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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

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

• Labor-intensive

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

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

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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

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

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

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

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

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On This Page:

Qualitative research is a type of research methodology that focuses on gathering and analyzing non-numerical data to gain a deeper understanding of human behavior, experiences, and perspectives.

It aims to explore the “why” and “how” of a phenomenon rather than the “what,” “where,” and “when” typically addressed by quantitative research.

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research involves researchers interpreting data to identify themes, patterns, and meanings.

Qualitative research can be used to:

• Gain deep contextual understandings of the subjective social reality of individuals
• To answer questions about experience and meaning from the participant’s perspective
• To design hypotheses, theory must be researched using qualitative methods to determine what is important before research can begin. 

Examples of qualitative research questions include: 

• How does stress influence young adults’ behavior?
• What factors influence students’ school attendance rates in developed countries?
• How do adults interpret binge drinking in the UK?
• What are the psychological impacts of cervical cancer screening in women?
• How can mental health lessons be integrated into the school curriculum? 

Characteristics 

Naturalistic setting.

Individuals are studied in their natural setting to gain a deeper understanding of how people experience the world. This enables the researcher to understand a phenomenon close to how participants experience it. 

Naturalistic settings provide valuable contextual information to help researchers better understand and interpret the data they collect.

The environment, social interactions, and cultural factors can all influence behavior and experiences, and these elements are more easily observed in real-world settings.

Reality is socially constructed

Qualitative research aims to understand how participants make meaning of their experiences – individually or in social contexts. It assumes there is no objective reality and that the social world is interpreted (Yilmaz, 2013). 

The primacy of subject matter 

The primary aim of qualitative research is to understand the perspectives, experiences, and beliefs of individuals who have experienced the phenomenon selected for research rather than the average experiences of groups of people (Minichiello, 1990).

An in-depth understanding is attained since qualitative techniques allow participants to freely disclose their experiences, thoughts, and feelings without constraint (Tenny et al., 2022). 

Variables are complex, interwoven, and difficult to measure

Factors such as experiences, behaviors, and attitudes are complex and interwoven, so they cannot be reduced to isolated variables , making them difficult to measure quantitatively.

However, a qualitative approach enables participants to describe what, why, or how they were thinking/ feeling during a phenomenon being studied (Yilmaz, 2013). 

Emic (insider’s point of view)

The phenomenon being studied is centered on the participants’ point of view (Minichiello, 1990).

Emic is used to describe how participants interact, communicate, and behave in the research setting (Scarduzio, 2017).

Interpretive analysis

In qualitative research, interpretive analysis is crucial in making sense of the collected data.

This process involves examining the raw data, such as interview transcripts, field notes, or documents, and identifying the underlying themes, patterns, and meanings that emerge from the participants’ experiences and perspectives.

Collecting Qualitative Data

There are four main research design methods used to collect qualitative data: observations, interviews,  focus groups, and ethnography.

Observations

This method involves watching and recording phenomena as they occur in nature. Observation can be divided into two types: participant and non-participant observation.

In participant observation, the researcher actively participates in the situation/events being observed.

In non-participant observation, the researcher is not an active part of the observation and tries not to influence the behaviors they are observing (Busetto et al., 2020). 

Observations can be covert (participants are unaware that a researcher is observing them) or overt (participants are aware of the researcher’s presence and know they are being observed).

However, awareness of an observer’s presence may influence participants’ behavior. 

Interviews give researchers a window into the world of a participant by seeking their account of an event, situation, or phenomenon. They are usually conducted on a one-to-one basis and can be distinguished according to the level at which they are structured (Punch, 2013). 

Structured interviews involve predetermined questions and sequences to ensure replicability and comparability. However, they are unable to explore emerging issues.

Informal interviews consist of spontaneous, casual conversations which are closer to the truth of a phenomenon. However, information is gathered using quick notes made by the researcher and is therefore subject to recall bias. 

Semi-structured interviews have a flexible structure, phrasing, and placement so emerging issues can be explored (Denny & Weckesser, 2022).

The use of probing questions and clarification can lead to a detailed understanding, but semi-structured interviews can be time-consuming and subject to interviewer bias. 

Focus groups 

Similar to interviews, focus groups elicit a rich and detailed account of an experience. However, focus groups are more dynamic since participants with shared characteristics construct this account together (Denny & Weckesser, 2022).

A shared narrative is built between participants to capture a group experience shaped by a shared context. 

The researcher takes on the role of a moderator, who will establish ground rules and guide the discussion by following a topic guide to focus the group discussions.

Typically, focus groups have 4-10 participants as a discussion can be difficult to facilitate with more than this, and this number allows everyone the time to speak.

Ethnography

Ethnography is a methodology used to study a group of people’s behaviors and social interactions in their environment (Reeves et al., 2008).

Data are collected using methods such as observations, field notes, or structured/ unstructured interviews.

The aim of ethnography is to provide detailed, holistic insights into people’s behavior and perspectives within their natural setting. In order to achieve this, researchers immerse themselves in a community or organization. 

Due to the flexibility and real-world focus of ethnography, researchers are able to gather an in-depth, nuanced understanding of people’s experiences, knowledge and perspectives that are influenced by culture and society.

In order to develop a representative picture of a particular culture/ context, researchers must conduct extensive field work. 

This can be time-consuming as researchers may need to immerse themselves into a community/ culture for a few days, or possibly a few years.

Qualitative Data Analysis Methods

Different methods can be used for analyzing qualitative data. The researcher chooses based on the objectives of their study. 

The researcher plays a key role in the interpretation of data, making decisions about the coding, theming, decontextualizing, and recontextualizing of data (Starks & Trinidad, 2007). 

Grounded theory

Grounded theory is a qualitative method specifically designed to inductively generate theory from data. It was developed by Glaser and Strauss in 1967 (Glaser & Strauss, 2017).

This methodology aims to develop theories (rather than test hypotheses) that explain a social process, action, or interaction (Petty et al., 2012). To inform the developing theory, data collection and analysis run simultaneously. 

There are three key types of coding used in grounded theory: initial (open), intermediate (axial), and advanced (selective) coding. 

Throughout the analysis, memos should be created to document methodological and theoretical ideas about the data. Data should be collected and analyzed until data saturation is reached and a theory is developed. 

Content analysis

Content analysis was first used in the early twentieth century to analyze textual materials such as newspapers and political speeches.

Content analysis is a research method used to identify and analyze the presence and patterns of themes, concepts, or words in data (Vaismoradi et al., 2013). 

This research method can be used to analyze data in different formats, which can be written, oral, or visual. 

The goal of content analysis is to develop themes that capture the underlying meanings of data (Schreier, 2012). 

Qualitative content analysis can be used to validate existing theories, support the development of new models and theories, and provide in-depth descriptions of particular settings or experiences.

The following six steps provide a guideline for how to conduct qualitative content analysis.

• Define a Research Question : To start content analysis, a clear research question should be developed.
• Identify and Collect Data : Establish the inclusion criteria for your data. Find the relevant sources to analyze.
• Define the Unit or Theme of Analysis : Categorize the content into themes. Themes can be a word, phrase, or sentence.
• Develop Rules for Coding your Data : Define a set of coding rules to ensure that all data are coded consistently.
• Code the Data : Follow the coding rules to categorize data into themes.
• Analyze the Results and Draw Conclusions : Examine the data to identify patterns and draw conclusions in relation to your research question.

Discourse analysis

Discourse analysis is a research method used to study written/ spoken language in relation to its social context (Wood & Kroger, 2000).

In discourse analysis, the researcher interprets details of language materials and the context in which it is situated.

Discourse analysis aims to understand the functions of language (how language is used in real life) and how meaning is conveyed by language in different contexts. Researchers use discourse analysis to investigate social groups and how language is used to achieve specific communication goals.

Different methods of discourse analysis can be used depending on the aims and objectives of a study. However, the following steps provide a guideline on how to conduct discourse analysis.

• Define the Research Question : Develop a relevant research question to frame the analysis.
• Gather Data and Establish the Context : Collect research materials (e.g., interview transcripts, documents). Gather factual details and review the literature to construct a theory about the social and historical context of your study.
• Analyze the Content : Closely examine various components of the text, such as the vocabulary, sentences, paragraphs, and structure of the text. Identify patterns relevant to the research question to create codes, then group these into themes.
• Review the Results : Reflect on the findings to examine the function of the language, and the meaning and context of the discourse. 

Thematic analysis

Thematic analysis is a method used to identify, interpret, and report patterns in data, such as commonalities or contrasts. 

Although the origin of thematic analysis can be traced back to the early twentieth century, understanding and clarity of thematic analysis is attributed to Braun and Clarke (2006).

Thematic analysis aims to develop themes (patterns of meaning) across a dataset to address a research question. 

In thematic analysis, qualitative data is gathered using techniques such as interviews, focus groups, and questionnaires. Audio recordings are transcribed. The dataset is then explored and interpreted by a researcher to identify patterns. 

This occurs through the rigorous process of data familiarisation, coding, theme development, and revision. These identified patterns provide a summary of the dataset and can be used to address a research question.

Themes are developed by exploring the implicit and explicit meanings within the data. Two different approaches are used to generate themes: inductive and deductive. 

An inductive approach allows themes to emerge from the data. In contrast, a deductive approach uses existing theories or knowledge to apply preconceived ideas to the data.

Phases of Thematic Analysis

Braun and Clarke (2006) provide a guide of the six phases of thematic analysis. These phases can be applied flexibly to fit research questions and data. 

Template analysis

Template analysis refers to a specific method of thematic analysis which uses hierarchical coding (Brooks et al., 2014).

Template analysis is used to analyze textual data, for example, interview transcripts or open-ended responses on a written questionnaire.

To conduct template analysis, a coding template must be developed (usually from a subset of the data) and subsequently revised and refined. This template represents the themes identified by researchers as important in the dataset. 

Codes are ordered hierarchically within the template, with the highest-level codes demonstrating overarching themes in the data and lower-level codes representing constituent themes with a narrower focus.

A guideline for the main procedural steps for conducting template analysis is outlined below.

• Familiarization with the Data : Read (and reread) the dataset in full. Engage, reflect, and take notes on data that may be relevant to the research question.
• Preliminary Coding : Identify initial codes using guidance from the a priori codes, identified before the analysis as likely to be beneficial and relevant to the analysis.
• Organize Themes : Organize themes into meaningful clusters. Consider the relationships between the themes both within and between clusters.
• Produce an Initial Template : Develop an initial template. This may be based on a subset of the data.
• Apply and Develop the Template : Apply the initial template to further data and make any necessary modifications. Refinements of the template may include adding themes, removing themes, or changing the scope/title of themes. 
• Finalize Template : Finalize the template, then apply it to the entire dataset. 

Frame analysis

Frame analysis is a comparative form of thematic analysis which systematically analyzes data using a matrix output.

Ritchie and Spencer (1994) developed this set of techniques to analyze qualitative data in applied policy research. Frame analysis aims to generate theory from data.

Frame analysis encourages researchers to organize and manage their data using summarization.

This results in a flexible and unique matrix output, in which individual participants (or cases) are represented by rows and themes are represented by columns. 

Each intersecting cell is used to summarize findings relating to the corresponding participant and theme.

Frame analysis has five distinct phases which are interrelated, forming a methodical and rigorous framework.

• Familiarization with the Data : Familiarize yourself with all the transcripts. Immerse yourself in the details of each transcript and start to note recurring themes.
• Develop a Theoretical Framework : Identify recurrent/ important themes and add them to a chart. Provide a framework/ structure for the analysis.
• Indexing : Apply the framework systematically to the entire study data.
• Summarize Data in Analytical Framework : Reduce the data into brief summaries of participants’ accounts.
• Mapping and Interpretation : Compare themes and subthemes and check against the original transcripts. Group the data into categories and provide an explanation for them.

Preventing Bias in Qualitative Research

To evaluate qualitative studies, the CASP (Critical Appraisal Skills Programme) checklist for qualitative studies can be used to ensure all aspects of a study have been considered (CASP, 2018).

The quality of research can be enhanced and assessed using criteria such as checklists, reflexivity, co-coding, and member-checking. 

Co-coding 

Relying on only one researcher to interpret rich and complex data may risk key insights and alternative viewpoints being missed. Therefore, coding is often performed by multiple researchers.

A common strategy must be defined at the beginning of the coding process  (Busetto et al., 2020). This includes establishing a useful coding list and finding a common definition of individual codes.

Transcripts are initially coded independently by researchers and then compared and consolidated to minimize error or bias and to bring confirmation of findings. 

Member checking

Member checking (or respondent validation) involves checking back with participants to see if the research resonates with their experiences (Russell & Gregory, 2003).

Data can be returned to participants after data collection or when results are first available. For example, participants may be provided with their interview transcript and asked to verify whether this is a complete and accurate representation of their views.

Participants may then clarify or elaborate on their responses to ensure they align with their views (Shenton, 2004).

This feedback becomes part of data collection and ensures accurate descriptions/ interpretations of phenomena (Mays & Pope, 2000). 

Reflexivity in qualitative research

Reflexivity typically involves examining your own judgments, practices, and belief systems during data collection and analysis. It aims to identify any personal beliefs which may affect the research. 

Reflexivity is essential in qualitative research to ensure methodological transparency and complete reporting. This enables readers to understand how the interaction between the researcher and participant shapes the data.

Depending on the research question and population being researched, factors that need to be considered include the experience of the researcher, how the contact was established and maintained, age, gender, and ethnicity.

These details are important because, in qualitative research, the researcher is a dynamic part of the research process and actively influences the outcome of the research (Boeije, 2014). 

Reflexivity Example

Who you are and your characteristics influence how you collect and analyze data. Here is an example of a reflexivity statement for research on smoking. I am a 30-year-old white female from a middle-class background. I live in the southwest of England and have been educated to master’s level. I have been involved in two research projects on oral health. I have never smoked, but I have witnessed how smoking can cause ill health from my volunteering in a smoking cessation clinic. My research aspirations are to help to develop interventions to help smokers quit.

Establishing Trustworthiness in Qualitative Research

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability.

1. Credibility in Qualitative Research

Credibility refers to how accurately the results represent the reality and viewpoints of the participants.

To establish credibility in research, participants’ views and the researcher’s representation of their views need to align (Tobin & Begley, 2004).

To increase the credibility of findings, researchers may use data source triangulation, investigator triangulation, peer debriefing, or member checking (Lincoln & Guba, 1985). 

2. Transferability in Qualitative Research

Transferability refers to how generalizable the findings are: whether the findings may be applied to another context, setting, or group (Tobin & Begley, 2004).

Transferability can be enhanced by giving thorough and in-depth descriptions of the research setting, sample, and methods (Nowell et al., 2017). 

3. Dependability in Qualitative Research

Dependability is the extent to which the study could be replicated under similar conditions and the findings would be consistent.

Researchers can establish dependability using methods such as audit trails so readers can see the research process is logical and traceable (Koch, 1994).

4. Confirmability in Qualitative Research

Confirmability is concerned with establishing that there is a clear link between the researcher’s interpretations/ findings and the data.

Researchers can achieve confirmability by demonstrating how conclusions and interpretations were arrived at (Nowell et al., 2017).

This enables readers to understand the reasoning behind the decisions made. 

Audit Trails in Qualitative Research

An audit trail provides evidence of the decisions made by the researcher regarding theory, research design, and data collection, as well as the steps they have chosen to manage, analyze, and report data. 

The researcher must provide a clear rationale to demonstrate how conclusions were reached in their study.

A clear description of the research path must be provided to enable readers to trace through the researcher’s logic (Halpren, 1983).

Researchers should maintain records of the raw data, field notes, transcripts, and a reflective journal in order to provide a clear audit trail. 

Discovery of unexpected data

Open-ended questions in qualitative research mean the researcher can probe an interview topic and enable the participant to elaborate on responses in an unrestricted manner.

This allows unexpected data to emerge, which can lead to further research into that topic. 

The exploratory nature of qualitative research helps generate hypotheses that can be tested quantitatively (Busetto et al., 2020).

Flexibility

Data collection and analysis can be modified and adapted to take the research in a different direction if new ideas or patterns emerge in the data.

This enables researchers to investigate new opportunities while firmly maintaining their research goals. 

Naturalistic settings

The behaviors of participants are recorded in real-world settings. Studies that use real-world settings have high ecological validity since participants behave more authentically. 

Limitations

Time-consuming .

Qualitative research results in large amounts of data which often need to be transcribed and analyzed manually.

Even when software is used, transcription can be inaccurate, and using software for analysis can result in many codes which need to be condensed into themes. 

Subjectivity 

The researcher has an integral role in collecting and interpreting qualitative data. Therefore, the conclusions reached are from their perspective and experience.

Consequently, interpretations of data from another researcher may vary greatly. 

Limited generalizability

The aim of qualitative research is to provide a detailed, contextualized understanding of an aspect of the human experience from a relatively small sample size.

Despite rigorous analysis procedures, conclusions drawn cannot be generalized to the wider population since data may be biased or unrepresentative.

Therefore, results are only applicable to a small group of the population. 

While individual qualitative studies are often limited in their generalizability due to factors such as sample size and context, metasynthesis enables researchers to synthesize findings from multiple studies, potentially leading to more generalizable conclusions.

By integrating findings from studies conducted in diverse settings and with different populations, metasynthesis can provide broader insights into the phenomenon of interest.

Extraneous variables

Qualitative research is often conducted in real-world settings. This may cause results to be unreliable since extraneous variables may affect the data, for example:

• Situational variables : different environmental conditions may influence participants’ behavior in a study. The random variation in factors (such as noise or lighting) may be difficult to control in real-world settings.
• Participant characteristics : this includes any characteristics that may influence how a participant answers/ behaves in a study. This may include a participant’s mood, gender, age, ethnicity, sexual identity, IQ, etc.
• Experimenter effect : experimenter effect refers to how a researcher’s unintentional influence can change the outcome of a study. This occurs when (i) their interactions with participants unintentionally change participants’ behaviors or (ii) due to errors in observation, interpretation, or analysis. 

What sample size should qualitative research be?

The sample size for qualitative studies has been recommended to include a minimum of 12 participants to reach data saturation (Braun, 2013).

Are surveys qualitative or quantitative?

Surveys can be used to gather information from a sample qualitatively or quantitatively. Qualitative surveys use open-ended questions to gather detailed information from a large sample using free text responses.

The use of open-ended questions allows for unrestricted responses where participants use their own words, enabling the collection of more in-depth information than closed-ended questions.

In contrast, quantitative surveys consist of closed-ended questions with multiple-choice answer options. Quantitative surveys are ideal to gather a statistical representation of a population.

What are the ethical considerations of qualitative research?

Before conducting a study, you must think about any risks that could occur and take steps to prevent them. Participant Protection : Researchers must protect participants from physical and mental harm. This means you must not embarrass, frighten, offend, or harm participants. Transparency : Researchers are obligated to clearly communicate how they will collect, store, analyze, use, and share the data. Confidentiality : You need to consider how to maintain the confidentiality and anonymity of participants’ data.

What is triangulation in qualitative research?

Triangulation refers to the use of several approaches in a study to comprehensively understand phenomena. This method helps to increase the validity and credibility of research findings. 

Types of triangulation include method triangulation (using multiple methods to gather data); investigator triangulation (multiple researchers for collecting/ analyzing data), theory triangulation (comparing several theoretical perspectives to explain a phenomenon), and data source triangulation (using data from various times, locations, and people; Carter et al., 2014).

Why is qualitative research important?

Qualitative research allows researchers to describe and explain the social world. The exploratory nature of qualitative research helps to generate hypotheses that can then be tested quantitatively.

In qualitative research, participants are able to express their thoughts, experiences, and feelings without constraint.

Additionally, researchers are able to follow up on participants’ answers in real-time, generating valuable discussion around a topic. This enables researchers to gain a nuanced understanding of phenomena which is difficult to attain using quantitative methods.

What is coding data in qualitative research?

Coding data is a qualitative data analysis strategy in which a section of text is assigned with a label that describes its content.

These labels may be words or phrases which represent important (and recurring) patterns in the data.

This process enables researchers to identify related content across the dataset. Codes can then be used to group similar types of data to generate themes.

What is the difference between qualitative and quantitative research?

Qualitative research involves the collection and analysis of non-numerical data in order to understand experiences and meanings from the participant’s perspective.

This can provide rich, in-depth insights on complicated phenomena. Qualitative data may be collected using interviews, focus groups, or observations.

In contrast, quantitative research involves the collection and analysis of numerical data to measure the frequency, magnitude, or relationships of variables. This can provide objective and reliable evidence that can be generalized to the wider population.

Quantitative data may be collected using closed-ended questionnaires or experiments.

What is trustworthiness in qualitative research?

Trustworthiness is a concept used to assess the quality and rigor of qualitative research. Four criteria are used to assess a study’s trustworthiness: credibility, transferability, dependability, and confirmability. 

Credibility refers to how accurately the results represent the reality and viewpoints of the participants. Transferability refers to whether the findings may be applied to another context, setting, or group.

Dependability is the extent to which the findings are consistent and reliable. Confirmability refers to the objectivity of findings (not influenced by the bias or assumptions of researchers).

What is data saturation in qualitative research?

Data saturation is a methodological principle used to guide the sample size of a qualitative research study.

Data saturation is proposed as a necessary methodological component in qualitative research (Saunders et al., 2018) as it is a vital criterion for discontinuing data collection and/or analysis. 

The intention of data saturation is to find “no new data, no new themes, no new coding, and ability to replicate the study” (Guest et al., 2006). Therefore, enough data has been gathered to make conclusions.

Why is sampling in qualitative research important?

In quantitative research, large sample sizes are used to provide statistically significant quantitative estimates.

This is because quantitative research aims to provide generalizable conclusions that represent populations.

However, the aim of sampling in qualitative research is to gather data that will help the researcher understand the depth, complexity, variation, or context of a phenomenon. The small sample sizes in qualitative studies support the depth of case-oriented analysis.

What is narrative analysis?

Narrative analysis is a qualitative research method used to understand how individuals create stories from their personal experiences.

There is an emphasis on understanding the context in which a narrative is constructed, recognizing the influence of historical, cultural, and social factors on storytelling.

Researchers can use different methods together to explore a research question.

Some narrative researchers focus on the content of what is said, using thematic narrative analysis, while others focus on the structure, such as holistic-form or categorical-form structural narrative analysis. Others focus on how the narrative is produced and performed.

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organisation?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalisability

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

• Labour-intensive

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

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

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

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organisation to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

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

• Prepare and organise your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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How to use and assess qualitative research methods

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

Neurological Research and Practice volume  2 , Article number:  14 ( 2020 ) Cite this article

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

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

What is qualitative research?

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

Why conduct qualitative research?

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

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

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

How to conduct qualitative research?

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

Iterative research process

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

Data collection

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

Document study

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

Observations

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

Semi-structured interviews

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

Focus groups

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

Choosing the “right” method

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

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

Possible combination of data collection methods

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

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

Data analysis

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

From data collection to data analysis

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

How to report qualitative research?

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

How to combine qualitative with quantitative research?

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

Three common mixed methods designs

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

How to assess qualitative research?

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

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

Reflexivity

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

Sampling and saturation

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

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

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

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

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

Member checking

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

Stakeholder involvement

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

How not to assess qualitative research

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

Protocol adherence

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

Sample size

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

Randomisation

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

Interrater reliability, variability and other “objectivity checks”

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

Not being quantitative research

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

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

Availability of data and materials

Not applicable.

Abbreviations

Endovascular treatment

Randomised Controlled Trial

Standard Operating Procedure

Standards for Reporting Qualitative Research

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Qualitative Research : Definition

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

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Qualitative Research: An Overview

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Article Contents

Introduction, when to use qualitative research, how to judge qualitative research, conclusions, authors' roles, conflict of interest.

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Qualitative research methods: when to use them and how to judge them

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K. Hammarberg, M. Kirkman, S. de Lacey, Qualitative research methods: when to use them and how to judge them, Human Reproduction , Volume 31, Issue 3, March 2016, Pages 498–501, https://doi.org/10.1093/humrep/dev334

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In March 2015, an impressive set of guidelines for best practice on how to incorporate psychosocial care in routine infertility care was published by the ESHRE Psychology and Counselling Guideline Development Group ( ESHRE Psychology and Counselling Guideline Development Group, 2015 ). The authors report that the guidelines are based on a comprehensive review of the literature and we congratulate them on their meticulous compilation of evidence into a clinically useful document. However, when we read the methodology section, we were baffled and disappointed to find that evidence from research using qualitative methods was not included in the formulation of the guidelines. Despite stating that ‘qualitative research has significant value to assess the lived experience of infertility and fertility treatment’, the group excluded this body of evidence because qualitative research is ‘not generally hypothesis-driven and not objective/neutral, as the researcher puts him/herself in the position of the participant to understand how the world is from the person's perspective’.

Qualitative and quantitative research methods are often juxtaposed as representing two different world views. In quantitative circles, qualitative research is commonly viewed with suspicion and considered lightweight because it involves small samples which may not be representative of the broader population, it is seen as not objective, and the results are assessed as biased by the researchers' own experiences or opinions. In qualitative circles, quantitative research can be dismissed as over-simplifying individual experience in the cause of generalisation, failing to acknowledge researcher biases and expectations in research design, and requiring guesswork to understand the human meaning of aggregate data.

As social scientists who investigate psychosocial aspects of human reproduction, we use qualitative and quantitative methods, separately or together, depending on the research question. The crucial part is to know when to use what method.

The peer-review process is a pillar of scientific publishing. One of the important roles of reviewers is to assess the scientific rigour of the studies from which authors draw their conclusions. If rigour is lacking, the paper should not be published. As with research using quantitative methods, research using qualitative methods is home to the good, the bad and the ugly. It is essential that reviewers know the difference. Rejection letters are hard to take but more often than not they are based on legitimate critique. However, from time to time it is obvious that the reviewer has little grasp of what constitutes rigour or quality in qualitative research. The first author (K.H.) recently submitted a paper that reported findings from a qualitative study about fertility-related knowledge and information-seeking behaviour among people of reproductive age. In the rejection letter one of the reviewers (not from Human Reproduction ) lamented, ‘Even for a qualitative study, I would expect that some form of confidence interval and paired t-tables analysis, etc. be used to analyse the significance of results'. This comment reveals the reviewer's inappropriate application to qualitative research of criteria relevant only to quantitative research.

In this commentary, we give illustrative examples of questions most appropriately answered using qualitative methods and provide general advice about how to appraise the scientific rigour of qualitative studies. We hope this will help the journal's reviewers and readers appreciate the legitimate place of qualitative research and ensure we do not throw the baby out with the bath water by excluding or rejecting papers simply because they report the results of qualitative studies.

In psychosocial research, ‘quantitative’ research methods are appropriate when ‘factual’ data are required to answer the research question; when general or probability information is sought on opinions, attitudes, views, beliefs or preferences; when variables can be isolated and defined; when variables can be linked to form hypotheses before data collection; and when the question or problem is known, clear and unambiguous. Quantitative methods can reveal, for example, what percentage of the population supports assisted conception, their distribution by age, marital status, residential area and so on, as well as changes from one survey to the next ( Kovacs et al. , 2012 ); the number of donors and donor siblings located by parents of donor-conceived children ( Freeman et al. , 2009 ); and the relationship between the attitude of donor-conceived people to learning of their donor insemination conception and their family ‘type’ (one or two parents, lesbian or heterosexual parents; Beeson et al. , 2011 ).

In contrast, ‘qualitative’ methods are used to answer questions about experience, meaning and perspective, most often from the standpoint of the participant. These data are usually not amenable to counting or measuring. Qualitative research techniques include ‘small-group discussions’ for investigating beliefs, attitudes and concepts of normative behaviour; ‘semi-structured interviews’, to seek views on a focused topic or, with key informants, for background information or an institutional perspective; ‘in-depth interviews’ to understand a condition, experience, or event from a personal perspective; and ‘analysis of texts and documents’, such as government reports, media articles, websites or diaries, to learn about distributed or private knowledge.

