some studies even reporting fewer associated adverse events in digital intervention groups than in control groups ( 19 ). However, attempts at implementing such digital health interventions in real-life clinical practice frequently encounter various barriers ( 20 ). From the perspective of CVD patients, two consistently reported barriers are poor digital literacy and skills (i.e., lack of understanding of, or lack of physical capabilities to interact with digital health interventions) and low acceptability (i.e., lack of perceived effectiveness and low use of digital health interventions; 20 ).

Insight into CVD patients’ experiences and perspectives regarding the use of digital technology can assist developers, researchers and clinicians in addressing or pre-empting these patient-related barriers. These patient perspectives can be incorporated in the design of digital health interventions and in the design of evaluation studies and implementation strategies for digital health interventions. But to date, there have not been any publications of such studies for the Austrian cardiac rehabilitation community.

The present study was therefore conducted to investigate the experiences and perspectives of cardiac rehabilitation patients in Austria with regard to using digital technology, in particular for physical activity and exercise. The study addressed the following research questions: What are the reasons for use or non-use of digital devices? What are obstacles to the implementation of digital health interventions? What is the user experience and acceptance of currently available digital technology? And what are patients' views on recent developments and challenges in digital health around data protection, data sharing and artificial intelligence?

2 Materials and methods

2.1 study design.

We conducted a qualitative study with semi-structured interviews to explore patients' experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation. The reporting of this study follows the Consolidated Criteria for Reporting Qualitative Research (COREQ; 21 ). The COREQ checklist is provided in Supplementary Appendix S1 . In the overarching methodological orientation of this work, we took a phenomenological approach, aiming to explore the topic from the perspective of those who have lived experience of CVD and cardiac rehabilitation ( 22 ).

2.2 Setting and sampling

The study was conducted at the Ludwig Boltzmann Institute for Digital Health and Prevention in Salzburg, Austria. Participants were recruited from among current and previous cardiac rehabilitation patients at the University Institute of Sports Medicine, Prevention and Rehabilitation in Salzburg, Austria. The sampling strategy was purposive, aiming for diverse representation in terms of age, gender and time since cardiac event.

A target sample of 25 participants was possible within the study resources and timeline and expected to yield relevant breadth and depth of data. Eligible were adult patients with a diagnosed CVD who were current or previous participants in phase II cardiac rehabilitation and residents of the city of Salzburg or its surrounding areas. Excluded were individuals with limited German language proficiency. Forty-nine eligible patients were identified from patient records at the recruiting site and invited to take part in the study, either in writing by letter or in person by clinical staff at the site. Patients were provided with a study information leaflet including a contact for patients to inquire further about the study. Patients were given at least 48 h to consider their participation in the study. All patients who agreed to take part in the study gave written informed consent.

2.3 Data collection

The content of the semi-structured interviews was developed based on relevant literature and included questions to explore two major topic areas: physical activity in cardiac rehabilitation, and digital technology. The interview guide was piloted with members of the Ludwig Boltzmann Institute's service user advisory group, consisting of CVD patients who had attended cardiac rehabilitation. All interviews were conducted by JG either face-to-face in a private room at the Ludwig Boltzmann Institute or remotely via video call if preferred by the participant. Interviews lasted between 34 and 92 min. No other persons were present during the interviews. Each participant gave one interview. All interviews took place during July to October 2020. All interviews were conducted in German. Interviews were audio-recorded on two voice recorders. Opening questions were asked verbatim according to the interview guide, and follow-up questions were asked optionally and depending on the course of the conversation. An English translation of the interview guide is attached in Supplementary Appendix S2 .

Concluding the interview, participants were asked to answer demographic and disease-related questions, and to self-complete the German version of the International Physical Activity Questionnaire Short Form (IPAQ-SF; 23 ) and the German TA-EG questionnaire, a measure of affinity for technology ( 24 ). The IPAQ-SF includes seven questions to capture the volume and intensity of physical activity during the past seven days, allowing an estimate of physical activity levels (low, moderate, high) based on metabolic equivalents of tasks. The TA-EG questionnaire comprises 19 statements about technology (enthusiasm in the interaction with technology, subjectively experienced competence, positive consequences and negative consequences of the usage of technology), and respondents rate the extent to which each statement applies to them. Ratings range from 1 to 5, with higher scores reflecting higher affinity for technology. Participants completed the questionnaires independently while the interviewer remained in the room, available to answer questions if needed.

2.4 Data analysis

For our data analysis, we applied a mixed deductive and data-driven inductive approach using framework analysis according to the steps described by Gale et al. ( 25 ): transcription, familiarisation with the interview, coding, developing a working analytical framework, applying the analytical framework, charting data into a framework matrix and interpreting the data.

All audio-recorded interviews were transcribed verbatim, partly by the interviewing researcher (JG) and partly by a professional transcription service. Transcripts were pseudonymised, removing any information that could identify the speaking participant. These transcripts, supplemented by the IPAQ-SF and TA-EG questionnaires, constituted the data for analysis.

Data analysis was conducted by AZ with methodological support from STK and using Delve qualitative analysis software ( https://delvetool.com/ ). During the familiarisation process, AZ read and re-read the interview transcripts several times, listened to the interview recordings, and wrote down her thoughts and impressions in analytical notes. Due to the richness of the data, we decided to restrict the analysis to interview sections related to digital technology, specifically with a focus on understanding the facilitators and barriers to use of digital technology for physical activity and exercise. AZ first read several transcripts and conducted line-by-line coding, describing her interpretation of quotes. These codes gave rise to the initial framework development. As AZ coded further transcripts, the initial framework was discussed and reviewed iteratively with STK and RC until consent was achieved. Afterwards, the coding framework was applied to the remaining transcripts, including one open category (“other”) to allow inductive coding of passages that did not match any of the framework codes but were considered interesting and relevant regarding the aim of the study. The coding framework and definitions of codes are provided in Supplementary Appendix S3 . Once all the transcripts were coded, the data was summarised by category and charted into a thematic matrix. The final step of the data analysis was the interpretation of the data by identifying characteristics and differences, generating typologies and integrating theoretical concepts ( 25 ).

2.5 Research team and reflexivity

At the time of the study, the female interviewer (JG) was a pre-doctoral researcher at the Ludwig Boltzmann Institute with a background in nursing, master's degree and previous experience in qualitative interviewing. Other than communicating and establishing rapport with participants who expressed interest in the study, JG did not have any prior relationship with study participants. Participants knew that the research was conducted by JG in her role as researcher at the institute. The female data analyst (AZ) was a medical student with a previously completed psychology degree and conducted the data analysis as a research project towards her medical degree. AZ worked with the transcripts only and had no contact with study participants. STK was a research group leader at the Ludwig Boltzmann Institute with a background in physiotherapy and a doctoral degree in clinical neuroscience. He led the study and provided supervision and methodological support to JG and AZ. RC was professor of behaviour change and technology. He provided methodological and content expertise in the study design and data analysis. JN was professor of cardiology, scientific director of the Ludwig Boltzmann Institute and medical director of the recruiting site. He provided operational support for study recruitment and content expertise in the study design and data analysis.

Our reflexive stance, and in particular the reflexive stance of AZ as the main data analyst, was to take a descriptive approach aligned with transcendental phenomenology. We sought to bracket our individual subjectivity and to remain vigilant to the bracketing work, so as not to bias the analysis and interpretation ( 22 ).

We employed several strategies for enhancing scientific rigour in qualitative research. AZ recorded reflexive and analytic notes throughout the analysis and interpretation process and discussed these in regular peer review meetings with STK and RC. We did not conduct member checking of interview transcripts or analysis results with study participants. We used the questionnaire data (IPAQ-SF, TA-EG) to incorporate an element of triangulation to the qualitative analysis. In the reporting of this study, we followed an international reporting standard for qualitative research ( 21 ).

2.7 Ethical and regulatory considerations

This study was conducted according to standard ethical practice in healthcare research with humans ( 26 ). Study participation was voluntary, and all participants provided written informed consent. Participants were free to discontinue their participation without giving a reason and without incurring any negative consequences. The study was submitted for review to the medical research ethics committee of the county of Salzburg (reference number 1040/2020) and was exempt from formal ethical review due to its low risk.

Eighteen (72%) male and seven (28%) female patients participated in the study. Participants' age ranged from 39 to 83 years, with a mean age of 65.1 (SD = 9.6) years for male participants and 69.4 (SD = 9.8) years for female participants. Fifteen participants (60%) reported high physical activity levels, two (8%) reported moderate physical activity levels and eight (32%) answered the IPAQ-SF questionnaire incompletely. The sample's affinity for technology according to the TA-EG questionnaire was slightly above average, scoring 2.9 (SD = 0.9) for “enthusiasm”, 3.2 (SD = 1.0) for “competence”, 3.6 (SD = 0.6) for “positive attitude” and 3.2 (SD = 0.8) for “negative attitude”. Participant characteristics are presented in Table 1 .

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Table 1 . Participant characteristics.

Figure 1 gives an overview of themes and codes according to the coding framework ( Supplementary Appendix S3 ). For this results section, complementary codes were combined and are presented together to offer meaningful descriptions under the following sub-headings: reasons for using digital devices; reasons for non-use of digital devices; type of technology being used; need for improvement and complaints; attitude towards data protection; preparedness to share personal data; General Data Protection Regulation (GDPR); communication of data protection regulations; awareness of artificial intelligence; and trustworthiness of artificial intelligence. The description of results is supported with direct quotes, which were translated from the original German to English by AZ and STK. Quotes include participant pseudonyms, allowing cross-referencing with participant characteristics in Table 1 .

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Figure 1 . Overview of themes and codes. AI, artificial intelligence; GDPR, general data protection regulation.

3.1 Reasons for using digital devices

Although all the participants in the study owned a smartphone, only a little over half used it for more than simply making phone calls. For analytic purposes, participants were categorised into users ( n  = 15, 60%) and non-users ( n  = 10, 40%) of digital devices, whereby those who reported using digital technology such as smartphone applications, smartwatches or other tracking devices to support a healthy lifestyle and exercise in the context of their cardiac rehabilitation were categorised as “users of digital technology”.

The majority of users explained that digital technology had been recommended to them during cardiac rehabilitation and that their awareness of the importance of regular exercise and health monitoring had been created by healthcare professionals:

Since they have actually recommended that [the use of digital devices] in the cardiac rehabilitation centre. (P08)
[I use that] in order to move in a better way, in order to move more. That is quite important! (P03)

For digital device users, features related to health monitoring were of great importance. The three most mentioned health monitoring aspects were heart rate, blood pressure and caloric consumption. Many participants were concerned about being able to track their heart rate during physical activity:

Well, of course, I need a heart rate monitor on my watch, because the heart rate should not rise too much. (P01)
To me, the minimum requirement is the blood pressure measurement. (P04)
Well, the step counter is important to me, because it shows my calorie consumption, doesn't it? (P03)

Some participants not only appreciated the ability to continuously monitor their health through digital devices, but also wished for extended monitoring capabilities, including longer battery life and the ability to monitor health during sleep:

The battery life [needs to be improved]. Because, if you are out and about all day, it needs to work for more than a maximum of four hours, in order to monitor without interruption. (P04)

Apart from being able to monitor health parameters, many participants enjoyed the motivating features of digital devices:

It is simply nice; if I am out and about anywhere, the watch on my wrist is suddenly vibrating, and I realise that I have at least met today's minimum requirement. (P3)
It is kind of motivating! Right now, it is a little fun. (P08)

Some interviewees also highlighted that use of digital devices provided them with a sense of security and encouraged them to reflect on their own health behaviour:

I use that right now because it simply gives me a sense of security. (P23)
Well, it is kind of a reflection tool to me. (P08)

One participant stated that their main reason for exercising and using digital devices to improve their overall health was grounded in self-love. The interviewee explained that any technology was useless, unless one took care of oneself and one's health and well-being:

Actually, it is all about self-love. (P12)

3.2 Reasons for non-use of digital devices

Reasons for not using digital devices in cardiac rehabilitation or for exercise were varied. While some patients claimed to have “too little time” for dealing with technologies, others expressed an aversion to digital devices, due to negative past experiences:

I am annoyed by the sounds […] it stresses me out. (P16)
I once owned such a device. That means, it actually never really worked. (P25)

Several participants stated that they actively avoided handling digital devices:

I actually try to avoid such devices […] I am more the analogue type. (P14)
I am old-fashioned. (P15)

Other participants outright rejected digital devices, finding them unnecessary:

I think I don't need that. Because I got a kind of feeling. I can do things without that. I don't need that. (P20)

Some also considered technology as a threat and expressed concerns about being under constant surveillance and controlled by technology:

I don't want to be controlled by such a device! (P07)
That's my opinion. It is bad for people. (P16)

The difference in attitudes between users and non-users of digital technology was also reflected in the TA-EG scores, which averaged 3.3 (SD = 0,7) vs. 2.3 (SD = 0,8) for “enthusiasm”, 3.4 (SD = 0.8) vs. 2.9 (SD = 1.2) for “competence”, 3.8 (SD = 0.5) vs. 3.4 (SD = 0.6) for “positive attitude” and 3.3 (SD = 0.7) vs. 3.0 (SD = 0.9) for “negative attitude”, respectively.

Notably, many participants among both users and non-users of digital technology mentioned their dependence on younger relatives when handling digital devices, describing that they relied on someone to regularly explain and show them new features and applications:

My son got me a tablet for Christmas, and he showed me how to look at pictures. I cannot do much more than that with it, but I don't want to anyway. (P06)

3.3 Type of technology being used

Participants stated that the devices they predominately used to monitor exercise and health parameters were smartphones and smartwatches. Most participants expressed their appreciation for simple handling and pre-installed health applications on their devices, such as the step counter function:

Yes, the walking function is on it [the phone]. My 6,000 steps are on it. That has already been integrated on the smartphone, completely installed. (P02)
Yes, I have such an app. […] that means I have to always carry my phone with me. It exactly shows how many steps one takes or what one has done in a day. (P18)
[…] so, if I look at my watch today, I look at a quite good, new Suunto. That's where my step counter has been installed automatically. (P21)
Well, the Apple watch is quite convenient, […] insofar as I find all relevant applications in the main menu. (P10)

Only a few participants reported using health and exercise-promotion programmes offered on television or online during the COVID-19 pandemic. Few participants also used more sophisticated devices such as global positioning system (GPS) sensors and other types of monitors incorporated into their bicycles or other sports equipment:

Yes, that's the GPS on the mountain bike. It shows altitude and helps with orientation, geographically, kilometres, and distances and so on. […] That's actually my favourite device. (P04)

3.4 Need for improvement and complaints

With regard to complaints about digital technology and suggestions for improvement, the most often mentioned suggestion for improvement was a call for more simplicity. Participants stated that they did not want to use devices if they were too complicated to handle. Additionally, it was highlighted that the screen design and the text format had to be accessible and appealing:

It has so many features that I do not need at all. (P02)
Some devices go far too much into detail. (P13)
It is important that you don't have to search for applications again and again. It should be clearly visible. Otherwise, one loses one's temper. (P13)

Some interviewees complained about the high level of dependence that technical devices would lead to:

People rely too much on the feedback from those devices and not on things that your body is telling you. (P12)
I have already started to sometimes take the smartwatch off. […] to get a feel for it heart rate] again, otherwise, I would non-stop check the watch. (P23)

A few participants criticised that the price of digital devices was too high and therefore unaffordable to them:

Well, if that [smartwatches] would be available at a reasonable price, then I certainly would be interested. (P08)

Some other users, however, stated that they were very pleased and satisfied with their devices and their handling.

