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Qualitative Research – Methods, Analysis Types and Guide

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Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Qualitative Research Methods: Types, Analysis + Examples

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

What is qualitative research?

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

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

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

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

Gather research insights

Types of qualitative research methods with examples

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

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

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

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

1. One-on-one interview

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

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

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

2. Focus groups

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

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

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

3. Ethnographic research

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

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

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

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

4. Case study research

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

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

5. Record keeping

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

6. Process of observation

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

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

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

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

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

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

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

B. Qualitative data analysis

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

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

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

Characteristics of qualitative research methods

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

Qualitative research method case study

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

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

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

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

When to use qualitative research

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

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

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

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

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

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Chapter 1. Introduction

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

Why an Open Access Textbook on Qualitative Research Methods?

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

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

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

What is Research?

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

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

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

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

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

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

What is Qualitative Research?

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

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

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

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

Examples of Qualitative Research

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

Example 1 : The End Game (ethnography + interviews)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

How Is This Book Organized?

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

Chapter Descriptions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Recommended Reading: Other Qualitative Research Textbooks

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

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

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

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

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

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

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

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

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

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

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

Patton’s Ten Suggestions for Doing Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Qualitative Research: Characteristics, Design, Methods & Examples

Lauren McCall

MSc Health Psychology Graduate

MSc, Health Psychology, University of Nottingham

Lauren obtained an MSc in Health Psychology from The University of Nottingham with a distinction classification.

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“Not everything that can be counted counts, and not everything that counts can be counted“ (Albert Einstein)

Qualitative research is a process used for the systematic collection, analysis, and interpretation of non-numerical data (Punch, 2013). 

Qualitative research can be used to: (i) gain deep contextual understandings of the subjective social reality of individuals and (ii) to answer questions about experience and meaning from the participant’s perspective (Hammarberg et al., 2016).

Unlike quantitative research, which focuses on gathering and analyzing numerical data for statistical analysis, qualitative research focuses on thematic and contextual information.

Characteristics of Qualitative Research 

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).

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 context of the research setting (Scarduzio, 2017).

Why Conduct Qualitative Research? 

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

Qualitative research allows researchers to gain an in-depth understanding, which is difficult to attain using quantitative methods. 

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). 

This helps to further investigate and understand quantitative data by discovering reasons for the outcome of a study – answering the why question behind statistics. 

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

To design hypotheses, theory must be researched using qualitative methods to find out what is important in order to begin research. 

For example, by conducting interviews or focus groups with key stakeholders to discover what is important to them. 

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? 

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.

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). 

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). 

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).

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. 

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. 

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.

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Choosing a Qualitative Research Approach

Associated data.

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

The Challenge

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

What Is Known

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

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

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

Choosing a Qualitative Approach

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

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

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

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

Methodology Overview

How You Can Start TODAY

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

What You Can Do LONG TERM

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

Supplementary Material

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

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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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Types Of Qualitative Research Designs And Methods

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its…

Qualitative research design comes in many forms. Understanding what qualitative research is and the various methods that fall under its umbrella can help determine which method or design to use. Various techniques can achieve results, depending on the subject of study.

Types of qualitative research to explore social behavior or understand interactions within specific contexts include interviews, focus groups, observations and surveys. These identify concepts and relationships that aren’t easily observed through quantitative methods. Figuring out what to explore through qualitative research is the first step in picking the right study design.

Let’s look at the most common types of qualitative methods.

What Is Qualitative Research Design?

Types of qualitative research designs, how are qualitative answers analyzed, qualitative research design in business.

There are several types of qualitative research. The term refers to in-depth, exploratory studies that discover what people think, how they behave and the reasons behind their behavior. The qualitative researcher believes that to best understand human behavior, they need to know the context in which people are acting and making decisions.

Let’s define some basic terms.

Qualitative Method

A group of techniques that allow the researcher to gather information from participants to learn about their experiences, behaviors or beliefs. The types of qualitative research methods used in a specific study should be chosen as dictated by the data being gathered. For instance, to study how employers rate the skills of the engineering students they hired, qualitative research would be appropriate.

Quantitative Method

A group of techniques that allows the researcher to gather information from participants to measure variables. The data is numerical in nature. For instance, quantitative research can be used to study how many engineering students enroll in an MBA program.

Research Design

A plan or outline of how the researcher will proceed with the proposed research project. This defines the sample, the scope of work, the goals and objectives. It may also lay out a hypothesis to be tested. Research design could also combine qualitative and quantitative techniques.

Both qualitative and quantitative research are significant. Depending on the subject and the goals of the study, researchers choose one or the other or a combination of the two. This is all part of the qualitative research design process.

Before we look at some different types of qualitative research, it’s important to note that there’s no one correct approach to qualitative research design. No matter what the type of study, it’s important to carefully consider the design to ensure the method is suitable to the research question. Here are the types of qualitative research methods to choose from:

Cluster Sampling

This technique involves selecting participants from specific locations or teams (clusters). A researcher may set out to observe, interview, or create a focus group with participants linked by location, organization or some other commonality. For example, the researcher might select the top five teams that produce an organization’s finest work. The same can be done by looking at locations (stores in a geographic region). The benefit of this design is that it’s efficient in collecting opinions from specific working groups or areas. However, this limits the sample size to only those people who work within the cluster.

Random Sampling

This design involves randomly assigning participants into groups based on a set of variables (location, gender, race, occupation). In this design, each participant is assigned an equal chance of being selected into a particular group. For example, if the researcher wants to study how students from different colleges differ from one another in terms of workplace habits and friendships, a random sample could be chosen from the student population at these colleges. The purpose of this design is to create a more even distribution of participants across all groups. The researcher will need to choose which groups to include in the study.

Focus Groups

A focus group is a small group that meets to discuss specific issues. Participants are usually recruited randomly, although sometimes they might be recruited because of personal relationships with each other or because they represent part of a certain demographic (age, location). Focus groups are one of the most popular styles of qualitative research because they allow for individual views and opinions to be shared without introducing bias. Researchers gather data through face-to-face conversation or recorded observation.

Observation

This technique involves observing the interaction patterns in a particular situation. Researchers collect data by closely watching the behaviors of others. This method can only be used in certain settings, such as in the workplace or homes.

An interview is an open-ended conversation between a researcher and a participant in which the researcher asks predetermined questions. Successful interviews require careful preparation to ensure that participants are able to give accurate answers. This method allows researchers to collect specific information about their research topic, and participants are more likely to be honest when telling their stories. However, there’s no way to control the number of unique answers, and certain participants may feel uncomfortable sharing their personal details with a stranger.

A survey is a questionnaire used to gather information from a pool of people to get a large sample of responses. This study design allows researchers to collect more data than they would with individual interviews and observations. Depending on the nature of the survey, it may also not require participants to disclose sensitive information or details. On the flip side, it’s time-consuming and may not yield the answers researchers were looking for. It’s also difficult to collect and analyze answers from larger groups.

A large study can combine several of these methods. For instance, it can involve a survey to better understand which kind of organic produce consumers are looking for. It may also include questions on the frequency of such purchases—a numerical data point—alongside their views on the legitimacy of the organic tag, which is an open-ended qualitative question.

Knowledge of the types of qualitative research designs will help you achieve the results you desire.

With quantitative research, analysis of results is fairly straightforward. But, the nature of qualitative research design is such that turning the information collected into usable data can be a challenge. To do this, researchers have to code the non-numerical data for comparison and analysis.

The researcher goes through all their notes and recordings and codes them using a predetermined scheme. Codes are created by ‘stripping out’ words or phrases that seem to answer the questions posed. The researcher will need to decide which categories to code for. Sometimes this process can be time-consuming and difficult to do during the first few passes through the data. So, it’s a good idea to start off by coding a small amount of the data and conducting a thematic analysis to get a better understanding of how to proceed.

The data collected must be organized and analyzed to answer the research questions. There are three approaches to analyzing the data: exploratory, confirmatory and descriptive.

Explanatory Data Analysis

This approach involves looking for relationships within the data to make sense of it. This design can be useful if the research question is ambiguous or open-ended. Exploratory analysis is very flexible and can be used in a number of settings. But, it generally looks at the relationship between variables while the researcher is working with the data.

Confirmatory Data Analysis

This design is used when there’s a hypothesis or theory to be tested. Confirmatory research seeks to test how well past findings apply to new observations by comparing them to statistical tests that quantify relationships between variables. It can also use prior research findings to predict new results.

Descriptive Data Analysis

In this design, the researcher will describe patterns that can be observed from the data. The researcher will take raw data and interpret it with an eye for patterns to formulate a theory that can eventually be tested with quantitative data. The qualitative design is ideal for exploring events that can’t be observed (such as people’s thoughts) or when a process is being evaluated.

With careful planning and insightful analysis, qualitative research is a versatile and useful tool in business, public policy and social studies. In the workplace, managers can use it to understand markets and consumers better or to study the health of an organization.

Businesses conduct qualitative research for many reasons. Harappa’s Thinking Critically course prepares professionals to use such data to understand their work better. Driven by experienced faculty with real-world experience, the course equips employees on a growth trajectory with frameworks and skills to use their reasoning abilities to build better arguments. It’s possible to build more effective teams. Find out how with Harappa.

Explore Harappa Diaries to learn more about topics such as What is Qualitative Research , Quantitative Vs Qualitative Research , Examples of Phenomenological Research and Tips For Studying Online to upgrade your knowledge and skills.

• Methodology
• Open access
• Published: 28 March 2024

Leveraging human-centered design and causal pathway diagramming toward enhanced specification and development of innovative implementation strategies: a case example of an outreach tool to address racial inequities in breast cancer screening

• Leah M. Marcotte   ORCID: orcid.org/0000-0003-3130-3525 1 ,
• Raina Langevin 2 ,
• Bridgette R. Hempstead 3 ,
• Anisha Ganguly 4 ,
• Aaron R. Lyon 5 ,
• Bryan J. Weiner 6 , 7 ,
• Nkem Akinsoto 8 ,
• Paula L. Houston 8 ,
• Victoria Fang 1 , 8 &
• Gary Hsieh 2  

Implementation Science Communications volume  5 , Article number:  31 ( 2024 ) Cite this article

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Implementation strategies are strategies to improve uptake of evidence-based practices or interventions and are essential to implementation science. Developing or tailoring implementation strategies may benefit from integrating approaches from other disciplines; yet current guidance on how to effectively incorporate methods from other disciplines to develop and refine innovative implementation strategies is limited. We describe an approach that combines community-engaged methods, human-centered design (HCD) methods, and causal pathway diagramming (CPD)—an implementation science tool to map an implementation strategy as it is intended to work—to develop innovative implementation strategies.

We use a case example of developing a conversational agent or chatbot to address racial inequities in breast cancer screening via mammography. With an interdisciplinary team including community members and operational leaders, we conducted a rapid evidence review and elicited qualitative data through interviews and focus groups using HCD methods to identify and prioritize key determinants (facilitators and barriers) of the evidence-based intervention (breast cancer screening) and the implementation strategy (chatbot). We developed a CPD using key determinants and proposed strategy mechanisms and proximal outcomes based in conceptual frameworks.

We identified key determinants for breast cancer screening and for the chatbot implementation strategy. Mistrust was a key barrier to both completing breast cancer screening and using the chatbot. We focused design for the initial chatbot interaction to engender trust and developed a CPD to guide chatbot development. We used the persuasive health message framework and conceptual frameworks about trust from marketing and artificial intelligence disciplines. We developed a CPD for the initial interaction with the chatbot with engagement as a mechanism to use and trust as a proximal outcome leading to further engagement with the chatbot.

Conclusions

The use of interdisciplinary methods is core to implementation science. HCD is a particularly synergistic discipline with multiple existing applications of HCD to implementation research. We present an extension of this work and an example of the potential value in an integrated community-engaged approach of HCD and implementation science researchers and methods to combine strengths of both disciplines and develop human-centered implementation strategies rooted in causal perspective and healthcare equity.

Peer Review reports

Contributions to the literature

The integration of human-centered design and implementation science researchers and methods can synthesize strengths of both disciplines.

Human-centered design methods can be employed as part of an overarching co-creation approach to including partners/communities in research.

A human-centered design approach rooted in causal pathway diagramming can help to address challenges of both basing implementation strategies in theory and meeting the needs of partners and/or communities.

The field of implementation science was created to address the gap between what should be done based on existing evidence and what is done in practice. Implementation strategies—“methods or techniques used to enhance the adoption, implementation, and sustainability of a clinical program or practice” [ 1 ]—are central to implementation science. In 2015, the Expert Recommendations for Implementing Change project compiled 73 different implementation strategies used in the field [ 2 ]. However, as implementation science has evolved, experts have recognized that (a) more implementation strategies exist than have been cataloged and (b) developing or tailoring implementation strategies may benefit from integrating approaches from other disciplines (e.g., behavioral economics and human-centered design) [ 3 , 4 , 5 ]. Yet, current guidance on how to effectively incorporate methods from other disciplines to develop and refine innovative implementation strategies is limited.