Qualitative methods have been used to reveal, for example, potential problems in implementing a proposed trial of elective single embryo transfer, where small-group discussions enabled staff to explain their own resistance, leading to an amended approach ( Porter and Bhattacharya, 2005 ). Small-group discussions among assisted reproductive technology (ART) counsellors were used to investigate how the welfare principle is interpreted and practised by health professionals who must apply it in ART ( de Lacey et al. , 2015 ). When legislative change meant that gamete donors could seek identifying details of people conceived from their gametes, parents needed advice on how best to tell their children. Small-group discussions were convened to ask adolescents (not known to be donor-conceived) to reflect on how they would prefer to be told ( Kirkman et al. , 2007 ).

When a population cannot be identified, such as anonymous sperm donors from the 1980s, a qualitative approach with wide publicity can reach people who do not usually volunteer for research and reveal (for example) their attitudes to proposed legislation to remove anonymity with retrospective effect ( Hammarberg et al. , 2014 ). When researchers invite people to talk about their reflections on experience, they can sometimes learn more than they set out to discover. In describing their responses to proposed legislative change, participants also talked about people conceived as a result of their donations, demonstrating various constructions and expectations of relationships ( Kirkman et al. , 2014 ).

Interviews with parents in lesbian-parented families generated insight into the diverse meanings of the sperm donor in the creation and life of the family ( Wyverkens et al. , 2014 ). Oral and written interviews also revealed the embarrassment and ambivalence surrounding sperm donors evident in participants in donor-assisted conception ( Kirkman, 2004 ). The way in which parents conceptualise unused embryos and why they discard rather than donate was explored and understood via in-depth interviews, showing how and why the meaning of those embryos changed with parenthood ( de Lacey, 2005 ). In-depth interviews were also used to establish the intricate understanding by embryo donors and recipients of the meaning of embryo donation and the families built as a result ( Goedeke et al. , 2015 ).

It is possible to combine quantitative and qualitative methods, although great care should be taken to ensure that the theory behind each method is compatible and that the methods are being used for appropriate reasons. The two methods can be used sequentially (first a quantitative then a qualitative study or vice versa), where the first approach is used to facilitate the design of the second; they can be used in parallel as different approaches to the same question; or a dominant method may be enriched with a small component of an alternative method (such as qualitative interviews ‘nested’ in a large survey). It is important to note that free text in surveys represents qualitative data but does not constitute qualitative research. Qualitative and quantitative methods may be used together for corroboration (hoping for similar outcomes from both methods), elaboration (using qualitative data to explain or interpret quantitative data, or to demonstrate how the quantitative findings apply in particular cases), complementarity (where the qualitative and quantitative results differ but generate complementary insights) or contradiction (where qualitative and quantitative data lead to different conclusions). Each has its advantages and challenges ( Brannen, 2005 ).

Qualitative research is gaining increased momentum in the clinical setting and carries different criteria for evaluating its rigour or quality. Quantitative studies generally involve the systematic collection of data about a phenomenon, using standardized measures and statistical analysis. In contrast, qualitative studies involve the systematic collection, organization, description and interpretation of textual, verbal or visual data. The particular approach taken determines to a certain extent the criteria used for judging the quality of the report. However, research using qualitative methods can be evaluated ( Dixon-Woods et al. , 2006 ; Young et al. , 2014 ) and there are some generic guidelines for assessing qualitative research ( Kitto et al. , 2008 ).

Although the terms ‘reliability’ and ‘validity’ are contentious among qualitative researchers ( Lincoln and Guba, 1985 ) with some preferring ‘verification’, research integrity and robustness are as important in qualitative studies as they are in other forms of research. It is widely accepted that qualitative research should be ethical, important, intelligibly described, and use appropriate and rigorous methods ( Cohen and Crabtree, 2008 ). In research investigating data that can be counted or measured, replicability is essential. When other kinds of data are gathered in order to answer questions of personal or social meaning, we need to be able to capture real-life experiences, which cannot be identical from one person to the next. Furthermore, meaning is culturally determined and subject to evolutionary change. The way of explaining a phenomenon—such as what it means to use donated gametes—will vary, for example, according to the cultural significance of ‘blood’ or genes, interpretations of marital infidelity and religious constructs of sexual relationships and families. Culture may apply to a country, a community, or other actual or virtual group, and a person may be engaged at various levels of culture. In identifying meaning for members of a particular group, consistency may indeed be found from one research project to another. However, individuals within a cultural group may present different experiences and perceptions or transgress cultural expectations. That does not make them ‘wrong’ or invalidate the research. Rather, it offers insight into diversity and adds a piece to the puzzle to which other researchers also contribute.

In qualitative research the objective stance is obsolete, the researcher is the instrument, and ‘subjects’ become ‘participants’ who may contribute to data interpretation and analysis ( Denzin and Lincoln, 1998 ). Qualitative researchers defend the integrity of their work by different means: trustworthiness, credibility, applicability and consistency are the evaluative criteria ( Leininger, 1994 ).

Trustworthiness

A report of a qualitative study should contain the same robust procedural description as any other study. The purpose of the research, how it was conducted, procedural decisions, and details of data generation and management should be transparent and explicit. A reviewer should be able to follow the progression of events and decisions and understand their logic because there is adequate description, explanation and justification of the methodology and methods ( Kitto et al. , 2008 )

Credibility

Credibility is the criterion for evaluating the truth value or internal validity of qualitative research. A qualitative study is credible when its results, presented with adequate descriptions of context, are recognizable to people who share the experience and those who care for or treat them. As the instrument in qualitative research, the researcher defends its credibility through practices such as reflexivity (reflection on the influence of the researcher on the research), triangulation (where appropriate, answering the research question in several ways, such as through interviews, observation and documentary analysis) and substantial description of the interpretation process; verbatim quotations from the data are supplied to illustrate and support their interpretations ( Sandelowski, 1986 ). Where excerpts of data and interpretations are incongruent, the credibility of the study is in doubt.

Applicability

Applicability, or transferability of the research findings, is the criterion for evaluating external validity. A study is considered to meet the criterion of applicability when its findings can fit into contexts outside the study situation and when clinicians and researchers view the findings as meaningful and applicable in their own experiences.

Larger sample sizes do not produce greater applicability. Depth may be sacrificed to breadth or there may be too much data for adequate analysis. Sample sizes in qualitative research are typically small. The term ‘saturation’ is often used in reference to decisions about sample size in research using qualitative methods. Emerging from grounded theory, where filling theoretical categories is considered essential to the robustness of the developing theory, data saturation has been expanded to describe a situation where data tend towards repetition or where data cease to offer new directions and raise new questions ( Charmaz, 2005 ). However, the legitimacy of saturation as a generic marker of sampling adequacy has been questioned ( O'Reilly and Parker, 2013 ). Caution must be exercised to ensure that a commitment to saturation does not assume an ‘essence’ of an experience in which limited diversity is anticipated; each account is likely to be subtly different and each ‘sample’ will contribute to knowledge without telling the whole story. Increasingly, it is expected that researchers will report the kind of saturation they have applied and their criteria for recognising its achievement; an assessor will need to judge whether the choice is appropriate and consistent with the theoretical context within which the research has been conducted.

Sampling strategies are usually purposive, convenient, theoretical or snowballed. Maximum variation sampling may be used to seek representation of diverse perspectives on the topic. Homogeneous sampling may be used to recruit a group of participants with specified criteria. The threat of bias is irrelevant; participants are recruited and selected specifically because they can illuminate the phenomenon being studied. Rather than being predetermined by statistical power analysis, qualitative study samples are dependent on the nature of the data, the availability of participants and where those data take the investigator. Multiple data collections may also take place to obtain maximum insight into sensitive topics. For instance, the question of how decisions are made for embryo disposition may involve sampling within the patient group as well as from scientists, clinicians, counsellors and clinic administrators.

Consistency

Consistency, or dependability of the results, is the criterion for assessing reliability. This does not mean that the same result would necessarily be found in other contexts but that, given the same data, other researchers would find similar patterns. Researchers often seek maximum variation in the experience of a phenomenon, not only to illuminate it but also to discourage fulfilment of limited researcher expectations (for example, negative cases or instances that do not fit the emerging interpretation or theory should be actively sought and explored). Qualitative researchers sometimes describe the processes by which verification of the theoretical findings by another team member takes place ( Morse and Richards, 2002 ).

Research that uses qualitative methods is not, as it seems sometimes to be represented, the easy option, nor is it a collation of anecdotes. It usually involves a complex theoretical or philosophical framework. Rigorous analysis is conducted without the aid of straightforward mathematical rules. Researchers must demonstrate the validity of their analysis and conclusions, resulting in longer papers and occasional frustration with the word limits of appropriate journals. Nevertheless, we need the different kinds of evidence that is generated by qualitative methods. The experience of health, illness and medical intervention cannot always be counted and measured; researchers need to understand what they mean to individuals and groups. Knowledge gained from qualitative research methods can inform clinical practice, indicate how to support people living with chronic conditions and contribute to community education and awareness about people who are (for example) experiencing infertility or using assisted conception.

Each author drafted a section of the manuscript and the manuscript as a whole was reviewed and revised by all authors in consultation.

No external funding was either sought or obtained for this study.

The authors have no conflicts of interest to declare.

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What is qualitative research?

Quantitative vs qualitative research, approaches to qualitative research, qualitative data types and category types, disadvantages of qualitative research, how to use qualitative research to your business’s advantage, 6 steps to conducting good qualitative research, how do you arrange qualitative data for analysis, qualitative data analysis, how qualtrics products can enhance & simplify the qualitative research process, try qualtrics for free, your ultimate guide to qualitative research (with methods and examples).

31 min read You may be already using qualitative research and want to check your understanding, or you may be starting from the beginning. Learn about qualitative research methods and how you can best use them for maximum effect.

Qualitative research is a research method that collects non-numerical data. Typically, it goes beyond the information that quantitative research provides (which we will cover below) because it is used to gain an understanding of underlying reasons, opinions, and motivations.

Qualitative research methods focus on the thoughts, feelings, reasons, motivations, and values of a participant, to understand why people act in the way they do .

In this way, qualitative research can be described as naturalistic research, looking at naturally-occurring social events within natural settings. So, qualitative researchers would describe their part in social research as the ‘vehicle’ for collecting the qualitative research data.

Qualitative researchers discovered this by looking at primary and secondary sources where data is represented in non-numerical form. This can include collecting qualitative research data types like quotes, symbols, images, and written testimonials.

These data types tell qualitative researchers subjective information. While these aren’t facts in themselves, conclusions can be interpreted out of qualitative that can help to provide valuable context.

Because of this, qualitative research is typically viewed as explanatory in nature and is often used in social research, as this gives a window into the behavior and actions of people.

It can be a good research approach for health services research or clinical research projects.

Free eBook: The qualitative research design handbook

In order to compare qualitative and quantitative research methods, let’s explore what quantitative research is first, before exploring how it differs from qualitative research.

Quantitative research

Quantitative research is the research method of collecting quantitative research data – data that can be converted into numbers or numerical data, which can be easily quantified, compared, and analyzed .

Quantitative research methods deal with primary and secondary sources where data is represented in numerical form. This can include closed-question poll results, statistics, and census information or demographic data.

Quantitative research data tends to be used when researchers are interested in understanding a particular moment in time and examining data sets over time to find trends and patterns.

The difference between quantitative and qualitative research methodology

While qualitative research is defined as data that supplies non-numerical information, quantitative research focuses on numerical data.

In general, if you’re interested in measuring something or testing a hypothesis, use quantitative research methods. If you want to explore ideas, thoughts, and meanings, use qualitative research methods.

Where both qualitative and quantitative methods are not used, qualitative researchers will find that using one without the other leaves you with missing answers.

For example, if a retail company wants to understand whether a new product line of shoes will perform well in the target market:

• Qualitative research methods could be used with a sample of target customers, which would provide subjective reasons why they’d be likely to purchase or not purchase the shoes, while
• Quantitative research methods into the historical customer sales information on shoe-related products would provide insights into the sales performance, and likely future performance of the new product range.

There are five approaches to qualitative research methods:

• Grounded theory: Grounded theory relates to where qualitative researchers come to a stronger hypothesis through induction, all throughout the process of collecting qualitative research data and forming connections. After an initial question to get started, qualitative researchers delve into information that is grouped into ideas or codes, which grow and develop into larger categories, as the qualitative research goes on. At the end of the qualitative research, the researcher may have a completely different hypothesis, based on evidence and inquiry, as well as the initial question.
• Ethnographic research : Ethnographic research is where researchers embed themselves into the environment of the participant or group in order to understand the culture and context of activities and behavior. This is dependent on the involvement of the researcher, and can be subject to researcher interpretation bias and participant observer bias . However, it remains a great way to allow researchers to experience a different ‘world’.
• Action research: With the action research process, both researchers and participants work together to make a change. This can be through taking action, researching and reflecting on the outcomes. Through collaboration, the collective comes to a result, though the way both groups interact and how they affect each other gives insights into their critical thinking skills.
• Phenomenological research: Researchers seek to understand the meaning of an event or behavior phenomenon by describing and interpreting participant’s life experiences. This qualitative research process understands that people create their own structured reality (‘the social construction of reality’), based on their past experiences. So, by viewing the way people intentionally live their lives, we’re able to see the experiential meaning behind why they live as they do.
• Narrative research: Narrative research, or narrative inquiry, is where researchers examine the way stories are told by participants, and how they explain their experiences, as a way of explaining the meaning behind their life choices and events. This qualitative research can arise from using journals, conversational stories, autobiographies or letters, as a few narrative research examples. The narrative is subjective to the participant, so we’re able to understand their views from what they’ve documented/spoken.

Qualitative research methods can use structured research instruments for data collection, like:

Surveys for individual views

A survey is a simple-to-create and easy-to-distribute qualitative research method, which helps gather information from large groups of participants quickly. Traditionally, paper-based surveys can now be made online, so costs can stay quite low.

Qualitative research questions tend to be open questions that ask for more information and provide a text box to allow for unconstrained comments.

Examples include:

• Asking participants to keep a written or a video diary for a period of time to document their feelings and thoughts
• In-Home-Usage tests: Buyers use your product for a period of time and report their experience

Surveys for group consensus (Delphi survey)

A Delphi survey may be used as a way to bring together participants and gain a consensus view over several rounds of questions. It differs from traditional surveys where results go to the researcher only. Instead, results go to participants as well, so they can reflect and consider all responses before another round of questions are submitted.

This can be useful to do as it can help researchers see what variance is among the group of participants and see the process of how consensus was reached.

• Asking participants to act as a fake jury for a trial and revealing parts of the case over several rounds to see how opinions change. At the end, the fake jury must make a unanimous decision about the defendant on trial.
• Asking participants to comment on the versions of a product being developed, as the changes are made and their feedback is taken onboard. At the end, participants must decide whether the product is ready to launch.

Semi-structured interviews

Interviews are a great way to connect with participants, though they require time from the research team to set up and conduct, especially if they’re done face-to-face.

Researchers may also have issues connecting with participants in different geographical regions. The researcher uses a set of predefined open-ended questions, though more ad-hoc questions can be asked depending on participant answers.

• Conducting a phone interview with participants to run through their feedback on a product. During the conversation, researchers can go ‘off-script’ and ask more probing questions for clarification or build on the insights.

Focus groups

Participants are brought together into a group, where a particular topic is discussed. It is researcher-led and usually occurs in-person in a mutually accessible location, to allow for easy communication between participants in focus groups.

In focus groups , the researcher uses a set of predefined open-ended questions, though more ad-hoc questions can be asked depending on participant answers.

• Asking participants to do UX tests, which are interface usability tests to show how easily users can complete certain tasks

Direct observation

This is a form of ethnographic research where researchers will observe participants’ behavior in a naturalistic environment. This can be great for understanding the actions in the culture and context of a participant’s setting.

This qualitative research method is prone to researcher bias as it is the researcher that must interpret the actions and reactions of participants. Their findings can be impacted by their own beliefs, values, and inferences.

• Embedding yourself in the location of your buyers to understand how a product would perform against the values and norms of that society

One-to-one interviews

One-to-one interviews are one of the most commonly used data collection instruments for qualitative research questions, mainly because of their approach. The interviewer or the researcher collects data directly from the interviewee one-to-one. The interview method may be informal and unstructured – conversational. The open-ended questions are mostly asked spontaneously, with the interviewer letting the interview flow dictate the questions to be asked.

Record keeping

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

Process of observation

In this data collection method, the researcher immerses themselves in the setting where their respondents are, keeps a keen eye on the participants, and takes notes. This is known as the process of observation.

Besides taking notes, other documentation methods, such as video and audio recording, photography, and similar methods, can be used.

Longitudinal studies

This data collection method is repeatedly performed on the same data source over an extended period. It is an observational research method that goes on for a few years and sometimes can go on for even decades. Such data collection methods aim to find correlations through empirical studies of subjects with common traits.

Case studies

This method gathers data from an in-depth analysis of case studies. The versatility of this method is demonstrated in how this method can be used to analyze both simple and complex subjects. The strength of this method is how judiciously it uses a combination of one or more qualitative methods to draw inferences.

What is data coding in qualitative research?

Data coding in qualitative research involves a systematic process of organizing and interpreting collected data. This process is crucial for identifying patterns and themes within complex data sets. Here’s how it works:

• Data Collection : Initially, researchers gather data through various methods such as interviews, focus groups, and observations. The raw data often includes transcriptions of conversations, notes, or multimedia recordings.
• Initial Coding : Once data is collected, researchers begin the initial coding phase. They break down the data into manageable segments and assign codes—short phrases or words that summarize each piece of information. This step is often referred to as open coding.
• Categorization : Next, researchers categorize the codes into broader themes or concepts. This helps in organizing the data and identifying major patterns. These themes can be linked to theoretical frameworks or emerging patterns from the data itself.
• Review and Refinement : The coding process is iterative, meaning researchers continuously review and refine their codes and categories. They may merge similar codes, adjust categories, or add new codes as deeper understanding develops.
• Thematic Analysis : Finally, researchers perform a thematic analysis to draw meaningful conclusions from the data. They explore how the identified themes relate to the research questions and objectives, providing insights and answering key queries.

Methods and tools for coding

• Manual Coding : Involves using highlighters, sticky notes, and physical organization methods.
• Software Tools : Programs like NVivo, ATLAS.ti, and MAXQDA streamline the coding process, allowing researchers to handle large volumes of data efficiently.

Data coding transforms raw qualitative data into structured information, making it essential for deriving actionable insights and achieving research objectives.

Qualitative research methods often deliver information in the following qualitative research data types:

• Written testimonials

Through contextual analysis of the information, researchers can assign participants to category types:

• Social class
• Political alignment
• Most likely to purchase a product
• Their preferred training learning style

Why is qualitative data important?

Qualitative data plays a pivotal role in understanding the nuances of human behavior and emotions. Unlike quantitative data, which deals with numbers and hard statistics, qualitative data captures the vivid tapestry of opinions, experiences, and motivations.

Understanding emotions and perceptions

One primary reason qualitative data is crucial is its ability to reveal the emotions and perceptions of individuals. This type of data goes beyond mere numbers to provide insights into how people feel and think. For example, understanding consumer sentiments can help businesses tailor their products and services to meet customer needs more effectively.

Rich context and insights

Qualitative analysis dives deep into textual data, uncovering rich context and subtle patterns that might be missed with quantitative methods alone. This kind of data provides comprehensive insights by examining the intricate details of user feedback, interviews, or focus group discussions. For instance, companies like IBM and Nielsen use qualitative data to gain a deeper understanding of market trends and consumer preferences.

Forming research parameters

Researchers use qualitative data to establish parameters for broader studies. By identifying recurring themes and traits, they can design more targeted and effective surveys and experiments. This initial qualitative phase is essential in ensuring that subsequent quantitative research is grounded in real-world observations.

Solving complex problems

In market research, qualitative data is invaluable for solving complex problems. It enables researchers to decode the language of their consumers, identifying pain points and areas for improvement. Brands like Coca-Cola and P&G frequently rely on qualitative insights to refine their marketing strategies and enhance customer satisfaction.

In sum, qualitative data is essential for its ability to capture the depth and complexity of human experiences. It provides the contextual groundwork needed to make informed decisions, understand consumer behavior, and ultimately drive successful outcomes in various fields.

How do you organize qualitative data?

Organizing qualitative data is crucial to extract meaningful insights efficiently. Here’s a step-by-step guide to help you streamline the process:

1. Align with research objectives

Start by revisiting your research objectives. Clarifying the core questions you aim to answer can guide you in structuring your data. Create a table or spreadsheet where these objectives are clearly laid out.

2. Categorize the data

Sort your data based on themes or categories relevant to your research objectives. Use different coding techniques to label each piece of information. Tools like NVivo or Atlas.ti can help in coding and categorizing qualitative data effectively.

3. Use visual aids

Visualizing data can make patterns more apparent. Consider using charts, graphs, or mind maps to represent your categorized data. Applications like Microsoft Excel or Tableau are excellent for creating visual representations.

4. Develop a index system

Create an index system to keep track of where each piece of information fits within your categories. This can be as simple as a detailed index in a Word document or a more complex system within your data analysis software.

5. Summary tables

Develop summary tables that distill large amounts of information into key points. These tables should reflect the core themes and subthemes you’ve identified, making it easier to draw conclusions.

6. Avoid unnecessary data

Don’t fall into the trap of hoarding unorganized or irrelevant information. Regularly review your data to ensure it aligns with your research goals. Trim any redundant or extraneous data to maintain clarity and focus.

By following these steps, you can turn your raw qualitative data into an organized, insightful resource that directly supports your research objectives.

Advantages of qualitative research

• Useful for complex situations: Qualitative research on its own is great when dealing with complex issues, however, providing background context using quantitative facts can give a richer and wider understanding of a topic. In these cases, quantitative research may not be enough.
• A window into the ‘why’: Qualitative research can give you a window into the deeper meaning behind a participant’s answer. It can help you uncover the larger ‘why’ that can’t always be seen by analyzing numerical data.
• Can help improve customer experiences: In service industries where customers are crucial, like in private health services, gaining information about a customer’s experience through health research studies can indicate areas where services can be improved.
• You need to ask the right question: Doing qualitative research may require you to consider what the right question is to uncover the underlying thinking behind a behavior. This may need probing questions to go further, which may suit a focus group or face-to-face interview setting better.
• Results are interpreted: As qualitative research data is written, spoken, and often nuanced, interpreting the data results can be difficult as they come in non-numerical formats. This might make it harder to know if you can accept or reject your hypothesis.
• More bias: There are lower levels of control to qualitative research methods, as they can be subject to biases like confirmation bias, researcher bias, and observation bias. This can have a knock-on effect on the validity and truthfulness of the qualitative research data results.

Qualitative methods help improve your products and marketing in many different ways:

• Understand the emotional connections to your brand
• Identify obstacles to purchase
• Uncover doubts and confusion about your messaging
• Find missing product features
• Improve the usability of your website, app, or chatbot experience
• Learn about how consumers talk about your product
• See how buyers compare your brand to others in the competitive set
• Learn how an organization’s employees evaluate and select vendors

Businesses can benefit from qualitative research by using it to understand the meaning behind data types. There are several steps to this:

• Define your problem or interest area: What do you observe is happening and is it frequent? Identify the data type/s you’re observing.
• Create a hypothesis: Ask yourself what could be the causes for the situation with those qualitative research data types.
• Plan your qualitative research: Use structured qualitative research instruments like surveys, focus groups, or interviews to ask questions that test your hypothesis.
• Data Collection: Collect qualitative research data and understand what your data types are telling you. Once data is collected on different types over long time periods, you can analyze it and give insights into changing attitudes and language patterns.
• Data analysis: Does your information support your hypothesis? (You may need to redo the qualitative research with other variables to see if the results improve)
• Effectively present the qualitative research data: Communicate the results in a clear and concise way to help other people understand the findings.

Transcribing and organizing your qualitative data is crucial for robust analysis. Follow these steps to ensure your data is systematically arranged and ready for interpretation.

1. Transcribe your sata

Converting your gathered information into a textual format is the first step. This involves:

• Listening to audio recordings: Jot down every nuance and detail.
• Reading through notes: Ensure all handwritten or typed notes are coherent and complete.

2. Choose a suitable format

Once transcribed, your data needs to be formatted for ease of analysis. You have several options:

• Spreadsheets: Tools like Microsoft Excel or Google Sheets allow for easy sorting and categorization.
• Specialized software: Consider using computer-assisted qualitative data analysis software (CAQDAS) such as NVivo, ATLAS.ti, or MAXQDA to handle large volumes of data efficiently.

3. Organize by themes

Begin to identify patterns or themes in your data. This method, often called coding, involves:

• Highlighting Key Points: Use different colors or symbols to mark recurring ideas.
• Creating Categories: Group similar themes together to form a coherent structure.

4. Label and store

Finally, label and store your data meticulously to ensure easy retrieval and reference. Label:

• Files and Documents: With clear titles and dates.
• Sections within Documents: With headings and subheadings to distinguish different themes and patterns.

By following these systematic steps, you can convert raw qualitative data into a structured format ready for comprehensive analysis.

Evaluating qualitative research can be tough when there are several analytics platforms to manage and lots of subjective data sources to compare.

Qualtrics provides a number of qualitative research analysis tools, like Text iQ, powered by Qualtrics iQ , provides powerful machine learning and native language processing to help you discover patterns and trends in text.

This also provides you with:

• Sentiment analysis — a technique to help identify the underlying sentiment (say positive, neutral, and/or negative) in qualitative research text responses
• Topic detection/categorisation — this technique is the grouping or bucketing of similar themes that can are relevant for the business & the industry (e.g., ‘Food quality,’ ‘Staff efficiency,’ or ‘Product availability’)

Validating your qualitative data

Validating data is one of the crucial steps of qualitative data analysis for successful research. Since data is quintessential for research, ensuring that the data is not flawed is imperative. Please note that data validation is not just one step in this analysis; it is a recurring step that needs to be followed throughout the research process.

There are two sides to validating data:

• Ensuring that the methods used are designed to produce accurate data.
• The extent to which the methods consistently produce accurate data over time.

Incorporating these validation steps ensures that the qualitative data you gather through tools like Text iQ is both reliable and accurate, providing a solid foundation for your research conclusions.

What are the approaches to qualitative data analysis?

Qualitative data analysis can be tackled using two main approaches: the deductive approach and the inductive approach. Each method offers unique benefits and caters to different research needs.

Deductive approach

The deductive approach involves analyzing qualitative data within a pre-established framework. Typically, researchers use predefined questions to guide their analysis, making it a structured and straightforward process. This method is particularly useful when researchers have a clear hypothesis or a reasonable expectation of the data they will gather.

Advantages :

• Quick and efficient
• Suitable for studies with known variables

Disadvantages :

• Limited flexibility
• May not uncover unexpected insights

Inductive approach

Contrastingly, the inductive approach is characterized by its flexibility and open-ended nature. Rather than starting with a set structure, researchers use this approach to let patterns and themes emerge naturally from the data. This method is time-consuming but thorough, making it ideal for exploratory research where little is known about the phenomenon under study.

• High flexibility
• Uncovers insights that may not be immediately obvious
• Time-intensive
• Requires rigorous interpretation skills

Both approaches have their merits and can be chosen based on the objectives of your research. By understanding the key differences between the deductive and inductive methods, you can select the approach that best suits your analytical needs.

What is the inductive approach to qualitative data analysis?

The inductive approach to qualitative data analysis is a flexible and explorative method. Unlike approaches that follow a fixed framework, the inductive approach builds theories and patterns from the data itself. Here’s a closer look:

• No fixed framework: This method does not rely on predetermined structures or strict guidelines. Instead, it allows patterns and themes to naturally emerge from the data.
• Exploratory nature: Often used when little is known about the research phenomenon, this approach helps researchers unearth new insights without preconceptions.
• Time-consuming but thorough: Due to its comprehensive nature, the inductive approach can be more time-intensive. Researchers meticulously examine data to uncover meaningful connections and build a deep understanding of the subject matter.
• Flexible and adaptive: This approach is particularly useful in dynamic research environments where the subject matter is complex or not well understood.

In essence, the inductive approach is about letting the data lead the research, allowing for the discovery of unexpected insights and a more nuanced understanding of the studied phenomena.