There is not really a thing that I would want to improve. I have not even thought about that. (P03)
There is absolutely nothing irritating about that [device]. (P02)

3.5 Attitude towards data protection

When asked about data protection, interviewees displayed rather divergent attitudes. While some participants had a clear opinion on this issue, others stated that they did not care much about the topic of data protection, or that they simply found it to be an annoying issue:

The problem is, if you want to use certain apps, you have to give your consent anyway. (P02)
[…] the whole data protection issue is the dumbest thing in the world that someone could possibly think of. (P21)

Most participants stated that they were not too concerned about their data because they had “nothing to hide” anyway:

To be honest, when it comes to data protection, I usually say: “I don’t have any secrets!” […] I don't take that too seriously. If they want to know something, let them know. (P02)
In principle, I go through life like that: if you are not really up to anything [secretive], nothing can happen to you with regard to data protection. (P12)

In contrast, a few interviewees expressed their concerns about the use and transfer of data, as well as their wish for more transparency around data usage:

That's why I say: I simply want to be in control of my data. (P10)
Well, when it comes to the internet, I am rather cautious. I am fully aware that all the data is certainly used somehow. In my opinion, more education and transparency on this topic would be quite important. (P16)

3.6 Preparedness to share personal data

Some participants stated that they would be prepared to share all their personal data, and that they did not consider anything to be private data which should be handled confidentially:

I don't have that kind of data that I would not be prepared to share. (P18)
I am like an open book. (P03)

Most participants, however, reported at least one type of personal data that they were not willing to share. Many participants were most concerned about their financial data:

When it comes to financial data, one must be particularly careful. (P04)
I have a small book back home. In there, all my bank data, the credit card number and stuff like that is handwritten and safe. I would never put that sort of data on my phone. (P17)

To other participants, data about their leisure time, their current location or their family life was viewed as most important and confidential, and not to be shared:

Well, I don't want to share my current location. I don't want to disclose any GPS data to any apps. (P15)
[I would not share] anything that has to do with my leisure time. (P12)

Regarding the sharing of personal health data, interviewees' views were divided. Some participants stated that they would never willingly share their own health data, while others considered it their duty to share health data with healthcare institutions and providers, for example for health research purposes:

Yes, of course [I would share my data] for research purposes! (P18)
Concerning medicine, I have to say, due to my personal medical history, I feel kind of obligated to return some favours to the health care system in any manner. (P19)

Some of those who were not prepared to share their personal health data explained that they were afraid that this type of data could disadvantage them or be used against them by health and social care organisations:

I don't have ELGA [Austrian electronic personal health record]. When it comes to health data, they pigeonhole people due to previous illnesses and stuff like that. (P24)
When it comes to health data, like serious diseases that are dealt with by the health insurance, I have to fear that it is passed on or traded. (P13)
If they are going to cut any benefits, then I have concerns! They have been talking about cutting certain things if one is obese. (P02)

3.7 General data protection regulation

Most participants reported that they were not familiar with the meaning or the content of the European Union General Data Protection Regulation (GDPR):

I have heard about it, but I don’t know what it is about. (P16)

Other participants stated that they were well-aware of the GDPR and its content. Moreover, a few interviewees had personally made use of the regulation by asking companies and organisations to delete their data:

[…] and that's when I told them, well, that I didn't [want] my data [to be used] any longer. Well, I think that worked automatically. (P18)
[…] so I sent a text message that referred to the GDPR and told them to delete all of my personal data and to never contact me again. The IT department even sent me a confirmation that everything has been removed. (P12)

Personal attitudes towards the GDPR varied. While some participants expressed their appreciation for the regulation, the majority did not approve of it:

I appreciate that. Yes, that is awesome! […] that I have the right to make use of it; this is very good! (P09)
No, this is totally unnecessary, because I know exactly whom I contact. (P24)
There is no point. (P05)
No, I have no need for that. […] I think I have nothing to hide, so I don't care at all. (P21)

3.8 Communication of data protection regulations

When participants were asked about their opinion regarding the need to confirm data protection declaration or data privacy statements (for example, when downloading apps or programmes), most participants expressed their preference for a shorter, simpler and more appealing presentation of data protection regulations. Some suggested the use of keywords or the highlighting of essential passages:

Of course, that could be designed in a better way. The key points could be highlighted, so there won't be misunderstandings. It could be reduced to the three or four most important questions. (P08)
That's the problem: who would ever have enough time to read and go through all that stuff? (P05)

Others wished for more transparency, larger font size and a more accessible design:

If the content is written in small print on the last page, no one is going to find that. (P21)
[…] if there was more transparency, that would be good! (P18)
[…] it is hard for the user to understand the content. […]no, it is too complicated. (P12)

3.9 Awareness of artificial intelligence

With regard to awareness of artificial intelligence, the sample represented a range from those who had little or no awareness to those who had in-depth knowledge about artificial intelligence. Only very few participants stated that they had never heard of artificial intelligence before:

No, [I have not heard about artificial intelligence yet]. What is it about? (P01)

Most participants reported having some general idea about artificial intelligence and its areas of application:

Well, I think artificial intelligence is becoming increasingly important in the medical sector. (P23)
Sure, Tesla, for example. Self-propelled cars, robots, drones. (P13)

And some participants stated that they had personal experience with artificial intelligence in the past:

Yes, I have been dealing with that. […] well, it is a double-edged sword. (P08)
You see, I have worked for an advertising agency, and artificial intelligence has been an important issue at work. […] everything that's happening in online stores or social media; in the background, there is always an algorithm and artificial intelligence and so on. (P19)

3.10 Trustworthiness of artificial intelligence

In terms of the trustworthiness of artificial intelligence, participants' opinions diverged. Some participants explained that they would feel comfortable relying on artificial intelligence:

I would rely blindly on. I would trust it. […] however, there is always somebody who initially had to program it, hence, the intelligence is still coming from people, in my opinion. (P17)
This is our future, for sure! Artificial intelligence, yes definitely! (P18)
Yes, of course [I would trust artificial intelligence]! It can be controlled. You can always recheck and do another test. (P02)
All that, it is unrealistic to me! I don't comprehend it, that's very suspicious to me. Well, I mean, it is artificial. I have to say; I am always skeptical regarding anything artificial. (P03)
I don't think that artificial intelligence can or should be trusted blindly. (P19)
If I would receive a Tesla S with an autopilot as a gift, I would never hand the steering wheel to artificial intelligence or electronics. (P13)

Some interviewees expressed concerns and fears over the use of artificial intelligence and its applications:

Well, let me put it that way: if a machine suddenly is way more intelligent than its owner, then it's getting worrisome. Jobs are going to be lost! (P25)
Indeed, that's a bit creepy, to be honest! I am scared, yes! (P16)

4 Discussion

We conducted semi-structured interviews to investigate the experiences and perspectives of 25 current and former cardiac rehabilitation patients in Austria with regard to using digital technology. The sample included individuals who readily used digital devices to support their physical activity, exercise and health monitoring, and individuals who did not. Simplicity, convenience and accessibility were highlighted as important facilitators for the use of digital technology, while annoyance with digital devices, concerns about becoming dependent on them, or simply a preference to not use digital technology were commonly stated reasons for non-use. Interviewees' views on data protection, data sharing and artificial intelligence revealed wide variations in individuals' prior knowledge and experience about these topics, and a need for greater accessibility and transparency of data protection regulation and data sharing arrangements.

4.1 Age-specific requirements

Although all participants reported owning a smartphone, only slightly more than half of the study group actually used smartphone applications and features beyond the simple function of calling. This observation is also mirrored in the Austrian general population of the corresponding age groups, although there has been an increasing tendency to use internet-based digital devices over the past 15 years ( 27 ). Reasons for non-use of digital technology may be attributed to generally low affinity for technology—as reflected in the low TA-EG scores for “enthusiasm” in our sample –, negative experiences related to technology, specific fears or concerns about using digital devices, or barriers related to older age ( 28 – 30 ). Krishnaswami and colleagues emphasise that age-specific barriers must be considered in the development and utilisation of technologies for older age groups ( 31 ). Participants in the present study suggested more simplicity of digital technology, including more appealing interfaces and less disrupting or irritating features, which echoes the findings of other studies. This poses the challenge to developers of digital health interventions to identify and be responsive to barriers across different age groups, and to design solutions that meet age-specific needs.

4.2 Dependence on support from others

Interviewees in the present study frequently reported a dependence on younger relatives, as many expressed a need for someone to explain features and applications to them, or to perform the installation and set-up of software and digital devices. Such lack of digital skills and limited knowledge and experience with digital applications present considerable obstacles to implementing digital health interventions in clinical practice ( 32 ). The active involvement of more digitally skilled spouses, partners, family members or friends in care processes might offer a solution ( 33 , 34 ). Nevertheless, not all CVD patients can rely on such a support system, and healthcare providers should consider to also offer formal user training and support to accompany the implementation of a digital health intervention ( 31 ). In addition to equipping patients with the skills to use a specific digital health intervention, such formal training and support provides an opportunity to educate patients about the more general technological background, infrastructure and regulations, thereby helping to reduce reservations and concerns about digital health.

4.3 Peer support

The importance of strategies that promote peer support among cardiac rehabilitation patients is frequently reported in other studies (e.g., 35 ), but interestingly this was not a prominent topic in the present study. Digital technology offers many possibilities to create opportunities for peer support, by connecting patients to each other through remote communication technology (video calls, email, messaging) or social media platforms (Facebook, WhatsApp, etc.), or by incorporating specific behavioural techniques for peer support in digital health interventions, such as the sharing and affirming of one's behavioural intentions, goals and achievements in the digital peer group. In this context, previous studies have highlighted the importance of face-to-face contact and the value of developing a sense of community with other patients as well as with clinical staff ( 30 , 33 , 35 , 36 ). While it is possible to achieve this through digital technology, for example using video conferencing platforms for face-to-face meetings and facilitating online communities via social media platforms, intervention developers may also consider blended formats including periodic in-person meetings for users of a digital health intervention.

4.4 Continuous monitoring and feedback

In Austria, cardiac rehabilitation programmes incorporate a focus on reducing the risk of recurrence by encouraging CVD patients to track their own health parameters ( 6 , 37 ). Hence, it is not surprising that many interviewees in our study talked about their motivation and ambition to monitor heart rate, blood pressure and calorie consumption. Most users of digital technology perceived the monitoring functions of their digital devices as very beneficial for improving their physical activity and health. Some interviewees even expressed an interest in more extended and continuous monitoring capabilities of their devices, for example suggesting that devices should have longer lasting batteries to enable longer and continuous operation. Additionally, receiving frequent or continuous feedback seemed to not only provide users of digital technology with a sense of security, but to also serve as a motivating factor, as reaching one's goals was perceived as increasing one's motivation, self-confidence (self-efficacy) and self-esteem. Other qualitative studies of digital health interventions have reported similarly positive perceptions of self-monitoring and self-evaluation among CVD patients (e.g., 36 ). This was in stark contrast to interviewees in the “non-user” group, some of whom expressed that self-tracking and the generated data from it could lead to uncertainty, anxiety or fear. Some participants stated more nuanced concerns about relying too much on the feedback from digital devices and losing touch with feeling one's own body, while others decidedly considered technology and surveillance a threat. From an intervention developer's perspective this indicates a need to acknowledge these different sides of patients' experiences and to incorporate patients' views about useful features in the design of digital health interventions. Empowering users by giving them control over the extent and pervasiveness of digital monitoring functionalities may offer a solution for catering to different levels of engagement.

4.5 Data protection

Aside from the GDPR, which was introduced in 2018 and has significantly contributed to raising the profile of data protection issues across the European Union ( 38 ), the concept of “do-it-yourself data protection”—describing that comprehensive data protection needs to be done more and more by individuals themselves—has become increasingly relevant, as a growing number of actors are interested in individuals' personal data ( 39 ). This is compounded by the “digital divide”, i.e., the gap between those who have access to forms of modern information technology and those who do not ( 40 , 41 ), placing individuals who lack knowledge, social status or resources to access digital technology or information at a disadvantage, also with regard to the protection of their personal data. Of note, the majority of interviewees in the present study appeared to care little about data protection. The statement “I have nothing to hide” was made frequently, expressing a sense of carefree light-heartedness that may reflect age, as it has been reported that older people are less likely to use tools or strategies that protect their personal data as compared to younger generations ( 39 ).

Conversely, some participants did express concerns about online security, called for more transparency and information about how their data was being processed, and stated a desire to be more in control of what was happening to/with their data and whether/how it was being shared, traded or otherwise used. However, this does not necessarily mean that these participants' online privacy behaviours were consistent with their attitudes, which can be explained by a knowledge gap ( 42 ). It has been reported that, although people express concerns about using and trading their personal data, they still share personal content online and accept that their data is taken and used by online providers. This observation indicates a lack of privacy literacy that prevents people from acting in a way that represents their beliefs and needs ( 42 ). Consistent with this observation, many participants in the present study stated that they provided their consent to privacy policies of websites and apps because, in their opinion, there was no alternative. Fostering knowledge about the technical aspects of online privacy and protection, laws and legal aspects, and strategies for individual privacy regulation is necessary in order to increase privacy literacy.

4.6 Sharing personal health data

There is now great international momentum towards enabling the sharing of personal health data to support healthcare delivery (“primary use of data”), and to facilitate access to health data for research and policy-making purposes (“secondary use of data”), for example through the establishment of the European Health Data Space ecosystem for data sharing ( 43 ). While some participants in the present study were fully prepared to share their personal health data with healthcare or research institutions, others expressed their preference to not share their personal data with anyone. Two main concerns were that health data could in some way be used against the person, and that there was a need for more transparency and information about data processing and trading. In particular, some participants expressed concerns that health insurances would deny payments based on information gained from personal health records. Public health research, however, relies on access to medical records and personal health data. If informed consent is required to access data from health records, this can lead to bias introduced through systematic differences between those who provide consent and those who do not. Therefore, it is essential to foster trust by offering patients information, education and transparency about data sharing processes and across all stages of data collection and processing ( 44 ). Public involvement in the discourse about the use of individual health records for healthcare research is of strategic importance to gain acceptance and reduce concerns and suspicion ( 45 ).

4.7 Artificial intelligence

Artificial intelligence has significantly advanced clinical care, for example by improving software for medical devices, facilitating the processing of large amounts of data and enabling greater precision of imaging technologies ( 46 ). In the past few years, the field has made great strides particularly in the development of large language models and natural language processing tools such as ChatGPT, with predictions that such applications of artificial intelligence could become valuable resources for clinical practice in the future ( 47 ). In this study, many participants viewed artificial intelligence with skepticism or even considered it worrisome or frightening. With regard to medical treatments, some participants stated that they would trust medical doctors more than they would trust any sort of artificial intelligence. This skeptical attitude might arise from a lack of information or a general objection to anything “artificial” as opposed to “natural”. Medical decision-making in general needs to account for uncertainty and often heterogeneous, erroneous, inaccurate or unknown data. While artificial intelligence might offer a way to integrate, fuse or map various data sources to support personalised decision-making and therapy prescription, it needs to be explainable and traceable to the extent that healthcare professionals have a possibility to understand how and why an artificial intelligence has arrived at a certain outcome ( 48 ). This level of transparency of the decision-making process is likely to also increase patients' trust. Some authors warn that the growth of artificial intelligence in healthcare might compound a trend from “hands-on” personal clinical practice to disembodied technological procedures ( 49 ). Others raise concerns whether artificial intelligence applications truly serve the patients' interests, or rather those who developed them ( 50 ). Against the background of these current academic discourses, the skeptical stance of many interviewees in the present study—albeit grounded mainly in intuitive reasoning rather than in an in-depth knowledge of the topic—certainly appears justified.