The causal pathway diagram (CPD) is an implementation science method that can be used to support development and refinement of implementation strategies [ 6 ]. CPDs help researchers to understand implementation strategies as they are intended to work. In building a CPD, researchers identify the implementation strategy, the mechanism(s) through which the strategy is thought to lead to the intended outcome, proximal outcomes which may provide signals of effect earlier than the intended outcome, and the distal (intended) outcome. CPDs also include moderators which may enhance or dampen pathway effect and pre-conditions which are necessary for the pathway to proceed. In developing and refining implementation strategies, CPDs help investigators map key determinants (barriers or facilitators) that implementation strategies address and mechanisms by which strategies are posited to effect change. Theory and existing evidence are typically used to construct CPDs [ 7 ]. One potential limitation of the CPD is that while there is an emphasis on incorporating theory and existing evidence, there are fewer examples of incorporating implementation partners’ and/or community needs and context in the initial creation of the CPD [ 8 ].

Co-creation—a collaborative process including people with a diversity of roles/positions to attain goals—is increasingly recognized as an approach for implementation scientists to integrate partners/communities in research [ 9 ]. In co-creation, researchers may employ several different methodologies and methods. For example, many researchers use community-engaged research approaches to meaningfully include community members in intervention development and implementation with goals to increase relevance, effectiveness, and sustainment of interventions [ 9 , 10 ]. Co-creation can be framed as an overarching concept that includes co-design (intervention development) and co-production (intervention implementation) [ 11 ]. Co-design is specifically relevant for the design of novel implementation strategies and researchers often use human-centered design methods for co-designing interventions [ 12 , 13 ]. In co-design, multiple methods may be used synergistically. For example, researchers can simultaneously use community-based participatory research methods to meaningfully include community members and human-centered design (HCD) methods to guide intervention design [ 14 , 15 ].

HCD methods are particularly useful in co-design for technology-based implementation strategies with key standards and principles for designing interactive systems [ 16 ]. HCD is a “flexible, yet disciplined and repeatable approach to innovation that puts people at the center of activity.” [ 17 ] HCD methods elicit information regarding user environment and experience through continuous partner/user engagement and draw from multidisciplinary expertise [ 18 ]. An initial phase of HCD is to establish the context of use and requirements of users [ 19 ]. In this exploratory phase, researchers often collect and analyze qualitative data through interviews, focus groups, and/or co-design sessions. In addition to questions about context and user requirements, interviews will often include “mockups” or early prototypes for initial reactions and feedback.

Establishing context of use and user requirements in HCD is synergistic to the needs for specifying implementation strategies and developing CPDs [ 20 ]. HCD methods can be used to build and inform CPDs by gaining understanding of key determinants to the desired program or practice within a specific context and identifying potential facilitators and barriers to the implementation strategy itself. Early qualitative data from HCD methods and identification of key determinants can help to inform use of theory in building CPDs. Finally, HCD methods can further help to understand and test assumptions related to mechanisms of an implementation strategy [ 20 ].

Haines et al. described the application of HCD methods in defining context and connecting to evidence-based practices and implementation strategies. [ 4 ] We build on this work by describing a way to explicitly include partners (organizational and community) in the co-design of implementation strategies while maintaining a causal basis and perspective. We present an example incorporating HCD methods in CPDs to design an innovative outreach strategy to address inequities in breast cancer screening using mammography among Black women. In this case study, we illustrate how HCD methods were used to (1) identify and prioritize key determinants, (2) select and apply conceptual frameworks, and (3) understand (and design for) strategy mechanisms.

Case example: designing an outreach tool to address breast cancer screening inequities

Inequities in breast cancer mortality among Black people have been recognized for decades and yet persist [ 21 , 22 ]. These inequities are partly due to later stage breast cancer diagnosis [ 21 ]. Regular interval breast cancer screening with mammography aligned with the United States Preventive Services Task Force (USPSTF) guidelines is an evidence-based intervention to improve earlier diagnosis of and mortality from breast cancer [ 23 ]. Therefore, addressing breast cancer screening inequities among Black people eligible for screening aligned with guidelines may facilitate early detection and improve breast cancer survival [ 24 , 25 , 26 ]. Research to date has demonstrated that Black women experience multiple barriers to breast cancer screening including reduced access to care, mistrust and decreased self-efficacy, fear of diagnosis, prior negative health care experiences, and lack of information regarding breast cancer risk [ 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. Black women may also not feel included or prioritized in breast cancer screening campaigns [ 30 ].

Tailored interventions to improve breast cancer screening among Black women have demonstrated modest effect in improving breast cancer screening rates, yet many of these interventions, such as use of health navigators, are resource intensive and must be repeated annually [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ]. Mobile technology interventions can be culturally tailored and may address limitations related to cost and time [ 48 , 49 ]. Mobile technology interventions using short message service (SMS) text are accessible to individuals across a range of sociodemographic factors and have been shown to be effective in primary care behavioral and disease management interventions [ 50 ]. Black women have reported SMS text-based breast cancer screening interventions to be accessible and acceptable [ 51 ]. SMS text-based interventions are also more accessible than patient portal-based interventions which lack adequate reach due to substantial racial inequities in patient portal use [ 52 , 53 ]. Mobile health interventions using conversational interfaces such as chatbots via SMS text can act as virtual health navigators providing individualized information about and connecting individuals to healthcare [ 54 ]. Prior research has shown chatbots increase levels of trust in web-based information and are easy to use and scale [ 55 , 56 ].

While the use of health navigators is an established implementation strategy, there are little data on integrating conversational agents in primary care outreach and none that we are aware of that specifically address healthcare inequities in cancer screening [ 57 ]. Literature on digital health interventions emphasizes need for careful attention to and planning for implementation to optimize integration in the healthcare system and patient use [ 58 ]. Moreover, evidence of bias in artificial intelligence raises caution in the design of chatbot interventions [ 59 , 60 , 61 ]. We identified chatbots as a promising, innovative implementation strategy to address breast cancer screening inequities; however, one that warrants rigorous methods and community engagement to design and tailor.

In late 2020, we brought together a team of researchers and health system leaders at a large academic medical center to address inequities in breast cancer screening through the design of a chatbot that could facilitate outreach. Breast cancer screening rates in the health system at the time using the National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set measure based on the USPSTF guidelines were 61.5% among Black women compared to 73.3% among White women (internal health system data) [ 23 , 62 ]. The chatbot implementation strategy was favored as an intervention among interdisciplinary team members because of its innovation and the low resource burden to primary care with better potential for sustainability. Usual care consisted of chart review and telephone outreach by a primary care health navigator and then connection to radiology for mammogram scheduling. The chatbot intervention could be sent to people due for screening and could be configured to schedule a mammogram during the chatbot interaction, expending less resources with greater efficiency. The study protocol was reviewed and determined exempt by the University of Washington Institutional Review Board. This manuscript adheres to the Enhancing the Quality and Transparency of health research (EQUATOR) Better Reporting of Interventions: template for intervention description and replication (TIDieR) checklist and guide and the Consolidated criteria for REporting Qualitative research (COREQ) guidelines [ 63 , 64 ].

To approach implementation-focused research questions, interdisciplinary teams of researchers, operational partners, and end-users are advantageous to develop optimized implementation strategies or innovations. Implementation science and human-centered design researchers co-leading efforts (e.g., as PI, Co-PI, or MPIs) can help to support integration of methods and perspectives. In patient-facing interventions—particularly those addressing inequities among marginalized communities—including patient/community partners can center intervention development on patient/community needs, facilitate participant recruitment, help refine study protocol, and support the analyses of collected data [ 10 , 65 ].

In designing a chatbot for breast cancer screening outreach to address racial inequities, our team included an HCD researcher (G.H.), a primary care physician and early-stage investigator with focus in implementation science (L.M.M.), an HCD PhD candidate (R.L.), and a community-based organization leader (B.R.H.) with expertise in conducting interviews and focus groups for qualitative research and extensive community connections. We received project mentorship from the Optimizing Implementation in Cancer Control (OPTICC) team that includes several leaders and experts in implementation science (e.g., B.J.W., A.R.L.) [ 66 ]. We drew input from key health system partners including health care equity leadership (P.L.H.), primary care and population health leadership (N.A., V.F.), and primary care health navigators. We held regular interdisciplinary team meetings, most frequently in the initial stages of innovation design. Throughout the development of the chatbot tool, we sought feedback from community members through interviews, focus groups, and (planned) co-design sessions.

Positionality statement

Our team included trainees, researchers, clinicians, and operational leaders at the University of Washington and a community-based organization leader. Previous research interests/experience included communication technologies to promote health and well-being (G.H.) and improving quality and equity in primary care services (L.M.M.). B.R.H. provided health equity expertise; she has led a Seattle-based survivor and support organization for African American women with cancer for over 25 years; in that time, she has collaborated with researchers on over 60 grants. Most of our team identifies as women and several of our team members identify as Black women. Research analysis was conducted primarily by R.L., G.H., and L.M.M. (none of whom are Black/African American); all data analysis/interpretation was reviewed with B.R.H. in bi-weekly research meetings.

Identify and prioritize key determinants

Key determinant (i.e., facilitators and barriers) identification is critical in implementation strategy development and a first step in creating a CPD. Determinants may be identified initially through evidence review and contextually through qualitative (e.g., interviews) and/or quantitative (e.g., survey) methods. The use of HCD methods can augment identification of key determinants and other components in CPD via mockups and/or early prototypes to elicit feedback on initial design and use. This approach is particularly useful because determinants can be elicited in the context of the implementation strategy—which may help to optimize determinant-strategy matching. We identified and prioritized key determinants through rapid evidence review of breast cancer screening determinants among Black women and HCD methods. We conducted qualitative analysis of semi-structured interviews including a chatbot mockup and focus groups with end-users who were shown an early prototype of the chatbot which was iterated based on qualitative data analysis of the interviews. Interviews and focus groups were led almost entirely by B.R.H., a community member, to provide comfortable environments to share perspectives. Our underlying interpretive framework most closely followed social constructivism; we focused on the content of participant words and experiences with the goal to minimize researcher interpretation [ 67 ]. Any question of participant meaning was reviewed with B.R.H.

Rapid evidence review

Our objective was to identify determinants to breast cancer screening among Black women emergent from recent literature.

We conducted rapid evidence review following established methods described in the National Collaborating Centre for Methods and Tools Rapid Review Guidebook [ 68 ]. We defined a research question—“among Black women in the United States, what are determinants (i.e., facilitators and barriers) to breast cancer screening?”, searched for research evidence, critically appraised information sources, and synthesized evidence.

Search strategy

Our search strategy prioritized evidence in the past 3 years and included search terms in or related to the research question: (Mammogram, Mammography, Cancer Screening, Breast Cancer Screening), (Breast Cancer), (Women), (Black, African American, African American, Minority), (Race, Ethnicity), (Disparities, Determinants), and (Facilitators, Barriers). Searches were conducted in PubMed, Health Evidence, Public Health + , and the National Institute of Health and Care Excellence.

Review criteria

We considered studies done in the USA as race is a social construct and the experience and impacts of individual and systemic racism differ geographically. We focused on results among Black/African American individuals given the research question and aim to identify specific determinants within this group; however, we did include studies with multiple racial groups represented. We focused on studies that included individuals aged 40–74 years to match the population eligible for average-risk breast cancer screening. Publications in the 3 years prior to evidence review were prioritized acknowledging determinants may change over time (e.g., with technology advancements such as online scheduling or policy changes allowing for mammogram scheduling without primary care provider (PCP) referral) and in keeping with methods in the National Collaborating Centre for Methods and Tools Rapid Review Guidebook [ 68 ].

Critical appraisal and evidence synthesis

Critical appraisal was guided by the 6S Pyramid framework developed and made available by the National Collaborating Centre for Methods and Tools [ 69 ]. We categorized data by source (i.e., search engine), study type (e.g., single study, meta-analysis), population, and results.

Interviews with mockup

Our objective was to elicit determinants to breast cancer screening among Black women living in western Washington as well as feedback about an initial mockup of the chatbot through interviews with community members.

Interview guide

The interview guide was developed by our research team with additional input from members of the Breast Health Equity committee—a health system committee including operational leaders, physicians, and researchers dedicated to addressing inequities in care related to breast cancer screening, diagnosis, and treatment (Additional file 1 : Appendix A). While we incorporated feedback from committee members after the guide was drafted, we did not pilot test with community members before starting interviews. Questions focused on determinants to breast cancer screening and past experiences with breast cancer screening. Additionally, two members of the research team (G.H. and R.L.) created a mockup of the chatbot tool including several mockups of a chatbot for breast cancer screening outreach (Fig. 1 ).