The deductive approach to qualitative data analysis is a method where researchers begin with a predefined structure or framework to guide their examination of data. Essentially, this means they start with specific questions or hypotheses in mind, which helps in directing the analysis process.

Key elements of the deductive approach:

• Researchers have a clear idea of what they are looking for based on prior knowledge or theories.
• This structured framework acts as a guide throughout the analysis.
• Specific questions are developed beforehand.
• These questions help in filtering and categorizing the data effectively.
• The deductive method is typically faster and more straightforward.
• It is particularly useful when researchers anticipate certain types of responses or patterns from their sample population.

In summary, the deductive approach involves using existing theories and structured queries to systematically analyze qualitative data, making the process efficient and focused.

How to conclude the qualitative data analysis process

Concluding your qualitative data analysis involves presenting your findings in a structured report that stakeholders can readily understand and utilize.

Start by describing your methodology . Detail the specific methods you employed during your research, including how you gathered and analyzed data. This helps readers appreciate the rigor of your process.

Next, highlight both the strengths and limitations of your study. Discuss what worked well and areas that posed challenges, providing a balanced view that showcases the robustness of your research while acknowledging potential shortcomings.

Following this, present your key findings and insights . Summarize the main conclusions drawn from your data, ensuring clarity and conciseness. Use bullet points or numbered lists to enhance readability where appropriate.

Moreover, offer suggestions or inferences based on your findings. Identify actionable recommendations or indicate future research areas that emerged from your study.

Finally, emphasize the importance of the synergy between analytics and reporting . Analytics uncover valuable insights, but it’s the reporting that effectively communicates these insights to stakeholders, enabling informed decision-making.

Even in today’s data-obsessed marketplace, qualitative data is valuable – maybe even more so because it helps you establish an authentic human connection to your customers. If qualitative research doesn’t play a role to inform your product and marketing strategy, your decisions aren’t as effective as they could be.

The Qualtrics XM system gives you an all-in-one, integrated solution to help you all the way through conducting qualitative research. From survey creation and data collection to textual analysis and data reporting, it can help all your internal teams gain insights from your subjective and categorical data.

Qualitative methods are catered through templates or advanced survey designs. While you can manually collect data and conduct data analysis in a spreadsheet program, this solution helps you automate the process of qualitative research, saving you time and administration work.

Using computational techniques helps you to avoid human errors, and participant results come in are already incorporated into the analysis in real-time.

Our key tools, Text IQ™ and Driver IQ™ make analyzing subjective and categorical data easy and simple. Choose to highlight key findings based on topic, sentiment, or frequency. The choice is yours.

Some examples of your workspace in action, using drag and drop to create fast data visualizations quickly:

Related resources

Market intelligence 10 min read, marketing insights 11 min read, ethnographic research 11 min read, qualitative vs quantitative research 13 min read, qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, request demo.

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Qualitative Research

What is qualitative research.

Qualitative research is the methodology researchers use to gain deep contextual understandings of users via non-numerical means and direct observations. Researchers focus on smaller user samples—e.g., in interviews—to reveal data such as user attitudes, behaviors and hidden factors: insights which guide better designs.

“ There are also unknown unknowns, things we don’t know we don’t know.” — Donald Rumsfeld, Former U.S. Secretary of Defense

• Transcript loading…

See how you can use qualitative research to expose hidden truths about users and iteratively shape better products.

Qualitative Research Focuses on the “Why”

Qualitative research is a subset of user experience (UX) research and user research . By doing qualitative research, you aim to gain narrowly focused but rich information about why users feel and think the ways they do. Unlike its more statistics-oriented “counterpart”, quantitative research , qualitative research can help expose hidden truths about your users’ motivations, hopes, needs, pain points and more to help you keep your project’s focus on track throughout development. UX design professionals do qualitative research typically from early on in projects because—since the insights they reveal can alter product development dramatically—they can prevent costly design errors from arising later. Compare and contrast qualitative with quantitative research here:

Qualitative research

Quantitative Research

You Aim to Determine

The “why” – to get behind how users approach their problems in their world

The “what”, “where” & “when” of the users’ needs & problems – to help keep your project’s focus on track during development

Loosely structured (e.g., contextual inquiries) – to learn why users behave how they do & explore their opinions

Highly structured (e.g., surveys) – to gather data about what users do & find patterns in large user groups

Number of Representative Users

Often around 5

Ideally 30+

Level of Contact with Users

More direct & less remote (e.g., usability testing to examine users’ stress levels when they use your design)

Less direct & more remote (e.g., analytics)

Statistically

You need to take great care with handling non-numerical data (e.g., opinions), as your own opinions might influence findings

Reliable – given enough test users

Regarding care with opinions, it’s easy to be subjective about qualitative data, which isn’t as comprehensively analyzable as quantitative data. That’s why design teams also apply quantitative research methods, to reinforce the “why” with the “what”.

Qualitative Research Methods You Can Use to Get Behind Your Users

You have a choice of many methods to help gain the clearest insights into your users’ world – which you might want to complement with quantitative research methods. In iterative processes such as user-centered design , you/your design team would use quantitative research to spot design problems, discover the reasons for these with qualitative research, make changes and then test your improved design on users again. The best method/s to pick will depend on the stage of your project and your objectives. Here are some:

Diary studies – You ask users to document their activities, interactions, etc. over a defined period. This empowers users to deliver context-rich information. Although such studies can be subjective—since users will inevitably be influenced by in-the-moment human issues and their emotions—they’re helpful tools to access generally authentic information.

Structured – You ask users specific questions and analyze their responses with other users’.

Semi-structured – You have a more free-flowing conversation with users, but still follow a prepared script loosely.

Ethnographic – You interview users in their own environment to appreciate how they perform tasks and view aspects of tasks.

Usability testing

Moderated – In-person testing in, e.g., a lab.

Unmoderated – Users complete tests remotely: e.g., through a video call.

Guerrilla – “Down-the-hall”/“down-and-dirty” testing on a small group of random users or colleagues.

User observation – You watch users get to grips with your design and note their actions, words and reactions as they attempt to perform tasks.

Qualitative research can be more or less structured depending on the method.

Qualitative Research – How to Get Reliable Results

Some helpful points to remember are:

Participants – Select a number of test users carefully (typically around 5). Observe the finer points such as body language. Remember the difference between what they do and what they say they do.

Moderated vs. unmoderated – You can obtain the richest data from moderated studies, but these can involve considerable time and practice. You can usually conduct unmoderated studies more quickly and cheaply, but you should plan these carefully to ensure instructions are clear, etc.

Types of questions – You’ll learn far more by asking open-ended questions. Avoid leading users’ answers – ask about their experience during, say, the “search for deals” process rather than how easy it was. Try to frame questions so users respond honestly: i.e., so they don’t withhold grievances about their experience because they don’t want to seem impolite. Distorted feedback may also arise in guerrilla testing, as test users may be reluctant to sound negative or to discuss fine details if they lack time.

Location – Think how where users are might affect their performance and responses. If, for example, users’ tasks involve running or traveling on a train, select the appropriate method (e.g., diary studies for them to record aspects of their experience in the environment of a train carriage and the many factors impacting it).

Overall, no single research method can help you answer all your questions. Nevertheless, The Nielsen Norman Group advise that if you only conduct one kind of user research, you should pick qualitative usability testing, since a small sample size can yield many cost- and project-saving insights. Always treat users and their data ethically. Finally, remember the importance of complementing qualitative methods with quantitative ones: You gain insights from the former; you test those using the latter.

Learn More about Qualitative Research

Take our course on User Research to see how to get the most from qualitative research.

Read about the numerous considerations for qualitative research in this in-depth piece.

This blog discusses the importance of qualitative research , with tips.

Explore additional insights into qualitative research here .

Answer a Short Quiz to Earn a Gift

What is the primary focus of qualitative research in user experience?

• To determine statistical significance of user behavior
• To explore user behaviors and motivations in-depth
• To quantify user interaction across multiple platforms

How many participants typically participate in qualitative research studies?

• About 5 to allow in-depth exploration
• Between 30 and 50 for moderate generalization
• Over 100 to guarantee statistical reliability

Which method do researchers often use in qualitative research to understand user experiences in their natural environment?

• Ethnographic interviews
• Laboratory experiments
• Online surveys

What characterizes the analysis of data in qualitative research?

• Simple tabulation of numeric responses
• Statistical analysis of large data sets
• Thematic analysis of detailed descriptions

What is a common challenge researchers face when they conduct qualitative research?

• The ability to obtain a large enough sample size for statistical analysis.
• The ability to remain objective and avoid bias in data interpretation.
• The ability to use advanced statistical tools to analyze data.

Better luck next time!

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Literature on Qualitative Research

Here’s the entire UX literature on Qualitative Research by the Interaction Design Foundation, collated in one place:

Learn more about Qualitative Research

Take a deep dive into Qualitative Research with our course User Research – Methods and Best Practices .

How do you plan to design a product or service that your users will love , if you don't know what they want in the first place? As a user experience designer, you shouldn't leave it to chance to design something outstanding; you should make the effort to understand your users and build on that knowledge from the outset. User research is the way to do this, and it can therefore be thought of as the largest part of user experience design .

In fact, user research is often the first step of a UX design process—after all, you cannot begin to design a product or service without first understanding what your users want! As you gain the skills required, and learn about the best practices in user research, you’ll get first-hand knowledge of your users and be able to design the optimal product—one that’s truly relevant for your users and, subsequently, outperforms your competitors’ .

This course will give you insights into the most essential qualitative research methods around and will teach you how to put them into practice in your design work. You’ll also have the opportunity to embark on three practical projects where you can apply what you’ve learned to carry out user research in the real world . You’ll learn details about how to plan user research projects and fit them into your own work processes in a way that maximizes the impact your research can have on your designs. On top of that, you’ll gain practice with different methods that will help you analyze the results of your research and communicate your findings to your clients and stakeholders—workshops, user journeys and personas, just to name a few!

By the end of the course, you’ll have not only a Course Certificate but also three case studies to add to your portfolio. And remember, a portfolio with engaging case studies is invaluable if you are looking to break into a career in UX design or user research!

We believe you should learn from the best, so we’ve gathered a team of experts to help teach this course alongside our own course instructors. That means you’ll meet a new instructor in each of the lessons on research methods who is an expert in their field—we hope you enjoy what they have in store for you!

All open-source articles on Qualitative Research

How to do a thematic analysis of user interviews.

• 1.3k shares
• 4 years ago

How to Visualize Your Qualitative User Research Results for Maximum Impact

• 3 years ago

Creating Personas from User Research Results

Best Practices for Qualitative User Research

Card Sorting

Contextual Interviews and How to Handle Them

Understand the User’s Perspective through Research for Mobile UX

Ethnography

7 simple ways to get better results from ethnographic research.

Semi-structured qualitative studies

Pros and cons of conducting user interviews.

Workshops to Establish Empathy and Understanding from User Research Results

How to Moderate User Interviews

Question Everything

Adding Quality to Your Design Research with an SSQS Checklist

• 8 years ago

Cognitive Maps in UX | IxDF

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Qualitative research: methods and examples

Last updated

13 April 2023

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Qualitative research involves gathering and evaluating non-numerical information to comprehend concepts, perspectives, and experiences. It’s also helpful for obtaining in-depth insights into a certain subject or generating new research ideas. 

As a result, qualitative research is practical if you want to try anything new or produce new ideas.

There are various ways you can conduct qualitative research. In this article, you'll learn more about qualitative research methodologies, including when you should use them.

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• What is qualitative research?

Qualitative research is a broad term describing various research types that rely on asking open-ended questions. Qualitative research investigates “how” or “why” certain phenomena occur. It is about discovering the inherent nature of something.

The primary objective of qualitative research is to understand an individual's ideas, points of view, and feelings. In this way, collecting in-depth knowledge of a specific topic is possible. Knowing your audience's feelings about a particular subject is important for making reasonable research conclusions.

Unlike quantitative research , this approach does not involve collecting numerical, objective data for statistical analysis. Qualitative research is used extensively in education, sociology, health science, history, and anthropology.

• Types of qualitative research methodology

Typically, qualitative research aims at uncovering the attitudes and behavior of the target audience concerning a specific topic. For example,  “How would you describe your experience as a new Dovetail user?”

Some of the methods for conducting qualitative analysis include:

Focus groups

Hosting a focus group is a popular qualitative research method. It involves obtaining qualitative data from a limited sample of participants. In a moderated version of a focus group, the moderator asks participants a series of predefined questions. They aim to interact and build a group discussion that reveals their preferences, candid thoughts, and experiences.

Unmoderated, online focus groups are increasingly popular because they eliminate the need to interact with people face to face.

Focus groups can be more cost-effective than 1:1 interviews or studying a group in a natural setting and reporting one’s observations.

Focus groups make it possible to gather multiple points of view quickly and efficiently, making them an excellent choice for testing new concepts or conducting market research on a new product.

However, there are some potential drawbacks to this method. It may be unsuitable for sensitive or controversial topics. Participants might be reluctant to disclose their true feelings or respond falsely to conform to what they believe is the socially acceptable answer (known as response bias).

Case study research

A case study is an in-depth evaluation of a specific person, incident, organization, or society. This type of qualitative research has evolved into a broadly applied research method in education, law, business, and the social sciences.

Even though case study research may appear challenging to implement, it is one of the most direct research methods. It requires detailed analysis, broad-ranging data collection methodologies, and a degree of existing knowledge about the subject area under investigation.

Historical model

The historical approach is a distinct research method that deeply examines previous events to better understand the present and forecast future occurrences of the same phenomena. Its primary goal is to evaluate the impacts of history on the present and hence discover comparable patterns in the present to predict future outcomes.

Oral history

This qualitative data collection method involves gathering verbal testimonials from individuals about their personal experiences. It is widely used in historical disciplines to offer counterpoints to established historical facts and narratives. The most common methods of gathering oral history are audio recordings, analysis of auto-biographical text, videos, and interviews.

Qualitative observation

One of the most fundamental, oldest research methods, qualitative observation , is the process through which a researcher collects data using their senses of sight, smell, hearing, etc. It is used to observe the properties of the subject being studied. For example, “What does it look like?” As research methods go, it is subjective and depends on researchers’ first-hand experiences to obtain information, so it is prone to bias. However, it is an excellent way to start a broad line of inquiry like, “What is going on here?”

Record keeping and review

Record keeping uses existing documents and relevant data sources that can be employed for future studies. It is equivalent to visiting the library and going through publications or any other reference material to gather important facts that will likely be used in the research.

Grounded theory approach

The grounded theory approach is a commonly used research method employed across a variety of different studies. It offers a unique way to gather, interpret, and analyze. With this approach, data is gathered and analyzed simultaneously.  Existing analysis frames and codes are disregarded, and data is analyzed inductively, with new codes and frames generated from the research.

Ethnographic research

Ethnography  is a descriptive form of a qualitative study of people and their cultures. Its primary goal is to study people's behavior in their natural environment. This method necessitates that the researcher adapts to their target audience's setting. 

Thereby, you will be able to understand their motivation, lifestyle, ambitions, traditions, and culture in situ. But, the researcher must be prepared to deal with geographical constraints while collecting data i.e., audiences can’t be studied in a laboratory or research facility.

This study can last from a couple of days to several years. Thus, it is time-consuming and complicated, requiring you to have both the time to gather the relevant data as well as the expertise in analyzing, observing, and interpreting data to draw meaningful conclusions.

Narrative framework

A narrative framework is a qualitative research approach that relies on people's written text or visual images. It entails people analyzing these events or narratives to determine certain topics or issues. With this approach, you can understand how people represent themselves and their experiences to a larger audience.

Phenomenological approach

The phenomenological study seeks to investigate the experiences of a particular phenomenon within a group of individuals or communities. It analyzes a certain event through interviews with persons who have witnessed it to determine the connections between their views. Even though this method relies heavily on interviews, other data sources (recorded notes), and observations could be employed to enhance the findings.

• Qualitative research methods (tools)

Some of the instruments involved in qualitative research include:

Document research: Also known as document analysis because it involves evaluating written documents. These can include personal and non-personal materials like archives, policy publications, yearly reports, diaries, or letters.

Focus groups:  This is where a researcher poses questions and generates conversation among a group of people. The major goal of focus groups is to examine participants' experiences and knowledge, including research into how and why individuals act in various ways.

Secondary study: Involves acquiring existing information from texts, images, audio, or video recordings.

Observations:   This requires thorough field notes on everything you see, hear, or experience. Compared to reported conduct or opinion, this study method can assist you in getting insights into a specific situation and observable behaviors.

Structured interviews :  In this approach, you will directly engage people one-on-one. Interviews are ideal for learning about a person's subjective beliefs, motivations, and encounters.

Surveys:  This is when you distribute questionnaires containing open-ended questions

Free AI content analysis generator

Make sense of your research by automatically summarizing key takeaways through our free content analysis tool.

• What are common examples of qualitative research?

Everyday examples of qualitative research include:

Conducting a demographic analysis of a business

For instance, suppose you own a business such as a grocery store (or any store) and believe it caters to a broad customer base, but after conducting a demographic analysis, you discover that most of your customers are men.

You could do 1:1 interviews with female customers to learn why they don't shop at your store.

In this case, interviewing potential female customers should clarify why they don't find your shop appealing. It could be because of the products you sell or a need for greater brand awareness, among other possible reasons.

Launching or testing a new product

Suppose you are the product manager at a SaaS company looking to introduce a new product. Focus groups can be an excellent way to determine whether your product is marketable.

In this instance, you could hold a focus group with a sample group drawn from your intended audience. The group will explore the product based on its new features while you ensure adequate data on how users react to the new features. The data you collect will be key to making sales and marketing decisions.

Conducting studies to explain buyers' behaviors

You can also use qualitative research to understand existing buyer behavior better. Marketers analyze historical information linked to their businesses and industries to see when purchasers buy more.

Qualitative research can help you determine when to target new clients and peak seasons to boost sales by investigating the reason behind these behaviors.

• Qualitative research: data collection

Data collection is gathering information on predetermined variables to gain appropriate answers, test hypotheses, and analyze results. Researchers will collect non-numerical data for qualitative data collection to obtain detailed explanations and draw conclusions.

To get valid findings and achieve a conclusion in qualitative research, researchers must collect comprehensive and multifaceted data.

Qualitative data is usually gathered through interviews or focus groups with videotapes or handwritten notes. If there are recordings, they are transcribed before the data analysis process. Researchers keep separate folders for the recordings acquired from each focus group when collecting qualitative research data to categorize the data.

• Qualitative research: data analysis

Qualitative data analysis is organizing, examining, and interpreting qualitative data. Its main objective is identifying trends and patterns, responding to research questions, and recommending actions based on the findings. Textual analysis is a popular method for analyzing qualitative data.

Textual analysis differs from other qualitative research approaches in that researchers consider the social circumstances of study participants to decode their words, behaviors, and broader meaning. 

Learn more about qualitative research data analysis software

• When to use qualitative research

Qualitative research is helpful in various situations, particularly when a researcher wants to capture accurate, in-depth insights. 

Here are some instances when qualitative research can be valuable:

Examining your product or service to improve your marketing approach

When researching market segments, demographics, and customer service teams

Identifying client language when you want to design a quantitative survey

When attempting to comprehend your or someone else's strengths and weaknesses

Assessing feelings and beliefs about societal and public policy matters

Collecting information about a business or product's perception

Analyzing your target audience's reactions to marketing efforts

When launching a new product or coming up with a new idea

When seeking to evaluate buyers' purchasing patterns

• Qualitative research methods vs. quantitative research methods

Qualitative research examines people's ideas and what influences their perception, whereas quantitative research draws conclusions based on numbers and measurements.

Qualitative research is descriptive, and its primary goal is to comprehensively understand people's attitudes, behaviors, and ideas.

In contrast, quantitative research is more restrictive because it relies on numerical data and analyzes statistical data to make decisions. This research method assists researchers in gaining an initial grasp of the subject, which deals with numbers. For instance, the number of customers likely to purchase your products or use your services.

What is the most important feature of qualitative research?

A distinguishing feature of qualitative research is that it’s conducted in a real-world setting instead of a simulated environment. The researcher is examining actual phenomena instead of experimenting with different variables to see what outcomes (data) might result.

Can I use qualitative and quantitative approaches together in a study?

Yes, combining qualitative and quantitative research approaches happens all the time and is known as mixed methods research. For example, you could study individuals’ perceived risk in a certain scenario, such as how people rate the safety or riskiness of a given neighborhood. Simultaneously, you could analyze historical data objectively, indicating how safe or dangerous that area has been in the last year. To get the most out of mixed-method research, it’s important to understand the pros and cons of each methodology, so you can create a thoughtfully designed study that will yield compelling results.

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Qualitative Research Definition

Qualitative research methods and examples, advantages and disadvantages of qualitative approaches, qualitative vs. quantitative research, showing qualitative research skills on resumes, what is qualitative research methods and examples.

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Qualitative research seeks to understand people’s experiences and perspectives by studying social organizations and human behavior. Data in qualitative studies focuses on people’s beliefs and emotional responses. Qualitative data is especially helpful when a company wants to know how customers feel about a product or service, such as in user experience (UX) design or marketing . 

Researchers use qualitative approaches to “determine answers to research questions on human behavior and the cultural values that drive our thinking and behavior,” says Margaret J. King, director at The Center for Cultural Studies & Analysis in Philadelphia.

Data in qualitative research typically can’t be assessed mathematically — the data is not sets of numbers or quantifiable information. Rather, it’s collections of images, words, notes on behaviors, descriptions of emotions, and historical context. Data is collected through observations, interviews, surveys, focus groups, and secondary research. 

However, a qualitative study needs a “clear research question at its base,” notes King, and the research needs to be “observed, categorized, compared, and evaluated (along a scale or by a typology chart) by reference to a baseline in order to determine an outcome with value as new and reliable information.”

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Who Uses Qualitative Research?

Researchers in social sciences and humanities often use qualitative research methods, especially in specific areas of study like anthropology, history, education, and sociology. 

Qualitative methods are also applicable in business, technology , and marketing spaces. For example, product managers use qualitative research to understand how target audiences respond to their products. They may use focus groups to gain insights from potential customers on product prototypes and improvements or surveys from existing customers to understand what changes users want to see. 

Other careers that may involve qualitative research include: 

• Marketing analyst
• UX and UI analyst
• Market researcher
• Statistician
• Business analyst
• Data analyst
• Research assistant
• Claims investigator

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Good research begins with a question, and this question informs the approach used by qualitative researchers. 

Grounded Theory

Grounded theory is an inductive approach to theory development. In many forms of research, you begin with a hypothesis and then test it to see if you’re correct. In grounded theory, though, you go in without any assumptions and rely on the data you collect to form theories. You start with an open question about a phenomenon you are studying and collect and analyze data until you can form a fully-fledged theory from the information. 

Example: A company wants to improve its brand and marketing strategies. The company performs a grounded theory approach to solving this problem by conducting interviews and surveys with past, current, and prospective customers. The information gathered from these methods helps the company understand what type of branding and marketing their customer-base likes and dislikes, allowing the team to inductively craft a new brand and marketing strategy from the data. 

Action Research

Action research is one part study and one part problem-solving . Through action research, analysts investigate a problem or weakness and develop practical solutions. The process of action research is cyclical —- researchers assess solutions for efficiency and effectiveness, and create further solutions to correct any issues found. 

Example: A manager notices her employees struggle to cooperate on group projects. She carefully reviews how team members interact with each other and asks them all to respond to a survey about communication. Through the survey and study, she finds that guidelines for group projects are unclear. After changing the guidelines, she reviews her team again to see if there are any changes to their behavior.  

>>MORE: Explore how action research helps consultants serve clients with Accenture’s Client Research and Problem Identification job simulation .

Phenomenological Research

Phenomenological research investigates a phenomenon in depth, looking at people’s experiences and understanding of the situation. This sort of study is primarily descriptive and seeks to broaden understanding around a specific incident and the people involved. Researchers in phenomenological studies must be careful to set aside any biases or assumptions because the information used should be entirely from the subjects themselves. 

Example : A researcher wants to better understand the lived experience of college students with jobs. The purpose of this research is to gain insights into the pressures of college students who balance studying and working at the same time. The researcher conducts a series of interviews with several college students, learning about their past and current situations. Through the first few interviews, the researcher builds a relationship with the students. Later discussions are more targeted, with questions prompting the students to discuss their emotions surrounding both work and school and the difficulties and benefits arising from their situation. The researcher then analyzes these interviews, and identifies shared themes to contextualize the experiences of the students.

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Ethnography

Ethnography is an immersive study of a particular culture or community. Through ethnographic research, analysts aim to learn about a group’s conventions, social dynamics, and cultural norms. Some researchers use active observation methods, finding ways to integrate themselves into the culture as much as possible. Others use passive observation, watching closely from the outside but not fully immersing themselves. 

Example: A company hires an external researcher to learn what their company’s culture is actually like. The researcher studies the social dynamics of the employees and may even look at how these employees interact with clients and with each other outside of the office. The goal is to deliver a comprehensive report of the company’s culture and the social dynamics of its employees.

Case Studies

A case study is a type of in-depth analysis of a situation. Case studies can focus on an organization, belief system, event, person, or action. The goal of a case study is to understand the phenomenon and put it in a real-world context. Case studies are also commonly used in marketing and sales to highlight the benefits of a company’s products or services. 

Example: A business performs a case study of its competitors’ strategies. This case study aims to show why the company should adopt a specific business strategy. The study looks at each competitor’s business structure, marketing campaigns, product offerings, and historical growth trends. Then, using this data on other businesses, the researcher can theorize how that strategy would benefit their company.

>>MORE: Learn how companies use case study interviews to assess candidates’ research and problem-solving skills. 

Qualitative research methods are great for generating new ideas. The exploratory nature of qualitative research means uncovering unexpected information, which often leads to new theories and further research topics. Additionally, qualitative findings feel meaningful. These studies focus on people, emotions, and societies and may feel closer to their communities than quantitative research that relies on more mathematical and logical data. 

However, qualitative research can be unreliable at times. It’s difficult to replicate qualitative studies since people’s opinions and emotions can change quickly. For example, a focus group has a lot of variables that can affect the outcome, and that same group, asked the same questions a year later, may have entirely different responses. The data collection can also be difficult and time-consuming with qualitative research. Ultimately, interviewing people, reviewing surveys, and understanding and explaining human emotions can be incredibly complex.

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While qualitative research deals with data that isn’t easily manipulated by mathematics, quantitative research almost exclusively involves numbers and numerical data. Quantitative studies aim to find concrete details, like units of time, percentages, or statistics. 

Besides the types of data used, a core difference between quantitative and qualitative research is the idea of control and replication. 

“Qualitative is less subject to control (as in lab studies) and, therefore, less statistically measurable than quantitative approaches,” says King.

One person’s interview about a specific topic can have completely different responses than every other person’s interview since there are so many variables in qualitative research. On the other hand, quantitative studies can often be replicated. For instance, when testing the effects of a new medication, quantifiable data, like blood test results, can be repeated. Qualitative data, though, like how people feel about the medication, may differ from person to person and from moment to moment.

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You can show your experience with qualitative research on your resume in your skills or work experience sections and your cover letter . 

• In your skills section , you can list types of qualitative research you are skilled at, like conducting interviews, performing grounded theory research, or crafting case studies. 
• In your work or internship experience descriptions , you can highlight specific examples, like talking about a time you used action research to solve a complex issue at your last job. 
• In your cover letter , you can discuss in-depth qualitative research projects you’ve completed. For instance, say you spent a summer conducting ethnographic research or a whole semester running focus groups to get feedback on a product. You can talk about these experiences in your cover letter and note how these skills make you a great fit for the job. 

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Qualitative Research in Psychology

Research Methods in Psychology

January 2023

This twelve-hour course on qualitative research in psychology begins by exploring the historical and cross-disciplinary foundations of the field, emphasizing philosophical underpinnings such as postpositivism, constructivism, transformative, and pragmatism. The course highlights the iterative, naturalistic, and contextual facets of qualitative research, focusing on trustworthiness criteria like credibility, transferability, dependability, and confirmability. It also addresses common critiques from a quantitative perspective and the concept of reflexivity, stressing the importance of the researcher’s role and biases.