4.8 Technological solutionism

The terms “technological solutionism” and “technological fix” describe an ideology in which social or individual problems are considered discrete processes that can be improved and optimised by technological interventions ( 51 ). The steadily increasing body of evidence that demonstrates positive impacts of digital health interventions serves to amplify the widely publicised expectations that digital technology will (continue to) transform, or even revolutionise, healthcare ( 52 , 53 ). This plays into a narrative of technological solutionism, placing emphasis on digital technology and its role for improving health. However, some authors criticise technological solutionism for denying the role of intrinsic and personal factors for individual health, as illustrated by one participant in the present study who was asked how CVD patients’ level of physical activity and exercise could be further increased and replied that “[…] actually, it is all about self-love!” (P12). There is therefore a balance to be struck, between, on the one hand, leveraging the fantastic capabilities of the many digital technologies that are available to us today and driving digital development forward, and, on the other hand, maintaining the focus on understanding individual patients' core needs and their personal motivating factors to incorporate these into personalised care that may include digital health interventions.

4.9 Limitations

We acknowledge several limitations to this study. Due to the recruitment of study participants via one clinical service, interviewees could have been influenced to some extent by clinical practice at the site, for example by rehabilitation professionals promoting digital technology as part of their practice. The sample size for this study was determined a priori by available resources, and we did not formally assess data saturation. However, acknowledging differences in interpretations and approaches to data saturation ( 54 ), we suggest that our sampling strategy achieved its purpose and resulted in a dataset that provided diverse views and depth of data. The analysing researcher (AZ) lacked the proximity to interviewees and interviews that comes with conducting interviews oneself, but she developed close familiarity to the data by repeatedly reading the transcripts and listening to the audio recordings of the interviews.

5 Conclusion

This qualitative interview study has provided insights into CVD patients' experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation. The findings support the importance that is attributed to user-centred design methodologies in the conceptualisation and design of digital health interventions, and the imperative to develop solutions that are simple, accessible and that can be personalised according to the personal preferences and capabilities of the individual patient. With regard to data protection, data sharing and artificial intelligence, the findings indicate opportunity for information and education, as well as the need to offer patients transparency and accountability in order to build trust in digital technologies and digital health interventions.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The requirement of ethical approval was waived by Medical Research Ethics Committee of the County of Salzburg for this study involving humans because of its low risk. The study was conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

AZ: Formal Analysis, Writing – original draft, Writing – review & editing. JG: Writing – review & editing, Investigation. JN: Writing – review & editing, Formal Analysis, Methodology. RC: Conceptualization, Formal Analysis, Methodology, Writing – review & editing. SK: Formal Analysis, Methodology, Writing – review & editing, Conceptualization, Writing – original draft.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

The authors would like to thank all study participants for sharing their views and experiences, members of the Ludwig Boltzmann Institute's advisory group of cardiac patients for assistance in piloting the interview guide, and Hannah McGowan for support with manuscript editing.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fspor.2024.1371652/full#supplementary-material

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Keywords: artificial intelligence, cardiovascular disease, data protection, digital health literacy, mobile health, physical activity, secondary prevention, telemedicine

Citation: Zeller A, Gutenberg J, Niebauer J, Crutzen R and Kulnik ST (2024) Patients' experiences and perspectives regarding the use of digital technology to support exercise-based cardiac rehabilitation: a qualitative interview study. Front. Sports Act. Living 6:1371652. doi: 10.3389/fspor.2024.1371652

Received: 16 January 2024; Accepted: 6 March 2024; Published: 18 March 2024.

Reviewed by:

© 2024 Zeller, Gutenberg, Niebauer, Crutzen and Kulnik. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Stefan Tino Kulnik [email protected]

This article is part of the Research Topic

Physical Fitness via Advanced Technology - ICT and AI Solutions for Healthier Ageing

  • Open access
  • Published: 23 March 2024

Technology, data, people, and partnerships in addressing unmet social needs within Medicaid Managed Care

  • Rachel Hogg-Graham 1 ,
  • Allison M. Scott 2 ,
  • Emily R. Clear 1 ,
  • Elizabeth N. Riley 1 &
  • Teresa M. Waters 3  

BMC Health Services Research volume  24 , Article number:  368 ( 2024 ) Cite this article

Metrics details

Individuals with unmet social needs experience adverse health outcomes and are subject to greater inequities in health and social outcomes. Given the high prevalence of unmet needs among Medicaid enrollees, many Medicaid managed care organizations (MCOs) are now screening enrollees for unmet social needs and connecting them to community-based organizations (CBOs) with knowledge and resources to address identified needs. The use of screening and referral technology and data sharing are often considered key components in programs integrating health and social services. Despite this emphasis on technology and data collection, research suggests substantial barriers exist in operationalizing effective systems.

We used qualitative methods to examine cross-sector perspectives on the use of data and technology to facilitate MCO and CBO partnerships in Kentucky, a state with high Medicaid enrollment, to address enrollee social needs. We recruited participants through targeted sampling, and conducted 46 in-depth interviews with 26 representatives from all six Kentucky MCOs and 20 CBO leaders. Qualitative descriptive analysis, an inductive approach, was used to identify salient themes.

We found that MCOs and CBOs have differing levels of need for data, varying incentives for collecting and sharing data, and differing valuations of what data can or should do. Four themes emerged from interviewees’ descriptions of how they use data, including 1) to screen for patient needs, 2) to case manage, 3) to evaluate the effectiveness of programs, and 4) to partner with each other. Underlying these data use themes were areas of alignment between MCOs/CBOs, areas of incongruence, and areas of tension (both practical and ideological). The inability to interface with community partners for data privacy and ownership concerns contributes to division. Our findings suggest a disconnect between MCOs and CBOs regarding terms of their technology interfacing despite their shared mission of meeting the unmet social needs of enrollees.

Conclusions

While data and technology can be used to identify enrollee needs and determine the most critical need, it is not sufficient in resolving challenges. People and relationships across sectors are vital in connecting enrollees with the community resources to resolve unmet needs.

Peer Review reports

Introduction

Individuals with unmet social needs, like food and housing insecurity and transportation challenges, experience higher rates of adverse health outcomes [ 1 , 2 , 3 , 4 , 5 , 6 , 7 ] and are subject to greater inequities in health and social outcomes [ 8 ]. Unmet social needs are especially prevalent among Medicaid enrollees [ 9 ]. For this reason, state Medicaid programs are particularly interested in testing strategies that encourage and incentivize Medicaid managed care organizations (MCOs) to identify and address the complex social needs of enrollees [ 10 , 11 ]. Many Medicaid MCOs are now screening enrollees for their unmet social needs and connecting them to community-based organizations (CBOs) better equipped with knowledge and resources to address these needs [ 12 , 13 ].

The use of screening and referral technology and data sharing are often considered key components in programs integrating health and social services to address social needs [ 12 , 14 ]. Data sharing infrastructure has been highlighted as a way to streamline coordination and social need resolution [ 12 , 14 ]. In some instances, successful integration has facilitated strong connections between health and social services organizations, ensuring that patients move efficiently between sectors [ 14 , 15 , 16 ]. Despite this emphasis on technology and data collection and some positive integration, research suggests substantial barriers exist in operationalizing effective systems [ 12 , 17 ]. CBOs often have limited resources, financial and personnel, to put toward the use of advanced social need screening and referral systems [ 12 , 17 , 18 , 19 ]. The reliance on grant funding and other time-limited resource streams likely presents another barrier in the adoption of tools [ 17 ]. CBOs can also be hesitant to adopt technology and data systems owned by MCOs, hospitals, and other clinically oriented organizations because of data privacy and HIPAA-related issues [ 16 , 20 ].

Research examining health and community partnerships has identified technology adoption by CBOs and other social services organizations as an important barrier to collaboration [ 14 , 15 , 17 ]. Most prior studies examining data and technology include clinical organization perspectives on the use of tools but do not include robust information from community partners [ 12 , 14 , 16 ]. Further, those studies that do include perspectives from multiple organization types on the integration of health and social services are not focused on adopting screening and referral systems. Technology typically emerges in subthemes, and the evidence included does not provide in-depth information on benefits and challenges from both community and clinical partners [ 17 ].

This study examines CBO and MCO perspectives on the use of technology in social need screening and referral. The qualitative analysis presented here is part of a larger mixed methods study examining how Kentucky (KY) MCOs address unmet social needs in partnership with community organizations [ 21 ]. KY offers a unique opportunity to examine strategies addressing Medicaid enrollee needs. Just under 29% of all KY residents are enrolled in Medicaid, making it the third highest enrollment among US states [ 22 ]. KY is also geographically diverse, with distinct urban, rural, and Appalachian regions.

Setting and study population

A project Stakeholder Advisory Board (SAB), including representatives from all Medicaid MCOs, academia, a community-based organization, the State Department for Medicaid Services, and enrollees, met quarterly to provide expertise, guide research, and assist with the dissemination of study results. MCO representatives serving on our SAB were asked to 1) identify individuals in their organization leading efforts to address unmet social needs and population health outcomes among their enrollees and 2) identify CBOs they work closely with in their social need referral process. As part of a targeted sampling strategy, identified contacts were invited via email by the research team to participate in key informant interviews to discuss how MCOs and CBOs address social needs. Inclusion criteria were that participants were at least 18 years old, were employed at an MCO/CBO in Kentucky, and were willing to engage in an interview in English. A total of 32 MCO contacts were invited and 33 CBOs, giving us response rates of 81% and 58% respectively.

Participants

Our sample of 46 participants comprised 26 representatives from 6 MCOs (ranging from 3 to 6 participants per MCO) and 20 representatives from 19 unique CBOs. MCO participants represented various organizational roles, including vice presidents, directors, population health, case management, and community engagement. CBO participants represented roles including directors, Chief Executive Officers, Chief Operating Officers, Medical Coordinators, Presidents, Chief Engagement officers, program managers, and outreach coordinators. The services provided by community-based organizations included food security, health, housing, employment, and work readiness, refugee and immigrant services, and community support; many CBOs addressed multiple social needs. CBO interviewees represented organizations operating in both urban and rural areas of the state.

Data collection

In-depth one-on-one interviews with 46 stakeholders from identified CBOs ( n  = 20) and MCOs ( n  = 26) were conducted between May 24, 2021, and November 8, 2021. Interviews were conducted via Zoom, audio-recorded, and transcribed verbatim. The qualitative researcher and facilitator conducting these interviews have extensive training and experience with structural interviewing using a semi-structured interview guide. The guide used was developed for this study [ 23 ].

Data analysis

We conducted an iterative content analysis of the transcribed interview data using qualitative descriptive analysis [ 24 ], an inductive, low-inference method designed to gain an accurate understanding of a phenomenon in the everyday terms of stakeholders. Our data analysis unfolded in two stages. The first stage involved open coding [ 25 ], in which the transcripts were independently coded by two authors and one study team member (AM, ER, and HS), who then met to discuss and reach consensus on the central themes in the data related to technology and data sharing. In this meeting, the authors identified the themes of to screen for patient needs, to case manage, to evaluate the effectiveness of programs, and to partner with each other. The second stage of analysis involved focused coding, with the three individuals again independently coding transcripts for subthemes within each identified central theme. The coders met again to compare findings and finalize themes (and subthemes for Theme 4). At this time, we recognized that there were areas of alignment, incongruence, and tension between the responses of participants from MCOs and CBOs, and we reached agreement in this meeting about which themes demonstrated each dynamic. Finally, all authors met a third time to review the subthemes and select illustrative quotations for each. All analytic decisions were made through discussion until consensus was reached. We used the team-based approach to reaching consensus, which considered dependability and trustworthiness of the data [ 26 ]. This paper focuses on responses addressing technology platforms and data sharing to support MCO and CBO partnerships.

We identified several themes related to the use of technology and data in MCO-CBO partnerships to address enrollee social needs. MCOs and CBOs noted differing levels of need for data, differing incentives for collecting and sharing data, and differing valuations of what data can or should do. MCO and CBO interviewees described how they collect and use data in their work, which fell into four major themes: to screen for patient needs, to case manage, to evaluate the effectiveness of programs, and to partner with each other. Within these themes, the interview responses illuminated areas of alignment between MCOs/CBOs, incongruence, and tension (both practical and ideological; see Table  1 ).

Theme 1. Alignment on collecting data to identify and prioritize patient needs

Using data to identify and prioritize patient needs was largely an area of alignment for MCOs and CBOs. All MCOs and nearly all CBOs recognized the value of data in this area. As one CBO noted,

“By completing the needs assessment with our families, it helps the case managers understand your immediate needs.”

Similarly, MCOs often used the data for targeted programming and social needs referrals,

“ When our members are enrolled, we attempt to engage them in our health risk assessment. And so that health risk assessment is going to not only ask them questions about their specific health, but also about some additional needs that would help us be able to identify them at enrollment and also to be able to target them for programs and other [benefits].”

Several MCO and CBO interviewees also discussed using the data to understand individual enrollee/client needs and to track overall trends among their clients. As one MCO shared,

“The end of 2021, we had a tremendous amount of referrals for food. And so maybe we need to look at doing some of our community investment work and partnering with additional providers and community partners that are in that space for next year.”

There were some differences between MCOs and CBOs in the formality and degree to which social need data was collected. MCO interviewees, particularly those on the front lines of this work, could describe detailed and comprehensive data screening metrics for patient needs and how needs were tracked in their data systems. Using data on patient needs to identify areas for intervention was described as an essential part of patient care:

“We use the screening data, not just to meet the individual member need, but to also inform health equity and types of programs that we bring to play...”

CBO interviewees, on the other hand, had greater variability in their responses about the importance of using data on social needs at an organizational-level. Most described data as having potential value but stopped short of calling it essential for their operations. One CBO stated,

“I don't know what I would do with the information if we had it.”

Conversely, one food-oriented CBO reported that they collect demographic data and use that to help with distribution,

“So think about the local pantry that I talked about earlier. Because we know, we drive a truck into [KY County]. We know that the last five times that we've been in [KY County], we saw, on average, 150 households at each of those five visits. That tells us how much product to put on the truck so that we don't run out.”

Theme 2. Differences in organizational capacity, mission, and resources influenced variability in data use to support case management

Using data to support case management activities was an area of both alignment and incongruence between MCOs and CBOs. All MCOs and many CBOs saw value in using data systems to identify resources available, track referrals and follow-ups, keep notes, and stay in contact with patients. However, there was considerable variability in the sophistication of the data systems. Most MCOs reported elaborate data tracking systems designed specifically for screening, referral, and tracking (e.g., combining medical records applications with Unite Us [ 27 ] or Find Help (formerly Aunt Bertha [ 28 ]). Some CBOs have systems designed specifically for tracking data (e.g., Electronic Health Systems or Vesta [ 29 ]), whereas others employ systems not designed specifically for tracking (e.g., Microsoft Excel spreadsheets). Most CBOs used informal data collection to screen for needs (e.g., Post-it notes, memory, a hand-written planner), and several CBOs reported that they did not use formal data systems to screen and track patient needs at all,

“Are you kidding me? No books. What I usually tell anybody who's working with me is to either email me or text me, and that's my filing system.”