Initial mockup

Sample and recruitment

We used convenience sampling through fliers posted in primary care clinics and email to the research team’s established community networks to identify and recruit individuals who identified as Black/African American women between the ages of 40 and 74 years and lived in either King or Pierce counties in Washington state. We recruited 21 individuals for interviews which we estimated would be adequate to provide sufficient data for understanding our research question [ 70 ].

Two members of the research team (B.R.H., A.G.) conducted interviews ( n  = 21); the community engagement lead on the team (B.R.H.) conducted the vast majority ( n  = 18). Interviews were conducted via Zoom videoconferencing technology and were audio recorded. In addition to questions regarding determinants to and experience of breast cancer screening, we showed participants screenshots of the initial mockup for the chatbot tool and asked specific questions for feedback. No field notes were collected during/after interviews. All interviews were transcribed.

Four members of the research team (R.L. and three undergraduate students listed in acknowledgements: A.A., N.S., X.S.) read and coded the transcripts to generate and refine themes through several iterations until consensus was reached. Each interview was analyzed and coded once by individuals on the research team using a directed content analysis approach; codes were then discussed as a team [ 5 , 71 ]. Deductive codes were created using prior research organizing breast cancer screening barriers as personal, structural, and clinical [ 34 ]. Inductive codes emerged from a close reading of an initial subset of the transcripts and were added to the codebook (Additional file 1 : Appendix Table B). Qualitative data analysis resulted in themes around the chatbot design, and determinants to breast cancer screening. We facilitated an ideation workshop with the research team and Breast Health Equity committee to brainstorm how this research might address the themes brought up in the interviews. We used a 2 × 2 prioritization matrix as a tool to identify the most impactful and feasible ideas that arose. This analysis was used to develop an early chatbot prototype. Results were shared with participants in a newsletter with invitation to respond to interpretation and/or presentation prior to manuscript submission (Additional file 1 : Appendix C).

Focus groups

The objectives were to elicit feedback on an early static prototype of the chatbot tool informed by the interviews.

Early prototype creation

The research team developed an early static prototype of the chatbot tool iterating on the initial mockup using themes and feedback that emerged from qualitative data analysis of the individual interviews (Fig. S 1 ). In addition to the prototype screens, we included short videos with questions and answers to questions such as—“Why should I get screened?”, “What can I expect from a mammogram?”, “What happens if the mammogram is abnormal?”.

Focus group guide

The focus group guide was developed by our research team with additional input from members of the Breast Health Equity committee (Additional file 1 : Appendix D). The guide included questions about perceptions of, engagement with, and usability of the chatbot based on the prototype screens and videos.

The same sampling and recruiting methods were used for the focus groups as were used for the individual interviews. We conducted three focus groups with a total of nine participants.

Focus groups were led by B.R.H. and joined by multiple members of the research team (V.F., A.G., R.L., L.M.M.). We showed participants three example interactions with the chatbot prototype, (1) patient-initiated scheduling of a mammogram, (2) system-initiated patient education, and (3) system-initiated re-scheduling, and asked specific questions for feedback. The same procedures were followed as for the individual interviews; team members debriefed after each focus group.

We used template analysis with pre-defined domains derived from focus group questions and interview themes to analyze focus group content [ 72 ]. Template analysis may be used as a rapid qualitative analysis approach for focus group data [ 73 ]. Template domains were agreed upon by investigators (L.M.M., G.H., R.L., B.R.H.). One investigator (L.M.M.) then reviewed focus groups and conducted content analysis using the templates. The completed templates were summarized in a matrix for data visualization and reviewed by all investigators; any disagreements were addressed and resolved. Results were shared with participants in a newsletter with invitation to respond to interpretation and/or presentation prior to manuscript submission (Additional file 1 : Appendix C).

Synthesis: developing a causal pathway diagram

CPDs can help to map out the pathway of an implementation strategy as it is intended to work [ 6 ]. For innovative implementation strategies, CPDs can help establish and test theorized mechanisms. Conceptual frameworks help to inform pathway components and may be drawn from disciplines outside of implementation research for novel strategies.

From our rapid evidence review, qualitative interviews, and focus groups, we identified key determinants—both in the context of breast cancer screening and the chatbot implementation strategy—and hypothesized mechanisms. Our research team prioritized determinants that were identified across data sources (e.g., in interviews and in rapid evidence review). We focused CPD development on the initial engagement with the chatbot.

Using the selected key determinants, we worked to identify conceptual frameworks to develop a CPD. We expanded the search for conceptual frameworks outside of healthcare to include disciplines such as marketing and computer science that are relevant to the implementation strategy. We selected frameworks based on relevance to and connection of our implementation strategy and proposed mechanism. We used the conceptual frameworks to inform mechanisms through which we hypothesize the implementation strategy to work and moderators which could increase or decrease strategy effect via the strategy mechanism. We iterated on the CPD as a team and received feedback from the OPTICC center team (B.J.W. and A.R.L.).

Informing CPD development: identifying and prioritizing key determinants

In the rapid evidence review, 41 relevant studies were identified out of 114 search results. A narrative synthesis was written summarizing determinants identified in the literature (Additional file 1 : Appendix E). Determinants identified were cataloged and prioritized based on relevance to the implementation strategy. For example, one study found perceptions of lower quality of care if mammograms were done in a mobile clinic setting; we did not include this as a priority determinant because this would not be particularly modifiable in the chatbot design [ 33 ]. Priority determinants included facilitators such as having personal or family history of breast cancer and recommendations from PCPs and barriers such as medical mistrust (Table  1 ).

One priority barrier that emerged from the rapid evidence review was lack of knowledge about breast cancer screening; prior literature recommended patient education to explain and help individuals learn about the process of getting a mammogram [ 33 , 76 , 78 ]. This informed our design of the initial mockup and early chatbot prototype as a patient education and scheduling tool.

For the qualitative data analysis, we interviewed 21 of 39 individuals who responded to recruitment and completed a screening survey. Only 4 of 39 were ineligible due to living outside the 2 designated counties. Several people invited for interviews had to cancel due to schedule conflicts. All interviews were completed once started (no one dropped out of the study after starting an interview). Interview participants all identified as Black/African American, were between the ages of 40 and 69 years, and several were multilingual. We did not collect specific demographic characteristics for focus group participants. Focus group participants signed up for 1 of 4 focus groups; we did not have anyone drop out of focus groups once started.

In the qualitative analysis of interviews and focus groups, we elicited facilitators and barriers to breast cancer screening. Most of the determinants that emerged from interviews and focus groups were also identified in the evidence review (Table  1 ). Facilitators that appeared in evidence review and interviews and/or focus groups included recommendations and/or advocacy from a PCP, health-related social support, family or personal history of breast cancer, and adequate preparation before a mammogram (lack of preparation was framed as a barrier in evidence review). Overlapping barriers included lack of resources (e.g., cost, insurance, transportation), anxiety about what to expect, fear about negative outcomes associated with the procedure (e.g., pain), medical mistrust, prior negative experiences with the health system (including experiences of racism), lack of knowledge about breast cancer screening, lack of discussion with family and friends, and lack of clear recommendation from a PCP. Some determinants that arose from the interview and focus group data were not present in the evidence review but were prioritized given relevance to the implementation strategy. For example, participants identified the time spent to make an appointment and the time until the appointment as moderators to scheduling a mammogram (i.e., a barrier if time to make an appointment and time until appointment is long and facilitator if time to make an appointment and time until appointment is relatively short). In terms of initial reactions to the chatbot mockup, 18 out of 20 participants asked thought that the chatbot would be useful for scheduling (one participant was not asked this question).

In the template analysis of focus groups, we elicited facilitators and barriers to and feedback about the chatbot implementation strategy (Table  2 ; Additional file 1 : Appendix F). Participants appreciated the purpose of the chatbot but thought that in many ways it fell short.

“I mean because that's what the app is for… To kind of make us feel… to draw us in and make us feel taken care of and informed. Educated.” (Participant, Focus Group 2).

Participants expressed mistrust in the chatbot persona, questioning the chatbot’s credibility and describing privacy concerns and intent. They emphasized the importance of cultural inclusivity and familiarity but did not feel like the chatbot prototype achieved these goals.

“I do agree with the fact that it needs to be more culturally inclusive and appropriate for us. I didn't feel like it was personalized outside of [B.R.H.’s] involvement, there was nothing that really spoke to our people.” (Participant, Focus Group 2).

The chatbot presented to the focus groups was named “Sesi” which means “sister” in Sotho, a Bantu language spoken mostly in Southern Africa. Participants expressed frustration about conflating African and Black American experience.

“Sometimes, because we're Black, other communities patronize on us being Black… they just patronize us as if we know what it is to be in Africa and we don't. We've never been to Africa. We still have the same issues, yes, but we've never been there so we can't relate to certain things or cultures that have because we don't have that. We've never, that was not brought along with us here.” (Participant, Focus Group 3).

They questioned the value-add of the chatbot presumed to be an app that would require effort to download onto a phone but might only be used once a year. Though participants did think that they would use the chatbot if it could be used to schedule a mammogram more efficiently than by telephone conversation.

Overall, mistrust was a major theme in both qualitative data analyses and rapid evidence review. In interviews and focus groups, mistrust arose both in the context of interactions with the health care system and the chatbot technology. At the same time, participants noted aspects of the chatbot that increased trust and engagement. For example, they felt reassured to see women who looked like themselves in the chatbot interaction, such as an image of a Black female mammography technician. Given these findings, we decided to focus on optimizing trust in the design of the initial chatbot engagement.

Causal pathway diagram

We drew from multiple theoretical frameworks regarding trust as a determinant to the evidence-based intervention (breast cancer screening) and the implementation strategy (chatbot) (Table  3 ). The persuasive health message framework for developing culturally specific messages details source, channel, and message as distinct components in health messaging and has been used in prior breast cancer screening campaigns [ 81 , 82 ]. We defined our implementation strategy components using these conventions—source (i.e., chatbot persona—communication style and identity), channel (i.e., form of message delivery, e.g., SMS text), and message (i.e., content of messages) (Fig. 2 ). As we focused first on the initial engagement with the chatbot, we attended to source credibility to engender trust. We drew from a conceptual framework in marketing that identifies expertise, homophily, and trustworthiness as characteristics of source credibility—or the belief that a source of information can be trusted [ 83 ]. Finally, to capture trustworthiness in technology, we used a conceptual framework regarding trust in artificial intelligence which includes personality and ability as human characteristics that are important drivers of trust in AI [ 84 ].

We used the CPD to model how we might address the barrier of mistrust using initial engagement with the chatbot as a mechanism and trust as a proximal outcome. Using the conceptual frameworks described above, we posited moderators to be (1) chatbot expertise, (2) chatbot designed for familiarity (i.e., homophily), and (3) chatbot personality or communication style. With our components defined, we created a CPD (Fig.  2 ).

We presented a case study example of the use of HCD methods to inform and build CPDs to design an implementation strategy rooted in causal perspective and informed by community partners. This approach addresses gaps in the use of implementation strategies including identifying and prioritizing determinants and knowledge of strategy mechanisms [ 6 , 66 ].

Our work highlights the value of HCD methods which integrate end-users in the development of innovative implementation strategies and provides an approach for community/partner engagement that is especially useful when designing technology-based strategies. By using HCD methods, we were able to elicit determinants to both the evidence-based practice (breast cancer screening) and the proposed implementation strategy (chatbot). Moreover, we received nuanced feedback about the chatbot in its current design rather than as a hypothetical strategy (as visual tools in qualitative research can enhance the quality and clarity of data) [ 85 ]. By doing so, we gained important insights about the implementation strategy—e.g., our early prototype design lacked the depth of cultural inclusivity and familiarity needed to elicit trust and promote use of the chatbot despite being informed by breast cancer screening determinants elicited in our initial interviews. These insights were integral to the CPD development and prioritization of trust as a determinant to chatbot use and subsequent breast cancer screening.

Using HCD methods meant that we brought community partners into the design process in the earliest stages. Having text and visual content to react to allowed community partners to identify specifically what they liked and disliked about the design and how they would word chatbot messages differently—giving very concrete feedback to incorporate into future design iterations. There have been many calls to incorporate health equity in implementation science frameworks, strategies, and outcomes [ 65 , 86 , 87 , 88 , 89 ]. Integrating the perspectives of populations with marginalized identities into the development of implementation strategies can help to address health equity more effectively and mitigate intervention-generated inequities [ 90 , 91 ].

The CPD which was constructed by data from HCD methods directly informed our next steps in development of the chatbot prototype—(1) a factorial design experiment measuring degree of trust and engagement with different chatbot personas and (2) co-design sessions to craft chatbot messaging. While our case example details the design of an innovative implementation strategy, we believe this approach could be useful in tailoring a broad spectrum of implementation strategies and adds to existing literature on methods to tailor implementation strategies [ 92 ].