Phenomenology, narrative inquiry, and constructivist grounded theory are explored next. Phenomenology captures the essence of human experiences through in-depth interviews, revealing nuances like maternal identity development. Narrative inquiry uses storytelling to uncover life nuances, such as the challenges faced by first-generation college students. Constructivist grounded theory develops theories based on participants’ experiences, explaining social processes like identity development and resilience-building. Interviewing techniques tailored to each tradition are explored, emphasizing the researcher’s role as the core instrument of data collection.

The course then explores ethnographic inquiry and case studies. Ethnography involves direct engagement in the setting of interest, uncovering cultural phenomena through various genres like classical, mainstream, public, and postmodern. Case studies investigate phenomena bounded by time and place, focusing on individuals, interventions, organizations, or systems.

Finally, the course examines qualitative data analysis and coding techniques. The iterative nature of qualitative research is emphasized, where data collection and analysis occur simultaneously, allowing for constant comparison and refinement of codes.

Learning objectives

• Describe the philosophical and interpretive foundations of qualitative research.
• Differentiate qualitative claims, methods, and analyses from quantitative claims, methods, and analyses.
• Explore, identify, and evaluate core qualitative traditions (phenomenology, narrative inquiry, constructivist grounded theory, ethnographic inquiry, and case study).
• Distinguish common methods (e.g., interviewing, focus groups) and analytical techniques (qualitative data analysis) used within and across core qualitative traditions.
• Begin thinking about your own qualitative study of a topic in psychology.

This program does not offer CE credit.

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Article contents

Qualitative interviewing.

• John J. Brent , John J. Brent School of Justice Studies, Eastern Kentucky University
• Peter B. Kraska Peter B. Kraska School of Justice Studies, Eastern Kentucky University
•  and  Justin Hutchens Justin Hutchens School of Justice Studies, Eastern Kentucky University
• https://doi.org/10.1093/acrefore/9780190264079.013.850
• Published online: 21 August 2024

Given the multifaceted and interdisciplinary nature of studying crime and criminal justice, the pursuit of credible, reliable, and rigorous knowledge requires a well-developed methodological infrastructure. To explore and examine these areas, there are times when research needs to document probabilities, examine rates, identify correlations, and test theoretical propositions. There are also times when research needs to explore the more qualitative elements, namely the perspectives, interpretations, lived experiences, and constructed realities. Among the more prominent qualitative methods within the field’s methodological toolbox are interviews. Aiding other approaches, qualitative interviews contribute to the field’s methodological means by first offering a more inductive and interpretive framework to study crime-related phenomena. From these foundations, they are replete with avenues through which to conceptualize, construct, and administer research efforts. They also provide a host of unique and beneficial methodological means to collect, code, and analyze collected data. When their overall impact is examined, the continued use and development of qualitative methods—more specifically, interviews—can progress the field’s body of knowledge while contributing to more informed practices and policies. Given their use and utility, interviews have become some of the most used methodological approaches within the social sciences.

• qualitative
• interviewing
• ethnographic
• research methods
• criminal justice
• criminology

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date: 06 September 2024

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A qualitative study on the relationship between faculty mobility and scientific impact: toward the sustainable development of higher education, 1. introduction, 2. literature review, 2.1. faculty mobility, 2.2. scientific impact, 2.3. relationship between faculty mobility and scientific impact, 3. data and research methodology, 3.1. dataset, 3.2. research methodology, 3.2.1. descriptive statistical analysis.

• Mobility Frequency: This study uses the change in the authors’ correspondence addresses as an indicator of mobility frequency. Samples with abnormal data and excessive mobility experiences were excluded, and only samples with 1–5 instances of mobility were included in the subsequent analysis.
• Citation Count: The number of times a paper is cited by other papers after publication is called the citation count. This reflects the referential value and importance of an original paper for subsequent research. Highly cited papers represent the frontier and hot issues in the field.
• Difference in Citation Count ( δ ): This refers to the difference in citation counts of papers by faculty members after mobility compared to the citation counts before mobility.

3.2.2. Normality Test

3.2.3. spearman’s rank correlation coefficient, 3.2.4. wilcoxon signed-rank test, 4.1. spearman’s rank correlation analysis of faculty mobility and citations, 4.1.1. correlation analysis of overall faculty mobility frequency and citations, 4.1.2. correlation analysis of faculty mobility frequency and paper citations by discipline, 4.2. wilcoxon signed-rank test analysis of faculty mobility and paper citations, 4.3. wilcoxon signed-rank test analysis of faculty mobility frequency and paper citations, 4.3.1. analysis of differences in paper citations by overall faculty mobility frequency, 4.3.2. analysis of differences in citations by discipline, 5. discussion and conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

Zhang, J.; Su, X.; Wang, Y. A Qualitative Study on the Relationship between Faculty Mobility and Scientific Impact: Toward the Sustainable Development of Higher Education. Sustainability 2024 , 16 , 7739. https://doi.org/10.3390/su16177739

Zhang J, Su X, Wang Y. A Qualitative Study on the Relationship between Faculty Mobility and Scientific Impact: Toward the Sustainable Development of Higher Education. Sustainability . 2024; 16(17):7739. https://doi.org/10.3390/su16177739

Zhang, Jun, Xiaoyan Su, and Yifei Wang. 2024. "A Qualitative Study on the Relationship between Faculty Mobility and Scientific Impact: Toward the Sustainable Development of Higher Education" Sustainability 16, no. 17: 7739. https://doi.org/10.3390/su16177739

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• Open access
• Published: 05 September 2024

Bridging the generational gap between nurses and nurse managers: a qualitative study from Qatar

• Ahmad A. Abujaber 1 ,
• Abdulqadir J. Nashwan   ORCID: orcid.org/0000-0003-4845-4119 1 ,
• Mark D. Santos 1 ,
• Nabeel F. Al-Lobaney 1 ,
• Rejo G. Mathew 1 ,
• Jamsheer P. Alikutty 1 ,
• Jibin Kunjavara 3 &
• Albara M. Alomari 2  

BMC Nursing volume  23 , Article number:  623 ( 2024 ) Cite this article

Metrics details

The nursing workforce comprises multiple generations, each with unique values, beliefs, and expectations that can influence communication, work ethic, and professional relationships. In Qatar, the generational gap between nurses and nurse managers poses challenges to effective communication and teamwork, impacting job satisfaction and patient outcomes.

This study investigates the generational gap between nurses and nurse managers in Qatar, aiming to identify strategies to enhance collaboration and create a positive work environment.

A qualitative research design was used, involving semi-structured interviews with 20 participants, including frontline nurses and senior nurse managers. Participants were purposively sampled to represent different generations. Data were collected through face-to-face and virtual interviews, then transcribed and thematically analyzed.

Four key themes emerged: Optimizing the Work Environment : Older generations preferred transformational and situational leadership, while younger nurses valued respect, teamwork, accountability, and professionalism. Strengthening Work Atmosphere through Communication and values : Older nurses favored face-to-face communication, while younger nurses preferred digital tools. Cultivating Respect and Empathy : Younger nurses emphasized fairness in assignments and promotions, while older nurses focused on empathy and understanding. Dynamic Enhancement of Healthcare Systems : Younger nurses were more adaptable to technology and professional development, while older nurses prioritized clinical care and patient outcomes.

The study reveals significant generational differences in leadership preferences, communication styles, and adaptability to technology. Addressing these gaps through effective leadership, ongoing education, and open communication can improve job satisfaction and patient care.

Peer Review reports

Introduction

The nursing profession faces a significant challenge of a multigenerational workforce that can cause conflict and hinder effective communication, especially between nurse managers and nurses [ 1 ]. In addition, a literature review of studies conducted over the past two decades indicates that the generational gap between nurses and nurse managers is a complex phenomenon requiring concerted efforts to address it [ 2 , 3 ].

The nursing workforce comprises four generations, including the Baby Boomers (born between 1946 and 1964), Generation X (born between 1965 and 1979), Generation Y or Millennials (born between 1980 and 1994), and Generation Z (born after 1995) [ 4 ]. These generations have unique values, beliefs, attitudes, and expectations that influence their communication style, work ethic, and approach to work [ 4 ].

In 2013, Hendricks and Cope discussed the impact of generational differences on the nursing workforce and the challenges it presents for nurse managers [ 5 ]. They searched various databases electronically and found that generational diversity affects nurses’ attitudes, beliefs, work habits, and expectations. The paper suggested that accepting and embracing this diversity can lead to a more harmonious work environment and facilitate nurse retention [ 5 ].

The article focused on the cultural and work ethic differences between Baby Boomers and Generation Xers, with Baby Boomers primarily managing the workforce [ 6 ]. Baby Boomers are described as driven and dedicated, equating work with self-worth and personal fulfillment [ 6 ]. At the same time, Generation Xers have ideas of an acceptable workplace, and their terms of employment are usually non-negotiable [ 6 ]. The article summarized recent literature and studies to guide healthcare leadership in recruiting, retaining, and managing Generation X workers in the nursing field [ 6 ].

Similarly, Carver & Candela (2008) conducted a study to inform nurse managers about the generational differences among nurses and how they affect the work environment [ 7 ]. With four generations in the nursing workforce, understanding the characteristics of each generation can lead to increased job satisfaction, productivity, and decreased turnover [ 7 ]. Considering generational differences as part of an overall strategy to increase organizational commitment can improve nursing work environments and address the global nursing shortage [ 7 ]. Managers should increase their knowledge of generational diversity to tap into the strengths of each generation [ 7 ]. In addition, Younger nurses have different career expectations than their older colleagues [ 8 ]. They seek a balanced lifestyle with reasonable work hours, demand to use the latest technology, and expect to be vocal team members [ 8 ].

Managing a multigenerational workforce requires recognizing and valuing the strengths of each generation. Leaders who maximize everyone’s talents and address individual and generational needs can create synergy and improve team performance. Each generation brings unique strengths to the workforce that should be celebrated and utilized to the organization’s advantage. Meeting the needs of each employee, such as providing opportunities for advancement, work/life balance, compensation, benefits, and learning and development, can lead to higher-functioning work teams [ 9 ]. Nurse leaders should know their employees’ multigenerational characteristics and expectations and provide timely and specific feedback to manage them effectively [ 9 ]. With an appreciation of multigenerational differences and a commitment to higher-functioning work teams, leaders can improve organizational efficiency and patient care outcomes [ 9 ].

To bridge the generational gap in nursing, the SIT offers a comprehensive approach to enhancing communication, collaboration, and teamwork between nurses and nurse managers [ 5 ]. This involves acknowledging and respecting each generation’s unique characteristics, values, and experiences, which fosters a better understanding and more effective cooperation. Establishing a shared vision and goal for patient care unites nurses and nurse managers, helping to overcome any multigenerational conflicts that might arise in the workplace [ 5 ]. Additionally, encouraging multigenerational communication and mentoring is vital. This can be facilitated through programs where experienced nurses share their knowledge and skills with younger colleagues, promoting a cohesive and supportive team environment. Furthermore, providing training and development opportunities tailored to each generation’s diverse learning styles and preferences is essential for building a more skilled and competent workforce [ 10 ].

The literature indicates that the generational gap between nurses and nurse managers is a global complex phenomenon that can affect communication, work values, job satisfaction, retention, and quality of care [ 11 ]. Nursing leaders can recognize generational differences in values and behaviors as potential strengths. By gaining a deeper understanding of generational influences, these insights can be harnessed to develop effective strategies that sustain the diverse yet shrinking nursing workforce. Leveraging generational differences can also create positive work environments, enhance quality and productivity, and ultimately improve patient care. As generational differences increasingly become a critical aspect of diversity, it is essential to understand the dynamics between work engagement and meaningful work across generational cohorts to tailor approaches that align with each organization’s unique needs [ 12 , 13 ].

Understanding how to bridge the generational gap in nursing is crucial for nurses and nurse managers to work together effectively and provide better patient care, ultimately leading to improved patient outcomes. This study aims to enhance workplace communication and collaboration by identifying and addressing the factors contributing to multigenerational workplace conflicts. By doing so, nurses and nurse managers can build more cohesive and supportive teams, resulting in a more positive work environment. Finally, addressing the generational gap in nursing benefits the workplace and enables the organization to develop a more engaged and motivated workforce. Multigenerational learning and development opportunities can increase job satisfaction and retention. Recognizing and valuing the unique perspectives and experiences each generation brings is essential.

Study significance

To the best of our knowledge, no studies have been conducted in Qatar that addressed the generational gap among nurses. In line with this, the study aims to identify and compare the work engagement levels and managerial approaches among nurses and nurse managers across different generations and explore and propose effective strategies for improving communication, collaboration, and job contentment in an intergenerational work environment. The findings will contribute to the nursing profession’s knowledge and provide practical solutions for managing a diverse nursing workforce in Qatar.

This study utilized a descriptive qualitative research design. After considering the participants’ time limits, commitments, and convenience, data were collected through semi-structured interviews with nurses and nurse managers (Executive and assistant executive directors of nursing). The authors developed the interview questions for this study (Supplementary File 1). Participants were recruited from healthcare facilities within the organization through purposive sampling. The sample size was determined based on the data saturation point, where no new themes or perspectives emerged. Interviews were conducted face-to-face or virtually, depending on the participant’s preference and availability. With the participant’s permission, interviews were audio-recorded to aid in accurate transcription and were thematically analyzed.

Development of the interview guide

The interview guide was thoughtfully developed to capture participants’ experiences and insights effectively. The process began with an in-depth review of studies examining the generational gap between nurses and managers, identifying key themes such as work engagement, organizational environment, communication, and technological advancement. These themes provided the framework for creating open-ended questions to elicit detailed and reflective responses. Probing questions were also included to deepen the data collected by clarifying and expanding on participants’ initial answers. The draft questions underwent multiple rounds of review and refinement to ensure clarity, relevance, and the elimination of bias, with potential input from qualitative research experts.

Qualitative research aimed to generate a deep understanding of the generational gap between nurses and their managers. This understanding could not be answered in a quantitative approach. Several strategies were employed throughout the research process to ensure the credibility of the findings.

Firstly, to ensure the credibility of the data collected, the researcher established trust and rapport with the participants. This was achieved by being transparent about the research aims, building rapport, and showing genuine interest in the participants’ experiences. The researcher also ensured that the participants felt comfortable sharing their experiences and opinions by creating a safe and non-judgmental environment.

Secondly, data triangulation was used to enhance the credibility of the data. Data triangulation involves using multiple data sources to provide a more comprehensive understanding of the phenomenon being studied.

Thirdly, the researcher conducted member checking to validate the data collected. Member checking involved sharing the findings with the participants and asking for their feedback on whether the findings accurately represented their experiences and opinions. This process ensured that the researcher’s interpretation of the data aligned with the participants’ experiences and perceptions.

Fourthly, the researcher engaged in reflexivity throughout the research process. Reflexivity involves reflecting on the researcher’s biases, values, and assumptions that might have influenced the research process and findings. By being aware of their biases, the researcher ensured they did not influence the data collection or interpretation of the findings.

Finally, the researcher used a systematic and rigorous approach to analyze the data collected. This study used thematic analysis to identify patterns and themes in the data. The analysis was conducted using a coding scheme, and the findings were supported with quotes from the participants, enhancing the credibility of the findings.

Study population and setting

The participants were approached using a purposive sampling technique. A total of 20 participants were expected to join the study. All participants were approached based on an email from the corporate nursing mail group. The participants of this study met the following criteria: they represented diverse generations, with 3–4 from each of the subsequent generations: Generation X (1965–1980), Generation Y (1981–1996), and Generation Z (1997–2012); they had joined HMC for at least one year; and they were willing to participate in the study.

Study procedures

Before conducting the study, the researcher had obtained the consent of the participants (Research Information Sheet). Interviews were done face-to-face or virtually, depending on the participants’ preferences and availability. During the interviews, conversations were audio-recorded to facilitate transcriptions of the responses, completed within 24 h of the interview, and reviewed by two study researchers. The data saturation was determined by redundancy of information is indicated when similar patterns, themes, or categories keep appearing in the data, and no new information is being uncovered during additional interviews or data collection efforts.

The richness and depth of the data collected are critical. Saturation is considered reached when the data sufficiently explores and explains the research questions and key concepts, providing a comprehensive understanding of the phenomenon. Data saturation was reached after twenty interviews; however, two additional interviews were conducted to confirm this. Ethical principles were strictly observed, primarily explaining the nature and purpose of the study before obtaining their consent to participate. Identifiers were removed from the transcripts, and codes were used to label participants (e.g., Participants 1, 2, etc.). Participants were informed that they had the right to withdraw from the study at any time should they decide not to participate in further sessions.

Data analysis

Initially, all interviews were professionally transcribed verbatim, with pseudonyms used to anonymize participants and protect their identities. Both authors (JK and NFA) thoroughly read and re-read the transcripts multiple times to become familiar with the content and ensure the transcripts accurately reflected the audio recordings. then applied an inductive coding approach, deriving codes directly from the data rather than imposing them beforehand. This involved systematically identifying and highlighting significant quotes and segments within the transcripts that were relevant to the research questions. These initial codes were subsequently organized into potential themes by grouping together codes that shared a common essence or underlying concept. Following this, the researchers organized these initial codes into potential themes by grouping codes that shared a common essence or underlying concept.

The potential themes underwent a two-phase review and refinement process. In the first phase, the researchers reviewed the coded data extracts to ensure they coherently supported the identified themes. In the second phase, the themes were examined in relation to the entire data set to confirm that they accurately represented the data and captured the full range of participants’ experiences. Some themes were modified, combined, or discarded during this process based on their relevance and data representation.

The final step involved crafting a coherent and compelling narrative that provided a detailed account of each theme. The report included illustrative quotes from participants to substantiate the themes and vividly depict their experiences. This structured approach ensured that the analysis was thorough and that the resulting themes were deeply rooted in the data. By following Braun and Clarke’s six-step process, the study moved from raw transcripts to well-defined themes that offer meaningful insights into the generational gap among nurses and Nurse managers.

This study had a cohort of ten frontline nurses from the new generation and ten senior nurse managers from the old generation, as shown in Table  1 . The mean age of the new generation was 32.4 years (SD 4.9 years). The nurses had an average of 8.3 years of overall work experience (SD 3.09 years), specifically at Hamad Medical Corporation (HMC); they had a mean work experience of 4.7 years (SD 1.1 years). Gender distribution among the participants was 80% male and 20% female. This demographic profile reveals a well-experienced group, particularly regarding their tenure at HMC, providing a stable basis for analyzing their professional perspectives and experiences.

On the other hand, the old generation demographics: 60% were Executive Directors and 40% were Assistant Executives. Most participants belonged to Generation X (ages 44 to 59 years old), suggesting a consistent age distribution. On average, the executives had 27.9 years of overall work experience (SD 9.46 years), highlighting substantial professional tenure with considerable variability. Specifically, their mean work experience at Hamad Medical Corporation (HMC) was 17.4 years (SD 8.24 years), reflecting a diverse range of service durations at this institution. The gender distribution was evenly split, with 50% male and 50% female participants. Details on the demographic data of the old generation participants are detailed in Table  2 . Three major themes were derived from the study, as illustrated in Fig.  1 .

The major themes and Sub-Themes derived from the study

Optimizing the working environment

Healthy work environments that maximize the health and well-being of nurses are essential in achieving good patient and societal outcomes, as well as optimal organizational performance. This theme consisted of three sub-themes: Influencing leadership style, Patient outcome and nurse satisfaction, and Adaptation of technological advancement.

Influential leadership styles

When investigating the leadership style, all older generations consistently agreed to prefer the transformational one because of its capacity to inspire and motivate frontline staff. However, to respond to specific situational demands, the older generation in our study modified and combined aspects of situational and democratic leadership.

Which type of leadership I’m following is transformational leadership. But sometimes , we can take that democratic leadership in some situations , but not all of it. We can say situational leadership at the same time. But any leadership style you will follow should be , I can tell , a combination of some practice and attitude toward your staff”. (Participant 17).

On the other hand, the new generation perceives leadership style by retrieving the inner values of their leaders, such as respect, teamwork, accountability, and professionalism.

“Actually , our leaders primarily lead by maintaining a good relationship , and he is making sense of decreasing the distance between the higher and lower positions. So , I can say that I share the same attitudes and values with my senior managers , but it might differ from one person to another.” ( Participant 1).

Enhanced patient outcomes and nurses’ satisfaction

The older generation perceived the working environment as a motivator for enhancing patient outcomes. Mainly, they are putting serving humanity at the top of their priority, which might be achieved through creativity, collaboration, and compassion. As articulated by Participant 7, “I believe that exerting the best effort in one’s job demonstrates ownership and respect for the profession. Serving humanity , I prioritize creativity , collaboration , and compassion in my work”.

This quote demonstrates the deep values held by this group, highlighting their strategy of combining individual achievement with a wider humanitarian influence.

The new generation views the working environment as a vital element in improving nurses’ satisfaction, considering many contributing factors, such as the current status of the global economy and the opportunities for nurses to work and move abroad. As elaborated by Participant 13,

“I think we can see a difference between the young and the old generation , and I think the way they look at nursing as a profession. There is a big difference between all the new generations , and I can see how the old generation looks at it. The older generation is looking at ways to help people. It is a way to provide support for older people. Unfortunately , I think the new generation has started looking at it as a job—more than a way of helping people. And I believe there are many different reasons for this. I think about the economic status around the world , and the other thing that you know is that I believe the world is open nowadays for nurses to travel around. Therefore , it’s started becoming a job more than a profession. Unfortunately , that’s why people start looking at it in a completely different way , which is not something good.” (Participant 13).

Adaptation to technological advancements

When examining the technological aspects, the older generation acknowledges the presence of the gab. Most of them believe the gap exists because they adhere to the old practices they learned previously.

“There is a noticeable difference between the younger and older generations of nurses , primarily due to advancements in technology and medical knowledge. Younger nurses are often more up-to-date with the latest care techniques and medical research , as they can access various modern resources. Older nurses , however , may adhere to practices they learned earlier in their careers , which might not incorporate recent technological changes”. (Participant 16)

On the other hand, the new generation views new technologies as an easy-to-adopt opportunity. They like to use the new potentials that come with AI. For example, the new generation is becoming more dependent on technology due to the greater benefits it provides compared to traditional approaches in terms of diagnosis and treatment.

“Technology is a significant factor for us , being part of the newer generation. It’s very important in our year of nursing. We use computers , advanced machines , and electronic documentation , which differ from past practices.”(participant 10) . “The younger generation is adapting more easily to new technologies and software , like using EMR for documentation. The older generation , who are used to manual documentation , find it harder to adapt to this new system in patient care. I’ve also heard that some facilities are using GPS and AI systems to assist in diagnoses and results. So , artificial intelligence is becoming a part of nursing , and younger generations are adapting more easily to it. It will take time for the older generation to adapt because they are accustomed to different practices”. (Participant 8)

Strengthening the work atmosphere through communication and values

Effective communication enhances working relationships and knowledge translation and reduces conflict responsible for errors, improving patient safety. This theme consisted of three sub-themes, diverse and practical communication approaches, positive work atmosphere cultivation, and emphasis on shared values across teams.

Diverse and effective communication approaches

The older generation emphasizes the importance of training sessions on communication skills and advanced technologies to bridge the gap with the new generation. Moreover, they believe the new generation needs to be more skilled in direct interpersonal communication.

“Effective communication strategies that bridge generational gaps should be promoted. This could include training on communication best practices and the use of technology for older nurses and encouraging younger nurses to develop strong interpersonal skills for face-to-face interactions”. (Participant 20) “The older generations , always think of , they are more of insightful , in terms of , in the meetings they will be able to translate or interpret the information much differently. And that’s how I see.”( Participants − 18) .

According to the new generation, effective and direct communication without any mediator can enhance the work atmosphere and ease professional communication with older generations. It can help the new generation have more chances to interact with the old generation.

“Certainly , open and direct communication is helpful. As previously said , it is crucial to have someone who can assist in communicating with my manager in my home country. Establishing a direct line of communication with my management and developing a robust professional connection without intermediaries is vital. I appreciate the older generation’s facilitation of an open-door policy , as it cultivates a direct and efficient communication atmosphere.” (Participant 1).

Positive work atmosphere cultivation

When examining the intergenerational dynamics in the workplace, the findings indicated that differences in experience, training, and access to technology significantly impact the work environment and the level of collaboration among employees. As one participant articulated,

“The work atmosphere impacts collaboration. I think it does impact that and impacts these differences from one generation to another. It’s not about good and bad , but it’s rather about the differences in the experiences , differences in the training , and differences in the work environment as well as the availability of technology. So , I would say that there is a difference.” (Participant 19). However, the new generation focuses on the technological aspect and how that might affect the work atmosphere positively.

Emphasis on shared values across teams

Conflicts arise when older generations rely on experience while new generations prefer evidence-based practices. This affects workplace shared values.

“For instance , there might be a conflict over a non-scientifically backed common practice. The older generation might argue that they’ve been doing it for years without issues. However , from a knowledge-based perspective , the practice might be incorrect. Overall , the older generation’s viewpoint is based on their experience , where they haven’t seen negative outcomes. Conversely , the new generation would argue based on scientific principles and current best practices. The older generation might resist changing to these new practices. So , conflicts like these might arise from differing viewpoints on practices and approaches.” (Participant 9) .

The new generations perceive shared values as part of the staff-manager relationship and can’t isolate it. When the old generation leads, the staff investigates the old generation’s way of leading, which will affect the new generation’s attitudes and values. Consequently, the new generation still takes the old generation as an example to be followed. This meaning can be found in Participant 1 answers. “Actually , our leaders primarily lead by maintaining a good relationship , and he is making sense of decreasing the distance between the higher and lower positions. So , I can say that I share the same attitudes and values with my senior managers , but it might differ from one person to another.” ( Participant 1) .

Cultivating respect and empathy

This theme focuses on two subthemes: commitment to fairness and fostering a sense of purpose among staff.

Commitment to fairness

The results of the older generation highlight the importance of fostering empathy in the workplace. Participant 20 suggests promoting understanding by encouraging the new generation to consider their colleagues’ perspectives and motivations, enhancing mutual respect and cooperation.

“Encourage Empathy: Foster empathy among employees by encouraging them to put themselves in each other’s shoes. Encouraging individuals to consider the motivations and experiences of their colleagues can lead to better understanding” (Participant 20). “They can challenge you as a leader and they can challenge each other. That’s how you build a better workplace to have a conversation , a clear professional conversation. If you want to build a professional conversation , the two respect the critiques to respect the differences. So those differences are not conflicts. Differences are differences of opinion due to the experiences everybody can brings in.”(Participants 18) .

However, the new generation demands that older generations be more open to work-related discussions, assignments, and promotion opportunities. They believe the new generation has a greater chance to be promoted if they get a fair chance as they are equipped and well-educated. This was clear by Participant 9.“ Compared to the older generation , the new generation of nurses has more opportunities for service and promotion based on education. In the past , nurses often held diplomas or auxiliary nursing qualifications , with the attitude focused primarily on patient care. Now , there’s a trend towards having more knowledgeable nurses capable of providing advanced care”( Participant 9).

Fostering a sense of purpose among staff

A sense of purpose plays a crucial role in developing cohesive nursing teams by promoting transparent communication and mutual learning, as emphasized by Participant 18.

“The most effective way that I felt worked during this period is the mentorship , working closely with the people and letting them have open communication all the time , providing the proper support , and providing the platform to share the experience and knowledge while you are learning or why they are learning from , and this learning process will be from both. So , this sharing of information through a clear mentorship , in one way or another , will create a culture of mutual respect , and this will end with time; this is not just easy; it takes time. But eventually , if it is done appropriately from the beginning , it will formulate a more cohesive nursing team.“(Participant 18).

The sense of purpose was more obvious among the new generation’s responses, as can be seen in Participant 7’s response: “ Our teamwork is initially built on collaboration , where each nurse supports and enhances the work of others.”

Dynamic enhancement of healthcare systems

The new generation is more adaptable to technological changes and modern healthcare systems. They often embrace new approaches and value work-life balance and a more collaborative approach to patient care. Older nurses have been exposed to a traditional healthcare system and may have had to adapt to technological changes later in their careers.