MCO interviewees were more likely to report using data analytics to support and enhance case management. Frontline MCO workers spoke about this aspect of data use more often than executives, and many saw data systems as the answer to case management problems. As one MCO stated,

“We do have a case management system that keeps track. So, we are able to schedule calls. They're able to pop back up on a calling queue, so that we're able to check in with members and attempt to continuously reach out to them. So, that's kind of how we try to make sure that those members don't fall through the cracks by continuously following up.”

Most CBOs indicated that case management occurred but was more personalized and less attached to data and technology use,

“We have a database that we use for client notes. We just record case notes in there. Some of our caseworkers keep basic Excel spreadsheets on their specific clients and what they're working on. Most of that would be informal.”

Only one MCO specifically mentioned the limits of data systems for tracking and the need for a personal touch in case management, a perspective more in line with most CBO interviewees. The MCO shared this when discussing platform capabilities, stating,

“We have a case management platform, of course, where we document everything, because just like everywhere else, if you don't write it down, it didn't happen, but a lot of it is just that manual follow-up and that human touch.”

The variability in tracking system sophistication and capabilities between MCOs and CBOs was also frequently highlighted as one of the critical challenges in collaboration and a notable source of frustration for both sides. When discussing their partnerships with MCOs and data sharing, one CBO stated,

“They really wanted to know about it. And so had to spend considerable time with them about, ‘This is what we do, this is how stuff works.’ And including it's like, ‘No, we can't track. We have no way of tracking [MCO] clientele through the [KY food security] program’."

While MCO interviewees often noted this tension in collaboration, they were aware that capacity and resources typically made it harder for CBOs to track and collect data. One MCO interviewee noted,

“I think the challenge is just the data piece and the complexity of the regulations that we have to navigate, all for good reason. When you're talking about how to best leverage those community resources, if we can't kind of have those data exchanges, it makes it so much more difficult. And so when you're trying to get at outcomes or have simplified referral processes, it just makes it harder because you may not be able to get through, they may not have the HIPAA, the high-tech clearance or whatever it is. It's expensive for them to have to do that.”

Theme 3. Funding and reimbursement structures shaped how MCOs and CBOs used data to evaluate program effectiveness

We found limited alignment between MCO and CBO perspectives on using data to evaluate social need programming and partnerships. Instead, evaluation was an area fraught with incongruencies and tension between the two sectors. The financial incentives and pressures for using data differ substantially between MCOs and CBOs. MCOs reported using data to evaluate the financial impact or effectiveness of programs (particularly claims data/utilization metrics) and partnerships to justify investments or show MCO executives that meeting unmet social needs is good business. As one MCO interviewee explained,

“I think every anything that we’re doing with the community-based partner, we’re studying all that. We’re studying the reduction, so I’m able to say, okay, because we have this member in this [CBO program], in this residential treatment program, not only mama’s healthier, baby is not born exposed to opiates, no NICU, ER utilization down. I think that’s the neat thing, there’s your answer, right?”

One reason MCOs seem to be driving data collection for demonstrated effectiveness/return on investment is that they are heavily regulated in terms of how they can invest funds,

“We are doing payment innovation, we want to take money out of what’s being spent on health care and invest it into social services and that is not easy.”

As another MCO highlighted continued investment often depends on what they can demonstrate,

“Sometimes, there are finance guidelines, right? Like when I’m fighting for my budget, they’ll say, ‘Well, where’s the return on investment numbers?’.”

Conversely, only a few CBOs used data-driven evaluation to support their financial operations. When CBOs did report using data for evaluation, it was typically in relation to using outcomes data in grant writing to gain funding specifically from MCOs, data which may not serve any other useful purpose for the CBO. As one CBO stated,

“Another kind of pain point, and for like one of the managed care companies that we contract with, they give us $8,000 a year. But the requirements to receive that $8,000 is very data heavy. We have to go through and pull all this data, get different releases signed with the participants. It’s great to have extra money, but it’s also a lot of work and nothing really being tied to it, if that makes sense. They just want the data to be able to review and any good outcomes and success stories and stuff like that, which is great. But it’s a lot of work for not a lot of money.”

Theme 4. Tension in using data to partner with other MCOs and CBOs

Both MCO and CBO interviewees described several reasons why they engage in data sharing within MCO-CBO partnerships (e.g., to garner funding, demonstrate effectiveness, or enhance case management), even if the values and importance placed on data sharing differed between agency types. When data sharing existed or was being contemplated, interviewees still described several barriers to sharing, both practical and ideological.

Overwhelmingly, CBO interviewees expressed a perception that they had to report data to the MCOs to prove impact so MCOs would maintain the partnership or provide funding. The first subtheme revealed a notable ideological difference between the MCOs/CBOs regarding whether data was useful to evaluate program effectiveness . While data-driven evaluation is routine and relied upon by most MCOs, many CBO interviewees perceived that data and metrics could harm their operations, diverting time and energy from serving clients and that there is much about program effectiveness that simply cannot be captured using formal data tracking systems. When discussing the course of their partnerships with MCOs, one CBO highlighted,

“So what does that support look like? Well, it is financial support for it. And, initially, it was very much focused on their clientele with [MCO] clientele and trying to track metrics about the impact that having access to better nutrition was going to have on the outcomes for their folks, right? So over the course of two years, I mean, we were able to show, "we," and I mean that collectively, we're able to show that it does have a positive impact. I mean, for [MCO], I think it's safe to say that they realize that it is more cost-effective to invest upfront in increasing access to healthy food better than the back end, to drugs and health care costs and all that kind of stuff. So they have, again, they have maintained that partnership.”

Indeed, most MCOs expressed wanting data from their CBO partners to justify the relationship and a reluctance to build relationships if data capacity is not present. One MCO discussed this directly, stating,

“They come us and they send us their flyer and they're like, "We want [MCO] to partner with us on our heart walk and we want you to give us $20,000." We still get a lot of people that do that because that's their old business model. Most of the time, we don't engage with those types of organizations. I always say, we want to hear from someone and I will take a meeting always if a community-based organization says, "We have an evidence-based solution that is solving for X," or "We have a solution that is solving for X and we want to work with you to help us prove that it's evidence-based," or we have research capabilities...”

Subtheme 2 illustrates how underlying the data sharing tension between CBOs and MCOs are challenges related to the need for more effective and user-friendly interfacing between tracking and referral systems, as well as the limited capacity of CBOs to track and analyze data . As mentioned, the sophistication of CBO data systems is highly variable, and even those organizations with more advanced tracking systems struggle with data sharing. When asked about data sharing, one CBO noted,

“Well that's another pain point. In my history, in my experience, every health plan has their own data system that don't talk to one another, that are very convoluted and messy. Right now we're filling stuff in on an Excel spreadsheet.”

Several MCOs also highlighted this as a challenge. As one MCO stated,

“Our system is designed to deal with hospital systems and health care providers, there's many different levels. I mean we go through a pretty comprehensive system and you have to have all kinds of, meet all kinds of requirements, share data, and different pieces that for a small community-based organization providing housing services, they might not even have the capacity to meet those requirements.”

Although some CBOs reported sharing data with MCOs willingly and saw this sharing as a natural facet of their partnership, other CBOs described significant concerns about data privacy and ownership ( subtheme 3 ). They noted how important data privacy was to the clients they served and how their organization valued serving their clients without the need to collect personal data or share it. Some CBO interviewees indicated that sharing or even collecting private client data might compromise their ability to do their work and serve their clients well,

“We respect their privacy, and we will never do any sharing of their data. In fact, a lot of people who come to us, one of the reasons they're with us is because we do not require them to show an ID.”

Subtheme 4 revealed how CBO and MCO interviewees expressed concerns about relying on data and technology as the solution to social need screening and referral systems building . Interviewees felt that data does not adequately capture utilization or partnership benefits. Primarily, this was attributed to issues related to data quality. One MCO interviewee highlighted this when discussing the challenges of understanding the quality of social need services:

“We also don't have a really long track record of managing quality for this type of provider. We have very distinct report cards and quality cards for every hospital in the state of Kentucky. I can tell you what the outcomes for [Hospital 1] compared to [Hospital 2] and compared to [Hospital 3]. We have very clear metrics on those types of things. We do not have that for the sort of soft services, especially since we don't pay for them.”

Most CBOs articulated challenges with data quality centered on their perception that data does not tell the whole story about what is happening at their organization and in the community. As one CBO noted,

“ We have a people problem. And I think right now there are a lot of hospitals and other organizations, MCOs, that want to kind of tech their way out of this. [T]hey're looking for technological [solutions] to try to streamline and expand services to folks. And that's just not really the answer. You need people.”

MCO interviewees recognized that databases and their tracking systems may be limited in what they capture. In subtheme 5 , several noted their technological ability to comprehensively track organizations in a community as a significant limitation . Maintaining accurate data has also been challenging because of community organization turnover and closures. As one MCO highlighted,

“These national repositories don't have the local knowledge so they don't know the churches that do the hot meals and they don't know the small organizations that are getting up and off their feet and tied to this one or that one, or it's an offshoot of whatever. There are some smaller organizations that don't always get into those big directories and you don't always know about them unless you have boots on the ground, people who live and work in the community and actually know what those are.”

Similarly, another MCO highlighted CBO data capacity as a major challenge in their partnerships, stating,

“Biggest challenges. I guess, you could say data might be the challenges, to close the loop around the return on investment on some of these organizations that are not ... They just don't have the staffing, or the professional leadership, if you will, to do all the tracking. The ones that do, do it very well. The ones that don't, it's just that they don't have the resources.”

In the final subtheme, all MCO interviewees acknowledged that CBOs are doing good work , even if that cannot be quantified, and the ability to share that data is often related to CBO capacity and resources. One MCO shared,

“[Food Pantry CBO] who's just like [Named Female] and her husband [Named Male], they might be the greatest people and we might know that members like going there versus the other food bank because [Named Female] like bakes brownies and gives them a hug and we want to quantify that but also it's just not realistic because they don't have the infrastructure sometimes that's needed to prove the business case, solidify the partnership and ultimately inform policy.”

Our study found alignment as well as discordance between MCOs and CBOs about how and when to leverage technology and data despite their shared mission to meet the unmet social needs of enrollees. Our findings offer important insights regarding why data and technology may create a barrier to effective MCO-CBO partnerships, potentially hindering efforts to improve health and social outcomes. They also provide guidance and identify key considerations for developing programs and partnerships that may be more effective in coordinating efforts between the two organizations.

As we observed in Themes 1 (Alignment on collecting data to identify and prioritize patient needs) and 2 (Differences in organizational capacity, mission, and resources influenced variability in data use to support case management), results suggest that data and technology can be important tools in screening and referral for social needs, but they are far from a universal panacea. Our data indicate that both logistical and cultural disconnects between MCOs and CBOs significantly limit data collection and sharing for coordination of services. On the logistical side, CBOs have extremely limited capacity (software, workforce) to collect and share data. Several participants reported serious concerns with collecting and sharing confidential client information. To make matters worse, MCOs use a range of proprietary and sophisticated referral and tracking systems that severely tax the resources and capacity of CBOs. On the cultural side, while MCOs view data and technology as essential to partnering with CBOs to meet enrollee social needs, CBOs do not. In fact, as we found in Theme 3 (Funding and reimbursement structures shaped how MCOs and CBOs used data to evaluate program effectiveness), many CBOs see data collection as a necessary evil to garner funding from potential donors. Instead, they emphasize the relationship-honoring aspects of their work as a core value.

Solutions that only focus on providing data collection and tracking technology to CBOs are unlikely to be completely successful because they fail to address the disparate cultures found in MCOs vs. CBOs. This conclusion is robustly supported by Theme 4 from our analysis (Tension in using data to partner with other MCOs and CBOs).In many ways, CBOs may view MCO efforts to grow their technological capacity as imposing profit-seeking values, norms, and structure rather than seeking true understanding and partnership. CBOs’ low enthusiasm for and capacity to use data can create difficulty for MCOs when MCOs rely on CBOs for data to justify their funding streams and partnerships. This fundamental disconnect is likely to severely impede partnership efforts without reevaluating the strengths and values each sector brings to the collaborative [ 30 ].

Successful partnerships are built on shared interest and trust [ 31 ]. Our study suggests a strong alignment between MCOs and CBOs in addressing the social needs of highly vulnerable Medicaid beneficiaries. This values alignment may offer a foundation for partnership. Our work underscores a key finding across studies on cross-sector partnerships integrating health and social services, more work must be done to build trust and understand each other’s organizational values [ 17 , 19 , 32 ]. MCOs and CBOs need each other to address social determinants of health (SDOH) effectively. MCOs have the resources and responsibility for finding more effective ways to support their beneficiaries. CBOs are ‘on the ground’ and have the trust of the clients they serve (many of whom are Medicaid enrollees). Forums that create a level playing field for both types of organizations and facilitate safe conversations to build trust are essential.

The Department of Health and Human Services (DHHS) has developed a three-pronged strategy for addressing SDOH: (1) better data, (2) improving health and social services connections, and (3) whole-of-government collaborations [ 8 ]. Our study suggests that their second strategy is essential and could be far more difficult than many imagine. Facilitating honest conversations about identifying and addressing the challenges in building these connections is a critical first step. Because many challenges involve “hearts and minds” and organizational culture, addressing these challenges will need to be a slow and iterative process. Moving forward, organizations like MCOs and other clinical partners must carefully consider how data and social need screening and referral technology can be a value-add to CBOs and not another burden on their already strained capacity.

Limitations

While our sample included at least one representative from all six state MCOs and nineteen different CBOs, the generalizability of study results may not apply to other states. However, many of the MCOs in KY operate in national markets and often use similar strategies in different geographic areas. Insights likely shed light on similar efforts and challenges in other states and markets. Future studies examining the use of data and technology nationally in social need resolutions would provide confirmation of the results we present and any potential geographic variability. Additionally, participant perspectives may not necessarily represent their MCOs or CBOs. Finally, our cross-sectional view of technology and referral platforms provides a snapshot of current processes; a more in-depth longitudinal study would capture changes over time as technology constantly evolves.

Despite a shared mission to meet unmet social needs, MCOs and CBOs do not agree on how and when to leverage technology and data. This discordance is a significant barrier to effective partnerships. Technology offers powerful tools for identifying and prioritizing enrollee needs and connecting them with services. However, trust and a shared understanding of organizational cultures and goals are critically needed to allow technology to realize its potential. Current efforts to build effective MCO-CBO partnerships should focus on creating a level playing field for all organizations and a space for honest conversations that can build strong connections and sustainable relationships across sectors.

Availability of data and materials

Deidentified aggregated data is available from the corresponding author ([email protected]) on reasonable request.

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Acknowledgements

The authors would like to thank the Study Advisory Board for their help in guiding the research.

This research was supported by a Robert Wood Johnson Foundation grant as part of the Research in Transforming Health and Health Systems Program (Grant ID 77256). Research reported in this publication was also supported by the Kentucky Cabinet for Health and Family Services, Department for Medicaid Services under Agreement C2517 titled “Medicaid Managed Care Organizational Strategies to Address Enrollee Unmet Social Needs.” The content is solely the responsibility of the authors and does not necessarily represent the official views of the Cabinet for Health and Family Services, Department for Medicaid Services.