Limitations

Our case study example has several limitations. Topically, while most people will have access to SMS-based interventions, this intervention will not be accessible and/or acceptable for all eligible patients [ 51 ]. During this work, we received feedback that the chatbot may be especially effective among younger age groups, but that uptake may be lower among older adults. As the USPSTF guidelines are expected to change to recommend earlier screening starting at 40 years, this implementation strategy could be particularly acceptable to outreach to newly eligible patients [ 93 ]. We readily acknowledge that a single intervention will not fully address breast cancer screening inequities and should be implemented as one part of a multi-faceted health system approach.

Methodologically, the chatbot development case example could have been strengthened using a determinant framework. We would encourage investigators interested in this approach to incorporate determinant frameworks in initial evidence review and data collection. Our methodological approach could also be strengthened by increasing community engagement [ 10 , 14 ]. While we incorporated several elements of community-engaged research (including community members on the research team, having a trained community member conduct research with community participants, and community member co-authorship), we could have further expanded community participation (e.g., seek community input in initial intervention design, create a community advisory board).

The use of interdisciplinary methods is core to implementation science [ 94 ]. HCD is a particularly synergistic discipline with multiple existing applications of HCD to implementation research. We present an extension of this work and an example of the potential value in an integrated approach of HCD and IS researchers and methods to combine strengths of both disciplines and develop human-centered, co-designed implementation strategies rooted in causal perspective and healthcare equity.

Availability of data and materials

Aggregated qualitative data is available by request in accordance with a funding agreement. Disaggregated data is not available to maintain privacy and confidentiality of interview and focus group participants.

Abbreviations

Electronic health record

Enhancing the Quality and Transparency of health research

• Human-centered design

Primary care provider

Short message service

Template for intervention description and replication

United States Preventive Services Task Force

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Acknowledgements

We thank Aiza Ali, Natasha Schmid, and Xuan Song for their work in qualitative data collection and analysis, Lorella Palazzo and Nora Henrikson for their support and feedback in rapid qualitative methods and rapid evidence review, respectively, and Predrag Klasnja for his advice and guidance in this work. We thank all the interview and focus group participants who gave us valuable feedback to inform this work.

Research reported in this publication was supported by the University of Washington Medicine Patients are First Innovation Pilot (institutional funding, no grant number), the National Cancer Institute of the National Institutes of Health under Award Number P50CA244432, and the Agency for Healthcare Research and Quality under Award Number K12HS026369. The content is solely the responsibility of the authors and does not necessarily represent the official views of University of Washington, the National Institutes of Health, or the Agency for Healthcare Research and Quality.

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L.M.M. and G.H. had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. L.M.M., R.L., B.R.H., A.G., A.R.L., B.J.W., N.A., P.L.H., V.F., and G.H. were involved in concept and design. L.M.M., R.L., B.R.H., A.G., N.A., V.F., and G.H. were involved in the data collection process. L.M.M., R.L., B.R.H., and G.H. analyzed and interpreted the data. L.M.M. drafted the manuscript and L.M.M., R.L., B.R.H., A.G., A.R.L., B.J.W., N.A., P.L.H., V.F., and G.H. revised the manuscript. L.M.M., R.L., B.R.H., A.G., A.R.L., B.J.W., N.A., P.L.H., V.F., and G.H. approved the final submitted version, agreed to be accountable for the report, and had final responsibility for the decision to submit for publication. L.M.M. and G.H. confirm that they had access to the data in the study and accept responsibility to submit for publication.

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Additional file 2: Fig. S1.

Early Chatbot Prototype.

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Marcotte, L.M., Langevin, R., Hempstead, B.R. et al. Leveraging human-centered design and causal pathway diagramming toward enhanced specification and development of innovative implementation strategies: a case example of an outreach tool to address racial inequities in breast cancer screening. Implement Sci Commun 5 , 31 (2024). https://doi.org/10.1186/s43058-024-00569-w

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Using the consolidated Framework for Implementation Research to integrate innovation recipients’ perspectives into the implementation of a digital version of the spinal cord injury health maintenance tool: a qualitative analysis

• John A Bourke 1 , 2 , 3 ,
• K. Anne Sinnott Jerram 1 , 2 ,
• Mohit Arora 1 , 2 ,
• Ashley Craig 1 , 2 &
• James W Middleton 1 , 2 , 4 , 5  

BMC Health Services Research volume  24 , Article number:  390 ( 2024 ) Cite this article

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Despite advances in managing secondary health complications after spinal cord injury (SCI), challenges remain in developing targeted community health strategies. In response, the SCI Health Maintenance Tool (SCI-HMT) was developed between 2018 and 2023 in NSW, Australia to support people with SCI and their general practitioners (GPs) to promote better community self-management. Successful implementation of innovations such as the SCI-HMT are determined by a range of contextual factors, including the perspectives of the innovation recipients for whom the innovation is intended to benefit, who are rarely included in the implementation process. During the digitizing of the booklet version of the SCI-HMT into a website and App, we used the Consolidated Framework for Implementation Research (CFIR) as a tool to guide collection and analysis of qualitative data from a range of innovation recipients to promote equity and to inform actionable findings designed to improve the implementation of the SCI-HMT.

Data from twenty-three innovation recipients in the development phase of the SCI-HMT were coded to the five CFIR domains to inform a semi-structured interview guide. This interview guide was used to prospectively explore the barriers and facilitators to planned implementation of the digital SCI-HMT with six health professionals and four people with SCI. A team including researchers and innovation recipients then interpreted these data to produce a reflective statement matched to each domain. Each reflective statement prefaced an actionable finding, defined as alterations that can be made to a program to improve its adoption into practice.

Five reflective statements synthesizing all participant data and linked to an actionable finding to improve the implementation plan were created. Using the CFIR to guide our research emphasized how partnership is the key theme connecting all implementation facilitators, for example ensuring that the tone, scope, content and presentation of the SCI-HMT balanced the needs of innovation recipients alongside the provision of evidence-based clinical information.

Conclusions

Understanding recipient perspectives is an essential contextual factor to consider when developing implementation strategies for healthcare innovations. The revised CFIR provided an effective, systematic method to understand, integrate and value recipient perspectives in the development of an implementation strategy for the SCI-HMT.

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Injury to the spinal cord can occur through traumatic causes (e.g., falls or motor vehicle accidents) or from non-traumatic disease or disorder (e.g., tumours or infections) [ 1 ]. The onset of a spinal cord injury (SCI) is often sudden, yet the consequences are lifelong. The impact of a SCI is devastating, with effects on sensory and motor function, bladder and bowel function, sexual function, level of independence, community participation and quality of life [ 2 ]. In order to maintain good health, wellbeing and productivity in society, people with SCI must develop self-management skills and behaviours to manage their newly acquired chronic health condition [ 3 ]. Given the increasing emphasis on primary health care and community management of chronic health conditions, like SCI, there is a growing responsibility on all parties to promote good health practices and minimize the risks of common health complications in their communities.

To address this need, the Spinal Cord Injury Health Maintenance Tool (SCI-HMT) was co-designed between 2018 and 2023 with people living with SCI and their General Practitioners (GPs) in NSW, Australia [ 4 ] The aim of the SCI-HMT is to support self-management of the most common and arguably avoidable potentially life-threatening complications associated with SCI, such as mental health crises, autonomic dysreflexia, kidney infections and pressure injuries. The SCI-HMT provides comprehensible information with resources about the six highest priority health areas related to SCI (as indicated by people with SCI and GPs) and was developed over two phases. Phase 1 focused on developing a booklet version and Phase 2 focused on digitizing this content into a website and smartphone app [ 4 , 5 ].

Enabling the successful implementation of evidence-based innovations such as the SCI-HMT is inevitably influenced by contextual factors: those dynamic and diverse array of forces within real-world settings working for or against implementation efforts [ 6 ]. Contextual factors often include background environmental elements in which an intervention is situated, for example (but not limited to) demographics, clinical environments, organisational culture, legislation, and cultural norms [ 7 ]. Understanding the wider context is necessary to identify and potentially mitigate various challenges to the successful implementation of those innovations. Such work is the focus of determinant frameworks, which focus on categorising or classing groups of contextual determinants that are thought to predict or demonstrate an effect on implementation effectiveness to better understand factors that might influence implementation outcomes [ 8 ].

One of the most highly cited determinant frameworks is the Consolidated Framework for Implementation Research (CFIR) [ 9 ], which is often posited as an ideal framework for pre-implementation preparation. Originally published in 2009, the CFIR has recently been subject to an update by its original authors, which included a literature review, survey of users, and the creation of an outcome addendum [ 10 , 11 ]. A key contribution from this revision was the need for a greater focus on the place of innovation recipients, defined as the constituency for whom the innovation is being designed to benefit; for example, patients receiving treatment, students receiving a learning activity. Traditionally, innovation recipients are rarely positioned as key decision-makers or innovation implementers [ 8 ], and as a consequence, have not often been included in the application of research using frameworks, such as the CFIR [ 11 ].

Such power imbalances within the intersection of healthcare and research, particularly between those receiving and delivering such services and those designing such services, have been widely reported [ 12 , 13 ]. There are concerted efforts within health service development, health research and health research funding, to rectify this power imbalance [ 14 , 15 ]. Importantly, such efforts to promote increased equitable population impact are now being explicitly discussed within the implementation science literature. For example, Damschroder et al. [ 11 ] has recently argued for researchers to use the CFIR to collect data from innovation recipients, and that, ultimately, “equitable population impact is only possible when recipients are integrally involved in implementation and all key constituencies share power and make decisions together” (p. 7). Indeed, increased equity between key constituencies and partnering with innovation recipients promotes the likelihood of sustainable adoption of an innovation [ 4 , 12 , 14 ].

There is a paucity of work using the updated CFIR to include and understand innovation recipients’ perspectives. To address this gap, this paper reports on a process of using the CFIR to guide the collection of qualitative data from a range of innovation recipients within a wider co-design mixed methods study examining the development and implementation of SCI-HMT. The innovation recipients in our research are people living with SCI and GPs. Guided by the CFIR domains (shown in the supplementary material), we used reflexive thematic analysis [ 16 ]to summarize data into reflective summaries, which served to inform actionable findings designed to improve implementation of the SCI-HMT.

The procedure for this research is multi-stepped and is summarized in Fig.  1 . First, we mapped retrospective qualitative data collected during the development of the SCI-HMT [ 4 ] against the five domains of the CFIR in order to create a semi-structured interview guide (Step 1). Then, we used this interview guide to collect prospective data from health professionals and people with SCI during the development of the digital version of the SCI-HMT (Step 2) to identify implementation barriers and facilitators. This enabled us to interpret a reflective summary statement for each CFIR domain. Lastly, we developed an actionable finding for each domain summary. The first (RESP/18/212) and second phase (2019/ETH13961) of the project received ethical approval from The Northern Sydney Local Health District Human Research Ethics Committee. The reporting of this study was conducted in line with the consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines [ 17 ]. All methods were performed in accordance with the relevant guidelines and regulations.

Procedure of synthesising datasets to inform reflective statements and actionable findings. a Two health professionals had a SCI (one being JAB); b Two co-design researchers had a SCI (one being JAB)

Step one: retrospective data collection and analysis

We began by retrospectively analyzing the data set (interview and focus group transcripts) from the previously reported qualitative study from the development phase of the SCI-HMT [ 4 ]. This analysis was undertaken by two team members (KASJ and MA). KASJ has a background in co-design research. Transcript data were uploaded into NVivo software (Version 12: QSR International Pty Ltd) and a directed content analysis approach [ 18 ] was applied to analyze categorized data a priori according to the original 2009 CFIR domains (intervention characteristics, outer setting, inner setting, characteristics of individuals, and process of implementation) described by Damschroder et al. [ 9 ]. This categorized data were summarized and informed the specific questions of a semi-structured interview guide. The final output of step one was an interview guide with context-specific questions arranged according to the CFIR domains (see supplementary file 1). The interview was tested with two people with SCI and one health professional.

Step two: prospective data collection and analysis

In the second step, semi-structured interviews were conducted by KASJ (with MA as observer) with consenting healthcare professionals who had previously contributed to the development of the SCI-HMT. Healthcare professionals included GPs, Nurse Consultants, Specialist Physiotherapists, along with Health Researchers (one being JAB). In addition, a focus group was conducted with consenting individuals with SCI who had contributed to the SCI-HMT design and development phase. The interview schedule designed in step one above guided data collection in all interviews and the focus group.

The focus group and interviews were conducted online, audio recorded, transcribed verbatim and uploaded to NVivo software (Version 12: QSR International Pty Ltd). All data were subject to reflexive, inductive and deductive thematic analysis [ 16 , 19 ] to better understand participants’ perspectives regarding the potential implementation of the SCI-HMT. First, one team member (KASJ) read transcripts and began a deductive analysis whereby data were organized into CFIR domains-specific dataset. Second, KASJ and JAB analyzed this domain-specific dataset to inductively interpret a reflective statement which served to summarise all participant responses to each domain. The final output of step two was a reflective summary statement for each CFIR domain.