Continuous education and professional development

The new generation is involved in all nursing and patient care areas. They are advancing in roles such as nurse advocates and nurse researchers. So, the new generation is expanding into new fields and trying to improve the nursing career by pursuing education and professional development. In contrast, the older generation focuses more on clinical areas and patient outcomes.

“There are more options available now , especially for the younger generations. Previously , options were limited. You would start at a hospital or a specific department and stay there. With education and different pathways , you can work in patient care or move into education or other areas. This variety of options makes it easier for the younger generations.” (Participant:8) . “The other thing that when you are dealing with the old generation , you’ll find the love to be with the patient , patient bedside dealing with the patient day today.” (Participant:13) .

Promotion of organizational openness and transparency

The old generation perceived transparency as the need for the new and old generations to openly discuss changes, address concerns, and collaboratively adapt to evolving practices, fostering a transparent and supportive environment in the nursing profession. “Create an environment where nurses and nurse managers can openly discuss changes in the profession , address concerns , and work together to adapt” (Participant 20).

The new generation perceives transparency as a valuable key to promoting change. Participant No. 1’s answers reveal this meaning: “By open communication , that will help. Straight communication and effective communication indeed will help in preparing for the change. As I mentioned before , I need some help or someone to communicate with my manager in my home country. Also , by ensuring that there is no second person between you and your manager , maintain good relationships.”(Participant:1).

This study assessed the generational gap between the new and the old generation. We have identified four main themes: optimizing the working environment, strengthening the work atmosphere through communication and values, cultivating respect and empathy, and dynamic enhancement of healthcare systems. Overall, the results of this study identify the generational gap between these two generations. Moreover, the findings of this research shed light on significant subthemes that highlight the evolving dynamics within the nursing profession, particularly the differences and similarities between new and old generations. The demographic data provided a clear understanding of the structure of both generations, with a notable representation of male staff nurses in the new generation and a diverse range of experiences in healthcare.

Working environment

Perceiving the work environment was evident as a generational gap in our study; the leadership style and other subthemes were also identified. This study discovered that the older generation significantly promotes effective leadership styles, including transformational and situational leadership. These styles enhance teamwork, promote autonomy, and ensure a supportive work environment. This is consistent with the findings of Cummings et al. (2018), who highlighted that transformational leadership positively impacts nurse satisfaction and patient outcomes by fostering a supportive and communicative work environment [ 14 ]. Furthermore, situational leadership is vital for the older generation in dynamic critical care units, offering flexibility to address staff readiness levels effectively [ 15 ].

On the other hand, the new generation stressed the importance of inner values such as respect, teamwork, accountability, and professionalism rather than the leadership style of the old generation. The new generation’s focus on internal values suggests a potential shift in organizational culture that prioritizes individual integrity and an attitude of collaboration over traditional hierarchical leadership approaches. This trend indicates that future healthcare entities’ strategies may incrementally prioritize cultivating an environment where ethical behaviors, mutual respect, and collective responsibility play crucial roles in achieving organizational success. This result is consistent with another study done by Boamah et al. (2018), who found that supportive leadership practices enhance nurses’ work engagement and patient care quality, emphasizing the need for recognition and acknowledgment strategies to boost job satisfaction [ 16 ].

In addition, our study evidently shows generational differences in adaptation to technological advancements, with the new generation demonstrating a higher ability to adopt new technologies into their practice. This finding is supported by Lera et al. (2020), who noted that the new generation is more comfortable with modern digital tools and evidence-based practices​ than the old generation [ 17 ].

Strengthening work atmosphere through communication and values

The current study has found that generational differences in communication preferences exist, with the new generation leveraging technology for more accessible communication. In contrast, the old generation prefers face-to-face interactions for clearer understanding. This aligns with the findings of Rosi et al. (2019), who noted that younger healthcare professionals are more likely to use digital communication tools, whereas the older generation favors traditional methods [ 18 ]. Effective communication strategies that bridge these generational gaps are crucial. Training on communication best practices and the use of technology for the old generation, as well as encouraging the new generation to develop strong interpersonal skills for face-to-face interactions, are crucial [ 19 ].

Regular feedback mechanisms are crucial for identifying and addressing concerns related to the work atmosphere. Boamah et al. (2018) suggest that understanding and addressing generational differences in work preferences can improve team cohesion and reduce conflicts, ultimately leading to better patient care [ 16 ]. The study participants also emphasized the importance of feedback in creating a positive work environment, consistent with the findings of Lin et al. (2021), who stressed the value of input in fostering a supportive workplace [ 20 ]. The current study found that creating a work culture where debate is encouraged, disagreements are respectful, and active listening helps build a team-oriented mindset. This finding aligns with research by Flores et al. (2023), who noted that promoting shared values and respectful communication enhances team cohesion and collaboration [ 21 ].

The current study has found another generational gap in respect and empathy. The new generation emphasizes the importance of having fair assignments, work-related discussions, and promotion opportunities [ 22 ]. Choi et al. (2018), consistent with our study, reported that fair clinical assignments will enhance staff satisfaction, improve nurses’ working conditions, and positively impact patient outcomes [ 23 ].

Professional self-concept is crucial to staff satisfaction, retention, and well-being [ 24 ]. The sense of purpose is part of the nurse’s professional self-concept; hence, the old generation, especially the leaders, must promote staff well-being by considering their purpose and fostering an environment of mutual benefit [ 25 ]. This finding aligns with the current study, which revealed that the new generation views a sense of purpose as fundamental to their professional needs.

The healthcare system is generally considered a significant influence on nursing careers. Regardless of generation, the healthcare system affects nurses and healthcare providers as it is continuously changed, modified, and developed, creating new challenges and opportunities for healthcare providers.

The progression of nursing practice has been significantly influenced by advancements in education and professional development, leading to a shift in roles and opportunities for nurses. The new generation, who are more adaptable to technological changes and evidence-based practices, are increasingly moving into diverse roles beyond traditional clinical settings. They are now prominent in fields such as nurse advocacy, research, and education, reflecting a broadening of the nursing profession and ultimately enhancing healthcare systems. This shift contrasts with the experiences of the older generation who have primarily focused on direct patient care within clinical environments. Recent studies support this trend. For instance, a study found that new nurses are more likely to engage in continuous education and seek roles that allow for more incredible professional growth and diversification than older nurses [ 26 ].

Our study revealed that creating an environment that promotes openness and transparency is essential for fostering effective communication and collaboration between different generations of nurses. Fostering mentorship and knowledge sharing bridges the generational gap and ensures the transmission of valuable experiences and practices. An open dialogue between nurses and nurse managers about changes in the profession, concerns, and adaptation strategies is critical for cohesive teamwork. These findings are consistent with Bragadóttir et al. (2022), which indicate that organizational transparency and open communication channels significantly enhance teamwork and job satisfaction among nursing staff [ 24 ].

This study highlights the evolving dynamics within the nursing profession, focusing on generational differences and similarities. The new generation is more skillful at integrating technology and embracing diverse roles beyond traditional clinical settings, whereas the old generation brings valuable experience and historical perspectives. Effective leadership, continuous education, and open communication are critical for optimizing the work environment, enhancing nurse satisfaction, and improving patient outcomes. Bridging the generational gap through mentorship and fostering a culture of respect and empathy are essential for a cohesive and resilient healthcare system.

Recommendations

Future research should explore strategies to effectively bridge the generational gap in nursing by integrating leadership styles, communication preferences, and technology adoption across different generations. Longitudinal studies could examine how generational dynamics evolve as new generations enter the workforce and older generations transition out, providing insights into the sustainability of organizational changes. Additionally, expanding research to diverse healthcare settings and cultural contexts would enhance the generalizability of findings. At the same time, intervention studies could test the effectiveness of tailored mentorship programs, continuous education initiatives, and organizational transparency in fostering intergenerational collaboration and improving patient care outcomes.

The study’s methodology, including potential sampling bias due to purposive selection, interviewer bias, and the subjective nature of data saturation, could also influence the results. Additionally, the context-specific nature of the study and the use of virtual interviews might limit the depth and transferability of the findings. Finally, time constraints may have restricted the comprehensiveness of the data collected.

Implications for nursing management

Nurse managers should adopt a multi-faceted leadership approach, embracing both transformational and situational styles, to meet the diverse needs of a multigenerational workforce. Implementing targeted communication training and fostering an environment of respect and empathy can improve team cohesion and patient outcomes. Investing in continuous professional development and technological training will further support the integration of new and experienced nurses.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to acknowledge the nurses and nurse managers who participated in the study.

This study was funded by the Medical Research Center at Hamad Medical Corporation (MRC-01-23-206).

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Department of Nursing, Hazm Mebaireek General Hospital, Hamad Medical Corporation, Doha, Qatar

Ahmad A. Abujaber, Abdulqadir J. Nashwan, Mark D. Santos, Nabeel F. Al-Lobaney, Rejo G. Mathew & Jamsheer P. Alikutty

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Albara M. Alomari

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AAA, AJN: Conceptualization. NFA, MDS, JK: Formal analysis.AAA, AJN, MDS, NFA, RGM, JPA, JK, AMA: Methodology, Data curation, Manuscript writing (draft and final review). All authors read and approved the final manuscript.

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Abujaber, A.A., Nashwan, A.J., Santos, M.D. et al. Bridging the generational gap between nurses and nurse managers: a qualitative study from Qatar. BMC Nurs 23 , 623 (2024). https://doi.org/10.1186/s12912-024-02296-y

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• Generational gap
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• Published: 06 September 2024

Self-perceived barriers to healthcare access for patients with post COVID-19 condition

• Iris M. Brus 1 ,
• Inge Spronk 1 ,
• Suzanne Polinder 1 ,
• Alfons G. M. Olde Loohuis 2 ,
• Peter Tieleman 2 ,
• Stella C. M. Heemskerk 1 ,
• Sara Biere-Rafi 2   na1 &
• Juanita A. Haagsma 1   na1  

BMC Health Services Research volume  24 , Article number:  1035 ( 2024 ) Cite this article

Metrics details

Many patients with post COVID-19 condition (PCC) require healthcare services. However, qualitative studies indicate that patients with PCC encounter many barriers to healthcare access. This cross-sectional study aimed to determine how many PCC patients report barriers to healthcare access and which barriers are reported, and to explore differences between subgroups.

Data were collected via an online survey from 10,462 adult patients with a confirmed or suspected COVID-19 infection in the Netherlands, who experienced persisting symptoms ≥ 3 months after the initial infection. To study self-perceived barriers, a list of eleven possible barriers was used, covering multiple aspects of healthcare access. Differences between subgroups based on sociodemographic characteristics, medical characteristics, PCC symptoms (fatigue, dyspnoea, cognitive problems, anxiety and depression), and healthcare use (general practitioner, paramedical professional, medical specialist, occupational physician and mental health professional) were studied through multivariable multinomial (0 vs. 1 vs. > 1 barrier) and binomial regression analyses (for each individual barrier).

A total of 83.2% of respondents reported at least one barrier to healthcare access. Respondents reported a median of 2.0 (IQR = 3.0) barriers. The barriers “I didn’t know who to turn to for help” (50.9%) and “No one with the right knowledge/skills was available” (36.8%) were most frequently reported. Respondents with younger age, higher educational level, not hospitalized during acute COVID-19 infection, longer disease duration, who had more severe PCC symptoms, and who did not consult an occupational physician or paramedical professional, were more likely to report barriers. Analyses per barrier showed that women were more likely to report financial and help-seeking barriers, while men were more likely to report barriers related to availability of care. Hospitalized respondents were less likely to report barriers related to availability of care, but not less likely to report financial or help-seeking barriers.

Conclusions

This study shows that the majority of patients with PCC experiences barriers to healthcare access. Particular attention should be paid to younger, non-hospitalized patients with a long disease duration and severe PCC symptoms. Efforts to remove barriers should focus not only on improving availability of care, but also on helping patients navigate care pathways.

Peer Review reports

The long-term effects of COVID-19 are increasingly recognized as a major public health challenge on a global scale [ 1 ]. Since the onset of the worldwide pandemic in 2020, there have been over 770 million confirmed cases of COVID-19 and although most patients recover shortly after the acute infection, an estimated 4–12% experience persisting symptoms [ 2 , 3 , 4 ]. The World Health Organization refers to these persisting symptoms as 'post COVID-19 condition' (PCC), defined as the continuation or development of symptoms occurring three months after the initial infection and lasting for at least two months, without any other explanation [ 5 ]. These symptoms encompass a broad spectrum, including fatigue, shortness of breath and cognitive problems, and appear to affect patients with both a mild and severe acute disease course [ 3 , 5 ].

Healthcare services for individuals with COVID-19 have rapidly been set up since the start of the pandemic, primarily for those with severe symptoms during the acute infection, through expanding the number of critical care beds, additional staffing and equipment, and temporary hospitals [ 6 ]. Less extensively, services have become available for those with PCC, primarily focusing on rehabilitation, with different care pathways being developed and studied [ 7 , 8 ]. Support for PCC patients is urgently needed, as a substantial number of patients suffering from PCC require healthcare services due to their persisting symptoms. Previous research shows increased healthcare utilization of PCC patients in the years following infection [ 9 , 10 , 11 , 12 ]. Given the substantial number of individuals likely affected by PCC, this increased healthcare utilization places a large burden on healthcare systems.

The care for PCC poses several challenges. Although the body of research on PCC is rapidly increasing and several different hypotheses are being studied, the pathophysiology remains unknown [ 13 ]. In addition, due to the complexity of the condition and the wide range of symptoms, previous studies emphasized the need for multidisciplinary, integrative care, involving many different specialties [ 7 , 14 ]. Moreover, as the degree of severity and the extent of functional limitations vary widely among those affected and as PCC might have a fluctuating or relapsing nature, adequate care likely requires tailoring to the needs of individual patients [ 7 , 14 ]. In spite of these challenges and the remaining uncertainty regarding the effects of rehabilitation for PCC, current evidence on the effectiveness of rehabilitation services for these patients suggests that it has beneficial effects on symptoms, functional limitations and quality of life [ 7 , 8 , 15 ].

Ensuring that PCC patients have access to adequate care is crucial, as earlier studies in other patient populations concluded that experiencing barriers to healthcare access is negatively associated with health-related quality of life and other health outcomes [ 16 , 17 , 18 ]. Yet previous research showed that patients with PCC experience difficulties in finding adequate care, including being unable to access care, long waiting lists, not being taken seriously, receiving conflicting and inconsistent advice, and fragmented healthcare services, i.e. lack of coordination between healthcare providers and no overall assessment of the impact of PCC [ 19 , 20 , 21 , 22 , 23 , 24 , 25 ]. Although these studies highlight relevant problems with current PCC care, the vast majority were of a qualitative nature, conducted in relatively small study populations. Research in a large population of PCC patients is needed to clarify the extent of these problems regarding access to care. Furthermore, it remains unknown whether certain subgroups of PCC patients experience more barriers to access healthcare than others. Previous studies in patient populations with other chronic diseases showed that factors such as gender, educational level, presence of comorbidities and disease severity are associated with experiencing barriers to care [ 26 ].

In order to ensure adequate healthcare access for PCC patients and to tackle barriers experienced by these patients, this study aimed to determine how many PCC patients report barriers to healthcare access, which barriers they report, and to explore differences between subgroups based on sociodemographic characteristics, medical characteristics, the presence of PCC symptoms and healthcare use. Based on previous qualitative research, we hypothesize that barriers experienced by PCC patients are related to different aspects of the healthcare system, including the navigation through available services. In addition, we hypothesize that patients with a low educational level, who have not been hospitalized, who experience severe symptoms and who experience cognitive problems have a higher likelihood of reporting barriers to healthcare access than other patients.

Study design, data collection and participants

For this cross-sectional study, data were collected via an online survey from patients with PCC registered at C-support. C-support is a Dutch foundation, commissioned by the Ministry of Health, that informs, advises and supports patients who experience long-term complaints after a confirmed or suspected COVID-19 infection. Patients can self-register at C-support if they experience symptoms and/or functional limitations at least 3 months after a COVID-19 infection. To register, patients are asked to complete an online form with some personal information and contact details, after which they are contacted by C-support to assess the need and possibility for support. Between February 2022 and February 2023, a total of 19,249 patients of all ages who were part of the C-support PCC registry were invited via email to participate in the study. If patients did not complete the survey within three weeks, a reminder email was sent. The survey was available in Dutch, and respondents were able to complete the survey in steps by saving their answers and resuming the survey later. Inclusion criteria for the present study were: age ≥ 18 years when completing the survey, an infection date ≥ 3 months prior to completing the survey, no missing data on PCC symptoms, reporting to have needed healthcare services, and having responded to the survey question on healthcare access. All data used in this study were extracted from the survey.

Sociodemographic characteristics

The survey contained questions on sociodemographic characteristics, including age (in years), gender, educational level, and ethnicity. Age was categorized into six groups: 18–24, 25–34, 35–44, 45–54, 55–64, and 65 years and older. Gender contained the following categories: man, woman, other, and rather not disclose. Educational level was categorized into three groups according to the International Standard Classification of Education (ISCED): low, middle, and high [ 27 ]. For ethnicity, the response options consisted of a list of the most common ethnicity groups in the Netherlands, an open option, and the option 'rather not disclose'.

Medical characteristics

Self-reported medical characteristics included month and year of initial COVID-19 infection, hospitalization during acute infection (yes/no), and the presence of comorbidity. Time since initial COVID-19 infection was calculated based on the number of months between initial infection and completing the survey, and was categorized into four groups: ≤ 6 months, 7–12 months, 13–18 months, and > 18 months. For comorbidity, the question consisted of a list of 14 chronic diseases (including asthma, COPD or chronic emphysema, inflammatory bowel disease, stroke, depressive disorder or anxiety disorder, serious heart or vascular problems, arthrosis, rheumatism, serious back problems, hypertension, cancer, diabetes, and thyroid abnormalities) and the options “other chronic disease” and “no chronic disease”. Respondents were categorized into two groups: no comorbidity and comorbidity [ 28 ].

PCC symptoms

Several self-reported PCC symptoms were assessed in the survey, including fatigue, dyspnoea, cognitive problems, anxiety, and depression. These symptoms were selected based on available information on commonly reported symptoms by PCC patients, and symptoms for which a standardized instrument was available. Fatigue was measured using the subscale fatigue severity of the Checklist Individual Strength (CIS) [ 29 ]. This subscale consists of eight items on a 7-point Likert scale. Total scores range from 8 to 56, and a score of 35 or higher is indicative of severe fatigue [ 30 ]. Dyspnoea was measured using the Medical Research Council (MRC) Dyspnoea Scale [ 31 ]. This scale assesses the degree of functional disability due to dyspnoea and ranges from grade 1 to 5. To measure cognitive problems, we used an additional item, or “bolt-on”, cognition for the EQ-5D-5L, a generic instrument to measure health-related quality of life [ 32 , 33 ]. Cognition was defined as “remembering, understanding, concentrating, thinking”. Respondents could select one of five response categories: “no problems”, “slight problems”, “moderate problems”, “severe problems” and “extreme problems”. Anxiety was measured using the GAD-2, the short version of the Generalized Anxiety Disorder 7-item questionnaire [ 34 ]. This version consists of two items assessing how often respondents were affected by each symptom during the last two weeks, with response categories ranging from 0 (“not at all”) to 3 (“nearly every day”). Total scores range from 0 to 6 and a score of 3 or higher indicates a possible generalized anxiety disorder. Depression was measured using the PHQ-2, the short version of the Patient Health Questionnaire 9-item [ 35 ], which also consists of two items with answers ranging from 0 (“not at all”) to 3 (“nearly every day”). A score of 3 or higher indicates a possible depressive disorder [ 36 ]. Although the instruments used to measure PCC symptoms have been validated in different patient population, they were not validated in PCC patients, due to the recent emergence of this condition.

Healthcare use

To assess healthcare use, respondents were asked which healthcare providers they had consulted for their complaints since the initial COVID-19 infection. Based on input from healthcare professionals and PCC patients, a list of 19 conventional healthcare providers was compiled. For the analyses, five dichotomous variables were created to determine whether respondents had consulted (1) a general practitioner, (2) a paramedical professional (including physiotherapist, occupational therapist, dietician or nutritionist, speech therapist, manual therapist, Cesar therapist, or Mensendieck therapist), (3) a medical specialist (including pulmonologist, internal medicine specialist, cardiologist, neurologist, rehabilitations specialist, ENT specialist, psychiatrist, or sports medicine specialist), (4) an occupational physician, or (5) a mental health professional (including psychologist, psychotherapist, or general practice mental health worker). Contextual information about the functioning of the healthcare system in the Netherlands and specific information about available PCC care is provided in Additional File 2.

Self-perceived barriers to healthcare access

To measure self-perceived barriers to healthcare, we used a list of 11 possible barriers (Table  2 ) based on a report from the Netherlands Institute for Health Services Research on the self-management of patients with chronic conditions [ 37 ]. The original list consisted of 14 barriers: two of the original barriers (“I couldn't find the specific help I wanted” and “I was not aware of the rules or procedures for asking for help”) were not included, as there was some overlap between barriers. In addition, the barriers “No one with the right knowledge was available” and “No one with the right skills was available” were merged into “No one with the right knowledge and/or skills was available”. The question was formulated as “Have you ever encountered one or more of the following problems when arranging healthcare services?”. Respondents could answer “Yes” or “No” for each barrier, in addition to the exclusive answer options “No, I have not encountered any of these problems” or “Not applicable, I did not need healthcare services”. Respondents could also select an option “Other, namely”. Respondents who did not need healthcare services or who only selected the option “Other” were excluded. Due to the limited number of characters available for respondents to elaborate on the option “Other” and the wide variety in provided answers, we were unable to use this information in the analyses.

Data analyses

Descriptive statistics were performed for sociodemographic characteristics, medical characteristics, PCC symptoms, and healthcare use. The total number of experienced barriers was reported (median and interquartile range (IQR)), as well as the proportion of respondents who reported each barrier. In addition, Pearson correlation coefficients between each pair of barriers were reported. To determine whether sociodemographic characteristics, medical characteristics, PCC symptoms or healthcare use were associated with self-perceived barriers to healthcare access, logistic regression analyses were performed. As the proportion of patients from ethnic minority groups was very low, this variable was not included in the analyses due to the lack of statistical power. First, multinomial logistic regression analyses were done with the number of reported barriers as the dependent variable, categorized into three groups: 0 reported barriers (reference), 1 barrier and > 1 barrier. Multinomial logistic regression was chosen as cumulative odds ordinal logistic regression was not possible due to violation of the assumption of proportional odds. The number of barriers was categorized into three groups as we hypothesized that respondents reporting only one barrier might differ from respondents reporting > 1 barrier, and this categorization provided additional insight into the association between independent variables and the likelihood of reporting barriers. Subsequently, the different types of barriers patients experienced were studied. As correlation coefficients between individual barriers were relatively low, we decided not to categorize the barriers and did not perform a cluster analysis. Instead, each barrier was studied individually to determine the association with sociodemographic characteristics, medical characteristics, PCC symptoms and healthcare use. Thus, binomial logistic regression analyses were performed for each individual barrier (coded as “did not experience specific barrier” versus “experienced specific barrier”). For both the multinomial and binomial logistic regression analyses, a backward stepwise selection process was used to determine the independent variables included in the final model, removing variables with the largest p -value until all remaining variables had a statistically significant p -value (< 0.05). All independent variables were categorical, and the largest category (i.e. the category containing most respondents) was selected as the reference category. The assumption of multicollinearity was checked (variance inflation factor < 10 indicating no multicollinearity). Odds ratios (OR), 95% confidence intervals (95%-CI) and p -values were reported. All analyses were performed using IBM SPSS version 28.

A total of 19,249 patients were invited to participate, of whom 11,230 completed the survey (58.3%). Of those, 211 respondents (1.9%) were excluded from the analyses because they were younger than 18 years old when completing the survey, infection date was unknown, infection date was less than 3 months prior to completing the survey, or because data on PCC symptoms was missing. An additional 557 respondents (5.1%) were excluded because they had not needed healthcare services ( n  = 209), or because they had only responded ‘Other’ to the survey question on healthcare access ( n  = 348). Thus, 10,462 respondents (93.2%) were included in the analyses (Additional File 1, Fig. 1).

The median age of respondents was 48.0 years (IQR = 17.0), and the majority were women (76.0%) and had a high educational level (54.0%) (Table  1 ). Almost half of the respondents had a comorbidity (47.0%), and 8.0% was hospitalized during the acute COVID-19 infection. Time since infection ranged from 3 to 35 months, with 17.0% infected ≤ 6 months prior to completing the survey, and 30.4% infected > 18 months prior. Most respondents experienced slight to extreme cognitive problems (92.4%), had severe fatigue (89.5%), and experienced at least some functional impairment due to dyspnoea (67.2%). About one quarter of respondents had a possible depressive disorder (28.9%) or anxiety disorder (24.8%). Most respondents had consulted a general practitioner (95.4%), a paramedical professional (93.4%), an occupational physician (74.0%), or a medical specialist (61.8%) for their complaints, while fewer respondents had consulted a mental health professional (45.7%).

Respondents who reported more barriers were slightly younger, had a higher educational level, less often had a comorbidity, were less often hospitalized and had a longer disease duration ( p  < 0.001) (Table  1 ). They had higher rates of fatigue, dyspnoea, cognitive problems, possible anxiety disorder and depressive disorder ( p  < 0.001). Healthcare use also significantly differed between the three groups. Respondents reporting 1 barrier were least likely to have consulted each type of healthcare provider, except a mental health professional. The largest percentage differences between groups were seen for medical specialist and mental health professional: a medical specialist was consulted by 56.4% of those reporting 1 barrier compared to 64.8% of those reporting > 1 barrier, and a mental health professional was consulted by 38.6% of those not reporting any barriers compared to 49.5% of those reporting > 1 barrier.

Reported barriers

A total of 83.2% of respondents reported at least one barrier to healthcare access; 19.3% reported 1 barrier, 63.9% reported > 1 barrier and 26.8% reported > 3 barriers (Additional File 1, Table  1 ). Respondents reported a median of 2.0 (IQR = 3.0) out of 11 barriers. The three most reported barriers were “I didn’t know who to turn to for help” (50.9%), “No one with the right knowledge and/or skills was available” (36.8%), and “The person I asked for help was unable to help me” (34.1%) (Table  2 ). The correlation between barriers is presented in Fig.  1 , showing relatively low correlation coefficients ranging from 0.026 to 0.362. Barriers with the strongest correlation were “The help I sought was not reimbursed” and “The help or aid I wanted was too expensive” (0.362), followed by “No one with the right knowledge and/or skills was available” and “The person I asked for help was unable to help me” (0.350).

Heat map of correlation coefficients between each pair of barriers. See Table 2 for the corresponding barrier

Differences between subgroups based on sociodemographic characteristics

Multinomial logistic regression analyses showed that younger respondents had higher odds of reporting 1 and > 1 barrier compared to no barriers than older respondents (e.g. 45–54 years = reference; 18–24 years: OR 1 barrier  = 2.006, p  = 0.015 and OR >1 barrier  = 3.042, p  < 0.001) (Table  3 ). Binomial logistic regression analyses showed the same pattern for each individual barrier: younger age was associated with higher odds of reporting each barrier (Additional File 1, Table  2 A-D).

No statistically significant association was found between gender and reporting 1 and > 1 barrier compared to no barriers. However, analyses per barrier showed that some barriers were significantly more often experienced by women compared to men, namely: “I felt uncomfortable asking for help, because I felt like a burden” (OR = 0.707; p < 0.001), “The help or aid I wanted was too expensive” (OR = 0.707, p  < 0.001), “The help I sought was not reimbursed (OR = 0.830, p  = 0.002), and “According to the care provider/organization, I was not eligible for help” (OR = 0.830, p  = 0.013). In contrast, the following barriers were significantly more often experienced by men: “No help was available for my specific needs” (OR = 1.445, p  < 0.001), “The person I asked for help was unable to help me”(OR = 1.227, p  < 0.001), “I didn’t know who to turn to for help” (OR = 1.171, p  < 0.001), and “No one with the right knowledge and/or skills was available” (OR = 1.144, p  = 0.009).