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Concept and design (RH-G, AMS, TMW); acquisition of data (RH-G, AMS, ERC, TMW); analysis and interpretation of data (RH-G, AMS, ER, TMW); drafting of the manuscript (RH-G, AMS, ER, ERC, TMW); critical revision of the manuscript for important intellectual content (RH-G, AMS, ER, TMW); provision of patients or study materials (RH-G, ERC); obtaining funding (RH-G, TMW); administrative, technical, or logistic support (RH-G, ERC, TMW); and supervision (RH-G).

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Hogg-Graham, R., Scott, A.M., Clear, E.R. et al. Technology, data, people, and partnerships in addressing unmet social needs within Medicaid Managed Care. BMC Health Serv Res 24 , 368 (2024). https://doi.org/10.1186/s12913-024-10705-w

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Women’s autonomy and maternal health decision making in Kenya: implications for service delivery reform - a qualitative study

  • Easter Olwanda 1 ,
  • Kennedy Opondo 2 ,
  • Dorothy Oluoch 1 ,
  • Kevin Croke 2 ,
  • Justinah Maluni 1 ,
  • Joyline Jepkosgei 1 &
  • Jacinta Nzinga 1  

BMC Women's Health volume  24 , Article number:  181 ( 2024 ) Cite this article

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Maternal and neonatal outcomes in, Kakamega County is characterized by a maternal mortality rate of 316 per 100,000 live births and a neonatal mortality rate of 19 per 1,000 live births. In 2018, approximately 70,000 births occurred in the county, with 35% at home, 28% in primary care facilities, and 37% in hospitals. A maternal and child health service delivery redesign (SDR) that aims to reorganize maternal and newborn health services is being implemented in Kakamega County in Kenya to improve the progress of these indicators. Research has shown that women’s ability to make decisions (voice, agency, and autonomy) is critical for gender equality, empowerment and an important determinant of access and utilization. As part of the Kakamega SDR process evaluation, this study sought to understand women’s processes of decision-making in seeking maternal health care and how these affect women’s ability to access and use antenatal, delivery, and post-natal services.

We adapted the International Centre for Research on Women (ICRW) conceptual framework for reproductive empowerment to focus on the interrelated concepts of “female autonomy”, and “women’s agency” with the latter incorporating ‘voice’, ‘choice’ and ‘power’. Our adaptation did not consider the influence of sexual relationships and leadership on SRH decision-making. We conducted key informant interviews, in-depth interviews, small group interviews and focus group discussions with pregnant women attending Antenatal clinics, women who had delivered, women attending post-natal clinics, and men in Kakamega County. A thematic analysis approach was used to analyze the data in NVivo 12.

The results revealed notable findings across three dimensions of agency. Women with previous birthing experiences, high self-esteem, and support from their social networks exhibited greater agency. Additionally, positive previous birthing experiences were associated with increased confidence in making reproductive health choices. Women who had control over financial resources and experienced respectful communication with their partners exhibited higher levels of agency within their households. Distance relational agency demonstrated the impact of health system factors and socio-cultural norms on women’s agency and autonomy. Finally, women who faced barriers such as long waiting times or limited staff availability experienced reduced agency in seeking healthcare.

Conclusions

Individual agency, immediate relational agency, and distance relational agency all play crucial roles in shaping women’s decision-making power and control over their utilization of maternal health services. This study offers valuable insights that can guide the ongoing implementation of an innovative service delivery redesign model, emphasizing the critical need for developing context-specific strategies to promote women’s voices for sustained use.

Peer Review reports

Globally, the provision of health care is evolving towards providing care that is respectful of and responsive to individual patient preferences, needs, and values, and ensuring that patient values guide all clinical decisions [ 1 ]. Patient-centered care, in relation to clinical decision-making, is grounded in concepts of intrinsic values, personal preferences, and partnership [ 2 ]. A patient-centered approach, empowers women by involving them in decision-making processes and respecting their choices [ 3 ]. Women’s empowerment, in turn, enhances their autonomy and ability to seek appropriate and timely maternal health care [ 4 ], ultimately affording women agency for their overall well-being. When women are not empowered or lack autonomy, they may face barriers to accessing quality care, resulting in adverse maternal health outcomes [ 5 ].

Research on patient-centered care for women shows that women’s autonomy (i.e., the freedom of women to exercise their judgment in order to act for their own interests) influences reproductive, maternal, and child health outcomes [ 6 , 7 , 8 , 9 , 10 , 11 ]. Conversely, the absence of women’s autonomy in decision-making results in delays and poor utilization of maternal health services and ultimately increased maternal morbidity and mortality [ 12 ]. Thus, empowered women can make informed decisions about their reproductive health, including family planning, timing and spacing of pregnancies, and the type of care they receive during pregnancy and childbirth [ 13 , 14 , 15 , 16 ].

Freedom of mobility, participation in household decision-making, and self-efficacy are key dimensions of women’s empowerment [ 17 , 18 ]. Empowering women to make their own decisions, pursue goals, and control their lives and resources is a crucial aspect of Sustainable Development Goal (SDG) 5, which seeks to attain gender equality and empower all women and girls [ 19 ]. Moreover, empowering women in reproductive and sexual matters is crucial, as intimate relationships often involve significant power imbalances that can limit women’s ability to negotiate with their partners on sexual issues [ 20 ].

The International Centre for Research on Women (ICRW) has developed a conceptual framework for reproductive empowerment merging “female autonomy” and “women’s agency”, which includes ‘voice’, ‘choice’, and ‘power’. This framework is relevant to women’s autonomy in Kakamega as it provides a comprehensive approach to understanding the factors influencing women’s agency and empowerment, informing targeted interventions and policies in the region. Women’s individual agency involves expressing opinions, making decisions about their lives, and pursuing their aspirations, which empowers them to assert their voices and seek personal and professional growth. Immediate relational agency focuses on the influence of close relationships such as family, friends, and intimate partners on an individual’s agency [ 21 ]. These relationships can either support or restrict a woman’s ability to exercise her voice, make choices, and pursue empowerment. Supportive relationships enable women to exercise their agency freely, while oppressive ones may limit their ability to make decisions and assert their voice, hindering empowerment. Distant relational agency refers to the broader social, cultural, and institutional influences that shape women’s agency and empowerment [ 22 ]. Societies that prioritize gender equality, offer legal protections, ensure access to education and healthcare, and promote women’s participation in decision-making enhance women’s agency. Conversely, gender inequalities and limited opportunities hinder women’s agency and empowerment.

The relationship between individual, immediate, and distant relational agency is complex and interconnected, with individual agency influenced by both immediate and distant relational agency. Supportive immediate relationships and equitable social structures can enhance individual agency, enabling women to exercise their voice and make choices while repressive immediate relationships and restrictive social structures can limit women’s agency [ 23 ]. Aligning all three levels of agency positively leads to women’s voice, choice, power, and empowerment. These concepts are illustrated in Fig.  1 below.

figure 1

Borrowed from the Conceptual Framework of Reproductive Empowerment by the International Center for Research on Women (ICRW)

Evidence suggests that increasing women’s mobility can empower them to exercise greater control over their lives by increasing their access to healthcare, education, markets and information [ 6 , 24 ]. Additionally, women with strong sense of self-efficacy have the potential to anticipate different success scenarios, persevere in the face of obstacles, take action against the existing social norms [ 25 ], and navigate complicated healthcare contexts to receive care [ 26 ]. Relative to maternal and child health, increased postpartum maternal self-efficacy been has associated with improved functional status in the postpartum period [ 27 ]. Furthermore, women’s control over resources and decision-making within a household plays a crucial role in enhancing healthcare-seeking behaviors and maternal and child health outcomes [ 28 ]. Changes in women’s intra-household bargaining power, also increases a woman’s status and impacts her decision-making ability [ 29 , 30 ]. All these are key considerations in determining the implementation process and success of maternal and child health interventions and reforms. Existing literature primarily emphasizes the impact of women’s choice and agency on health decision-making and service use, but there is limited documentation on how women’s autonomy experiences can inform the implementation of improved maternal and child health interventions.

The implementation context

Kakamega County was selected due to its high maternal mortality rate of 316 per 100,000 live births and neonatal mortality rate of 19 per 1,000 live births, alongside approximately 70,000 births in 2018, distributed with 35% at home, 28% in primary care facilities, and 37% in hospitals. Part of recommendations from the Lancet Global Health Commission on High Quality Health Systems for improving quality of care is the implementation of “Service Delivery Redesign for Maternal and Newborn Health”, (SDR) reform. Kakamega County started the phased implemention of SDR in 2021 and is currently in its improvement phase.

During the SDR implementation period, improvements were made to health facilities, including the commissioning of a new Maternity wing and an increase in bed capacity at Malava. The Linda Mama health scheme provides affordable maternal and child health services, and Malava sub-county hospital increased its claims from 34 to 79%. Additionally, a newborn unit was constructed, and the facility currently has a resident pediatrician, surgeon and gynecologist supported by nurses, clinicians, and medical officers.

Similarly, Lumakanda sub-county hospital has reorganized its infrastructure at the maternity wing and the newborn unit, introduced emergency evacuation services, implemented pseudo-facility improvement fund (FIF) disbursements, enhanced accountability and visibility of blood resources through a blood tracker dashboard, enrolled women for pregnancy care text prompts, and provided Emergency obstetric and newborn care (EmONC) training to its staff while also training health workers from primary health care facilities. A summary of the SDR related implementation activities can be found in the Supplementary file 1 .

This paper aimed at examining how women’s processes of decision-making in seeking maternal and neonatal health care both influences and is influenced by the implementation of SDR in Kakamega county. It is anticipated that the learning from this paper will inform the implementation of SDR by highlighting patient voice in reforming delivery of MCH services.

Study setting

The study took place in Malava and Lumakanda sub-County hospitals which are maternity centers of excellence where the Kakamega Service Delivery Redesign (SDR) is being implemented. The Kakamega maternal and child health Service Delivery Redesign (SDR) is a structural reform that aims to reorganize the maternal and newborn health services by shifting deliveries for all women to advanced facilities that offer definitive care for complications. The reform is now being implemented by the Kakamega County government with the aim of improving the quality of antenatal, delivery and postnatal care. It purposes to ensure that all women can give birth in safe environments, with skilled providers that have the tools and competencies to care for women during uncomplicated birth and who can detect and deal with complications if and when they occur [ 31 ].

Study design

This was a cross-sectional exploratory study using qualitative research methods with purposively selected participants. We conducted key informant interviews, in-depth interviews, small group interviews and focus group discussions with pregnant women attending Antenatal clinics, women who had delivered, women attending post-natal clinics, and men in Kakamega County. In this context, small group interviews involved a small group of individuals, allowing for in-depth exploration of individual perspectives within a group setting, while focus group discussions were conversations guided by a moderator, emphasizing interactions among 8–10 participants to explore shared perspectives and group dynamics.

The FGDs had an average of 8 individuals while the small group discussions had an average of 4 individuals. For the FGDs demographic dynamics such as gender and age were managed through the selection of participants to ensure diverse representation within the groups. We formed homogeneous groups based on specific demographic criteria, to foster open and comfortable discussions among participants with shared characteristics. In this case we had FGDs specifically for younger women, another for older women, and lastly with the men separately. Conversely, for small groups, we intentionally chose participants representing various demographic profiles to capture a range of perspectives and experiences. The FGDs lasted between 45 and 60 min, the IDIs lasted between 30- 45 min and the KII lasted an average of 45 min.

See the Table  1 below.

The pre-set inclusion criteria included willingness to consent and to participate in the study, and good knowledge or understanding of the areas of inquiry. We employed purposeful participant selection to include diverse demographic characteristics, experiences, and perspectives in relation to the research topic.

Data collection

Data collection took place in November 2022 and in March 2023. Participants were recruited from the antenatal, delivery and post-natal clinics in Lumakanda and Malava sub-County hospitals. We conducted key informant interviews, in-depth interviews, small group interviews and focus group discussions with pregnant women attending Antenatal clinics, women who had delivered, women attending post-natal clinics, and men using guides with questions developed in English and then translated into Swahili.

The interviews covered three broad topics of interest (1) factors that affect women’s autonomy and decision-making power in the household, (2) the process of decision-making at the family level in seeking maternal health care during pregnancy, delivery, and the postpartum period, and (3) how the decision-making process affects women’s ability to access and use maternal health services. Interviews were audio-recorded for participants who consented. During the interviews, detailed descriptive field notes were written covering interactions between the interviewer and respondent, non-verbal communication, environment, and reflections from interview content. All interviews were transcribed verbatim in Swahili and translated to English then cross-checked to ensure appropriate data and its quality before data analysis. Interviews were conducted to the point of theoretical saturation through iterative data analysis of emerging themes which was done alongside data collection. Iterating between data collection and analysis enabled the research team to be mindful of their own biases and actively worked to mitigate them, thus contributing to the robust representation of opinions. A total of 27 interviews including the IDIs, KIIs and FGDs lasting 30-60 min were conducted sequentially.

Data analysis

A thematic analysis approach was adopted. The English transcripts were read several times to develop familiarity with the raw data. Open coding was done to identify women’s expressions highlighting their autonomy; axial coding then followed to relate and label codes with shared concepts, dimension, and properties. Finally selective coding was done to delimit coding to the identified core concepts from the data [ 32 ]. See Table  2 below. E.O independently coded the data in the first phase of analysis. This was then followed by discussions between E.O and J.N, comparing emerging codes and developing a consensus on a final coding framework that was used to code and analyze the data in NVIVO 12.

This section presents the findings from an in-depth exploration of women’s agency and autonomy. Several key themes and sub-themes emerged, providing valuable insights into the complex dynamics surrounding women’s agency and autonomy. These findings contribute to a deeper understanding of the challenges and opportunities women face in asserting their rights, making choices, and navigating their social and cultural environments. The results further reveal the multifaceted nature of women’s agency and autonomy, encompassing individual, immediate relational, and distance relational factors and shed light on the interplay between these factors and uptake and utilization of maternal and child health services.

Individual agency

Independent women with strong self-trust were more likely to exercise their agency with greater adaptability and confidence in decision-making. Such strong inherent trust mediated power within which consequently shaped women’s individual agency and their ability to make decisions regarding maternal care.

“In my life, I’ve always been very independent and doing things on my own. I’ve never really encountered those challenges where I was told that someone else had to speak for me. Most of the time, I just do my own thing.”-ANC2

Conversely, the perception of shame, and insignificance among young pregnant girls diminished their agency in seeking services.

“For some, some are just afraid, especially those of young age. They are scared of coming to the clinic, so they try to hide the pregnancy because it brings them shame.” FGD men

The power within was also influenced by other factors including social support and past experiences. Supportive social networks provided women with the necessary resources, information, and support to develop their power within and exercise agency. Our findings indicate that social networks played a crucial role in shaping women’s individual agency in maternal healthcare decisions as they provided women with information, knowledge, and resources that enhanced their agency. Women sought input from their social networks including, family members, friends, community health volunteers (CHVs), and birth companions. Some elements such as finances, relational trust, and experiences of people were considered before a social network was chosen to aid with the decision-making.