Step three: data synthesis

In the third step we aimed to co-create an actionable finding (defined as tangible alteration that can be made to a program, in this case the SCI-HMT [ 20 ]) based on each domain-specific reflective statement. To achieve this, three codesign researchers (KAS and JAB with one person with SCI from Step 2 (deidentified)) focused on operationalising each reflective statement into a recommended modification for the digital version of the SCI-HMT. This was an iterative process guided by the specific CFIR domain and construct definitions, which we deemed salient and relevant to each reflective statement (see Table  2 for example). Data synthesis involved line by line analysis, group discussion, and repeated refinement of actionable findings. A draft synthesis was shared with SCI-HMT developers (JWM and MA) and refinement continued until consensus was agreed on. The final outputs of step three were an actionable finding related to each reflective statement for each CFIR domain.

The characteristics of both the retrospective and prospective study participants are shown in Table  1 . The retrospective data included data from a total of 23 people: 19 people with SCI and four GPs. Of the 19 people with SCI, 12 participated in semi-structured interviews, seven participated in the first focus group, and four returned to the second focus group. In step 2, four people with SCI participated in a focus group and six healthcare professionals participated in one-on-one semi-structured interviews. Two of the healthcare professionals (a GP and a registrar) had lived experience of SCI, as did one researcher (JAB). All interviews and focus groups were conducted either online or in-person and ranged in length between 60 and 120 min.

In our overall synthesis, we actively interpreted five reflective statements based on the updated CFIR domain and construct definitions by Damschroder et al. [ 11 ]. Table  2 provides a summary of how we linked the updated CFIR domain and construct definitions to the reflective statements. We demonstrate this process of co-creation below, including illustrative quotes from participants. Importantly, we guide readers to the actionable findings related to each reflective statement in Table  2 . Each actionable statement represents an alteration that can be made to a program to improve its adoption into practice.

Participants acknowledged that self-management is a major undertaking and very demanding, as one person with SCI said, “ we need to be informed without being terrified and overwhelmed”. Participants felt the HMT could indeed be adapted, tailored, refined, or reinvented to meet local needs. For example, another person with SCI remarked:

“Education needs to be from the get-go but in bite sized pieces from all quarters when readiness is most apparent… at all time points , [not just as a] a newbie tool or for people with [long-term impairment] ” (person with SCI_02).

Therefore, the SCI-HMT had to balance complexity of content while still being accessible and engaging, and required input from both experts in the field and those with lived experience of SCI, for example, a clinical nurse specialist suggested:

“it’s essential [the SCI-HMT] is written by experts in the field as well as with collaboration with people who have had a, you know, the lived experience of SCI” (healthcare professional_03).

Furthermore, the points of contact with healthcare for a person with SCI can be challenging to navigate and the SCI-HMT has the potential to facilitate a smoother engagement process and improve communication between people with SCI and healthcare services. As a GP suggested:

“we need a tool like this to link to that pathway model in primary health care , [the SCI-HMT] it’s a great tool, something that everyone can read and everyone’s reading the same thing” (healthcare professional_05).

Participants highlighted that the ability of the SCI-HMT to facilitate effective communication was very much dependent on the delivery format. The idea of digitizing the SCI-HMT garnered equal support from people with SCI and health care professionals, with one participant with SCI deeming it to be “ essential” ( person with SCI_01) and a health professional suggesting a “digitalized version will be an advantage for most people” (healthcare professional_02).

Outer setting

There was strong interest expressed by both people with SCI and healthcare professionals in using the SCI-HMT. The fundamental premise was that knowledge is power and the SCI-HMT would have strong utility in post-acute rehabilitation services, as well as primary care. As a person with SCI said,

“ we need to leave the [spinal unit] to return to the community with sufficient knowledge, and to know the value of that knowledge and then need to ensure primary healthcare provider [s] are best informed” (person with SCI_04).

The value of the SCI-HMT in facilitating clear and effective communication and shared decision-making between healthcare professionals and people with SCI was also highlighted, as shown by the remarks of an acute nurse specialist:

“I think this tool is really helpful for the consumer and the GP to work together to prioritize particular tests that a patient might need and what the regularity of that is” (healthcare professional_03).

Engaging with SCI peer support networks to promote the SCI-HMT was considered crucial, as one person with SCI emphasized when asked how the SCI-HMT might be best executed in the community, “…peers, peers and peers” (person with SCI_01). Furthermore, the layering of content made possible in the digitalized version will allow for the issue of approachability in terms of readiness for change, as another person with SCI said:

“[putting content into a digital format] is essential and required and there is a need to put summarized content in an App with links to further web-based information… it’s not likely to be accessed otherwise” (person with SCI_02).

Inner setting

Participants acknowledged that self-management of health and well-being is substantial and demanding. It was suggested that the scope, tone, and complexity of the SCI-HMT, while necessary, could potentially be resisted by people with SCI if they felt overwhelmed, as one person with SCI described:

“a manual that is really long and wordy, like, it’s [a] health metric… they maybe lack the health literacy to, to consume the content then yes, it would impede their readiness for [self-management]” (person with SCI_02).

Having support from their GPs was considered essential, and the HMT could enable GP’s, who are under time pressure, to provide more effective health and advice to their patients, as one GP said:

“We GP’s are time poor, if you realize then when you’re time poor you look quickly to say oh this is a patient tool - how can I best use this?” (healthcare professional_05).

Furthermore, health professional skills may be best used with the synthesis of self-reported symptoms, behaviors, or observations. A particular strength of a digitized version would be its ability to facilitate more streamlined communication between a person with SCI and their primary healthcare providers developing healthcare plans, as an acute nurse specialist reflected, “ I think that a digitalized version is essential with links to primary healthcare plans” (healthcare professional_03).

Efficient communication with thorough assessment is essential to ensure serious health issues are not missed, as findings reinforce that the SCI-HMT is an educational tool, not a replacement for healthcare services, as a clinical nurse specialist commented, “ remember, things will go wrong– people end up very sick and in acute care “ (healthcare professional_02).

The SCI-HMT has the potential to provide a pathway to a ‘hope for better than now’ , a hope to ‘remain well’ and a hope to ‘be happy’ , as the informant with SCI (04) declared, “self-management is a long game, if you’re keeping well, you’ve got that possibility of a good life… of happiness”. Participants with SCI felt the tool needed to be genuine and

“acknowledge the huge amount of adjustment required, recognizing that dealing with SCI issues is required to survive and live a good life” (person with SCI_04).

However, there is a risk that an individual is completely overwhelmed by the scale of the SCI-HMT content and the requirement for lifelong vigilance. Careful attention and planning were paid to layering the information accordingly to support self-management as a ‘long game’, which one person with SCI reflected in following:

“the first 2–3 year [period] is probably the toughest to get your head around the learning stuff, because you’ve got to a stage where you’re levelling out, and you’ve kind of made these promises to yourself and then you realize that there’s no quick fix” (person with SCI_01).

It was decided that this could be achieved by providing concrete examples and anecdotes from people with SCI illustrating that a meaningful, healthy life is possible, and that good health is the bedrock of a good life with SCI.

There was universal agreement that the SCI-HMT is aspirational and that it has the potential to improve knowledge and understanding for people with SCI, their families, community workers/carers and primary healthcare professionals, as a GP remarked:

“[different groups] could just read it and realize, ‘Ahh, OK that’s what that means… when you’re doing catheters. That’s what you mean when you’re talking about bladder and bowel function or skin care” (healthcare professional_04).

Despite the SCI-HMT providing an abundance of information and resources to support self-management, participants identified four gaps: (i) the priority issue of sexuality, including pleasure and identity, as one person with SCI remarked:

“ sexuality is one of the biggest issues that people with SCI often might not speak about that often cause you know it’s awkward for them. So yeah, I think that’s a that’s a serious issue” (person with SCI_03).

(ii) consideration of the taboo nature of bladder and bowel topics for indigenous people, (iii) urgent need to ensure links for SCI-HMT care plans are compatible with patient management systems, and (iv) exercise and leisure as a standalone topic taking account of effects of physical activity, including impact on mental health and wellbeing but more especially for fun.

To ensure longevity of the SCI-HMT, maintaining a partnership between people with SCI, SCI community groups and both primary and tertiary health services is required for liaison with the relevant professional bodies, care agencies, funders, policy makers and tertiary care settings to ensure ongoing education and promotion of SCI-HMT is maintained. For example, delivery of ongoing training of healthcare professionals to both increase the knowledge base of primary healthcare providers in relation to SCI, and to promote use of the tools and resources through health communities. As a community nurse specialist suggested:

“ improving knowledge in the health community… would require digital links to clinical/health management platforms” (healthcare professional_02).

In a similar vein, a GP suggested:

“ our common GP body would have continuing education requirements… especially if it’s online, in particular for the rural, rural doctors who you know, might find it hard to get into the city” (healthcare professional_04).

The successful implementation of evidence-based innovations into practice is dependent on a wide array of dynamic and active contextual factors, including the perspectives of the recipients who are destined to use such innovations. Indeed, the recently updated CFIR has called for innovation recipient perspectives to be a priority when considering contextual factors [ 10 , 11 ]. Understanding and including the perspectives of those the innovation is being designed to benefit can promote increased equity and validation of recipient populations, and potentially increase the adoption and sustainability of innovations.

In this paper, we have presented research using the recently updated CFIR to guide the collection of innovation recipients’ perspectives (including people with SCI and GPs working in the community) regarding the potential implementation barriers and facilitators of the digital version of the SCI-HMT. Collected data were synthesized to inform actionable findings– tangible ways in which the SCI-HMT could be modified according of the domains of the CFIR (e.g., see Keith et al. [ 20 ]). It is important to note that we conducted this research using the original domains of the CFIR [ 9 ] prior to Damschroder et al. publishing the updated CFIR [ 11 ]. However, in our analysis we were able to align our findings to the revised CFIR domains and constructs, as Damschroder [ 11 ] suggests, constructs can “be mapped back to the original CFIR to ensure longitudinal consistency” (p. 13).

One of the most poignant findings from our analyses was the need to ensure the content of the SCI-HMT balanced scientific evidence and clinical expertise with lived experience knowledge. This balance of clinical and experiential knowledge demonstrated genuine regard for lived experience knowledge, and created a more accessible, engaging, useable platform. For example, in the innovation and individual domains, the need to include lived experience quotes was immediately apparent once the perspective of people with SCI was included. It was highlighted that while the SCI-HMT will prove useful to many parties at various stages along the continuum of care following onset of SCI, there will be those individuals that are overwhelmed by the scale of the content. That said, the layering of information facilitated by the digitalized version is intended to provide an ease of navigation through the SCI-HMT and enable a far greater sense of control over personal health and wellbeing. Further, despite concerns regarding e-literacy the digitalized version of the SCI-HMT is seen as imperative for accessibility given the wide geographic diversity and recent COVID pandemic [ 21 ]. While there will be people who are challenged by the technology, the universally acceptable use of the internet is seen as less of a barrier than printed material.

The concept of partnership was also apparent within the data analysis focusing on the outer and inner setting domains. In the outer setting domain, our findings emphasized the importance of engaging with SCI community groups, as well as primary and tertiary care providers to maximize uptake at all points in time from the phase of subacute rehabilitation onwards. While the SCI-HMT is intended for use across the continuum of care from post-acute rehabilitation onwards, it may be that certain modules are more relevant at different times, and could serve as key resources during the hand over between acute care, inpatient rehabilitation and community reintegration.

Likewise, findings regarding the inner setting highlighted the necessity of a productive partnership between GPs and individuals with SCI to address the substantial demands of long-term self-management of health and well-being following SCI. Indeed, support is crucial, especially when self-management is the focus. This is particularly so in individuals living with complex disability following survival after illness or injury [ 22 ], where health literacy has been found to be a primary determinant of successful health and wellbeing outcomes [ 23 ]. For people with SCI, this tool potentially holds the most appeal when an individual is ready and has strong partnerships and supportive communication. This can enable potential red flags to be recognized earlier allowing timely intervention to avert health crises, promoting individual well-being, and reducing unnecessary demands on health services.

While the SCI-HMT is an educational tool and not meant to replace health services, findings suggest the current structure would lead nicely to having the conversation with a range of likely support people, including SCI peers, friends and family, GP, community nurses, carers or via on-line support services. The findings within the process domain underscored the importance of ongoing partnership between innovation implementers and a broad array of innovation recipients (e.g., individuals with SCI, healthcare professionals, family, funding agencies and policy-makers). This emphasis on partnership also addresses recent discussions regarding equity and the CFIR. For example, Damschroder et al. [ 11 ] suggests that innovation recipients are too often not included in the CFIR process, as the CFIR is primarily seen as a tool intended “to collect data from individuals who have power and/or influence over implementation outcomes” (p. 5).