Educational level

Respondents with a low or middle educational level had lower odds of reporting > 1 barrier compared to no barriers than those with a high educational level (low educational level: OR >1 barrier  = 0.439, p  < 0.001; middle educational level: OR >1 barrier  = 0.643, p  < 0.001). Respondents with a lower educational level also had lower odds of reporting each individual barriers, except “The help or aid I wanted was too expensive” and “It was difficult to apply for help due to complicated laws and regulations”, for which no significant association was found.

Differences between subgroups based on medical characteristics

Comorbidity.

No association was found between comorbidity and reporting 1 and > 1 barrier compared to no barriers. However, analyses per barrier did show a significant association with two barriers. Those with comorbidity had lower odds of reporting the barriers “The help I sought was not reimbursed” (OR = 0.829, p  < 0.001) and “No one with right knowledge and/or skills was available” (OR = 0.865, p  = 0.001) than those without comorbidity.

Hospitalization during acute COVID-19 infection

Hospitalized respondents had lower odds of reporting 1 and > 1 barrier compared to no barriers than non-hospitalized respondents (OR 1 barrier  = 0.726, p  = 0.005; OR >1 barrier  = 0.550, p  < 0.001). Analyses per barriers showed that hospital admission was also significantly associated with lower odds of reporting the following five barriers: “No one with right knowledge and/or skills was available” (OR = 0.622, p  < 0.001), “The person I asked for help was unable to help me” (OR = 0.628, p  < 0.001), “No help was available for my specific needs” (OR = 0.632, p  < 0.001), “I had to wait a long time until help was available” (OR = 0.657, p  < 0.001) and “I didn’t know who to turn to for help” (OR = 0.803, p = 0.004). However, hospitalized respondents had higher odds of reporting “It was difficult to apply for help due to complicated laws and regulations” (OR = 1.396, p = 0.021).

Time since infection

Respondents infected more recently had lower odds of reporting 1 and > 1 barrier compared to no barriers than those infected earlier (e.g. > 18 months = reference;  ≤ 6 months: OR 1 barrier  = 0.515, p  < 0.001 and OR >1 barrier  = 0.301, p  < 0.001). Analyses per barrier showed the same pattern for all barriers, except for “The person I asked for help didn’t have time”, for which no significant association was found.

Differences between subgroups based on PCC symptoms

Severe fatigue.

Respondents without severe fatigue had lower odds of reporting > 1 barrier compared to no barriers than those who experienced severe fatigue (OR >1 barrier  = 0.730, p < 0.001). Analyses per barrier showed that those not experiencing severe fatigue also had lower odds of reporting the following individual barriers: “The help I sought was not reimbursed” (OR = 0.713, p < 0.001), “According to the care provider/organization, I was not eligible for help” (OR = 0.772, p  = 0.026), “I had to wait a long time until help was available” (OR = 0.819, p  = 0.025), and “I felt uncomfortable asking for help, because I felt like a burden” (OR = 0.811, p  = 0.012).

Dyspnoea was significantly associated with reporting barriers: compared to respondents with grade 1, those with more severe dyspnoea had higher odds of reporting > 1 barrier (e.g. grade 1 = reference; grade 5: OR >1 barrier  = 1.682, p  = 0.007), although no significant association was found between grade 4 and grade 1. Dyspnoea was also significantly associated with all individual barriers, except “I didn’t know who to turn to for help”, “The help I sought was not reimbursed” and “No help was available for my specific needs”.

Cognitive problems

Cognitive problems were also associated with reporting barriers, although the association was only statistically significant when comparing no problems to moderate problems (moderate = reference; OR 1 barrier  = 0.685, p  < 0.001 and OR >1 barrier  = 0.607, p  < 0.001) and severe problems to moderate problems (OR >1 barrier  = 1.177, p  < 0.001). Those experiencing more severe cognitive problems also had higher odds of reporting individual barriers, except for “The person I asked for help didn’t have time”.

Anxiety and depression

Respondents with a possible anxiety disorder had higher odds of reporting > 1 barrier compared to no barriers than those without a possible anxiety disorder (OR >1 barrier  = 1.300, p  = 0.001). Similarly, respondents with a possible depressive disorder had higher odds of reporting 1 and > 1 barrier compared to no barriers than those without a possible depressive disorder (OR 1 barrier  = 1.344, p  = 0.001; OR >1 barrier  = 1.496, p  < 0.001). In addition, those with possible anxiety disorder had higher odds of reporting 7 out of 11 individual barriers and those who had a possible depressive disorder had higher odds of reporting 5 out of 11 barriers. Only “According to the care provider/organization, I was not eligible for help” was not significantly associated with either possible anxiety disorder or possible depressive disorder.

Differences between subgroups based on healthcare use

General practitioner.

For general practitioner, there was a significant association when comparing those reporting 1 barrier to those not reporting any barriers: respondents who had not consulted a general practitioner had higher odds of reporting 1 barrier compared to no barriers than those who had consulted a general practitioner (OR 1 barrier  = 1.368, p  = 0.029). In contrast, analyses per barrier showed that those not having consulted a general practitioner had lower odds of reporting the following five barriers: “The person I asked for help was unable to help me” (OR = 0.488, p  < 0.001), “No help was available for my specific needs” (OR = 0.626, p  = 0.008), “No one with the right knowledge and/or skills was available” (OR = 0.682, p  < 0.001), “The help I sought was not reimbursed” (OR = 0.682, p  = 0.005), and “I felt uncomfortable asking for help, because I felt like a burden” (OR = 0.755, p  = 0.012).

Paramedical professional

Respondents who had not consulted a paramedical professional had higher odds of reporting 1 and > 1 barrier compared to no barriers than those who had consulted a paramedical professional (OR 1 barrier  = 2.170, p  < 0.001; OR >1 barrier  = 1.649, p  < 0.001). Those not having consulted a paramedical professional also had higher odds of reporting the barriers “I felt uncomfortable asking for help, because I felt like a burden” (OR = 1.433, p  < 0.001) and “No help was available for my specific needs” (OR = 1.296, p  = 0.028). However, they had lower odds of reporting the barriers “No one with the right knowledge and/or skills was available” (OR = 0.657, p  < 0.001) and “The help I sought was not reimbursed” (OR = 0.723, p  = 0.004).

Medical specialist

Respondents who had not consulted a medical specialist had lower odds of reporting > 1 barrier compared to no barriers than those who had consulted a medical specialist (OR >1 barrier  = 0.809, p  < 0.001). Those who had not consulted a medical specialist also had lower odds of reporting 7 out of the 11 total barriers (ORs ranging from 0.550–0.806), but had higher odds of reporting the barrier “I felt uncomfortable asking for help, because I felt like a burden” (OR = 1.129, p  = 0.014).

Occupational physician

Respondents who had not consulted an occupational physician had higher odds of reporting 1 and > 1 barrier compared to no barriers than those who had consulted an occupational physician (OR 1 barrier  = 1.485, p < 0.001; OR >1 barrier  = 1.477, p  < 0.001). Those not having consulted an occupational physician also had higher odds of reporting 7 individual barriers (ORs ranging from 1.191–1.550), but had lower odds of reporting the barrier “I had to wait a long time until help was available” (OR = 0.874, p  = 0.020).

Mental health professional

Respondents who had not consulted a mental health professional had lower odds or reporting > 1 barrier compared to no barriers than those who had consulted a mental health professional (OR >1 barrier  = 0.844, p  = 0.005). Those who had not consulted a mental health professional also had lower odds of reporting 8 individual barriers (ORs ranging from 0.595–0.877).

This study determined the extent to which PCC patients report barriers, which barriers they report, and explored differences between subgroups. We found that the majority of respondents experienced at least one barrier to healthcare access, with a median of 2 out of 11 barriers. The barriers most often reported were “I didn’t know who to turn to for help”, “No one with the right knowledge and/or skills was available” and “The person I asked for help was unable to help me”. The association between several independent variables and the number of reported barriers, as well as the types of barriers was studied. As correlations between barriers were relatively low, these analyses were performed for each barrier individually in order to stay as close as possible to the original data. Nevertheless, some barriers appeared to cover the same aspect of healthcare access, which was reflected in the pattern of associations with independent variables. These aspects of healthcare access include: financial barriers (“The help I sought was not reimbursed”, “The help or aid I wanted was too expensive” and “According to the care provider/organization, I was not eligible for help”), availability of care (“No one with the right knowledge and/or skills was available”, “The person I asked for help was unable to help me” and “No help was available for my specific needs”), and timeliness of care (“I had to wait a long time until help was available” and “The person I asked for help didn’t have time”), which is the terminology that will be used throughout the discussion. We found that respondents with lower age, higher educational level, who were not hospitalized during the acute COVID-19 infection, who had a longer disease duration, who had more severe PCC symptoms, and who had not consulted a paramedical professional or occupational physician had significantly higher odds of reporting 1 and > 1 barrier compared to no barriers to healthcare access. Analyses per barrier showed that women had higher odds of reporting financial barriers as well as feeling uncomfortable asking for help, while men had higher odds of reporting barriers related to availability of care. In addition, hospitalized respondents had lower odds of reporting barriers related to availability of care compared to non-hospitalized respondents.

The proportion of patients in our study population that reported at least one barrier to healthcare access was high: over 80% experienced at least one barrier, with over 25% reporting four barriers or more. In comparison, previous research on barriers to healthcare utilization among patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), a similar disabling condition, found that 55% reported at least one barrier [ 38 ]. A recent study by Karpman et al. among adult PCC patients in the United States corroborates the multitude of barriers to accessing healthcare services experienced by this patient population: they concluded that PCC patients were more likely to report unmet healthcare needs compared to those with COVID-19 diagnosis but without PCC and those who tested negative for COVID-19 [ 24 ]. Their findings showed that unmet healthcare needs among PCC patients were attributable to challenges including costs of care, finding a healthcare professional accepting new patients, and getting a timely appointment. The proportion of PCC patients reporting financial barriers and barriers related to timeliness of care in this earlier study was similar to our results (financial: 27.0% in study Karpman vs. 8–23% in our study depending on barrier; timeliness: 22% vs. 9–26%). However, the most common barriers in our study were different: our respondents most frequently reported that they did not know where to go for help and that there was lack of availability of care, which were not investigated in the study by Karpman et al. Nevertheless, studies in other patient populations, including chronic disease patients, confirm that the availability of services is one of the most commonly cited barriers to healthcare access [ 38 , 39 ].

Although we cannot fully elucidate the underlying causes of the reported barriers to healthcare access, these frequently reported barriers point towards several different problems with current PCC care. It appears that there is a lack of knowledge among healthcare providers consulted by PCC patients, resulting in patients receiving inadequate support, which has also been reported by earlier qualitative studies [ 19 , 21 , 25 ]. As PCC is a relatively new condition with, at the moment, an unknown pathophysiology, uncertain prognosis, and no curative treatment, the lack of knowledge and adequate support from healthcare providers is not surprising [ 13 ]. Nevertheless, this finding emphasizes the need to provide healthcare providers with clear and regularly updated clinical guidelines and to provide training and education to those involved in PCC care. Clearly, further development of the knowledge base, and continued funding for studies investigating the pathophysiology, prognosis and possible treatment options is also a priority in order to organize adequate care. In addition, the fact that over half of respondents report the barrier “I didn’t know who to turn to for help” highlights the need for easier navigation through health services and clear points of contact for patients. Previous qualitative studies similarly emphasized the importance of coordination and continuity of care to improve healthcare access, especially given the multifaceted nature of the condition, often requiring the involvement of many specialities [ 20 , 22 ]. One of the suggested solutions is assigning the responsibility for care coordination to one designated clinician to ensure continuity of care for these patients [ 22 ].

The problems and solutions mentioned in the previous paragraph are all related to factors on a healthcare system-level. However, factors on a personal level, such as having insufficient skills to seek healthcare services (e.g. lacking health literacy), are also known to affect access to healthcare. A review on barriers to healthcare access for patients with Parkinson’s disease, a similarly complex condition involving many different healthcare disciplines, showed that barriers occur at both a person- and health system-level [ 40 ]. The authors of this study primarily emphasized the need to overcome person-level barriers, as they concluded that there is a lack of attention for these types of barriers. However, as PCC is a new condition with a rapidly increasing body of research, and as care pathways are still under development, it appears that efforts to improve access to PCC care should primarily focus on resolving barriers related health system-level factors, while paying attention to personal-level factors.

Association with sociodemographic characteristics

Our findings show that several factors are associated with the number and type of barriers that PCC patients report. Lower age was associated with reporting more barriers, which is in line with previous research among patients with chronic diseases [ 41 , 42 ]. Possible explanations for these age differences are a lack of experience in navigating health services or different expectations from these services [ 43 ]. Interestingly, although previous studies among patients with ME/CFS and other chronic diseases concluded that women are more likely to report barriers than men, we found no association between gender and the likelihood of reporting barriers [ 38 , 41 ]. However, analyses per barrier showed that women and men reported different barriers, with women more often reporting financial barriers, which is in line with earlier research among patients with cardiovascular-related chronic diseases [ 44 ]. In contrast, men more often experienced barriers related to availability of care and knowing who to turn to for help.

In addition, our findings indicate that those with a high educational level report more barriers to healthcare access compared to those with a lower educational level. These results appear to be in contrast with previous studies that suggest either no association or an inverse association [ 38 ,  45 ]. We hypothesize that the association found in our study is at least partially due to the selection of participating PCC patients caused by the sampling method. All patients invited for this study self-registered in the C-support PCC registry. Due to the online self-registration process, highly educated respondents are likely overrepresented in our study sample, and low educated patients who experienced barriers might have been less likely to register compared to highly educated respondents who experience barriers. Another explanation for these surprising results could be that highly educated patients have higher levels of health literacy, and are possibly more familiar with ongoing research, current treatment and management options. Thus, they might be more aware of what is lacking in currently available PCC care, leading to highly educated patients reporting more barriers.

Association with medical characteristics

Hospitalization during the acute COVID-19 infection was associated with reporting barriers to healthcare access, as our results showed that hospitalized respondents are less likely to report 1 and > 1 barrier than non-hospitalized respondents. Previous qualitative studies among PCC patients corroborate this finding, as they reported a lack of guidance for non-hospitalized patients [ 21 ]. Analyses per barrier showed that hospitalized patients have lower odds of reporting barriers mainly related to availability of care. A possible explanation for these findings is that hospitalized patients might receive rehabilitation or follow-up consultations after discharge from the hospital, thus having easier access to support for long-term complaints [ 8 ]. In addition, healthcare providers might be more aware of the possibility of long-term complaints for this patient group compared to non-hospitalized patients who experienced a mild acute disease course.

Besides hospitalization, disease duration was also associated with barriers to healthcare access, as those with a longer disease duration were more likely to report 1 and > 1 barrier. This might be due to the limited availability of healthcare services during the earlier phases of the pandemic. Half of our study population was infected in 2020, and during this phase, the healthcare system struggled to handle the large influx of patients with acute COVID-19, services for PCC were still in the process of being set-up, and knowledge of healthcare providers on this new condition was very limited [ 20 , 46 ]. Aside from the pandemic phase, patients may experience more barriers the longer their symptoms last. As their symptoms and functional limitations continue to impact their daily life, and they possibly experience growing frustration with the available care, patients might be more likely to report barriers.

Association with PCC symptoms

Furthermore, our findings showed that PCC patients who experienced severe fatigue, dyspnoea, cognitive problems, a possible anxiety disorder, or a possible depressive disorder, were more likely to experience 1 and > 1 barrier than those who do not experience these symptoms or who experience less severe symptoms. These results indicate that those with a more complex manifestation of PCC, i.e. more symptoms or more severe symptoms, are more likely to experience barriers to healthcare access. A previous systematic review similarly suggested that factors such as disease severity and reduced health status are associated with experiencing barriers to receiving optimal care among individuals with chronic diseases [ 26 ]. Due to the cross-sectional design of this study, the direction of the association between PCC symptoms and barriers to healthcare access remains unclear. Although earlier research found that experiencing barriers to healthcare access has a negative impact on a multitude of health outcomes, having more severe PCC symptoms could also increase the likelihood of reporting barriers [ 18 ]. Future research with a longitudinal design could elucidate the impact of barriers to accessing PCC care on health outcomes.

Association with healthcare use

The association between healthcare use and barriers to access differed between the different types of healthcare providers. Respondents who had not consulted an occupational physician or paramedical professional were more likely to report 1 and > 1 barrier than those who had consulted these healthcare providers. In contrast, the inverse association was observed for medical specialists and mental health professionals: those who had consulted these providers actually more often reported barriers. For general practitioner, the association was unclear. Although these results seem somewhat conflicting, it does show that it is not the lack of access to a medical specialist that leads to barriers, as suggested in a previous study [ 22 ]. In addition, these findings seem to indicate that consulting a paramedical professional or occupational physician might lead to reporting less barriers. However, this does not appear to be the case for each individual barrier, so that conclusion should be interpreted with caution. When interpreting these results, it is also important to take into account that the timeline of healthcare use was not specified in the survey. Thus, whether respondents experienced barriers before or after they consulted a healthcare provider is unknown.

Strengths and limitations

The strengths of this study include the large cohort of PCC patients and the broad range of possible barriers that was studied, which covered multiple aspects of healthcare access. In addition, by looking at a variety of factors that could influence perceived access to care simultaneously, we provide a clear overview of subgroups that have a high risk of reporting suboptimal healthcare access. Furthermore, the response rate of 58% was quite high, particularly considering the severity of symptoms reported by respondents.

However, this study also has several limitations. The primary limitation concerns the sampling method: the study population consisted of patients who self-registered at a PCC registry, meaning that respondents might not be representative of all PCC patients in the Netherlands. Respondents appear to have quite severe symptoms and we hypothesize that patients in our study population have a higher likelihood of reporting barriers to healthcare access compared to the average PCC patient. Thus, the high proportion of patient reporting barriers is possibly an overestimation. Furthermore, these patients might have higher health literacy than the average patient, as they were aware of the existence of C-support and registered themselves at this foundation in order to receive support. In line with this assumption, patients with a high educational level appear to be overrepresented in our sample. Nevertheless, we believe that our findings provide valuable insight into the most important barriers experienced by PCC patients and those who are most at risk for experiencing barriers. Second, it is important to mention that self-perceived barriers do not directly translate to actual healthcare access, as a higher likelihood of reporting barriers could also be attributable to factors other than poor access. For example, a previous study suggested that patients who perceive barriers may be more sensitive to unmet care needs as a result of more engagement in their care or higher degrees of health literacy [ 44 ]. Third, the survey question on healthcare access was broadly formulated, meaning that respondents could have interpreted the question as referring to general barriers to healthcare access, instead of barriers specifically pertaining to PCC care. However, the purpose of the study was clearly stated multiple times in the invitation, title and the survey itself. Fourth, although we included multiple sociodemographic and medical characteristics, as well as several ‘core’ symptoms of PCC, the list of possible determinants was not exhaustive. For example, previous studies found that patients that are part of an ethnic minority experience more barriers, as well as different barriers, compared to other patients [ 19 ]. However, as only a very small proportion of respondents in this study belonged to an ethnic minority, we were unable to investigate the association between ethnicity and self-perceived barriers to healthcare access. The lack of representation of ethnic minorities in our study could have led to an underestimation of specific barriers that are more often experienced by ethnic minorities. For example, these patients could experience more financial barriers, be less likely to ask for help due to cultural differences or have more difficulty communicating with healthcare providers. Thus, it is important to take this into account in future studies to provide more generalizable results and to determine the influence of ethnicity on possible disparities in healthcare access. Future studies should specifically target minority groups and possibly use a different sampling method (e.g. using patient records) to reach these respondents. Future studies should also further look into the impact of socio-economic status on healthcare access, as our unexpected findings regarding this association might be due to the sampling method, selection bias and/or non-response bias. Additionally, while we examined multiple common PCC symptoms, other symptoms such as post-exertional malaise (PEM), postural orthostatic tachycardia syndrome (POTS), and headache were not included in the survey. As recent research has shown that these symptoms, among others, are frequently reported and possibly pose challenges in receiving adequate care, a more extensive list of core symptoms should be included in future research [ 47 , 48 , 49 ]. Fifth, although we used validated questionnaires for most symptoms, cognitive problems were measured using a single item with five response options comparable to the EQ-5D-5L items. However, this single cognition item is not an officially validated instrument. Sixth, due to the cross-sectional nature of this study, it is unclear whether symptoms were already present before the COVID-19 infection; these symptoms are not necessarily due to PCC. Lastly, the data collection period spans over a year, during which changes occurred regarding public health measures that were in place, availability of healthcare services and awareness of PCC, which have not been accounted for in our analyses.

The findings of this study show that many PCC patients experience barriers to healthcare access, with most of them having difficulty finding adequate support within the established healthcare facilities. The number and variety of barriers reported by patients highlights the complexity of organizing adequate care for this new and still relatively unknown condition. Nevertheless, addressing the obstacles that patients encounter when trying to access healthcare services is crucial, as PCC has a substantial impact on both patients and society, and suboptimal access to care could contribute to the persistence of long-term complaints. Efforts to improve healthcare access for this patient population should not only focus on the availability of healthcare services, but also on helping patients navigate care pathways, removing help-seeking barriers (e.g. feeling uncomfortable asking for help), and financial barriers. Creating national care paths for PCC patients with detailed guidelines about when to involve which professionals could provide both healthcare professionals and patients with clarity about treatment and support options. In addition, more patient education about the available care for PCC, government regulations and ongoing developments might also help patients navigate healthcare services, for example via patient information websites such as the Dutch Thuisarts.nl. A specific focus should be on providing easily accessible information for those with lower health literacy, low educational level and ethnic minority groups. Our study shows that sociodemographic characteristics, medical characteristics, and PCC symptom severity should be taken into account when addressing barriers, as these factors influence the number and type of barriers patients experience. Particular attention should be paid to younger, non-hospitalized patients with a long disease duration and severe PCC symptoms. We therefore recommend not only to increase awareness of the barriers experienced by PCC patients, but also educate key professionals in PCC care (e.g., general practitioner, physiotherapist, occupational physician, general practice mental health worker) on patient subgroups that have a higher likelihood of experiencing barriers. Additional research is needed to clarify the effect of factors such socioeconomic status and ethnicity, and to investigate potential measures to improve access to care for PCC patients.

Availability of data and materials

The dataset supporting the conclusions of the current study is available for researchers who meet the criteria for access to data upon request which can be applied at the Data Access Committee of C-support.

Abbreviations

Checklist Individual Strength

Generalized Anxiety Disorder 2-item questionnaire

Interquartile range

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Medical Research Council Dyspnoea Scale

• Post COVID-19 condition

Post-exertional malaise

Patient Health Questionnaire 2-item

Postural orthostatic tachycardia syndrome

95% Confidence interval

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The funding for this study was provided by C-support, a Dutch foundation, commissioned by the Ministry of Health, that informs, advises and supports patients who experience long-term complaints after the initial COVID-19 infection. C-support assisted in the design and execution of.

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Iris M. Brus, Inge Spronk, Suzanne Polinder, Stella C. M. Heemskerk & Juanita A. Haagsma

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IMB, IS, SP, AGMOL, PT, SBR and JAH conceptualized and designed the study. IMB, IS, PT and SP collected the data. IMB analysed the data. IMB, IS and JAH interpreted the data. IMB drafted the manuscript and IS, SP, AGMOL, PT, SCMH, SBR and JAH reviewed and critically revised the manuscript. All authors approved the final manuscript and agreed to be accountable for all aspects of the work.

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Research Article

Barriers and facilitators for implementing the WHO Safe Childbirth Checklist (SCC) in Mozambique: A qualitative study using the Consolidated Framework for Implementation Research (CFIR)

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Current address: Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, Connecticut, United States of America

Affiliation Department of Health Policy, Yale School of Public Health, New Haven, Connecticut, United States of America

Roles Data curation, Investigation, Methodology, Project administration, Resources, Validation

Affiliations Comité para Saúde de Moçambique, Maputo City, Mozambique, Mozambique Ministry of Health, Maputo City, Mozambique

Roles Validation, Writing – review & editing

Affiliation Department of Social and Behavioral Sciences, Yale School of Public Health, New Haven, Connecticut, United States of America

Roles Formal analysis

Roles Resources, Supervision

Affiliation Mozambique Ministry of Health, Maputo City, Mozambique

Roles Conceptualization, Supervision

Affiliation Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, United States of America

Roles Data curation, Methodology

Affiliation Comité para Saúde de Moçambique, Maputo City, Mozambique

Affiliation Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America

Roles Conceptualization, Methodology, Resources, Supervision, Validation, Writing – review & editing

Affiliation Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America

Roles Conceptualization, Data curation, Methodology, Resources, Validation, Writing – review & editing

Affiliation Department of Health Systems and Global Health, Southern Medical University, Guangzhou, Guangdong, China

• Anqi He, 
• Elsa Luís Kanduma, 
• Rafael Pérez-Escamilla, 
• Devina Buckshee, 
• Eusébio Chaquisse, 
• Rosa Marlene Cuco, 
• Mayur Mahesh Desai, 
• Danícia Munguambe, 
• Sakina Erika Reames, 

• Published: September 5, 2024
• https://doi.org/10.1371/journal.pgph.0003174
• Reader Comments

High maternal and neonatal mortality rates persist in Mozambique, with stillbirths remaining understudied. Most maternal and neonatal deaths in the country are due to preventable and treatable childbirth-related complications that often occur in low-resource settings. The World Health Organization introduced the Safe Childbirth Checklist (SCC) in 2015 to reduce adverse birth outcomes. The SCC, a structured list of evidence-based practices, targets the main causes of maternal and neonatal deaths and stillbirths in healthcare facilities. The SCC has been tested in over 35 countries, demonstrating its ability to improve the quality of care. However, it has not been adopted in Mozambique. This study aimed to identify potential facilitators and barriers to SCC implementation from the perspective of birth attendants, clinical administrators, and decision-makers to inform future SCC implementation in Mozambique. We conducted a qualitative study involving focus group discussions with birth attendants (n = 24) and individual interviews with clinical administrators (n = 6) and decision-makers (n = 8). The Consolidated Framework for Implementation Research guided the questions used in the interviews and focus group discussions, as well as the subsequent data analysis. A deductive thematic analysis of Portuguese-to-English translated transcripts was performed. In Mozambique, most barriers to potential SCC implementation stem from the challenges within a weak health system, including underfunded maternal care, lack of infrastructure and human resources, and low provider motivation. The simplicity of the SCC and the commitment of healthcare providers to better childbirth practices, combined with their willingness to adopt the SCC, were identified as major facilitators. To improve the feasibility of SCC implementation and increase compatibility with current childbirth routines for birth attendants, the SCC should be tailored to context-specific needs. Future research should prioritize conducting pre-implementation assessments to align the SCC more effectively with local contexts and facilitate sustainable enhancements in childbirth practices.

Citation: He A, Kanduma EL, Pérez-Escamilla R, Buckshee D, Chaquisse E, Cuco RM, et al. (2024) Barriers and facilitators for implementing the WHO Safe Childbirth Checklist (SCC) in Mozambique: A qualitative study using the Consolidated Framework for Implementation Research (CFIR). PLOS Glob Public Health 4(9): e0003174. https://doi.org/10.1371/journal.pgph.0003174

Editor: Julia Robinson, PLOS: Public Library of Science, UNITED STATES OF AMERICA

Received: January 2, 2024; Accepted: August 8, 2024; Published: September 5, 2024

Copyright: © 2024 He et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Our article includes selected excerpts from the qualitative data we collected and synthesized. When we sought ethical approval from the National Committee for Bioethics in Health (CNBS) in Mozambique and conducted the consent process with participants, we did not specify that the full transcripts would be made publicly available. Many of the topics discussed in interviews were of a sensitive nature, and participants may not have felt comfortable sharing their perspectives if we had asked to make the conversations public. Therefore, we feel that releasing full transcripts would not adhere to our ethics and consent practices, and would like to share further information only upon request. For those interested in accessing the interview transcripts, access requests can be directed to the National Committee for Bioethics in Health (CNBS) at [email protected] or to the study PI at [email protected] .