“At times, the husband will help in decision making because it could be a place that is far and needs transport, he will be the one to decide whether I will go to Malava or not. The decision comes from him.”-PNC 1

The contacts drawn from social networks also shared their previous birthing experience with women fostering a sense of agency. Negative birth experiences raised awareness of potential challenges and helped women make more informed decisions while choosing the best options for the next birthing experience. In such instances, while the objective was to look for quality, the previous experiences of others as well as social relationships with health workers constituted the yardstick in making the final choice as the experiences of some participants revealed:

“That time I heard negative views about this place, and I didn’t feel the need to come. I heard that in Lumakanda they are very harsh and I told myself that “let me get used to Turbo”, I never set foot here. But in 2014, I said no, let me try the local facility.”-PNC 3
“Number one, etiquette of these nurses towards these pregnant women. You know you can go somewhere else, and the nurse just shouts at you. It’s like she carries all her stress to the hospital. But here in Lumakanda, I have not faced anything. So, that’s why I decided to come all the way.”-ANC 2

Additionally, health literacy had a great influence on women’s individual agency through the knowledge, attitudes, and beliefs acquired through health education and media exposure. Collectively, we saw how health education, media exposure, and health-seeking behavior significantly impacted women’s individual agency and decision-making for maternal care. With improved knowledge, women were more empowered to actively participate in decision-making processes, assert their preferences, and access appropriate healthcare services. Of note, is how health and financial literacy empowered women by increasing their understanding and enabling them to actively participate in decision-making processes.

“Maybe the media can broadcast that, mothers with children, and pregnant women, need to go to the hospital to get health services. They need to understand that they will benefit from going there. They need to hear it for themselves.”-PNC 3

Additionally, m edia exposure had a substantial impact on shaping women’s perceptions and attitudes toward maternal care. Our findings show that access to accurate and reliable information through various media channels can contribute to informed decision-making and empower women to seek appropriate maternal care. The respondents identified and recognized the value of health literacy in gaining autonomy and control over their health and well-being as corroborated in the quote below.

“Through media, newspapers, radios, councils, through these open places, many mothers have now discovered their rights and they have power now”-CHV.

Immediate relational agency

We found that women’s immediate relationships were also linked to household decision-making and freedom of movement. Our findings demonstrated that when women had their own source of income, it often led to increased empowerment and decision-making power within the household. Conversely, women who did not participate in income generation could hardly participate in decision-making in the house as recounted by this respondent.

“The only thing affecting my ability to make decisions, it’s because I’m not working. I do see those who are working, have the ability to decide, they can do their own things, as they wish. Even if there are obstacles from the husband, she can decide, let me do this. But for someone like me, it’s difficult.”-PNC 3

Health-related decisions, including seeking medical treatment, had financial implications. The costs associated with treatment impacted decision-making, particularly if they were substantial or necessitated long-term financial obligations. In such cases, decisions were made, considering the financial impact and available resources.

“Our clients depend on their husbands and their mothers-in-law as decision-makers. Since they depend on them especially the husbands to give them transport to go to the facility, they (husbands) are the key decision makers on where they seek their service.”-NO-IC

Spousal communication allowed for open dialogue, negotiation, and compromise, leading to decisions that consider the needs and preferences of both partners. Couples who trusted each other navigated power over each other by considering each other and providing a morale boost that facilitated decision-making in the household.

“It’s my husband whom I confide in the most. I feel comfortable talking to him, especially during my pregnancy, when I had a lot of complications like high blood pressure, and even had to undergo an operation. He’s my husband, so I talk to him, and he’s the one who helps me.”-PNC 3

Freedom of movement also influenced women’s immediate rational agency. Household structures were mostly patriarchal, where men held dominant roles and women’s mobility and decision-making power was limited. The traditional role of men as heads of households mandated a restricted life for women as they were expected to be submissive and show respect towards male partners.

“You find in some cultures a woman cannot say anything in front of the husband. The man is the one who speaks. In some areas, you are told “When you get here you follow what the husband, the mother or the father says”. -ANC 1

In contrast, single/separated women had complete freedom of movement and were able to decide alone. This was evidenced by one of the respondents, who shared that.

“When it comes to decision-making, I don’t think anyone can influence me because I make decisions myself. Even if someone discourages me, I know what I’m doing and what I’m looking for.”-ANC 2

Engaging in domestic tasks restricted women’s mobility outside the home. The demands of household chores meant that women could not move freely. Their social functioning was largely restricted to the household, the fields, and tending to children.

“Well, there are hindrances, at times I am alone at home without a house help, and I need to go somewhere. There are cows to take care of and children who may have gone to school waiting for me to make lunch. You see, there are hindrances, and you cannot just leave like that until you plan yourself.”-PNC 3

Mistrust within the household also undermined women’s freedom of movement and decision-making. These restrictions were reinforced by societal expectations and gender norms that prescribe women’s roles as primarily confined to the private sphere. Women’s ability to move about was sometimes constrained due to trust issues between spouses.

“You know, sometimes I come here in the morning and leave at two or three. He thinks it’s not just the hospital, he doesn’t understand, but I only come to the hospital. That’s one of the things he considers that and regulates my time out.”-PNC 3

Distance relational agency

Finally, social-cultural, and health systems factors presented various influences and circumstances that affected women’s ability to exercise agency and make choices in their lives. In this context, religious norms limited women’s access to evidence-based maternal care. Some respondents acknowledged that some religions challenged the idea of seeking healthcare in health facilities.

“In terms of decision-making, the church does not hinder anyone, but our church believes in not taking medication. We believe that if I am sick and you come to pray for me, I will be healed. However, it also says that if you know that your faith is not strong enough, you can go and seek medical treatment. But after you have received treatment, don’t come back to the church until you have finished whatever you need to do. Then, you can call on the elders to come and pray for you before returning to the church.”-CHV

Patriarchal structures including male dominance also limited women’s ability to exercise agency and make decisions independently. Most respondents emphasized men’s cultural role in decision-making regarding seeking MCH care. They acknowledged that increasing the engagement of men would yield considerable health benefits and provide an important avenue for giving men information which would also foster trust between spouses.

“Well, I would really wish to bring him along so he can see for himself how busy it is, from here to there. If he doesn’t see it for himself, he won’t understand.”-PNC 3

However, there were instances where male involvement was recognized as enabler for agency, as evidenced by men accompanying their spouses for clinics.

“You see, for instance, today my husband accompanied me, and he needed to go to work, so he brought me and went to work, and he finished what he was doing, and now he is calling me because we have been waiting here for a long time.”-PNC 1

Additionally, gender norms affected women’s ability to make decisions at the household level. Several women had partial control of their households’ finances but also kept financial secrets from their partners. This could be attributed to the feeling of being disempowered and the belief that financial secrets would give them a sense of autonomy. Interestingly, even after saving this money secretly, some women still needed their spouse’s approval to spend.

“They (women) also fear, even after saving they still can’t use the money without getting approval from the husband because they cannot do anything. It is mandatory, the husband has to know.”-MCH in charge

Women also stressed the need for securing the buy-in of the decision makers through community units, the nyumba kumi initiative, counselors, and healthcare providers.

“If we can find partners like you, we can go to the assistant chief’s council through the community health volunteers (CHVs). We can invite men to attend, and even if not all of them will come, we can create a network by telling a friend who tells another friend. This is like politics, but if we can use this network to spread the importance of maternal healthcare, it will be beneficial.”-CHV.

Health system factors such as facility workload, wait times, staff availability, and distance to health facilities also impacted women’s agency. The healthcare facilities were often overwhelmed with a high patient load, leading to longer waiting times, and delays in receiving care which can reduce women’s agency in seeking timely healthcare and may force them to delay or forgo necessary care. Women’s ability to make decisions about their own health was compromised when they had limited choices or faced barriers to accessing services. It also created a burden on women who had additional responsibilities, such as caregiving or work, as they struggled to find time to visit busy healthcare facilities.

“The health workers here are often overworked and have many patients to attend to. This leads to longer waiting times, which can sometimes make the patients frustrated.”-CHV
“Because of the staff shortage, we have only 2 staff in the ANC area. So, if one goes on leave, the one who is there serves both sides, the ANC and the other clients, the immunization side. So, the long queues and the long waiting time affect them, they don’t like it. I think that demotivates them even just to come to seek the services” -NO IC.

The distance between women’s residences and healthcare facilities also impacted their agency due to challenges related to transportation, time constraints, and financial resources required for travel.

“Most of them I’ve seen prefer the rural facilities, that is health centers or dispensaries instead of coming back to Lumakanda. I think the issue affecting them is transport.”-MS.
“At night, for a car, you’ll spend Ksh. 2,000 and if it’s a motorcycle, you’ll give him Ksh.800 shilling.”-FGD-BC

In some cases, where improved road networks existed, there were reports of women being able to access hospitals easily without difficulties.

“They come to Lumakanda because the road is tarmacked, so, if it’s a pregnant woman, she will not be spun in potholes.”-FGD Men

Our results indicate that individual agency, immediate relational agency, and distance relational agency influence women’s agency and autonomy. In terms of individual agency, factors such as self-stigma, trust in oneself, social networks, and previous birthing experiences emerged as important determinants of women’s decision-making power and control over their lives. Immediate relational agency, on the other hand, highlighted the significance of household decision-making dynamics, including aspects like control of household finances, respect between couples, and spousal communication. These factors played a crucial role in shaping women’s ability to exercise agency within their immediate relationships. Furthermore, distance relational agency demonstrated the impact of health system factors and socio-cultural norms on women’s agency and autonomy. Factors such as facility workload, staff availability, and religious norms were found to significantly influence women’s decision-making power and freedom of movement. Overall, these findings underscore the importance of recognizing and addressing various dimensions of agency and autonomy in order to empower women and promote gender equality.

Our work highlights a myriad of factors that influenced decision-making among women attending ANC, delivery, and PNC clinics during the early days of implementing a service delivery reform aimed at shifting all delivery to hospitals in a rural county in Kenya. Women’s autonomy and agency is still limited despite it being a crucial determinant of the use of maternal healthcare services. In our case, literacy was a pointer when analyzing women’s individual agency and decision-making capacity in engaging with MCH interventions and reforms. Our work revealed how, women with limited health literacy were unaware of their options in regarding participation in decision-making over their own reproductive health. Respondents reported the positive contribution of mass media in enhancing the household decision-making capacity. Similarly, Seidu et al. [ 33 ] demonstrated that women who watched television almost every day had a higher capacity to take household decisions, compared to those who did not watch television at [ 33 ] all. Mass media influences women empowerment, including their ability to take household decisions [ 34 ] by changing some socio-cultural norms such as gender stereotyping [ 35 ] suggesting that interventions to promote shared decision-making may be particularly important for patients with limited health literacy.

When women had individual agency, they reported having informed and better financial choices for themselves, and their families. Thus, individual agency elevated perceived self-efficacy in their decision making. Choices about individual women’s reproductive pathways and decision-making for care seeking therefore depended their perception of self; the self in relation to social environment and reflection on risks associated with the decision to seek care or not [ 36 ]. Social identity influences decision-making practices of individuals emphasizing the importance of deliberately embracing diversity and promoting inclusion future in the design of interventions and reforms with a focus on. This involves acknowledging and valuing different social identities, creating spaces that are safe and accessible for all individuals, and actively involving them in decision-making processes [ 37 ].

Women’s autonomy can also be better understood from a relational perspective since individual autonomy often fails to incorporate social reality. Relational autonomy posits that persons are socially embedded and that their identities are formed within the context of social relationships and shaped by a complex of intersecting social determinants and health system determinants [ 38 ]. We found that in both joint and nuclear families, women who have better spousal communication with their husbands have greater agency. The role of immediate relational agency is therefore mediated through the family context and the quality of relationships the women have which consequently influences their agency. Male heads of households were central in health decisions, and in some instances discussing health issues with their wives before final decisions were made [ 39 , 40 ]. While joint and constructive communication leads to psychological well-being and protect against stressors during pregnancy [ 41 ] the process for decision-making often becomes delayed, consequently mothers’ ability to receive professional health care and other obstetric interventions on time.

Freedom of movement is also an important determinant of immediate relational agency, as the household structure affects women’s freedom of movement, since women residing in joint households are less likely to have decision-making power and need permission more often from other household members to execute some routine household activities [ 42 ]. Women require the permission of a husband or another male to pursue activities outside the home due to trust issues, social norms, and religious norm. This subsequently limited women’s ability to access and use skilled maternal health services including attending antenatal clinics or giving birth at a health facility. However, women who worked outside the home were more mobile, and women who were independent in the social sphere were also confident in their ability to negotiate independent mobility [ 40 ]. Additionally, it has been shown that husbands’ out-migration promotes women’s freedom of movement [ 43 ].

In summary, there is need for deliberate efforts towards empowering women’s autonomy in reproductive matters. Men might also benefit in the empowerment process through enlightenment and through effective implementation of male engagement interventions that leverage men’s power within households and promote women’s autonomy in decision making. Notably, women who receive male engagement education report making joint decisions (such as contraceptive choices, purchases of daily needs, and whether or not to work out of the home) compared to those who do not received such education [ 44 ].

The strength of this study includes the comprehensive exploration of agency across multiple dimensions, providing insights into the influence of factors such as previous birthing experiences, self-esteem, social support, financial control, respectful communication, and health system barriers on women’s agency. Although the challenge of establishing causality between the identified factors and women’s agency pose a challenge, the findings offer compelling descriptive explorations of the often undermined voice of women in shaping maternal and child health interventions policies and practices.

The study findings underscore the limited autonomy of women in Kakamega County, emphasizing the importance of considering women’s decision-making in the successful implementation of the SDR. Moving forward, it is crucial for SDR implementation strategies to recognize and promote women’s autonomy, engaging decision-makers to understand the significance of women’s choices regarding delivery in higher-level facilities. This calls for a concerted effort to enhance women’s autonomy in reproductive healthcare through initiatives such as male involvement, women’s empowerment programs, access to resources, and institutional support. Additionally, MCH programs should prioritize health and financial literacy, freedom of movement, gender equality, and media access to counter cultural and religious barriers to women’s autonomy.

Availability of data and materials

The data that supports the findings of this study are available in the article and its supplementary material.

Abbreviations

Antenatal clinics

Community Health Volunteers

Emergency obstetric and newborn care

Facility Improvement Fund

Focus Group Discussions

International Centre for Research on Women

In-depth interviews

Key Informant Interviews

Newborn Unit

National Health Insurance Fund

Sustainable Development Goal

Service Delivery Redesign

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Acknowledgements

We would like to express our gratitude to the Kakamega County Government for granting us permission to conduct the study and for providing the essential preliminary information that facilitated our research. Furthermore, we would like to convey our sincere appreciation to the study participants for their invaluable cooperation throughout the course of this study.

This study is funded by the Bill and Mellinda Gates Foundation grant number # 263771.5119872. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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JN conceptualized the study, EO conducted the interviews, JN and EO undertook the analysis, EO developed the first draft of the manuscript. KO, KC, DO, JM, and JJ contributed to subsequent drafts and all authors approved this version of the manuscript for publication.