Finally, we feel that our inclusion of innovation recipients’ perspectives presented in this article begins to address the notion of equity in implementation, whereby the inclusion of recipient perspectives in research using the CFIR both validates, and increases, the likelihood of sustainable adoption of evidence-based innovations, such as the SCI-HMT. We have used the CFIR in a pragmatic way with an emphasis on meaningful engagement between the innovation recipients and the research team, heeding the call from Damschroder et al. [ 11 ], who recently argued for researchers to use the CFIR to collect data from innovation recipients. Adopting this approach enabled us to give voice to innovation recipient perspectives and subsequently ensure that the tone, scope, content and presentation of the SCI-HMT balanced the needs of innovation recipients alongside the provision of evidence-based clinical information.

Our research is not without limitations. While our study was successful in identifying a number of potential barriers and facilitators to the implementation of the SCI-HMT, we did not test any implementation strategies to impact determinants, mechanisms, or outcomes. This will be the focus of future research on this project, which will investigate the impact of implementation strategies on outcomes. Focus will be given to the context-mechanism configurations which give rise to particular outcomes for different groups in certain circumstances [ 7 , 24 ]. A second potential concern is the relatively small sample size of participants that may not allow for saturation and generalizability of the findings. However, both the significant impact of secondary health complications for people with SCI and the desire for a health maintenance tool have been established in Australia [ 2 , 4 ]. The aim our study reported in this article was to achieve context-specific knowledge of a small sample that shares a particular mutual experience and represents a perspective, rather than a population [ 25 , 26 ]. We feel our findings can stimulate discussion and debate regarding participant-informed approaches to implementation of the SCI-HMT, which can then be subject to larger-sample studies to determine their generalisability, that is, their external validity. Notably, future research could examine the interaction between certain demographic differences (e.g., gender) of people with SCI and potential barriers and facilitators to the implementation of the SCI-HMT. Future research could also include the perspectives of other allied health professionals working in the community, such as occupational therapists. Lastly, while our research gave significant priority to recipient viewpoints, research in this space would benefit for ensuring innovation recipients are engaged as genuine partners throughout the entire research process from conceptualization to implementation.

Employing the CFIR provided an effective, systematic method for identifying recipient perspectives regarding the implementation of a digital health maintenance tool for people living with SCI. Findings emphasized the need to balance clinical and lived experience perspectives when designing an implementation strategy and facilitating strong partnerships with necessary stakeholders to maximise the uptake of SCI-HMT into practice. Ongoing testing will monitor the uptake and implementation of this innovation, specifically focusing on how the SCI-HMT works for different users, in different contexts, at different stages and times of the rehabilitation journey.

Data availability

The datasets supporting the conclusions of this article are available available upon request and with permission gained from the project Steering Committee.

Abbreviations

spinal cord injury

HMT-Spinal Cord Injury Health Maintenance Tool

Consolidated Framework for Implementation Research

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Acknowledgements

Authors of this study would like to thank all the consumers with SCI and healthcare professionals for their invaluable contribution to this project. Their participation and insights have been instrumental in shaping the development of the SCI-HMT. The team also acknowledges the support and guidance provided by the members of the Project Steering Committee, as well as the partner organisations, including NSW Agency for Clinical Innovation, and icare NSW. Author would also like to acknowledge the informant group with lived experience, whose perspectives have enriched our understanding and informed the development of SCI-HMT.

The SCI Wellness project was a collaborative project between John Walsh Centre for Rehabilitation Research at The University of Sydney and Royal Rehab. Both organizations provided in-kind support to the project. Additionally, the University of Sydney and Royal Rehab received research funding from Insurance and Care NSW (icare NSW) to undertake the SCI Wellness Project. icare NSW do not take direct responsibility for any of the following: study design, data collection, drafting of the manuscript, or decision to publish.

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John A Bourke, K. Anne Sinnott Jerram, Mohit Arora, Ashley Craig & James W Middleton

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Project conceptualization: KASJ, MA, JWM; project methodology: JWM, MA, KASJ, JAB; data collection: KASJ and MA; data analysis: KASJ, JAB, MA, JWM; writing—original draft preparation: JAB; writing—review and editing: JAB, KASJ, JWM, MA, AC; funding acquisition: JWM, MA. All authors contributed to the revision of the paper and approved the final submitted version.

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The first (RESP/18/212) and second phase (2019/ETH13961) of the project received ethical approval from The Northern Sydney Local Health District Human Research Ethics Committee. All participants provided informed, written consent. All data were to be retained for 7 years (23rd May 2030).

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Bourke, J.A., Jerram, K.A.S., Arora, M. et al. Using the consolidated Framework for Implementation Research to integrate innovation recipients’ perspectives into the implementation of a digital version of the spinal cord injury health maintenance tool: a qualitative analysis. BMC Health Serv Res 24 , 390 (2024). https://doi.org/10.1186/s12913-024-10847-x

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• Mixed Methods Research | Definition, Guide & Examples

Mixed Methods Research | Definition, Guide & Examples

Published on August 13, 2021 by Tegan George . Revised on June 22, 2023.

Mixed methods research combines elements of quantitative research and qualitative research in order to answer your research question . Mixed methods can help you gain a more complete picture than a standalone quantitative or qualitative study, as it integrates benefits of both methods.

Mixed methods research is often used in the behavioral, health, and social sciences, especially in multidisciplinary settings and complex situational or societal research.

• To what extent does the frequency of traffic accidents ( quantitative ) reflect cyclist perceptions of road safety ( qualitative ) in Amsterdam?
• How do student perceptions of their school environment ( qualitative ) relate to differences in test scores ( quantitative ) ?
• How do interviews about job satisfaction at Company X ( qualitative ) help explain year-over-year sales performance and other KPIs ( quantitative ) ?
• How can voter and non-voter beliefs about democracy ( qualitative ) help explain election turnout patterns ( quantitative ) in Town X?
• How do average hospital salary measurements over time (quantitative) help to explain nurse testimonials about job satisfaction (qualitative) ?

Table of contents

When to use mixed methods research, mixed methods research designs, advantages of mixed methods research, disadvantages of mixed methods research, other interesting articles, frequently asked questions.

Mixed methods research may be the right choice if your research process suggests that quantitative or qualitative data alone will not sufficiently answer your research question. There are several common reasons for using mixed methods research:

• Generalizability : Qualitative research usually has a smaller sample size , and thus is not generalizable. In mixed methods research, this comparative weakness is mitigated by the comparative strength of “large N,” externally valid quantitative research.
• Contextualization: Mixing methods allows you to put findings in context and add richer detail to your conclusions. Using qualitative data to illustrate quantitative findings can help “put meat on the bones” of your analysis.
• Credibility: Using different methods to collect data on the same subject can make your results more credible. If the qualitative and quantitative data converge, this strengthens the validity of your conclusions. This process is called triangulation .

As you formulate your research question , try to directly address how qualitative and quantitative methods will be combined in your study. If your research question can be sufficiently answered via standalone quantitative or qualitative analysis, a mixed methods approach may not be the right fit.

But mixed methods might be a good choice if you want to meaningfully integrate both of these questions in one research study.

Keep in mind that mixed methods research doesn’t just mean collecting both types of data; you need to carefully consider the relationship between the two and how you’ll integrate them into coherent conclusions.

Mixed methods can be very challenging to put into practice, and comes with the same risk of research biases as standalone studies, so it’s a less common choice than standalone qualitative or qualitative research.

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There are different types of mixed methods research designs . The differences between them relate to the aim of the research, the timing of the data collection , and the importance given to each data type.

As you design your mixed methods study, also keep in mind:

• Your research approach ( inductive vs deductive )
• Your research questions
• What kind of data is already available for you to use
• What kind of data you’re able to collect yourself.

Here are a few of the most common mixed methods designs.

Convergent parallel

In a convergent parallel design, you collect quantitative and qualitative data at the same time and analyze them separately. After both analyses are complete, compare your results to draw overall conclusions.

• On the qualitative side, you analyze cyclist complaints via the city’s database and on social media to find out which areas are perceived as dangerous and why.
• On the quantitative side, you analyze accident reports in the city’s database to find out how frequently accidents occur in different areas of the city.

In an embedded design, you collect and analyze both types of data at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.

This is a good approach to take if you have limited time or resources. You can use an embedded design to strengthen or supplement your conclusions from the primary type of research design.

Explanatory sequential

In an explanatory sequential design, your quantitative data collection and analysis occurs first, followed by qualitative data collection and analysis.

You should use this design if you think your qualitative data will explain and contextualize your quantitative findings.

Exploratory sequential

In an exploratory sequential design, qualitative data collection and analysis occurs first, followed by quantitative data collection and analysis.

You can use this design to first explore initial questions and develop hypotheses . Then you can use the quantitative data to test or confirm your qualitative findings.

“Best of both worlds” analysis

Combining the two types of data means you benefit from both the detailed, contextualized insights of qualitative data and the generalizable , externally valid insights of quantitative data. The strengths of one type of data often mitigate the weaknesses of the other.

For example, solely quantitative studies often struggle to incorporate the lived experiences of your participants, so adding qualitative data deepens and enriches your quantitative results.

Solely qualitative studies are often not very generalizable, only reflecting the experiences of your participants, so adding quantitative data can validate your qualitative findings.

Method flexibility

Mixed methods are less tied to disciplines and established research paradigms. They offer more flexibility in designing your research, allowing you to combine aspects of different types of studies to distill the most informative results.

Mixed methods research can also combine theory generation and hypothesis testing within a single study, which is unusual for standalone qualitative or quantitative studies.

Mixed methods research is very labor-intensive. Collecting, analyzing, and synthesizing two types of data into one research product takes a lot of time and effort, and often involves interdisciplinary teams of researchers rather than individuals. For this reason, mixed methods research has the potential to cost much more than standalone studies.

Differing or conflicting results

If your analysis yields conflicting results, it can be very challenging to know how to interpret them in a mixed methods study. If the quantitative and qualitative results do not agree or you are concerned you may have confounding variables , it can be unclear how to proceed.

Due to the fact that quantitative and qualitative data take two vastly different forms, it can also be difficult to find ways to systematically compare the results, putting your data at risk for bias in the interpretation stage.

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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.

• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• 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.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

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.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

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Exploring athlete pain assessment experiences and priorities; A two-part qualitative series of athlete and physiotherapist interactions. Part Two. Forging Our Future - Athlete and physiotherapist priorities for pain assessment and beyond.

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Objectives: To explore the priorities and directions of athlete upper and lower limb pain assessment by facilitating shared understandings of athletes and sports physiotherapists. Design; Qualitative Research using a hermeneutic phenomenological approach. Methods: We carried out focus groups using a deliberate criterion sample and a constructivist perspective. At the end of each focus group, we used the nominal group technique method to generate a list of consensus-based priorities for future pain assessment. Our paper follows the consolidated criteria for reporting qualitative research (COREQ) guidelines. Results: We completed five focus groups, comprising twelve athletes (female, n=5, male n=7) and four sports physiotherapists (male, n=4 ) Two final themes (and six subthemes) were developed; (i) Enhanced Communication and Pain Descriptions (describing and representing pain, better communication, the role of technology, providing direction and setting the pace), (ii) Integrating Sport Specific and Multidimensional Assessments (broadening the pain assessment toolkit, the role of technology). We developed a set of thirteen practical priorities for pain assessment that span the subjective, objective, and general aspects of the athlete pain assessment. Conclusion: We have presented stakeholder-generated perspectives, directions, and priorities for athlete pain assessment. Athletes and Physiotherapists must continue to work together to achieve a comprehensive sport-specific multidimensional pain assessment experience alongside their wider support networks to ensure optimal representation and communication. We have highlighted some available pain assessment tools and strategies and outlined how novel tools may address certain gaps in the assessment process. Researchers, clinicians, and athletes can consider the practical guidance we have provided to address these priorities.

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This work was supported by funding from Science Foundation Ireland under the grant for the Insight SFI Research Centre for Data Analytics (SFI/12/RC/2289_P2) Funders had no role in the data collection, analysis or interpretation and will have no role in approving the final manuscript.

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9 methodologies for a successful qualitative research assignment

Qualitative research is important in the educational and scientific domains. It enables a deeper understanding of phenomena, experiences, and context. Many researchers employ such research activities in the fields of history, sociology, and anthropology. For such researchers, learning quality analysis insights is crucial. This way, they can perform well throughout their research journey. Writing a qualitative research assignment is one such way to practice qualitative interpretations. When students address various qualitative questions in these projects, they become efficient in conducting these activities at a higher level, such as for a master’s or Ph.D. thesis.

The FormPlus highlights why researchers prefer qualitative research over quantitative research. It is faster, scientific, objective, focused, and acceptable. Researchers who don’t know what to expect from the research outcomes usually choose qualitative research. In this guide, we will discuss the top methodologies that students can employ while writing their qualitative research assignments. This way, you can write an appealing document that perfectly demonstrates your qualitative research skills.