Funding: This work was supported by grants from the 2022 Wilbur G. Downs Fellowship at Yale University (AH, US$4,000), the 2022 Yale School of Medicine Fellowship for Medical Student Research (AH, US$2,000), and the 2022 Lindsay Fellowship for Research in Africa from the Yale MacMillan Center’s Council on African Studies (AH, US$1,000). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Wilbur G. Downs Fellowship: https://bit.ly/3aAvJCk Yale School of Medicine Fellowship: Internal application that doesn’t have a URL. Lindsay Fellowship for Research in Africa: https://bit.ly/3roHFh4 .

Competing interests: The authors have declared that no competing interests exist.

Introduction

The global efforts towards achieving the World Health Organization (WHO) Sustainable Development Goal 3 (Ensure healthy lives and promote well-being for all at all ages) have significantly reduced pregnancy-related deaths, especially in sub-Saharan Africa (SSA) [ 1 ], one of the regions most affected by maternal and neonatal mortality in the world [ 2 ]. Guided by the Mozambican Strategic Plan for Health Sector 2014–19 and the Government’s Five-Year Plan 2020–24 [ 3 , 4 ], the Mozambican government has substantially improved maternal and child health (MCH) outcomes by expanding care services and enhancing their quality. Between 2015 and 2021, maternal mortality in Mozambique decreased by 75.8% [ 5 ], neonatal mortality by 8% [ 6 ], and stillbirth rates declined by 7.4% [ 7 ]. While Mozambique shares a similar neonatal mortality ratio of 27 per 1,000 live births [ 8 ] and a stillbirth rate of 17 per 1,000 total births with overall SSA [ 9 ], it has a significantly lower maternal mortality ratio (MMR) of 127 deaths per 100,000 live births compared to the overall MMR of 536 deaths per 100,000 live births in SSA [ 10 ].

Despite these improvements, maternal and neonatal mortality ratios and stillbirth rates remain unacceptably high in Mozambique with pregnancy and childbirth complications as the leading causes: 86% of maternal deaths result from direct obstetric complications [ 11 ], and 75% of newborn deaths are caused by prematurity, childbirth-related complications, and neonatal infections [ 12 ]. Most of these deaths are preventable and treatable but continue to occur at high rates in low-resource settings [ 13 ].

To address maternal and perinatal morbidity and mortality, the WHO developed the Safe Childbirth Checklist (SCC) in 2015 (see S1 Text ) [ 13 ]. The SCC sets forth a structured list of evidence-based delivery practices which target the major causes of maternal deaths, neonatal deaths, and stillbirths in healthcare facilities, especially in lower- and middle-income countries (LMICs). The SCC streamlines the routine flow of childbirth delivery events into four pause points at which birth attendants ensure that they have completed essential birth practices: (a) on admission, (b) just before pushing (or just before a Caesarean-section), (c) soon after birth, and (d) just before discharge. The SCC prompts birth attendants to implement essential practices which have been shown to improve the quality of care delivered to mothers. A birth attendant’s omission of even one of the SCC items can render the mother and their newborn vulnerable to serious and potentially lethal complications.

The SCC has been implemented and evaluated in over 35 countries, demonstrating varied levels of effectiveness in reducing childbirth complications and improving maternal and newborn health outcomes [ 14 ]. Previous studies conducted in India, Ethiopia, Tanzania, Sri Lanka, Bangladesh, Kenya, Uganda, and Namibia have demonstrated that the implementation of SCC contributed to the overall improvement of the quality of care for mothers and newborns [ 15 – 21 ]. Key findings indicate that SCC adoption leads to increased birth attendant adherence to essential birth practices, improved inventory management for essential supplies, facilitated clinical decision-making, enhanced communication and teamwork among providers, and better management of complications. Moreover, research conducted across various settings has highlighted the significant impact of the SCC in reducing perinatal mortality and stillbirths. In Namibia, Kenya, Uganda, and Rajasthan, India, the implementation of the SCC was associated with decreased perinatal mortality, including facility-based stillbirths, very early neonatal deaths, and neonatal mortality among low-birthweight and preterm infants [ 18 , 21 , 22 ]. Moreover, a post-hoc analysis from the BetterBirth trial in Uttar Pradesh, India, revealed significantly lower odds of perinatal and early neonatal mortality with each additional SCC practice performed [ 15 ].

At least 11 countries in Africa have adopted and adapted the SCC: Rwanda, Ethiopia, Burkina Faso, Guinea, Côte d’Ivoire, Mali, Nigeria, Tanzania, Uganda, Kenya, and Namibia [ 14 , 16 – 18 , 23 – 25 ]. The experiences in these countries have provided fresh and valuable insights into local adaptations, facilitators, and barriers to successful implementation of the SCC [ 26 , 27 ]. The primary facilitators of SCC implementation were characteristics inherent to the checklist itself, including its ease of completion and comprehension, and its effectiveness as a job aid for essential practices [ 14 ]. Additional enabling factors identified included leadership commitment, provider motivation, and comprehensive training and supervision regarding SCC usage [ 14 , 23 ]. Barriers to SCC implementation frequently related to a shortage of clinical staff and essential birth and checklist supplies, a lack of professional training on the SCC, perceptions of increased workload due to the SCC usage, and challenges that often coincided with delivering quality maternal care [ 14 ]. Therefore, as research across multiple regions has underscored, adapting the SCC to the local context is crucial to align it with local guidelines and for its adoption by healthcare professionals. For example, in Burkina Faso and Côte d’Ivoire, health providers suggested integrating the SCC with existing tools like the partograph and displaying it in maternity wards as a reminder of critical birth practices [ 23 ]. In Kenya and Uganda, local modifications aimed at enhancing preterm birth outcomes included integrating a triage pause for initial assessments, focusing on assessing gestational age and managing preterm labor, and adjusting the SCC to better align with national care standards [ 25 ].

Despite its strong potential to improve maternal and newborn health outcomes, the SCC has not been adopted in Mozambique, one of the poorest countries in the world with major infrastructural constraints in its healthcare system, which could potentially benefit from the SCC implementation. Advancing improvements in lowering maternal and neonatal mortality, along with enhancing the overall health of the population, are key strategic aims outlined in the Mozambique Government’s 2020–2024 Five-Year Plan [ 4 ]. These objectives are also central to the UNICEF-Mozambique 2022–2026 Strategic Plan and key to the UNDP-Mozambique collaboration goals [ 28 , 29 ]. Although various national guidelines specific to certain procedures and complications during childbirth exist, they are not systematically integrated as in the SCC. Moreover, little is known about current childbirth practices in Mozambique and the feasibility and acceptability of adopting the SCC in local healthcare facilities. This formative study aims to identify facilitators and barriers to potential implementation of the SCC in Mozambique, provide insights into current childbirth practices and infrastructure in the country, and guide the Mozambique Ministry of Health (MoH)’s decisions on SCC adoption and adaptation to improve MCH outcomes nationwide.

Study setting

In Mozambique, the public health system is organized and administered at the national, provincial, and district levels. This structure includes four levels of health facilities, each with distinct roles and capacities. Maternity care is similarly organized within this structure [ 30 ].

Primary-level health facilities, designated as health centers, serve as the primary point of contact for the population. They provide primary health care and are classified as urban or rural based on their location, with some only having the minimal capacity to perform vaginal childbirth deliveries and others not being able to do so [ 31 ]. Secondary-level hospitals, divided into district, rural, and general hospitals, provide referral care, emergency services, and surgeries. They provide more comprehensive maternity services such as assisted deliveries and basic obstetric surgeries, but their capacity to perform C-sections varies by hospital. Tertiary and quaternary-level hospitals, which include provincial, central, and referral hospitals, provide specialized care and serve as referral centers with the capacity to offer advanced and comprehensive obstetric and neonatal care, including emergency C-sections for complicated pregnancies and births.

The study was conducted in Maputo city and Manhiça district in Maputo province, Mozambique. Maputo city is the capital and the largest city of Mozambique with a population of 1.09 million in 2017 [ 32 ]. It is located at the southern end of the country, close to Mozambique’s border with Eswatini and South Africa. The city is divided into 7administrative divisions, spanning a land area of 347.69 square kilometers. Compared to the rest of the country, Maputo City is notably better equipped with health personnel and facilities. It has 37 health facilities, including 1 quaternary central hospital, 3 secondary general hospitals, and 33 primary health centers—27 urban and 6 rural [ 33 ]. Manhiça District is a rural district in Maputo Province, covering 2,373 square kilometers and located 80 kilometers north of Maputo City, with a population of two hundred thousand [ 34 , 35 ]. Manhiça district has 21 primary rural health centers and health posts and 2 secondary rural, district referral hospitals [ 33 ].

Our study sites, Chamanculo General Hospital in Maputo City and Xinavane Rural Hospital in Manhiça District are both secondary hospitals offering comprehensive maternity care. While Chamanculo General Hospital does not offer C-section services, Xinavane Rural Hospital does. The maternity wards at both hospitals are divided into three areas: admission, delivery, and postpartum [ 31 ]. These areas correspond to the four pause points that the SCC uses to streamline the routine flow of childbirth delivery care: on admission, just before pushing (or C-section), soon after birth, and just before discharge. The birth attendants who participated in our study are essentially MCH nurses with midwifery skills, working 12-hour shifts [ 30 ]. They also rotate across various MCH departments within the hospitals, demonstrating proficiency in family planning, prenatal, intrapartum, and postnatal care, as well as gynecological services. Both hospitals employ a mix of different level MCH nurses, categorized by the extent of their education and training, including elementary (equals to Grade 7), basic (Grade 10), mid-level (Grade 12), and high-level (college-educated) nurses. MCH nurses with higher levels of education are equipped to manage more complex obstetric and gynecological cases, with those at the highest level being qualified to perform C-sections.

The information system in maternity care primarily consists of patient registration forms [ 36 ]. MCH nurses in maternity wards complete comprehensive registration forms for each mother, documenting clinical conditions and information from admission to discharge. These forms capture basic patient information, such as name, age, and national ID number, and clinical information, including gestational age, childbirth procedure and outcome, direct and indirect obstetric morbidity, and newborn conditions. Maternity care also incorporates data collection systems from various specific programs, such as the HIV and malaria programs [ 30 ]. From admission to the postpartum period, MCH nurses log and monitor progress of pregnancy, childbirth, postpartum conditions for mothers and newborns, and their medications.

Different guidelines are employed in different parts of the maternity ward. In general, the admission room personnel have access to guidelines for managing hypertension in pregnancy and sexually transmitted infections in pregnant women such as HIV and syphilis. The delivery room is equipped with guidelines for neonatal resuscitation. The postpartum services have guidelines for managing postpartum hypertension, postpartum infection management, and neonatal sepsis. All rooms follow guidelines for managing maternal bleeding before, during, and after childbirth. The current guidelines are specific to certain procedure or complication but are not integrated as the SCC. There is also no current standardized monitoring or reporting checklist used in the maternity wards.

The hospitals were selected as study sites for focus group discussions (FGDs) and interviews with providers taking into account the distance to the researchers’ office located in Maputo City, their capabilities to perform comprehensive maternity care, and their distinct rural and urban contexts. The inclusion of a diversity of hospitals offered a broad perspective on the varying conditions within Mozambican health facilities.

Study design

To ensure a comprehensive perspective, this qualitative study consists of three types of participants: birth attendants, clinical administrators, and decision-makers. The study conducted four FGDs with twenty-four birth attendants and six individual interviews with clinical administrators from Xinavane Rural Hospital in Manhiça District, Maputo Province, and Chamanculo General Hospital in Maputo City, as well as eight individual interviews with decision-makers at the MoH, the Departments of Public Health for Maputo city and Maputo province, and the Association of Midwives in Mozambique. The interviews and FGDs were guided by the Consolidated Framework for Implementation Research (CFIR) and covered four of five CFIR domains: (a) individual characteristics, (b) intervention (SCC) characteristics, and the facility’s (c) outer settings and (d) inner settings [ 37 ].

Data collection

Participants for this study were recruited using purposive sampling methods, aiming to include individuals with diverse backgrounds who were highly knowledgeable and experienced in following and implementing various policies and clinical guidelines related to childbirth practices and fulfilled the inclusion criteria and could offer valuable insights relevant to our research questions. The recruitment and data collection period took place September 16 th , 2022 to February 10 th , 2023. The FGDs with birth attendants and the interviews with clinical administrators were conducted at secure private offices at the two hospitals. One interview with a decision-maker was conducted via Zoom, while the other interviews with decision-makers took place either at the secure office of the Comité para a Saúde de Moçambique (Mozambique’s Health Committee) in Maputo or at the interviewees’ private offices. The clinical administrators interviewed at each clinical site included those managing MCH care. The clinical administrators also helped the study identified the birth attendants for FGDs. Each focus group comprised five to six birth attendants who met the inclusion criteria: being 18 years or older, having at least one year of experience in maternity care, availability and willingness to participate, fluency in Portuguese, and the ability and capacity to give consent. Similarly, clinical administrators and decision-makers were eligible if they had at least one year of experience managing or monitoring maternity services or MCH programs, were 18 years or older, fluent in Portuguese, available and willing to participate, and capable of giving informed consent. Decision makers were identified through the networks of our local collaborators with the Comité para Saúde de Moçambique and the Mozambique MoH. All participants were approached by a female researcher (AH, DM, or EK) and obtained written consent for participation in the interviews or the FGDs.

To assess the impact of various factors on SCC implementation, we designed the question guides of the FGD and interview based on CFIR. The questions were designed to assess current childbirth practices and infrastructure as well as the feasibility of implementing SCC to improve maternal and perinatal outcomes in Mozambique. The interview and FGD guides were tailored to the roles and responsibilities of the participants (see S2 Text ). We created a pilot FGD guide and tested it to ensure that study participants could adequately contribute to a rich discussion (see S1 Table ). The pilot FGD was conducted at Malhangalene Centro De Saúde (Health Center at Malhangalene) with seven birth attendants from five different health centers who did not work at the two selected clinical sites where formal data collection was to be conducted. The officers at Association of Midwives designated the birth attendants who participated in the pilot FGD. Each of them had rich prenatal-to-postnatal-care work experience from their clinical rotations in the maternity wards. We adjusted the structure and wording of the questions as needed and enhanced the moderating skills of the researchers during pilot [ 38 ].

Prior to data collection, all participants were given hard copies of the WHO SCC at least one day before the interview and FGD to familiarize themselves with its contents. After the interview and FGD, the SCC copies were collected by the researchers to avoid any unintended consequences resulting from the use of the SCC without proper instruction and support. The overall purpose of the SCC and each of its check items were explained to study participants before the FGD and interview. Participants were given opportunity before and after the FGD and interview to ask questions about the SCC and study, and those questions were subsequently addressed by the researchers. This was done to ensure all participants comprehended the content and intended use of the SCC. Participants received compensation for their participation.

Each interview and FGD lasted approximately 60 minutes, and each was scheduled at the convenience of participants, most often during their lunch breaks. All interviews and FGDs were conducted in Portuguese. A researcher (EK or DM) went through the SCC and the consent form verbatim in Portuguese before each interview or FGD and asked if there were any questions related to the study, the SCC, or the consent before the session started. Any questions raised by the participants were addressed accordingly. Participants signed written consent forms before interviews and FGDs. To assure their anonymity, participants were identified with a participant ID instead of their names during data collection and analysis. The interviews for clinical administrator and FGDs for birth attendants were conducted by two qualitative researchers, one of whom (EK) has a Doctor of Medicine degree from the School of Medicine at Eduardo Mondlane University in Mozambique and a Master of Public Health degree from Southern Medical University in China. EK had been working as a physician, district health director, and researcher at MoH since 2014, and she was also responsible for identifying and contacting the hospitals, clinical administrators, and decision-makers. The other researcher (DM) is a local research assistant has a bachelor’s degree in social science from Eduardo Mondlane University in Mozambique and is a qualitative researcher by training. The decision-maker interviews were conducted by EK and AH. AH has a Master of Public Health in Health Policy with formal qualitative study training from Yale School of Public Health in the U.S. The researchers worked in pairs during the interviews and FGDs. One served as the moderator and took detailed notes. The other researcher took comprehensive field notes and was also responsible for timekeeping. The field notes captured the behaviors and nonverbal cues of participants and, as complementary information to facilitate later data coding and analysis, described the physical spaces in which the interviews and FGDs were conducted [ 39 ].

All interviews and FGDs were recorded for later transcription, translation, and data analysis. Within 24 hours after each interview and FGD, the researchers also completed a summary report for each data collection session, including observations, personal reflections, memos, and key takeaways.

The hard copies of the research materials, such as field notes and consent forms, are stored in a locked cabinet in a locked office at Comité para a Saúde de Moçambique, and the electronic data, such as audio recordings and transcripts, were stored in Box, a secure password-protected database authorized by Yale University.

Data analysis

The audio recordings of the interviews and FGDs were uploaded to HappyScribe, a password-protected online software, and then transcribed and translated from Portuguese to English. To ensure their accuracy and integrity, the transcriptions and translations were then carefully reviewed by a bilingual researcher, EK.

The data analysis was performed by a team of three female researchers, AH, DB, and SR, from Yale University with formal qualitative study training. The data from FGDs and clinical administrators were coded and analyzed by AH, DB, and SR, and the data from decision-makers were coded and analyzed by AH and SR. The information in transcripts that might reveal the participant’s identity was removed. The data analysis employed a rigorous deductive thematic method, enabling a thorough and nuanced analysis of the data [ 40 ]. The coding process used a deductive approach, using the pre-established CFIR codebook as a guide [ 37 ]. During the development of the codebook, exemplar quotes, enriched code definitions and descriptions, and detailed inclusion and exclusion criteria were added to the initial CFIR codebook in Microsoft Excel to provide clear guidance for the coding process and contextualize the CFIR codebook for our study.

After developing the codebook, each member of the data analysis team independently coded each transcript using the comment feature in Microsoft Word. Throughout the coding process, the data analysis team met regularly to review and discuss the coded segments line by line and resolve any discrepancies through highly participatory group discussions to achieve consensus and ensure the coding consistency. When the coding was completed in the Microsoft Word, the transcripts were imported to NVivo 14, a qualitative analysis software, and recoded to match the coding in Word. The NVivo was used to enable the retrieval of the coded segments and facilitate the systematic analysis of the codes. The data analysis team also incorporated feedback from the interviews and FGDs moderators (EK and DM) to ensure the interpretations were aligned to the data. Furthermore, the detailed narrative for each code and findings from the coding process were organized according to each of the CFIR domains. Finally, the data analysis team identified common themes across the findings categorized by the CFIR domains. These themes were then categorized into SCC implementation facilitators and barriers.

Ethical statement

This study was approved prior to the start of data collection by the Human Subjects IRB committee at Yale University in the United States in May 2022 (IRB protocol #2000032748) and the Comité Nacional de Bioética para a Saúde in Mozambique (National Committee for Bioethics in Health, CNBS) in September 2022 (IRB protocol #00002657). Prior to collecting data, participants were provided with a consent form. EK went through the consent form in a thorough and word-for-word manner, explaining all aspects of the study, including the participants’ right to choose whether to participate, their ability to withdraw from the study at any point, the procedures in place for safeguarding the confidentiality and anonymity of their information, and the general contents of the FGD and interview. Participants were required to sign the consent forms if they wanted to participate, with one copy provided to them for their own records and another kept as part of the study documentation at the Maputo office of Comité para a Saúde de Moçambique.

Inclusivity in global research

Additional information regarding the ethical, cultural, and scientific considerations specific to inclusivity in global research for this study is included in the Supporting Information ( S1 Checklist ).

Conceptual framework

The CFIR examines the implementation environment of an intervention, and how to facilitate its effective implementation through the lens of five domains, (a) intervention characteristics, (b) outer setting, (c) inner setting, (d) individuals’ characteristics, and (e) implementation process [ 37 ]. As this is a formative study to assess the feasibility of SCC implementation, we excluded the implementation process domain as the SCC has not yet been implemented. Among the four domains, we identified eleven constructs that are relevant to our study for analyzing the qualitative data: (a) intervention characteristics (complexity, adaptability, relative advantage, and innovation cost), (b) outer setting (policies and laws, partnerships and connections, and societal pressure), (c) inner setting (compatibility, available resources, and culture), and (d) characteristics of individuals (knowledge and beliefs about the intervention).

Twenty-four birth attendants participated in the FGDs, and six clinical administrators and eight decision-makers took part in the individual interviews. As no new information emerged after the four FGDs and fourteen individual interviews, we considered that information saturation was reached. The duration of FGDs ranged from 39 minutes to 62 minutes, and interview time ranged from 26 minutes to 70 minutes. Detailed sociodemographic characteristics of the participants are presented in Table 1 .

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https://doi.org/10.1371/journal.pgph.0003174.t001

All codes identified from the transcripts were mapped to CFIR constructs. Of the 48 CFIR constructs assessed, eleven were determined to be relevant barriers and/or facilitators to implementing the SCC. Specifically, one CFIR construct addressed facilitators (complexity), and five CFIR constructs addressed barriers (adaptability, relative advantage, innovation cost, available resources, and societal pressure). Six other CFIR constructs addressed both facilitators and barriers (policies and laws, partnerships and connections, compatibility, culture, and knowledge and beliefs about the intervention). The study findings were organized by themes below, and Table 2 linked the barriers and facilitators of the SCC implementation to specific CFIR constructs.

https://doi.org/10.1371/journal.pgph.0003174.t002

Facilitators

The scc is simple and easy to understand..

When participants were asked about the complexity of the SCC, they agreed that the content and format of the checklist were easy to understand.

“I don’t think it is complicated at all. It just has basic aspects of everyday life in a maternity ward, or the day-to-day life of a midwife, or a nurse, so I don’t think it’s complicated. It’s direct, it has very concrete aspects.” (Decision-maker 5)

The SCC aligned with the national maternal and child health agenda.

The participants stated that the current MoH guidelines and efforts were consistent and reflected in the SCC objectives, indicating that the SCC implementation aligned with the national maternal and child health agenda.

“In general, one (SCC) is applying what are practices according to the MoH guideline, which is humanized childbirth or humanization of childbirth… All nurses have this orientation.” (Clinical Administrator 5)

Participants mentioned that strong support and commitment from both the local community and public health leaders about safe childbirth were crucial, as they can significantly contribute to spreading information on MCH and motivate clinics and birth attendants to engage in the SCC implementation effort.

“We, in the community, have the community leaders, maternal health nursing component, and the traditional midwives. They help information dissemination of the maternal and child health package… We will be able to involve them, to know that there is a checklist… so that they can help the dissemination of information.” (Decision-maker 4)

Furthermore, decision-makers emphasized that the MoH undertook regular supervision visits, offered technical support, and conducted in-service training at clinics. These initiatives are designed to ensure guidelines compliance and improve service quality in maternity wards. Such efforts aligned with the objectives of the SCC and may aid in its effective implementation.

“We do the monitoring of the activities, supervision… both scheduled supervisions and surprise visits. We make surprise visits to maternity hospitals, mainly to check if in fact they are doing their job well… We also reinforce it with some in-service training. When we get there, in these supervisions, we also explain: ‘Look, you are not doing it right here.’ We correct what is good practice and follow up on the needs.” (Decision-maker 1)

Participants had positive beliefs about the SCC.

During the interviews and FGDs, the participants displayed a strong understanding, wealth of knowledge, and a high level of professionalism and dedication to improving the quality of childbirth practices. They were open to updating their knowledge using the SCC and acknowledged the importance of continuously learning and keeping themselves informed.

“Science is dynamic. There are things that are being abolished and things that are being introduced. So, I try to say you should implement this study, while one thing or another could be abolished, so as we are here the council, we are here today to learn…. Let’s give progress to this study.” (Birth Attendant 8)

Moreover, participants expressed confidence that the implementation of SCC would lead to positive changes in current practices and result in improved quality of maternity services.

“I think that the list has a format that goes according to what we are talking about, because what we need is a standard procedure for the teams. Then, for the complications, we will have more trained people, but we also need team with a minimum standard procedure, and the list is simple. It is a list that reduces the time of work or procedure of the colleague… I find the list simple and sufficient.” (Decision-maker 7)

The SCC was viewed as redundant.

Participants expressed that the SCC did not offer a significant advantage over their current work routine, viewing it as an additional form to fill out and adding to the workload of birth attendants.

“It would be one more instrument. It would be a repetition of what we already do… All these flowcharts that we have already exist. And that is exactly what we do. And it looks like we don’t read it, because this, because that, but no. We already do that … We end up having less time to do our activities, to exercise the technique. We stay longer, we have [to] read and write, which doesn’t help us much either. It is very tiring.” (Birth Attendant 3) “I don’t think that the Checklist, by itself, will meet the needs… what will happen is this list will be one more paper in the maternity ward… The form alone is not going to change anything. It is one more piece of paper, it is going to be one more tool. As I said, the current guideline already recommends many of these questions, and they are in the form. What do we do? We fill it out, fill it out, fill it out.” (Decision-maker 6)

The SCC might be incompatible with the current workflows.

The concepts and practices outlined in the SCC were found to be mostly consistent with current practices in the maternity unit according to the participants. Filling out the SCC itself, however, is likely to impede existing workflows due to human resource shortages and time constraints. Participants expressed concerns about how to allocate time for other clinical activities and fill out the SCC, as there may be competing priorities.

“Because of the overload of work, one or another thing ends up slipping away… We have gynecology, maternity, c-sections, pathological pregnancy, gynecology, admission, delivery room, it’s for one nurse… So, everything that happens there ends up exhausting your knowledge, and your strength, you don’t know what to do…. It’s not because she is unwelcome [the SCC], she is welcome, yes. But treating the person himself, the work, it becomes difficult to follow the form.” (Birth Attendant 9)

Moreover, participants expressed concern about the workload related to paperwork. They already had a significant amount of paperwork to fill out, and the addition of SCC might increase their workload. Some participants suggested simplifying the current paperwork instead of introducing a new one.

“It is complicated because we already have many instruments. If the list doesn’t come to remove anything, it comes to add, it’s another job… Now, if the list comes and reduces the work for us, and summarizes a lot of things, it is welcome. If it is to add to it, it will not make us comfortable.” (Clinical Administrator 4)

The SCC needs to be better aligned with the context.

Although the SCC was viewed as simple and easy to understand, participants voiced the need to adapt it to the local context. Participants proposed multiple adaptations to integrate the SCC into their work routines and contexts, enhancing its implementation feasibility. These adaptations included transforming the SCC into a pocketbook rather than adding it to existing paperwork, displaying it as a wall poster, incorporating a section explaining incomplete practices, using it to evaluate supply availability, and merging it with existing tools like the patient clinical registration form, which includes medical history and diagnoses.

“My suggestion would be that it should be in a format like these HIV flowcharts, for example. You don’t make us waste time even opening a document and looking for how to do it. Then nail it to the wall…the person looks, sees the explanations and does it. It is easier to do than in the form of a list.” (Clinical Administrator 2) “Or maybe one could think of a decentralized instrument, which could perhaps feed into another instrument already at the central level… If we had an instrument that helps us to check what is the quality of the work of our maternity ward… And maybe to send the information to the central level as well, to see what is happening, what is failing, which is to take the proper precautions.” (Clinical Administrator 5)

Inadequate external support may hinder SCC implementation.

Participants emphasized that the external financial support from the MoH to maternal health care was inadequate, and the assistance from funders and partners was distributed unevenly across the country, often focused on specific diseases in a vertical manner. This could impede the adoption and implementation of the SCC, given that maternal health care is currently underfunded and not given priority.

“The financial allocation for the reduction of maternal and child mortality in a direct way is minimal, is reduced, and is ineffective. We have a maternal and child health plan in a year that cannot meet 50% of the needs… The use of external funds, which is far from the Paris Declaration, we don’t have much flexibility of funds to decide where they are allocated. The care area is underfunded, and it is the area that we should improve. We have pillars that are necessary [to be improved, including] educating how the delivery has to be, pregnancy care, the significance of various stages of pregnancy, labor expectations, pain management, and practices." (Decision-maker 7)

With the specific pillars the decision-maker highlighted also being key elements in the SCC, the current lack of financial support for maternal and child health care could signal potential challenges in implementing the SCC.

Resource shortfalls may impede SCC implementation Resource shortfalls may impede SCC implementation.