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Olwanda, E., Opondo, K., Oluoch, D. et al. Women’s autonomy and maternal health decision making in Kenya: implications for service delivery reform - a qualitative study. BMC Women's Health 24 , 181 (2024). https://doi.org/10.1186/s12905-024-02965-9

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DOI : https://doi.org/10.1186/s12905-024-02965-9

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  • Published: 21 March 2024

Stressors, emotions, and social support systems among respiratory nurses during the Omicron outbreak in China: a qualitative study

  • Wenzhen Yu 1 ,
  • Ying Zhang 1 ,
  • Yunyan Xianyu 1 &
  • Dan Cheng 1  

BMC Nursing volume  23 , Article number:  188 ( 2024 ) Cite this article

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Respiratory nurses faced tremendous challenges when the Omicron variant spread rapidly in China from late 2022 to early 2023. An in-depth understanding of respiratory nurses’ experiences during challenging times can help to develop better management and support strategies. The present study was conducted to explore and describe the work experiences of nurses working in the Department of Pulmonary and Critical Care Medicine (PCCM) during the Omicron outbreak in China.

This study utilized a descriptive phenomenological method. Between January 9 and 22, 2023, semistructured and individual in-depth interviews were conducted with 11 respiratory nurses at a tertiary hospital in Wuhan, Hubei Province. A purposive sampling method was used to select the participants, and the sample size was determined based on data saturation. The data analysis was carried out using Colaizzi’s method.

Three themes with ten subthemes emerged: (a) multiple stressors (intense workload due to high variability in COVID patients; worry about not having enough ability and energy to care for critically ill patients; fighting for anxious clients, colleagues, and selves); (b) mixed emotions (feelings of loss and responsibility; feelings of frustration and achievement; feelings of nervousness and security); and (c) a perceived social support system (team cohesion; family support; head nurse leadership; and the impact of social media).

Nursing managers should be attentive to frontline nurses’ needs and occupational stress during novel coronavirus disease 2019 (COVID-19) outbreaks. Management should strengthen psychological and social support systems, optimize nursing leadership styles, and proactively consider the application of artificial intelligence (AI) technologies and products in clinical care to improve the ability of nurses to effectively respond to future public health crises.

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Introduction

As of January 29, 2023, more than 753 million confirmed cases of COVID-19 have been reported globally, with more than 6.8 million deaths [ 1 ]. The Omicron variant (Omicron, B.1.1.529) is one of the five World Health Organization (WHO) variants of concern (VOCs). Compared with other VOCs, the Omicron variant has significantly increased transmission and immune escape [ 2 ]. An analysis by the Chinese Center for Disease Control and Prevention (CCDC) revealed that from December 1, 2022, to early January 2023, Omicron BA.5.2 and BF.7 were the prevalent strains in China, with these two lineages accounting for 97.5% of all indigenous cases [ 3 ]. At the press conference of the Joint COVID-19 Prevention and Control Mechanism of the State Council on January 14, 2023, the number of hospitalizations due to COVID-19 reached a peak of 1.63 million on January 5, and from December 8, 2022, to January 12, 2023, a total of 59,938 deaths related to hospitalizations due to COVID-19 occurred in medical institutions across the country. There were 5,503 deaths due to respiratory failure [ 4 ].

Nurses play a vital role in rescuing and treating COVID-19 patients. Nurses are at the forefront of the fight against disease, facing enormous physical and mental pressure while adopting effective strategies to overcome unprecedented challenges [ 5 – 6 ]. Research has shown that frontline nurses faced numerous challenges during the COVID-19 pandemic. A systematic review and meta-analysis exploring the impact of the COVID-19 pandemic on the prevalence of psychological symptoms among nurses showed that the pooled prevalence of anxiety, depression, and sleep disturbance was 37%, 35% and 43%, respectively [ 7 ]. During the COVID-19 pandemic, the workload of frontline nurses also increased significantly due to multiple factors, such as increased patient requirements and work content, longer work hours, and a shortage of staff and personal protective equipment [ 8 – 9 ]. In addition, nurses also expressed feelings of helplessness and inadequacy because, despite hard work, they were unable to provide dignified and acceptable-quality care [ 10 ]. Therefore, it is necessary to emphasize the significance of support for nurses from governments, policy-makers, and nursing organizations to reduce the negative impacts on nurses’ well-being during and after a pandemic or epidemic [ 11 ]. Otherwise, nurses may feel burnout, leading to turnover [ 12 – 13 ].

Nevertheless, existing studies on frontline nurses’ work experiences have been conducted predominantly in the context of nurses as physically healthy individuals providing health care services to COVID-19 patients. With the rapid spread of the Omicron BA.5.2 and BF.7 variants, it was estimated that most of the Chinese population was infected in December 2023 [ 14 ]. It has been reported that the number of clinic visits due to fever in China peaked on December 23, 2023. Two weeks later, the number of critical hospitalizations for COVID-19 also peaked [ 4 ]. During that period, the challenges faced by nurses in China were unprecedented and vastly different from those of other nurses worldwide. Most nurses were both health care providers and infected patients. The present qualitative study aimed to explore the work experiences of frontline respiratory nurses during the Omicron epidemic, develop better nursing countermeasures and management strategies for managers and promote better support for frontline nurses to provide patients with higher-quality care in possible future outbreaks.

Study design

The present study adopted a qualitative descriptive phenomenological design to conduct in-depth interviews. This design is suitable for providing detailed descriptions of participants’ emotions, opinions, and experiences and interpreting the meaning of their behaviours [ 15 ].

Participants and setting

All participants were recruited from a tertiary hospital in Wuhan, Hubei Province, China. A purposive sampling method was used in the present study. To obtain a wide range of experiences, we considered a diverse range of personal details, including age, sex, education level, marital status, years of nursing experience, professional title, type of employment, and workplace type, during the selection of participants. The sample size was determined based on data saturation [ 16 ].

The inclusion criteria were registered nurses working at the PCCM who provided direct care to COVID-19 patients between December 8, 2022, and January 8, 2023, and those who expressed willingness to participate in the study and share their experience. Nurse managers and nurses working less than two weeks during the abovementioned period were excluded.

Data collection

The data were collected through individual and face-to-face, in-depth interviews from January 9 to 22, 2023.

After a literature review and panel discussion, an interview guide was developed. Two pilot interviews were also conducted to investigate the appropriateness of the interview questions, and the guide remained the same. The data from the pilot interviews were not included in the analysis. All interviews were conducted by one researcher (first author), who completed a thorough and systematic study of qualitative research methods and reviewing skills before the start of the study. The final semistructured interview guide consisted of nine open-ended questions (see Supplementary file 1 ).

The interviewer and the participants had been colleagues for 3–7 years and trusted each other. The interviewer informed the participants about the purpose, voluntariness, anonymity, and confidentiality of the study one day before the interview and scheduled the time of the interview. Interviews were usually conducted on an afternoon when the participants were off duty, or an alternative time was arranged if the participants could not leave work on time. The interviews were conducted in a one-room office to ensure that the environment was quiet and undisturbed so that the participants could express their inner feelings to the interviewer with an open mind. With the participants’ permission, all interviews were audio-recorded using a digital voice recorder. The duration of the interviews varied between 30 and 60 min. Within 24 h of each interview, the audio-recorded data were fully transcribed, and two researchers independently evaluated the data saturation. Any disagreements were resolved through a panel discussion. Behavioural data (laughing, crying, sighing, silence or pausing, etc.) were also recorded during transcription for data analysis. Data saturation was reached at the 10th interview, but an additional interview was also conducted to ensure that no new information emerged. Therefore, a total of 11 respiratory nurses were recruited. None of the nurses dropped out of the study.

Data analysis

Colaizzi’s method was used to analyse the data [ 17 ]. This method involved the following steps: (a) Familiarization: rereading the transcripts verbatim multiple times to become familiar with the data; (b) Identifying significant statements: identifying and extracting meaningful statements relevant to the phenomenon; (c) Formulating meanings: formulating and encoding meanings from important statements; (d) Clustering themes: aggregating the encoded meanings into preliminary themes; (e) Developing an exhaustive description: providing a detailed description of each of the themes generated in step d with the addition of participants’ original statements; (f) Producing the fundamental structure: generating themes to reveal the basic structure of the phenomenon using short and condensed phrases; and (g) Verifying the fundamental structure: presenting the transcripts of the interviews, codes, and themes to the participants for feedback on whether their experience of the phenomenon had been accurately represented. Two independent researchers analysed the data simultaneously.

In this study, Lincoln and Guba’s criteria of credibility, transferability, dependability, and confirmability were utilized to ensure rigor [ 18 ]. The following strategies were implemented to achieve credible study findings: conducting semistructured, in-depth interviews with open-ended questions and field notes; transcribing audio-recorded data word-for-word and independently analysing the raw data by two researchers; and asking participants to provide feedback on the transcripts, codes, and themes. Transferability was established by considering maximum variations in participant characteristics and presenting appropriate participant quotes. To facilitate dependability and confirmability, several meetings were held among the researchers to discuss and identify codes, subthemes, and themes.

Ethical considerations

This study was approved by the research and ethics committees of Renmin Hospital of Wuhan University (Approval NO: WDRY2023-K031). Before the interviews, the details of the study, the expected risks and benefits, and the right to withdraw at any time was verbally explained to all participants, and written informed consent was obtained. After the interviews were transcribed, the participants’ names were deleted instead of their identities (A‒K). To ensure confidentiality and privacy, the text data were stored in a locked cabinet, and the audio data were stored on a password-protected computer.

Participant characteristics

A total of 11 nurses, including 10 females (90.9%) and 1 male (9.1%), were included. The mean age was 32.09 ± 5.45 years (range = 24–43 years), and the mean number of years of nursing experience was 10.36 ± 5.50 years (range = 3–21 years). The sociodemographic data are displayed in Table  1 .

Thematic results

Three major themes emerged: multiple stressors, mixed emotions, and a perceived social support system. Ten subthemes were identified. The findings are described in Fig.  1 .

figure 1

Themes and sub-themes of work experience for respiratory nurses during Omicron outbreak

Theme 1: Multiple Stressors

This theme focused on the workplace stressors experienced by respiratory nurses during the Omicron outbreak. Three subthemes were identified in this theme: intense workload due to high variability in COVID patients; worry about not having enough ability and energy to care for critically ill patients; and fighting for anxious clients, colleagues, and selves.

Intense workload due to high variability in COVID patients

Most participants reported a high level of work pressure, such as a high number of admissions, a high percentage of critical patients, rapid changes in patient conditions, and frequent resuscitations. As one participant said,

“For some time now, the RICU has been particularly busy. Every shift is filled with resuscitation cases and the admission of new critically ill patients, usually those who need to be intubated. We borrowed much equipment from the Equipment Division, such as ventilators and high-flow nasal cannula oxygen therapy devices. We usually have enough equipment in our Department, but now we do not.” (Participant G)

Almost all participants stated that the workload of nursing care associated with COVID-19 had significantly increased, and nurses often had to work overtime to complete their work. As two participants said,

“Almost all newly admitted patients are given nebulizers and oxygen and undergo urgent arterial blood gas analysis. I could not leave work on time almost daily (bitter smile).” (Participant C)
“There are many patients on oral corticosteroids, which is different than usual. I have to talk to the patients about the use and the dosage, tell them when to taper, and talk to the doctor before I give the medication. It all takes time.” (Participant I)

Another participant said the following:

“Except for nursing records, I get things done during working hours. Then, I spend off-duty time writing the records.” (Participant E)

Some participants reported working at an accelerated pace during the work period. One of the participants described their experience as follows:

“Patients ask me questions, and maybe I am fast in my speech and, well, fast enough in my steps.” (Participant D)

Most participants reported returning to work after taking a short break from their infections. However, they were still symptomatic when they returned to work. One participant said the following:

“I had three days of rest and came back to work when my fever was down, and my cough has not gone away yet.” (Participant A)

Worry about not having enough ability and energy to care for critically ill patients

Some of the participants in this study reported significant psychological distress from worrying about not having enough ability and energy to care for critically ill patients. The following excerpts illustrate this subtheme:

“There are many patients on invasive mechanical ventilation, and the biggest worry is accidental extubation. It is nerve-wracking.” (Participant F)
“Some patients are ventilated in the prone position; some are intubated, and some are not. Although the therapeutic efficacy was quite good, at least four colleagues were needed to change the position. It is a big risk at night when we are short-staffed, especially in a resuscitation situation.” (Participant G)
“I was worried about making mistakes. During that time, I had night sweats, did not sleep well, often felt weak and dizzy during the day, and was afraid that I would make a mistake while providing care because of my lack of concentration.” (Participant K)

Fighting for anxious clients, colleagues, and selves

In this study, most participants said that patients and their family members, doctors, other nurses, and themselves were experiencing negative emotions such as anxiety. Some participants expressed this as follows:

“In my communication with patients, I have noticed that many patients are anxious, so I do more explaining than before when I give patients medication. Many patients ask me if their disease is serious…” (Participant I)
“Some patients are transferred to the RICU when their condition deteriorates, and their families have no sight of them and are very anxious every day. There is also much pressure on the doctors.” (Participant G)
“For us young nurses who are faced with so many critically ill patients who experience rapid changes in their conditions, we often have to communicate with doctors, especially senior doctors. If (we are) inexperienced, communication is slightly difficult. Additionally, because everyone has been working for a long time, it is difficult to know whether (the staff) are irritated or can communicate well with their colleagues. Because after a long shift, they may all be experiencing negative emotions.” (Participant F)
“I am not sure if it is because of my illness or because of my work. I often dream about saving patients, probably for both reasons… I hope the hospital will open a free psychiatric and sleep disorder clinic for us.” (Participant K)

Some participants mentioned maintaining a positive mindset through self-regulation and psychological suggestions as a stress management strategy and expressed the hope that managers would pay attention to the psychological states of frontline nurses and provide psychological support. One participant said,

“It is important to keep thinking positively. We are all in the same boat now (laughs). The other thing is to learn some relaxation techniques. Leaders should be aware of the psychological dynamics of nurses on the front line and provide psychological comfort.” (Participant F)

Theme 2: Mixed emotions

This theme focused on mixed emotional states, that is, the co-occurrence of positive and negative emotions in respiratory nurses during the Omicron outbreak. Within this theme, three subthemes were identified: feelings of loss and responsibility, feelings of frustration and achievement, and feelings of nervousness and security.