However, being stressed with academic and daily life commitments, if you find it challenging to manage time exclusively for such projects, availing of assignment writing services can make it manageable. Instead of doing anything wrong in the hustle, get it done by the professionals specifically working to handle these academic write-ups. Now, let’s define quality research before we discuss the actual topic.

What is meant by qualitative research?

Quality research is a market research method that gathers data from conversational and open-ended communication. In simple words, it is about what people think and why they think so. It relates to the nature or standard of something rather than dealing with its quantity. Such researchers collect nonnumerical data to understand opinions, concepts, and ideas.

How do you write a qualitative research assignment? Top 9 methodologies

Writing an assignment requires your command of various tasks. Qualitative research assignment design involves research, writing, structuring, and providing citations of the resources used. Assignment writing plays a crucial role in upgrading your grades.

So, you must make it accurate and authentic. Write it with the utmost care without skipping any important aspects. Sometimes, it can be hard, but it becomes easy if you correctly use effective methodologies. This is why we have brought together some of the common methodologies you can use to write your qualitative research assignments.

1. Interviews

A qualitative interview is mostly used in projects that involve market research. In this study personal interaction is required to collect in-depth information of the participants. In qualitative research for assignment, consider the interview as a personal form of research agenda rather than a focused group study. A qualitative interview requires careful planning so that you can gather meaningful data.

Here are the simple steps to consider for its implementation in a qualitative research assignment:

• Define research objectives.
• Identify the target population.
• Obtain informed consent of participants.
• Make an interview guideline.
• Select a suitable location.
• Conduct the interview.
• Show respect for participant’s perspectives.
• Analyse the data.

2. Observation

In qualitative observation, the researcher gathers data from five senses: sight, hearing, touch, smell, and taste. It is a subject approach that depends on the sensory organ of the researcher. This method allows you to better understand the culture, process, and people under study. Some of its characteristics to consider for writing a qualitative research assignment include,

• It is a naturalistic inquiry of the participants in a natural environment.
• This approach is subjective and depends on the researcher’s observation.
• It does not seek a definite answer to a query.
• The researcher can recognise their own biases when compiling findings.

3. Questionnaires

In this type of survey, the researcher asks open-ended questions to participants. This way, they price the long written or typed document. In writing qualitative research assignments, these questions aim to reveal the participants’ narratives and experiences. Once you know what type of information you need, you can start curating your questionnaire form. The questions must be specific and clear enough that the participants can comprehend them.

Below are the main points that must be considered when creating qualitative research questionnaires.

• Avoid jargon and ambiguity in the questions.
• Each question should contribute to the research objectives.
• Use simple language.
• The questions should be neutral and unbiased.
• Be precise, as the complex questions can overwhelm the respondents.
• Always conduct a pilot test.
• Put yourself in the respondent’s shoes while asking questions.

4. Case Study

A case study is a detailed analysis of a person, place, thing, organisation, or phenomenon. This method is appropriate when you want to gain a contextual, concrete, and in-depth understanding of the real-world problem for writing your qualitative research assignment. This method is especially helpful when you need more time to conduct large-scale research activities.

The four crucial steps below can be followed up with this methodology.

• Select a case that has the potential to provide new and unexpected insights into the subject.
• Make a theoretical framework.
• Collect your data from various primary and secondary resources.
• Describe and analyse the case to provide a clear picture of the subject.

5. Focus Groups

Focused group research has some interesting properties. In this method, a planned interview is conducted within a small group. For this purpose, some of the participants are sampled from the study population to record data for writing a qualitative research assignment. Typically, a focused group has features like,

• At least four to ten participants must meet for up to two hours.
• There must be a facilitator who can guide the discussion by asking open-ended questions.
• The emphasis must be put on the group discussion rather than the discussion of the group members with the facilitator.
• The discussion should be recorded and transcribed by the researchers.

6. Ethnographic Research

It is the most in-depth research method that involves studying people in their natural environment. It requires the researcher to adopt the target audience environment. The environment can be anything from an organisation to a city or any remote location.

However, the geographical constraints can be a problem in this study. For students who are writing their qualitative research assignment, some of the features of ethnographic research to write in their document include,

• The researcher can get a more realistic picture of the study.
• It uncovers extremely valuable insights.
• Provides accurate predictions.
• You can extend the observation to create more in-depth data.
• You can interact with people within a particular context.

7. Record Keeping

This method is similar to going to the library to collect data from books. You consult various relayed books, note the important points, and take note of the referencing. So, the researcher uses already existing data rather than introducing new things in the field.

Later on, this data can be used to conduct new research. Yet, when faced with the vast resources available in your institution’s library, seeking assistance from UK-based assignment writing services is an excellent solution if you need help pinpointing the most relevant information for your topic. Proficient in data gathering and adept at structuring qualitative research assignments, these professionals can significantly elevate your academic results.

This method is mostly used by companies to understand a group of customers’ behaviour, characteristics, and motivation. It allows respondents to ask in-depth questions about their experience. In a business market, it helps you understand how your customers make decisions. The intent is to understand them at their level and make related changes in your setup. The researcher must ask generic and precise questions that have a clear purpose.

Consider the below examples of qualitative survey questions. It can be useful in recording data and writing qualitative research assignments.

• Why did you buy this skin care product?
• What is the overall narrative of this brand?
• How do you feel after buying this product?
• What sets this brand apart from others?
• How will this product fulfil your needs?
• What are the things that you expect from this brand to grant you?

9. Action Research

This method involves collaboration and empowerment of the participants. It is mostly appropriate for marginalised groups where there is no flexibility.

The primary characteristics of the action research that can be quoted in your qualitative research assignment include,

• It is action-oriented, and participants are actively involved in the research.
• There is a collaborative process between participants and researchers.
• The nature of action research is flexible to the changing situation.

However, the survey also accompanies some of the limitations, including,

• The researcher can misinterpret the open-ended questions.
• The data ownership between the researcher and participants needs to be negotiated.
• The ethical considerations must be kept.
• It is not considered a scientific method as it is fluid in data collection. Consequently, it may not attract the finding.

What is the difference between quantitative and qualitative research?

Both research types share the common aim of knowledge acquisition. In quantitative research, the use of numbers and objective measures is used. It seeks answers to questions like when and where.

On the other hand, in qualitative research, the researcher is concerned with subjective phenomena. Such data can’t be numerically measured. For example, you might conduct a survey to analyse how different people experience grief.

What are the 4 types of qualitative research?

There are various types of qualitative research. It may include,

● Phenomenological studies:

It examines the human experience via description provided by the people involved. These are the lived experiences of the people. It is usually used in research areas where little knowledge is known.

● Ethnographic studies:

It involves the analysis of data about cultural groups. In such analysis, the researcher mostly lives with different communities and becomes part of their culture to provide solid interpretations.

● Grounded theory studies:

In this qualitative approach, the researcher collects and analyses the data. Later on, a theory is developed that is grounded in the data. It used both inductive and deductive approaches for theory development.

● Historical studies:

It is concerned with the location, identification, evaluation, and synthesis of data from the past. These researchers are not concerned with discovering past events but with relating these events to the present happenings.

The Research Gate provides a flow chart illustrating various qualitative research methods.

What are The 7 characteristics of qualitative research?

The following are some of the distinct features of qualitative research. You can write about them in your qualitative research assignment, as they are collected from reliable sources.

• It can even capture the changing attitude within the target group.
• It is beyond the limitations associated with quantitative research
• It explains something that numbers alone can’t describe.
• It is a flexible approach to improve the outcomes.
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Midwives’ lived experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini: a qualitative study

• Annie M. Temane 1 ,
• Fortunate N. Magagula 2 &
• Anna G. W. Nolte 1  

BMC Women's Health volume  24 , Article number:  207 ( 2024 ) Cite this article

Metrics details

Midwives encounter various difficulties while aiming to achieve excellence in providing maternity care to women with mobility disabilities. The study aimed to explore and describe midwives’ experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini.

A qualitative, exploratory, descriptive, contextual research design with a phenomenological approach was followed. Twelve midwives working in maternal health facilities in the Hhohho and Manzini regions in Eswatini were interviewed. Purposive sampling was used to select midwives to participate in the research. In-depth phenomenological interviews were conducted, and Giorgi’s descriptive phenomenological method was used for data analysis.

Three themes emerged from the data analysis: midwives experienced physical and emotional strain in providing maternity care to women with mobility disabilities, they experienced frustration due to the lack of equipment to meet the needs of women with mobility disabilities, and they faced challenges in providing support and holistic care to women with mobility disabilities during pregnancy, labour and puerperium.

Conclusions

Midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and the puerperium in Eswatini. There is a need to develop and empower midwives with the knowledge and skill to implement guidelines and enact protocols. Moreover, equipment and infrastructure are required to facilitate support and holistic maternity care for women with mobility disabilities.

Peer Review reports

Globally, few studies have focused on midwives’ views of providing maternity care to women with mobility disabilities during pregnancy, labour and the puerperium [ 1 ]. In The Disabled World [ 2 ], the World Health Organisation (WHO) defines ‘disability’ as an umbrella term covering impairments, activity limitations, and participation restrictions. Furthermore, the WHO defines an ‘impairment’ as a problem in bodily function or structure; an ‘activity limitation’ as a difficulty encountered by an individual in executing a task or action; and ‘participation restriction’ as a problem experienced by an individual in various life situations [ 2 ]. In this study, mobility disabilities refer to an impairment in the functioning of the upper and lower extremities as experienced by women during pregnancy, labour and the puerperium.

Midwives, as frontline workers in the delivery of maternity care [ 3 ] responsible for the lives of the mother and the baby, are accountable for providing competent and holistic care for women during pregnancy, labour and puerperium. As part of healthcare provision, midwives play an important role in ensuring that every woman, including women with mobility disabilities, receives the best maternity care during pregnancy, labour and puerperium. Moridi et al. [ 4 ] state that women with mobility disabilities are entitled to feel safe, respected and well cared for by midwives, who must be sufficiently prepared to care for these women.

According to the Global Population Report, [ 5 ] more than one billion people have some form of disability. Eswatini is classified as a middle-income setting in the southern African region, measuring 17 000 square kilometres with a population of 1 093 238. Of the population, 76.2% reside in rural areas (833 472), and 23.8% (259 766) reside in urban areas [ 6 ]. The economy is largely agricultural as most industries manufacture agricultural products [ 7 ]. Of the Eswatini population, 146 554 (13%) live with disabilities, with most being women (87 258; 16%), 22,871 (14.1%) and 26,270 (14.3%) of them reside in the Hhohho and Manzini regions respectively [ 8 ]. 15% (125 545) of people with disabilities live in rural areas, and 85% of the disabled population is unemployed [ 8 ], which means most of these individuals are economically disadvantaged. Furthermore, according to the Eswatini Central Statistics Office, 8 26.5% of people with disabilities have a mobility (walking) disability, with 63.5% of these being women.

Midwives may encounter difficulties while aiming to achieve excellence in providing maternity care to women with mobility disabilities in what may be challenging circumstances [ 9 ]. The WHO [ 10 ] claims people with disabilities do not receive the health services they need and are thus likely to find healthcare providers have inadequate skills. Lawler et al. [ 11 ] argue that ineffective interactions and poor communication with women needing care, particularly among health professionals engaged in providing maternity services, limit these women’s opportunities to participate in decision-making processes during pregnancy, childbirth, and postpartum care. According to the University of Johannesburg, [ 12 ] the midwife, together with the mother, have to engage collaboratively in order to come up with opportunities to promote health while removing any challenges that could impede the achievement thereof.

Walsh-Gallagher et al. [ 13 ] postulate that healthcare professionals tend to view women with disabilities as liabilities and regard them as high risk; they often exclude them from the individualised plan of care, which leads to an increase in these women’s fears about their maternity care. These challenges frequently result in health disparities and prevent women with mobility disabilities from receiving optimal maternity care. By exploring midwives’ experiences of this phenomenon, guidelines for support can be developed to extend available knowledge on maternity care for women with mobility disabilities during pregnancy, labour and puerperium.

Study design

The aim of the study was to explore and describe midwives’ experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in the Hhohho and Manzini regions of Eswatini. A qualitative, [ 14 ] exploratory, [ 15 ] descriptive, [ 16 ] contextual [ 17 ] research design with a phenomenological approach [ 18 ] was applied for this study to gain insight and understanding of the research phenomenon [ 19 ]. The phenomenon under study was midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium. The participants were approached face-to-face to participate in the study. The researchers followed the Consolidated Criteria for Reporting Qualitative Research (COREQ) to report on this qualitative study [ 20 ].

The setting for the study was the Hhohho and Manzini regions of Eswatini. The researcher collected data at the site where participants experienced the phenomenon, as emphasised by Yildiz, [ 21 ] within the context in which they were comfortable to be interviewed [ 22 ]. This setting included maternal health facilities in hospitals and public health units.