A major barrier to the SCC implementation is the limited availability of resources, including human resources, materials, physical space, and professional training. Despite the perceived benefits of SCC, the severe shortage of resources makes it challenging to successfully implement the SCC in clinical settings.

“What we need in Mozambique, in fact, is more equipped rooms, more spacious rooms, because our infrastructure sometimes does not create these types of conditions for a well-designed guideline. The strategies are well designed, but our conditions don’t help us, they don’t favor us having this model birth (SCC) that we are talking about, which would be better.” (Decision-maker 3)

Notably, participants expressed concern that the implementation of SCC would further increase their overwhelming workload as there is typically only one nurse per shift in the maternity unit, responsible for caring for both mothers and newborns. The already serious staff shortage could not accommodate the addition of another instrument that might increase the provider burnout. Allocating scarce time to complete the SCC would further increase staff workload.

“The implementation of the list is not bad. But as we were just saying… the lack of human resources, I think that this list will be more of an overload, an extra work, where the staff at that moment are few… But the list is not bad. It is very good, it helps. It is the moment when someone can forget something, looking here, sees that here is something that can be done or should be done. But looking at the work you already have in the maternity ward, it’s a lot. There are many documents to be filled out. One more document, it’s more overload.” (Birth Attendant 18) “We would feel overwhelmed. [The nurse] couldn’t fill out… and she is going to be overload. How is it? She will even ask herself, ‘but can’t you see? Because I am all alone.’” (Birth Attendant 17)

The scarcity of essential birth supplies in the maternity ward posed another significant barrier to implementing the SCC and achieve its purpose to enhance the quality of childbirth practices.

“For the maternity case, we are missing too many antihypertensives. Just talk about methyldopa, hydralazine, dihydralazine… and this has made our work very difficult.” (Clinical Administrator 5) “There are no gloves. How will it go well? How will you take care of yourself? How will you comply with what the document [SCC] asks for?” (Clinical Administrator 1)

Meanwhile, the participants highlighted the importance of professional training for successful SCC implementation and requested refresher training to improve their knowledge and skills.

“I think that if the people who are [going] to use the checklist are not very well trained, they can have a complication because it [the SCC] can be filled out not in the same standard way. The training of the people who are going to use the form itself needs to be standardized.” (Clinical Administrator 4)

Furthermore, the cost of the SCC implementation poses another challenge. The health facilities in Mozambique have very limited resources, and the costs of reproducing, distributing, storing, and completing the SCC, including expenses such as printers, paper, and storage space, could add an additional financial burden on the clinics.

“The list is produced, and then it is the health unit’s responsibility to reproduce it. And that doesn’t go very far, because we will see that the health unit doesn’t have the capacity to reproduce the form itself…It is already difficult for the health unit to continue because they are not all able to multiply their own records.” (Clinical Administrator 4)

Low motivation and societal pressures deter providers from adopting SCC.

Participants indicated that their existing workload, particularly with paperwork and completing instruments, was already overwhelming. They expressed concerns about their ability to properly fill out additional forms, suggesting that introducing a new instrument could be daunting.

“We get blinded in front of a document. Many times, we get scared just by looking at the document. Do this, we have to fill it out like this. Sometimes we fill it out, but not properly as it should be.” (Birth Attendant 10) “Whenever we get a new instrument, there is resistance in change, because at some point, the nurses have to give their reasons because they have too many instruments to be able to fill out, to be able to check. When more than one instrument arrives, they get a little tired, a little angry, because we have many books to fill in.” (Decision-maker1)

Additionally, some participants expressed concerns that failure to fill out the SCC could result in penalties or other negative consequences.

“It would be possible [to implement the SCC]. It would help some, but it could also penalize us for things that are not our level of competence to resolve, such as the issue of lack of medicines, lack of running water, at some point in the anesthesia machine, a shortage of operating room staff.” (Clinical Administrator 5)

Moreover, many birth attendants reported experiencing stigma and pressure from mass media, local community, and patients, which further limited their motivation to adopt another instrument like SCC and improve the quality of the maternal and child health services.

The participants expressed that the social recognition of birth attendants was low, and this lack of recognition was a demoralizing factor in their work. Despite the birth attendants’ strong desire to improve their work and adopt SCC, they felt that their efforts were not valued or recognized by the community.

“Because if we look at the media, they are against us. Just for someone to be born outside, we are already on television. But if I attend childbirth outside without gloves to help, I won’t be on television. But if someone is born outside, even five meters from the hospital, we are going to be smeared with all of this. ‘Chamanculo is negligent, there was no emergency room.’ So, motivation factor.” (Birth Attendant 15)

There were instances in which the companions or patients complained the practices of the birth attendants, resulting in the spreading of negative comments about the birth attendants in the community, further diminishing their motivation to work.

“Even being a woman, a companion [of the delivery mother] doesn’t understand what happens inside the maternity ward. Even the techniques that the nurse will perform, she thinks you’re mistreating that person… She starts talking bad about us in the community.” (Birth Attendant 6)

Main findings and interpretation

This formative qualitative study sought to identify potential facilitators and barriers to implementing the SCC in the context of the childbirth practices and conditions in Mozambique at the time this study was conducted. The study explored the feasibility of SCC implementation by assessing the initial knowledge and attitudes of a diverse group of stakeholders from various professional backgrounds.

The barriers and facilitators identified in our study agree with most of the findings from the countries where the SCC had been tested before [ 14 , 21 , 26 , 27 , 41 ]. The common facilitators of SCC use were related to the checklist itself, as it’s easy to complete and acts as a useful reminder for essential childbirth practices that aligned with the national and local guidelines [ 14 ]. The major barriers were linked to local challenges, including insufficient material and human resources, inadequate training, perceptions of increased workload associated with the SCC use, lack of staff motivation to use SCC, and an underfunded MCH care [ 14 , 21 , 27 , 41 , 42 ].

In Mozambique, due primarily to the structural challenges of the overall health system, the implementation of SCC faces multiple obstacles. Support for MCH care from the MoH and external funders was found to be inadequate and not given priority, with resource distribution often focused on specific diseases through a vertical approach. This lack of funding for maternal care might further limit the resources available for adopting SCC and hindered the implementation of quality, evidence-based delivery practices required by SCC. Clinics in our study commonly faced shortages of essential medicines, equipment, and materials needed for critical childbirth practices. Additionally, the costs associated with reproducing, distributing, storing, and completing the SCC imposed an extra financial burden on the already under-resourced maternity services in the clinics. Moreover, given that there was often only one birth attendant per shift in the maternity ward, implementing and completing the SCC may have competed with other clinical activities for the limited time, resources, and attention of the birth attendant. As a result, birth attendants viewed the SCC as redundant, feeling it added to their workload without offering significant advantages over their current practices. They also found the prospect of introducing another instrument daunting, given the already substantial paperwork in the clinics. Additionally, there was concern that failing to complete the SCC could lead to penalties.

Meanwhile, mothers’ mistrust and perceived poor quality of care have led to blame directed at birth attendants, which may have contributed to their low motivation. Negative comments from the community further undermine the birth attendants’ social recognition and increase societal pressure on them. Our study participants highlighted poor morale, weak motivation, and low recognition among the primary reasons for their reluctance to adopt another protocol like the SCC, in the context of their already overwhelming workload. These barriers need to be addressed to facilitate the SCC implementation in Mozambique.

We recognized that implementing the SCC in our study context involves many interacting factors that potentially reinforce each other within a dynamic system. Therefore, we hypothesized that there were negative feedback loops that hindered the health system’s ability to implement the SCC. Informed by our findings we further hypothesize that these feedback loops were likely to be (a) a weak MCH care system, (b) limited availability of resources, (c) heavy birth attendant workload, and (d) low motivation among birth attendants ( Fig 1 ). Our hypotheses are consistent with findings from a previous study conducted in Nampula Mozambique seeking to understand how to improve breast feeding counseling through the health system [ 43 ], highlighting the fact that our findings have implications beyond just the SCC.

https://doi.org/10.1371/journal.pgph.0003174.g001

Despite these obstacles, many birth attendants remained committed to improving the quality of childbirth practices and adopting SCC. They recognized that the SCC aligned with the national MCH goals and the need to continue educating themselves. Birth attendants did not express the need for pay-for-performance for filling out SCC but suggested that allocating more financial resources towards creating better working conditions and strengthening the healthcare system would be helpful. Moreover, participants suggested modifying the format of SCC, such as displaying it as a poster in the maternity ward or integrating it into existing tools like the patient clinical registration form. This would help contextualize SCC’s use, better integrate it into the health providers work routines and facilitate its implementation. However, it is possible that altering the use and format of the SCC might contribute to potential changes in its original purpose and affect its efficacy.

Limitations and strengths.

This study has several limitations. Firstly, since participants lacked real-life experience in SCC implementation, the barriers and facilitators identified were not directly informed by their experience of using the SCC. Moreover, without implementing the SCC, this formative research study was not able to assess the actual implementation process domain of the CFIR or identify potential effective activities utilized in the SCC implementation [ 37 ]. However, we provided the SCC to participants at least one day before the interviews and FGDs and explained the purposes of the SCC iteratively before and throughout the interviews and FGDs to facilitate their understanding of its content and use. While we could not confirm whether participants had read the SCC beforehand, we took steps to ensure their understanding of its purpose and checklist items. Before each FGD and interview, participants were explained the purpose of the SCC and each of its checklist items. Researchers addressed the participants’ questions to ensure that they all understood the content and intended use of the SCC before proceeding with, and during and after the interviews and FGDs were conducted.

Moreover, it’s important to highlight that in our study participants were deliberately chosen for their extensive knowledge and experience in adhering to and implementing various clinical guidelines related to childbirth practices and policies. As frontline health workers and policymakers, they had extensive familiarity with the objective and integrated content of the SCC. During the FGDs and interviews, they indeed indicated that although the SCC might present a new format as a clinical checklist, the content was familiar to them. Additionally, based on their experience they were able to identify specific items in the SCC that they felt would be challenging and provided substantive feedback on these items during the discussions.

Secondly, we sampled one rural and one urban hospital in Maputo Province and Maputo City, aiming to represent varying conditions in health facilities. Nonetheless, our sample may not fully capture the reality across Mozambique, given the substantial differences in health care quality and access across the country, the external validity of our findings must be interpreted with caution. Moving forward, future SCC studies in Mozambique should include various levels and types of health facilities, including primary health centers, from different regions of the country.

Thirdly, while we hypothesized the presence of several negative feedback loops involving barriers from system-level to individual-level that may make SCC implementation challenging, we acknowledge that this hypothesis needs to be confirmed through further research as causal relationships cannot be established through a qualitative study. We further recognize that the hypothesized feedback loops are an oversimplified representation of barriers to SCC implementation. Further research will also be needed to understand how to counteract negative with positive feedback loops to enable SCC implementation in the context of under-resourced maternity healthcare systems.

Lastly, we fully acknowledge that it will be crucial to include the views of women and the community in the co-design of the SCC implementation process in Mozambique. As an initial formative study, we chose to concentrate first on the perspectives of birth attendants, clinical administrators, and decision-makers in Mozambique, aligning with the clinical context where the SCC is intended to be applied. Future community-engaged co-design studies conducted by our team will incorporate the voices of local women and the community to ensure comprehensive and inclusive insights.

Despite the limitations, this study has several strengths. While our findings confirm findings previously reported in other countries, this study stands out as the sole formative qualitative study that was conducted prior to actual SCC implementation and the first SCC study conducted in Mozambique. Our approach aligns closely with the WHO Safe Childbirth Checklist Implementation Guide [ 44 ], emphasizing the necessity of assessing available resources and current practices prior to large-scale implementation to determine how the SCC can be optimally employed and what prerequisites must be met for its success.

Conducting this study before SCC implementation offers several benefits. This formative study reflects a commitment to ensuring that SCC implementation aligns with and addresses the country’s specific needs. As reported by a previous study, SCC implementation might increase the workload and frustration of birth attendants [ 21 ]. Ignoring this clear finding confirmed in our study could inadvertently generate unintended consequences within local communities and the MCH care system in Mozambique.

Moreover, our study was carried out in close collaboration with Mozambique’s MoH based on the principles of mutual respect and benefit, equitable communication, and productive dialogue between the global health research team and the local partners, with a commitment to reporting our findings to local healthcare leadership [ 45 ]. The findings of this study have been presented to the decision-makers and researchers in Mozambique and will be further disseminated in the country to assist the MoH in determining the next steps for SCC implementation. We expect for our findings to support a co-design phase of an initiative to implement the SCC in Mozambique.

Implications.

Our study identified severe health care systems resource shortage as a key barrier to the SCC implementation in Mozambique, emphasizing the need to reconsider the focus of MCH studies and research methods used. Unlike the typical practice of conducting pre-post-implementation studies or randomized controlled trials (RCTs) to investigate facilitators and barriers for SCC implementation, our study shows that a proactive pre-implementation assessment can provide equally important contextual insights. Furthermore, conducting pre-implementation assessments could inform resource allocation strategies to address critical gaps in human and material resources for the SCC implementation with the ultimate goal of strengthening the overall MCH care system.

Furthermore, given that numerous barriers to SCC implementation are fundamentally linked to the shortcomings of Mozambique’s healthcare system, we call for future funders and partners shifting their focus from vertical funding to initiatives that prioritize the provision of essential materials, human resources, and professional training in primary care. Moreover, recognizing that there is no one-size-fits-all model for SCC implementation due to various contexts, future implementation research should include different types of health facilities and various levels of healthcare systems across Mozambique. Future research should take into account what we have learned from our study in Maputo City and Maputo Province and determine the optimal complementary intervention packages to adapt SCC implementation strategies to the country’s unique settings [ 42 ], taking the voices of women and communities fully into account.

In conclusion, our innovative study has played a crucial role in empowering local providers by listening to their voices and engaging them in the decision-making process for the implementation of the SCC in Mozambique. Their contributions have highlighted the urgent need for improving the quality of MCH care and enhancing the capacity of the health system in the country. Moreover, our study has identified various key factors that are vital for the successful implementation of the SCC, which include ensuring the availability of adequate human and material resources, providing comprehensive professional training, adapting the SCC contextually, maintaining strong political commitment, and garnering support from equitable partnerships. Lastly, we call for future research to undertake a holistic evaluation of the local context prior to the implementation of the SCC, thereby promoting decolonized global health research and practice and ensuring that interventions are contextually relevant and culturally sensitive.

Supporting information

S1 text. who safe childbirth checklist..

https://doi.org/10.1371/journal.pgph.0003174.s001

S2 Text. Question guides for FGDs and interviews.

https://doi.org/10.1371/journal.pgph.0003174.s002

S1 Table. Codebook and question guide for pilot FGD.

https://doi.org/10.1371/journal.pgph.0003174.s003

S1 Checklist. PLOS questionnaire on inclusivity in global research.

https://doi.org/10.1371/journal.pgph.0003174.s004

Acknowledgments

The authors would like to thank Dr. Lucian J. Davis, Dr. Ashely K. Hagaman, and the staff at Comité para a Saúde de Moçambique for their generous guidance and support.

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• v.13(3); 1998 Mar

Making Use of Qualitative Research Techniques

Michael berkwits.

1 Philadelphia Veterans Affairs Medical Center and Division of General Internal Medicine, University of Pennsylvania Medical Center, Philadelphia

Thomas S Inui

2 Department of Ambulatory Care and Prevention, Harvard Community Health Plan and Harvard Medical School, Boston, Mass

Consider the following situation: You have recently taken on administrative responsibilities at a new hospital where you are responsible for improving patient care programs and organizational efficiency in the general medicine outpatient clinics. You are familiar with your department's general objectives for change and with theoretical strategies for improving operations, but you want to optimize the transitions for all involved parties. In early meetings, department and hospital staff express skepticism that any of the anticipated changes would serve them or the hospital's patients better.

In this situation, immediate action—such as announcing a new clinical or quality review program—would directly address the challenges you face. But more information might help you more effectively meet your professional responsibilities. You might want to learn what systems already work well in the clinics, or better understand what services would be valued in the local community. You might also want to learn about employees' perceptions of their mission and service to identify strategies that could motivate them for change. The information to help you meet these objectives will come primarily from the people involved in your questions and plans—your patients and coworkers, for example. One can gather this information by talking to people informally. Alternatively, one can use qualitative research techniques for this purpose, particularly in new situations and environments. This article addresses how and why busy clinicians might use qualitative techniques to answer questions and solve problems like those in the scenario above.

Qualitative research is a form of inquiry that analyzes information conveyed through language and behavior in natural settings. 1 It is used to capture expressive information not conveyed in quantitative data about beliefs, values, feelings, and motivations that underlie behaviors. Qualitative methods derive from a variety of disciplines and traditions. 2 They are used to learn directly from patients and others what is important to them, to provide the context necessary to understand quantitative findings, and to identify variables important for future clinical studies. Although qualitative inquiry has been championed as a way of “reaching the parts other methods cannot reach,” 3 it is also distrusted by some because it rarely provides a generalizable foundation for clinical decisions and policies. 4 Readers are referred to several recent editorials for overviews of these differences and proposals for their reconciliation. 3 – 7

Some qualitative approaches use technical methods (such as statistical content analysis) to determine the significance of findings, while others rely on researchers thoughtful reflection. Ethnography is a form of inquiry that can combine these approaches, and we will use techniques from this tradition to illustrate our points.

Ethnography is a semistructured way of learning about people and their culture. 8 With specific questions in mind, ethnographic researchers immerse themselves in an environment to discover the meanings, conventions of behavior, and ways of thinking important to individuals of a group as they emerge in unrehearsed encounters. Table 1 )outlines some of the techniques investigators use in this process.

Examples of Qualitative Techniques

Ethnographers' essential task is to observe study subjects in their natural settings. They can do so as silent background observers or as “participant-observers” who ask questions as they accompany study subjects in their activities. In either role they collect data in both unstructured and structured ways. They can write spontaneous “field” notes that detail what they see and hear, or organize their observations around categories, checklists, or rating scales that they bring to the setting. Beyond observing, ethnographers interview subjects with one or more objectives in mind: to learn from well-positioned individuals who can provide useful information (also called “key informant” interviews); to understand experiences especially important to shaping perceptions and decisions (“critical incident” reports); or to generate new information from groups of subjects in focus groups. Audiotaping or videotaping these interactions helps guarantee that expressive data are captured accurately and completely as they emerge. Taping also permits the researcher to carry the data to more controlled settings, where they can be transcribed, coded, analyzed for important themes and meanings, and verified using trained evaluators (aided by computer software if appropriate). 2

The use of more than one evaluator helps ensure the reliability of ethnographic data, as does a detailed accounting of how a study analysis is performed. Researchers can be reasonably assured of the validity of their findings by collecting data from independent sources, presenting preliminary findings to study participants for their feedback, and fully examining unusual or “outlying” information. These strategies are likely to become increasingly standardized as consensus emerges around the need for greater methodologic rigor in qualitative research. 9 , 10

These methods are appropriate for practical situations in which a fuller understanding of behavior, the meanings and contexts of events, and the influence of values on choices might be useful for physicians ( Table 2 ) We describe below how ethnographic techniques might be used to gather information necessary to plan and implement administrative changes in a clinical setting.

Professional Challenges for Which Qualitative Approaches Could Be Useful

USING QUALITATIVE TECHNIQUES FOR ADMINISTRATIVE CHANGE

Suppose that as one of your first initiatives you would like to improve the process that patients in the medicine clinics go through to see their providers. Specifically, you would like to minimize unnecessary administrative delays and improve patients' perceptions of waiting times. Reviewing registration sheets will give you valuable quantitative information about the timing of the process, but direct, semistructured observation of the clinic's operations could reveal other information about areas for attention. For example, you might observe the registration and waiting area with the following questions in mind: Is the clerical staff sufficient to register patients and perform other administrative work during the clinic's busiest hours? Are anticipated delays explained sympathetically to patients at the time they arrive? Are there sufficient diversions for patients in the waiting room? Is there evidence of impatience among the patients in the waiting area, and under what circumstances? Your observations may not answer all of these questions, but they can provide a working sense of which to investigate further, what other questions to ask, and a preliminary sense of the character of the administrative process as clinic patients experience it. More generally, they can reveal salient differences between abstract descriptions of what happens for patients and the way things really work in a specific setting.

Any such observation process will inevitably leave several impressions relevant to the setting or process one is exploring. You might discover that nursing staff are frequently distracted by clerical duties, for example, or that the variety and quality of patient-oriented material in the waiting area should be broader given the clinic population. These impressions need to be confirmed or revised through feedback from others before you can consider them valid. Realistically, you will also need help in developing practical solutions to the problems you identify. Colleagues and department leaders can provide this input, but a key informant among hospital staff is often more useful for this purpose. Asking the question “Who in the hospital knows the most about...?” can lead you to such an individual, who may have no formal title or authority but can provide insider's knowledge about the hospital and its environment. For instance, this person could cue you into the relative place of the general medicine clinics within the hospital's most important and efficient operations, as well as its priorities, missions, and long-standing values and traditions. Key informants are typically invaluable in practical matters, identifying those who know the most about making and approving budgets, hiring personnel, finding space, purchasing equipment, and setting and maintaining standards. And they often help distinguish among key organizational actors, such as those with formal authority, those with actual power, and those who get particular kinds of work done most effectively.

Suppose you look for and find such an informant in a clinic nurse, who has worked in the hospital for 18 years and in the outpatient clinics for the past 10 years. In an extensive interview she confirms your impressions about areas for improvement and points out other ways to improve efficiency, such as converting a procedure area to a multipurpose examining room and arranging for laboratory runs to and from the clinic. She gives you names of hospital staff who are approachable and can influence the allocation of space and other resources, but politely shares her doubts that effective change is possible based on her experience with efforts similar to yours which have failed in the past.

Knowing this, it would be useful to investigate whether other staff have had similar experiences in the hospital. Individuals who witnessed past changes in policy and procedure may be able to provide critical incident reports of successes and failures that have defined the attitudes of employees toward administrators and administrative change. An interview with these staff might begin with an open-ended, nondirective question, such as “What happened the last time someone tried to make changes in the clinics?,” and then follow through on expressions of enthusiasm, indifference, or disillusionment that emerge from initial responses. Jokes and “horror stories” shared in the interview or in more public settings should be taken seriously because they can convey a lot about the core values, traditions, and traumatic experiences of the staff who tell them. In general, critical incident interviews are invaluable for discovering past events and experiences that have proved influential to people in the present. In this scenario, they could help you anticipate sources of resistance to change among the staff who will encounter it.

You will also want to talk to patients to understand their views: their expectations for care, their needs for clinical and social support programs, and their satisfactions and frustrations with your institution, for example. You could obtain this information in individual interviews, but with the potential for a variety of opinions among a diverse clinic population, it may be more useful and efficient to seek it in the context of one or more focus groups. Participants interact with one another in these groups, and in the process generate useful data that are not always available in one-on-one interviews. For instance, dissent between group members about the desirability of educational programs could reveal important differences in their knowledge and needs, while consensus about the usefulness of evening clinic hours might validate one of your own untested ideas about enhancing clinic service availability.

You would organize these groups according to your objectives. To hear ideas about how you might improve clinical services from the patients who actively use them, you could recruit participants from the waiting area or from lists of individuals seen more than once in the past 6 months. To understand whether community outreach programs might attract new patients to the clinic, you could choose registered patients who reside within the hospital's ZIP code area. Or to discover sources of dissatisfaction, you might attempt to include patients who had a single initial visit to clinic physicians and did not return for follow-up. Because the optimal size for these groups is approximately four to eight people, you might organize several sessions with different individuals from these categories, or a series of sessions with a cross section of participants in each.

As with other qualitative techniques, facilitating a focus group requires a flexible approach in balancing minimal participation with active involvement to prompt group discussion in productive directions. You could initiate discussion with the question “How do you think this clinic could serve each of you better?” and intervene to stimulate participant interactions, to clarify important points or disagreements, or to ask questions that remain unanswered nearing the end of the session. Because group participants ideally control the content and pace of the conversation, it is particularly useful for facilitators of focus groups to record these sessions. An audiotape or videotape can be reviewed for meanings and interactions that were not evident in the course of the group discussion, and should be transcribed and coded for key themes or variables by a person familiar with common coding procedures. Information on these procedures is available in standard references. 11 , 12

WHY USE THESE TECHNIQUES?

Qualitative observations and interviews can provide invaluable practical information: who in the medical records department might improve the record retrieval rate, for instance, or what kinds of outreach programs would attract new patients. But at a deeper level qualitative encounters are also necessary to understand the “structure” of a system: how interdependent individuals, groups, and institutional components function (or fail to function) together. This is critical because in a hospital, as in any complex system, change or inertia in one dimension inevitably affects others.

Plans to offer evening clinic hours, for example, may require full consideration of clerical and nursing union standards, benefits requirements, security staffing, housestaff expectations, pharmacy availability, and other aspects of operations. Will compensatory time requirements for clerical staff who work overtime result in staff shortages during regular weekday working hours? Can hospital security staff guarantee safety after hours to an isolated and otherwise unpopulated clinic area? Will the pharmacy have sufficient personnel to fill outpatient prescriptions in addition to inpatient orders? And will the increased patient base and third-party payments generated by a general medicine evening clinic cover the total additional costs to these and other components of the system? These groups' members each have a potential stake in changes that at first glance may be obviously useful to patients and relevant only to personnel at a local level.

Qualitative research techniques are essential for uncovering the extent of these interdependencies and the values that members throughout the system place on them and on the status quo. They provide tools for the visitor or outsider to a complex social system to characterize its important components and to anticipate and coordinate the effects of change throughout it. Whereas commonly used quantitative research methods provide information about universal circumstances, properly applied qualitative techniques yield extensive structured knowledge about these kinds of circumstances, processes, sources of meanings, values, and interactions unique to one place and one system at a specific time. Because every existing institution is simultaneously a bureaucracy, business, social system, and web of vested interests, changes that make a significant impact on such institutions may only be fully understood, prospectively or retrospectively, by a combination of quantitative and qualitative approaches.

Faced with new responsibilities and skeptical about the relevance of qualitative research techniques, you nevertheless try them and learn in the process that developing an ideal clinical operation will require effort and patience. With small discretionary funds and an equipment request for a VCR and monitor, you can easily improve the quality and appeal of educational material in the waiting room. But finding alternatives to an oversold parking structure to help diminish unmanageably late arrivals and patient frustration will be virtually impossible. You learn that although your department's plans to increase the profile (and profit) of the outpatient clinics holds potential rewards for all involved parties, little has been done to negotiate limited resources from overextended hospital services. This will be a large portion of your job, and possibly its greatest challenge.

Without qualitative techniques you most likely would have discovered this information when programs or changes you proposed met resistance and perhaps frustrated or angered others. But with them you gain the foresight to anticipate and avoid obstacles rather than run in to them. You do so in a way that includes contributors at all levels of the hospital, enlisting them prospectively in programs both you and they can see as collaborative. With the goodwill of a newcomer, you establish meaningful contacts in multiple hospital services and better understand their responsibilities, affiliations, ambitions, and limits. You thereby identify likely areas of administrative movement and friction throughout the system that you can account for in present and future plans.

Beyond this administrative scenario, qualitative approaches can be equally useful in managing clinical, educational, and other challenges that arise in outpatient settings ( Table 2 ). Whether physicians are seeking to improve patient adherence, recruit trainees into generalist careers, or negotiate with superiors, taking time to discover what is important to patients, students, educators, section heads, and other leaders can put physicians in a position to elicit the best performance and contributions of each.

Physicians may already consider themselves well trained to observe and gather facts from other people, but qualitative research provides the principles and structure to do so in an empiric, trustworthy, and systematic manner. Admittedly, the procedural differences between qualitative research and everyday practice may not seem nearly as great as those between daily practice and quantitative research. Although this fact might be used to reinforce the impression that qualitative investigation lacks rigor, it requires much of the same effort, attention to procedures, resistance to bias, and attention to data integrity that characterize other methods. We have hoped to illustrate that the “proximity” between this form of research and practice can be used to practical advantage—to enhance our understanding of our patients and day-to-day settings, the meaningfulness of our interventions, and thereby our effectiveness in daily professional responsibilities.

Acknowledgments

Supported in part by the Robert Wood Johnson Foundation.