Feelings of loss and responsibility

Some of the participants in this study expressed a certain sense of loss. This feeling stemmed from nurses caring for patients, uncertain about when they might become infected, and their lack of a role in taking care of family. One of the participants said,

“There could still be a psychological setback. I went through the 2020 pandemic in Wuhan, and then I went to another city (to offer support) and witnessed another outbreak. Previously, we thought about how to protect ourselves while helping others. This time, it is unclear how to protect ourselves while treating others.” (Participant H)

Another participant said,

“My family members were infected. I was working hard and very busy, and I did not have the extra time or energy to care for them. My parents did not live with me, and I wanted to have time to get them some medicine and check on them. During that time, I was worried about their health because the risks for older people were high. I was worried that their health conditions would become more serious, and I was not caring for them.” (Participant I)

The majority of the participants in this study stated that they stayed in their jobs despite experiencing substantial and multiple pressures because of a sense of responsibility. One participant, who was asymptomatic and not sure if he was infected, said the following:

“I think we have to work and stick to the job. First, we have to go to work according to the schedule, which is the most important point, the duty. I cannot stay away from work just because I haven’t been infected. At this most critical point, running away at the first sign of difficulty is impossible. That is certainly not the right thing to do. The main thing is duty because that is one of the most fundamental qualities of an employee.” (Participant F)

Some participants who had symptoms indicated that their intention in returning to work without fully recovering was to allow other nurses to also have breaks. One participant mentioned,

“At the time, I had been off for 3 days. Some of my colleagues were just showing symptoms and had no breaks. I thought I should go to work so those colleagues could have breaks, so I picked myself up and came to work.” (Participant A)

Feelings of frustration and achievement

Some of the participants in this study reported that patient blaming made them feel frustrated. Some participants claimed that their frustration stemmed from not seeing a significant improvement in patient outcomes in the short term. Participants described their experiences as follows:

“When I came back to work after being sick, I had not fully recovered, and occasionally I moved a little slower. Some patients did not understand my situation. I felt despondent at that moment (tears).” (Participant A)
“It is very depressing. Intubated patients are difficult to wean from mechanical ventilation for an extended period, and even less severe patients still have symptoms.” (Participant G)

Most of the participants in this study reported feeling a sense of achievement. The reasons included receiving affirmation from patients or their families; noticing gradual improvement in patient conditions; being helpful to families, friends, or colleagues; and enhancing professional competence. The participants described their experiences as follows:

“Many patients expressed admiration for my hard work and understood the challenges I faced, some even telling me to take a break. Their empathy motivated me to continue making contributions.” (Participant D)
“When the patients were admitted, they were extremely unwell, struggling with speech and reluctant to move. Following treatment, they could eat independently, move about independently, and express gratitude for feeling better. Moments like this bring great happiness to me!” (Participant H)
“During this period, I received more calls from acquaintances for counselling and felt fulfilled. They asked questions, such as if azvudine was effective, and I could advise them on the optimal stage for taking medication. Consequently, I felt that I was valued and was motivated to be a respiratory nurse. We are also confident that the mortality rate in our ward is very low, and many patients have been discharged.” (Participant I)
“This experience can be considered a form of training, helping us develop specialized skills and gain personal insights. If we face a similar emergency in the future, we will possess greater knowledge and skills regarding how to tackle it.” (Participant F)

Feelings of nervousness and security

Some of the participants in this study expressed nervousness due to the fear of being infected and of passing the virus on to their family members. One participant who tested negative for SARS-CoV-2 antibodies described her feelings as follows:

“My workmates falling ill affected me. I did not know what the symptoms would be if I got it. It was that uncertainty. Therefore, going to work caused anxiety at the beginning of the outbreak. It is that feeling of not knowing if you will go down next… It is like there’s no escape.” (Participant H)

Another participant stated the following:

“I am feeling nervous. I am in daily contact with patients who have tested positive, and since I have elderly relatives and young children at home, I am more concerned about bringing the virus back with me. That is why, when I return home from work, I leave my clothes and shoes outside, and the first thing I do upon entering my home is shower. When I returned home, my children used to hug me, but I would say, “Stay back, stay back.” I had to take a shower before I embraced them. Will there be a second or third wave? Can elderly people and children withstand this? Will my health worsen over time?” (Participant B)

Some of the participants expressed that their work in the PCCM made them feel reassured:

“I feel that working in a hospital makes it easier to get help if I become infected. As a respiratory staff member, I feel safe.” (Participant K)
“ It is not really that worrying. I think I was in the PCCM, and if anything happened to me, everyone would save me. I’m in this department, and the backup is strong. ” (Participant C)

Theme 3: Perceived social support systems

The vast majority of participants talked about the social support systems they perceived and how these social support systems impacted them. Within this theme, four subthemes were identified: team cohesion, family support, head nurse leadership, and the impact of social media

Team cohesion

Most participants in this study reported that coworkers helped each other at work, comforted each other psychologically, and were more unified than before the epidemic. The following descriptions represented this subtheme:

“During that time, even though almost everyone was sick and very busy at work, the atmosphere in our department was amiable. Every time you were busy, others would come to help you, and so would I. No one slacked off or hid from work, and everyone worked hard. It was a positive boost because no one was dragging their feet.” (Participant B)
“In such a busy situation, our colleagues are more united. We help each other. It is more cohesive. Busier, but more in touch (smile).” (Participant C)
“After my colleagues got infected, they shared some of their feelings with me. It was not really that uncomfortable, so my mind quickly relaxed. When people’s symptoms subsided, their temperature dropped, or the pain in their bodies eased, you could sense their happiness. I also felt happy when I heard such news. I feel that this kind of happiness is different from usual.” (Participant H)

Family support

Some participants in this study indicated that the health and support of their families strongly supported them in focusing on fighting against the outbreak:

“My family was very supportive (laughs). Everyone was very supportive. They were trying to minimize my burden. Because I did not know if I was infected, but when they were infected, they drank water, took their own medicine, and took their temperature. They wore masks, and they disinfected at home. I think that this was also a kind of support. They did not delay buying food or cooking every day and did not stop cooking or eating just because they were lethargic after the infection. Therefore, I think that is a kind of support (laughs).” (Participant H)
“I think my family… my support system is stable (grin), so I think I would be fine (to work).” (Participant C)

Head nurse leadership

Some of the participants in this study indicated that the head nurses’ leadership had a significant impact on the nurses’ work experiences:

“Rational scheduling and decision-making by the nurse managers is important. Pairing senior nurses with junior nurses during scheduling can avoid several risks. It is also important to try to ensure that everyone gets enough rest while maximizing the potential of the frontline nurses.” (Participant F)
“One day, the on-call shift started. Zhang was on it, and she did not get a moment’s rest until the end of the shift, and neither did we. She came to help us. She helped everyone. Where we were busy, where she was, arranging that shift helped our whole team and individuals a lot.” (Participant B)
“Any shortage of supplies or equipment or emergency, just talk to the head nurse, and it all gets resolved, so it is not so draining to work.” (Participant D)

Impact of social media

In this study, some participants mentioned that social media use impacted their psychological feelings, as follows:

“There are some very positive short videos online. One of our colleagues and some well-known people have shared their personal experiences fighting the outbreak, and it has been helpful to see others actively confronting it.” (Participant H)

Some participants expressed the opposite view:

“It worries me a little bit because the reinfections that are rumoured online can be scary.” (Participant C).

This study describes the challenges faced by respiratory nurses caring for COVID-19 patients during the Omicron outbreak in China from late 2022 to early 2023. Specifically, the findings interpreted these experiences as multiple stressors, mixed emotions, and perceived social support systems.

Like in the study by Al Maqbali M [ 7 ], a significant proportion of participants in our study reported that they had psychological problems such as stress, anxiety, frustration, or sleep disturbance and expressed a need for psychological support. Falatah’s [ 12 ] study showed that nurses’ turnover intentions increased significantly during the COVID-19 pandemic compared with that before the pandemic, and stress, anxiety, and fear of disease were predictors of nurses’ turnover intentions. In contrast to those in other studies, the participants in our study expressed their sense of security, which stemmed from confidence in their own professional background and trust in their colleagues. A previous study emphasized that understanding the psychological needs of frontline nurses and providing them with tailored psychological support can improve their mental health status and promote quality responses to clinical nursing and public health emergencies [ 19 ]. In addition, a cross-sectional correlation study conducted by Hoşgör [ 20 ] revealed that there was a significant positive correlation between nurses’ psychological resilience and job performance during the COVID-19 pandemic. These findings show that adopting strategies to improve the psychological resilience of nurses is helpful for optimizing the efficiency of nursing work and improving the quality of patient care. Therefore, during a public health crisis, nurse managers should assess the mental health status of frontline nurses in a timely manner, understand in depth the sources of pressure experienced by nurses, and establish psychological treatment teams to provide offline or online psychological support in the form of one-on-one or group support to improve the mental resilience and physical health of nurses.

In our study, participants described their sources of perceived social support, such as support from their teams, family members, head nurses, and social media. This social support helped them cope with the challenges during this difficult time and encouraged them to provide nursing care to the best of their ability. The participants had positive expressions and emotions when discussing their perceived social support systems. These findings are consistent with the findings of the Shen study [ 21 ], which revealed that the greater the level of social support, the better the psychological condition of nurses during the COVID-19 pandemic. Therefore, we strongly recommend that hospital managers regularly visit clinics, interact with frontline nurses, praise their vital role in dealing with the outbreak, and take comprehensive measures to increase value awareness, including compensation, honorary certificates, and publicly recognizing nurses’ contributions. In addition, visiting nurses on the frontline will help address difficulties such as shortages of equipment and human resources in the early stages of outbreaks.

Conversely, some participants in our study reported that rumours on social media about the serious consequences of reinfection negatively affected them. This may be related to the fact that most of the study participants were both patients and caregivers at the beginning of the outbreak. This points to the importance of leading public health experts being organized by the executive branch to provide evidence-based information to the public through social media.

Consistent with the findings of previous research [ 22 ], some participants described concerns not only about their own health but also about the health of their family members. This highlights the necessity of extending support for frontline nurses to their family members, including providing medicine and medical counselling. In addition, developing contingency plans to ensure the timeliness and accessibility of social support systems is an issue that managers must address.

The results of this study showed that flexible shift scheduling, active communication, timely resolution of problems, and close working cooperation with nurses played crucial roles in facilitating frontline nurses’ responses to the outbreak. Nursing managers are critical in maximizing the retention of nursing human resources and maintaining productivity and efficiency in health care organizations. Nursing leadership styles strongly influence nurses’ happiness and work environments. Niinihuhta [ 23 ] suggested that nurse leaders should use a supportive and relationship-focused leadership style. Another systematic review conducted by Cummings [ 24 ] provided robust evidence that relational leadership styles, such as transformational and authentic leadership styles, are significantly associated with improved outcomes, including outcomes regarding job satisfaction, employee-work relationships, employee health and well-being, the organizational environment and productivity.

In contrast, leadership focusing only on task completion is insufficient for achieving positive nursing health and workforce outcomes. As revealed in the scoping review conducted by Sihvola [ 25 ], nurse leaders should adopt a relational leadership style and positive communication to support nurse resilience during the COVID-19 pandemic. Furthermore, as an extension of the relational leadership style, inclusive leadership could increase the psychological ownership of nurses and reduce turnover intentions [ 26 ].

Unlike in previous situations, most participants in our study had symptoms, such as coughing or weakness, while caring for their clients. Therefore, as the bellwether of frontline nursing caregivers, head nurses should consider the overall situation of hospital management when public health emergencies occur, pay attention to the needs of frontline nurses, consider nurses’ advice, tolerate nurses’ shortcomings and mistakes, and construct an organizational relationship with clear and transparent communication, updated information, flexible shift arrangements, and mutual trust among colleagues to achieve the common goals of organizations and individuals to defeat the pandemic.

According to the results of the present study, respiratory nurses generally work longer hours in the event of an outbreak. At the beginning of the outbreak, the care workload surged as a large number of patients flooded hospitals. As a result, the amount of time to required complete nursing records increased. Consequently, bedside care was commonly provided to patients during normal business hours, and care notes were commonly completed during off hours. In addition, staff shortages were exacerbated by the infection of most logistics staff, and nurses had to take over delivering meals to patients and transporting medical and living supplies.

To alleviate the acute shortage of nursing staff and improve the quality and efficiency of nursing care, attempts are being made worldwide to apply AI technology to care, including COVID-19 care. Kagiyama [ 27 ] reported that a telemedicine-based self-vital sign examination system could quickly and accurately obtain vital sign information by measuring and uploading COVID-19 patient data without the risk of spreading infections. Mairittha [ 28 ] integrated a spoken conversation system into a smartphone application for care records. They found that the method increased the documentation speed by approximately 58.3% compared to the traditional keyboard-based method. Alderden [ 29 ] explored an AI-based transparent machine learning model that could predict the risk of hospital-acquired pressure injuries in ICU patients with COVID-19. Other studies have shown that nurses already use AI to perform various tasks across multiple patient populations, such as assisting elderly patients or recovering patients with exercise and in pain management, communication, interviewing, and patient education [ 30 ]. Nurses should recognize the need using AI in care. Nurses should increase their awareness of AI development; actively communicate and collaborate with experts in related fields; and advocate for patient and nurse involvement in the design, implementation, and evaluation of all aspects of AI health technology to prepare for possible future public health events.

Limitations

All participants in this study were from a tertiary hospital in Wuhan, China. Therefore, the results of the current study may not be generalizable to other settings. Despite we utilized purposive sampling method to ensure diversity of opinions, the majority of participants were female, which was due to the relatively small proportion of male nurse in China. In addition, although our interviews began one month after the start of the outbreak, they took place for two weeks, which may have influenced the views and expressions of the participants over time.

Respiratory department nurses provided insight into their work experiences during the Omicron outbreak in China from late 2022 to early 2023. Despite experiencing exhaustion, nurses continued to take care of COVID-19 patients with the sense of responsibility of “angels without wings.” Respiratory nurses also experienced a sense of accomplishment from helping patients and a sense of security from their professional backgrounds. The mutual help of team members, support from family members, leadership by head nurses, and influence of social media are essential factors supporting frontline respiratory nurses in the fight against COVID-19. Hospital administrators should pay attention to the pressure and needs of frontline nurses during epidemics, improve psychosocial support systems, optimize the leadership styles of nurse managers, and actively explore the use of AI in the field of clinical nursing to improve nurses’ abilities to respond to public health emergencies.

Implications

The findings of this study reveal the multiple stressors and mixed emotions encountered by frontline respiratory nurses in combating COVID-19, which is helpful for nurse managers to develop comprehensive strategies that mitigate the adverse impact of these stressors and the negative emotions on nurses’ well-being and augment the positive emotions’ influence on nurses’ work engagement. Moreover, the identification of the nurses perceived social support system would assist policy-makers and hospital administrators in formulating more tailored polices to enhance their support for frontline nurses. Additionally, the design and implementation of training programs focusing on respiratory intensive care for nurses and leadership skills for charge nurse, will play a crucial role in effectively responding to extreme pandemic events. Furthermore, the researchers recommend that more qualitative research be carried out in different medical institutions and that more male nurses be included to improve understanding of the phenomenon. It is also suggested that further research be conducted to explore the psychosocial support needs of frontline nurses and ultimately improve their mental and physical health and quality of care for COVID-19 patients.

Data availability

The datasets generated and/or analyzed in this study are not publicly available because the data contain individual participant information, but are available from the corresponding author on reasonable request.

Abbreviations

Department of Pulmonary and Critical Care Medicine

Novel coronavirus disease 2019

Artificial intelligence

World Health Organization

Variants of concern

Chinese Center for Disease Control and Prevention

Respiratory intensive care unit

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Acknowledgements

The authors thank the participants in this study for sharing their experiences.

This study was supported by the Hubei key laboratory opening project of Health Commission of Hubei Province (2022KFH002) and general project of Health Commission of Hubei Province (WJ2021M150).

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Wenzhen Yu, Ying Zhang, Yunyan Xianyu & Dan Cheng

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W.Y., Y.Z., and D.C. conceptualized and designed the study. W.Y. collected the data. W.Y. and Y.Z. analyzed and interpreted the data. Y.X. acquired the funding and administered the projects. W.Y. wrote the original draft. W.Y., Y.Z., Y.X., and D.C. reviewed and edited the draft manuscript. All authors read and approved the final manuscript.

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Correspondence to Dan Cheng .

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Yu, W., Zhang, Y., Xianyu, Y. et al. Stressors, emotions, and social support systems among respiratory nurses during the Omicron outbreak in China: a qualitative study. BMC Nurs 23 , 188 (2024). https://doi.org/10.1186/s12912-024-01856-6

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