Population and sampling

The study’s population comprised midwives working in maternal health facilities in hospitals and public health units, that is, one referral hospital and one public health unit in the Hhohho region and two referral hospitals and one public health unit in the Manzini region of Eswatini. Purposive sampling was used to select midwives to participate in the study; [ 16 ] 12 midwives from both regions were included. The midwives were between the ages of 35 and 55, and all midwives were black in race and identified as females. The years of experience in the field ranged between 5 and 15 years. The criteria for inclusion were midwives who had provided maternity care to women with mobility disabilities during pregnancy, labour and puerperium for a period of not more than two to three years, willing to participate in the study. The sample size was determined by repetitions of key statements about the research phenomenon during data collection, termed data saturation [ 23 ]. None of the participants refused to participate in the study.

Table  1 summarises the participants’ demographic characteristics.

Data collection

In-depth phenomenological, face-to-face, individual interviews were conducted to collect data [ 17 ]. The researcher who was a Midwifery lecturer held a Master’s Degree in Maternal and Neonatal science at the time of the study requested approval from the Unit manager to seek permission from the midwives to take part in the study. The midwives were given an information letter which included objectives of the study and the reasons for conducting the study. After recruiting midwives and obtaining their written consent to participate in the study and permission to audio-record the interviews, the researcher set up appointments with them for the interviews, and the data collection process commenced. The central question posed to participants was: How was it for you to care for a woman with a mobility disability during pregnancy, labour and puerperium? A pilot of the tool was performed on the first participant who met the inclusion criteria and possessed the same characteristics as those of the study sample. The pre-testing question yielded positive results, the participant responded to the question asked and there was no need to rephrase it or further test it.

The interviews were conducted from March 2019 to July 2019 and lasted 30–45 min. The researcher conducted interviews until the data became redundant and repetitive, reflecting that saturation had been reached, in congruence with Fouché et al. [ 25 ] In addition, field notes were recorded in a notebook after each in-depth phenomenological interview. No repeat interviews were held. The researcher ensured bracketing by omitting any perceptions from her past experiences that were likely to influence her interpretation of the research findings.

Data analysis

Before data analysis commenced, data were organised in computer files after being transcribed and translated into narrative form. Data from each participant were coded and stored in the relevant file and kept in a safe place; only the researcher could access the information. Back-up copies were made of all the data, and the master copies were stored in a safe to which only the researcher had access.

Data collection and analysis occurred concurrently. The researcher was guided by Giorgi et al.’s [ 26 ] five-step method of data analysis. This entailed the researcher reading all the transcribed data and the entire ‘naïve description’ provided by the participants during the interviews. The demarcation of ‘meaning units’ within narratives followed. In addition, the researcher marked where meaning shifts occurred and transformed meaning units into descriptive expressions. The researcher laid out the general structure of midwives’ experiences. Moreover, an independent coder was provided with the raw data (after signing a confidentiality agreement) to analyse the findings. The researcher and independent coder analysed the data separately and met for a consensus discussion. Both agreed on all the units of analysis, with an inter-coder reliability of 100%.

Measures of trustworthiness

The research was informed by Guba and Lincoln’s [ 27 ] model in relation to credibility, transferability, dependability and confirmability. For credibility, the researcher ensured prolonged engagement in the field [ 28 ], peer debriefing, [ 29 ] member checking, and an external auditor was used [ 25 ]. The study was also presented at a national conference. Transferability refers to the ability to extend the findings of one’s study to comparable environments or participants, as stated by Pitney et al. [ 30 ] The researcher ensured the study’s transferability by providing a richly documented account and in-depth description of all aspects and processes of the study protocol. Data saturation also confirmed transferability [ 23 ]. Dependability is evident in a study when other researchers are able to follow the researcher’s decision trail [ 31 ]. The researcher ensured dependability by densely describing the research process in congruence with Fouché et al.’s [ 25 ] guidelines, so that other researchers can follow similar steps of the same research methodology. Confirmability occurs when the research is judged by the way in which the findings and conclusions achieve their aim and are not the result of the researcher’s prior assumptions and preconceptions [ 32 ]. The researcher ensured this by remaining true to the research process through reflexivity and not compromising the research process in any way [ 28 ]. In addition, the researcher engaged an independent coder and provided a chain of evidence of the entire research process to enable an audit. Therefore, all forms of collected data, including raw data, reflexive journals, [ 29 ] notes and transcriptions, were recorded.

Ethical clearance to conduct this study was obtained from the University of Johannesburg Faculty of Health Sciences Higher Degrees Committee (ref. no. HDC-01-50-2018), University of Johannesburg Faculty of Health Research Ethics Committee (ref. no. REC-01-82-2018), and the Eswatini National Health Research Review Board (ref. no. NHRRB982/2018). The researcher applied and adhered to the four principles to be considered when conducting research: autonomy, beneficence, non-maleficence and justice [ 33 ]. Autonomy was adhered to by affording the participants the right to choose to participate in the study and by signing a written informed consent form a week after it was given to them before the interviews commenced. Beneficence was ensured through doing good and doing no harm to participants by prioritising the participants’ interests above those of the researcher, and did not engage in any practice that jeopardised their rights. Non-maleficence was observed by eradicating any possible harmful risks in the study; the researcher ensured the safety of the participants by conducting interviews in a familiar, private environment where they felt free and safe from harm. Furthermore, justice was observed by treating all participants equally regardless of their biographical, social and economic status.

Three themes and categories emerged from the data analysis. Table  2 summarises the themes and categories of midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini.

Theme 1: physical and emotional efforts required from midwives to provide maternity care to women with mobility disabilities

Category 1.1: midwives experienced that woman with mobility disabilities needed assistance getting onto the bed during labour and delivery.

According to the participants, caring for women with mobility disabilities weighed heavily on them physically as they were required to assist the women onto delivery beds, which were too high for the women to climb up on their own:

“The beds are too high, they need to be adjustable…unless you change her to another room, we only have one in the other room…but to be honest she delivered on the same high bed with the help…It’s uncomfortable even with me who is normal, how about someone who has a disability? Getting the woman onto the bed is also uncomfortable for us we end up having pain on our backs.” (M3) . “The challenge is that I couldn’t help her to climb on to the bed, because I needed someone to assist when she came for postnatal care as she was even carrying 3 babies, I didn’t know what to do…I eventually went out and asked for assistance from my colleague…” (M10) . “I believe that the equipment should accommodate the women with disability, however, ours is not accommodative to the women…there are no special delivery beds, specifically designed for them because in my opinion the beds have to be shorter so they can be able to get on to them easily…yes so that they can be able to climb on the beds” (M1) .

Category 1.2: midwives experienced challenges in manoeuvring women with mobility disabilities during labour

Midwives reported it was difficult to perform some procedures while progressing these women during labour and delivery. This situation called for some adjustment and improvisation on their part, and they were unsure if it was the right thing to do.

“Even though she was a bit uncomfortable and anxious because the leg was just straight and could not bend, I reassured her…She had to remove the artificial leg and remain with the stump. I placed her on the lithotomy position. With the other hand she had to hold on to the ankle of the normal foot, even though it was awkward and difficult to manoeuvre, she managed to deliver the baby.” (M1) . “Luckily for us, she didn’t sustain a tear and we were saved from suturing her cause we foresaw difficulties as how we could have done it as she couldn’t open her thighs well due to the disability…yes I had to get a partner to assist, since she couldn’t even open her thighs. She also couldn’t cooperate possibly because of the pain that is also more reason I asked for my colleague to assist.” (M6) . “…yes…let me make an example, in my case she had a fracture, even if the pelvis was gynaecoid, there were problems of finding the right position for her during delivery, when she had to push the baby out…” (M8) . “The one that I saw did not have one leg. She had come for her postnatal care. We assisted and her on the couch, with my colleague. Since she couldn’t keep her legs open, I asked my colleague to keep one of her legs open whilst I examined her.” (M12) .

Category 1.3: midwives experienced anxiety and the need to exercise patience when caring for women with mobility disabilities

The participants experienced an emotional and psychological burden when caring for women with mobility disabilities. They felt unqualified and foresaw difficulties that triggered anxiety, which led to them not knowing what to do and how to handle these women.

“It was during labour…the woman was limping the woman she was on crutches. The moment she came into the ward I am a human being I just felt sorry for her kutsi (as to) how is she going to take care of the baby, and the hand was somehow deformed.” (M3) . “At first its emotionally draining as an individual you cause you start sympathising…(other midwife chips in)…yes you even find yourself saying things just because you pity her, and in the process they get hurt.” (M6) . “It came as a shock and it was my first experience, it came as a shock as to how I was going to help her as even my experience was limited in that area.” (M7) . “As I was taking care of her it became necessary for me to put myself into her shoes and to bear with her considering her situation….When you see her for the first time you would pity her yet she is now used to it.” (M1) .

Theme 2: lack of equipment to meet the needs of women with mobility disabilities

Category 2.1: midwives reported a lack of special beds and infrastructure to meet the needs of women with mobility disabilities.

Midwives reported their frustration at the lack of sufficient equipment like special beds and examination tables, tailored for women with mobility disabilities. It was a challenge to provide maternity care for women without this equipment.

“I believe that the infrastructure and equipment should accommodate the women with mobility disability, however, ours is not accommodative to the women…Usually we don’t have the prenatal ward in the maternity, most women who come in the latent phase have to ambulate, or go to the waiting huts and come back when the labour pains are stronger…There are no special delivery beds, specifically designed for them because in my opinion the beds have to be shorter so they can be able to get on to them easily. We do not even have toilets meant for them.” (M1) . “I was anxious as to how was she going to push how to push cause we do not have the right beds when it was time for pushing I asked for assistance…” (M2) . “The challenge is that I couldn’t help her to climb on to the bed, because I needed someone to assist when she came for postnatal care…the beds need to be adjustable so that they are able to be pushed lower for the mother to move from wheel chair to the bed and we pull the bed up again to examine her.” (M11) .

Theme 3: challenges in providing holistic care to women with mobility disabilities during pregnancy, labour, and puerperium

Category 3.1: midwives reported a lack of guidelines and protocols in caring holistically for women with mobility disabilities.

Midwives emphasised a lack of guidelines, protocols and knowledge about caring holistically for women with mobility disabilities. This resulted in everyone making their own decisions and doing as they saw fit in caring for these women:

“I think during antenatal care they (the women with mobility disabilities) need to be prepared for labour cause for others the pain is extraordinary, apart from the pain threshold, they also face self-esteem issues, they are looked down upon…I only saw that she was disabled during assessment cause nothing was recorded on the antenatal care card.” (M2) . “I was not aware of the disability at first, I only discovered when she was pushing…she was admitted and progressed by another midwife, I only attended to her when she was pushing… there was nothing written on the nurse’s notes/ handover notes about her disability.” (M5) . “There is no normal practice for a woman with mobility disability when they come and they are in labour, I usually admit regardless of the stage of labour or dilatation…It is not a protocol, it’s a midwife’s prerogative.” (M1) . “We assess and come up with our own discretion even in terms of admitting them (women with mobility disability). Some midwives will admit them regardless of the stage of labour and disregard the protocol that women who come into labour have to ambulate if they are in the latent phase.” (M8) . “There is one that came the past 3 days she has 3 children now and we just scheduled her for c/section because we know that she has been having c/section since she started. Just from looking at the way she walked, we could tell that she couldn’t deliver normally.” (M9) .

Category 3.2: midwives experienced challenges in allowing significant others to support women with mobility disabilities during labour and delivery

Consequent to the challenges in providing holistic care to women with mobility disabilities, midwives experienced challenges in allowing significant others to support these women during labour and delivery.

“It can depend on the patients themselves, they should decide and we need to be flexible for it to happen…as you can see our labour room also has the issue of privacy…we would need to restructure cause we have beds for 5 or more women in labour room…and then bringing someone from outside could be tricky” (M6) . “Maybe…not sure though, that they can bring their relatives, but maybe, considering staffing limitation…also the issue of discrimination and privacy, they (the women with disabilities) might feel we discriminate against them because they are disabled we now treat them differently.” (M7) . “Maybe if she can (bring her relative) but that’s not necessary, because I can always ask my colleague to assist, unless there is no one…” (M12) .

Childbirth is a special experience that requires a personal connection between the midwife and the woman giving birth, characterised by successful communication and respect [ 34 ]. However, the themes identified in the study indicated that midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and puerperium based on their limited capacity and preparedness, and lack of protocols to care for these women. They also reported a lack of supportive equipment for women with mobility disabilities. This posed a challenge for them in attending to these women’s specific needs, and they did not always know how to handle the situation appropriately.

One of the themes centred on midwives’ experiences of the physical and emotional efforts required of them to provide maternity care to women with mobility disabilities. They explained women with mobility disabilities required assistance getting onto the bed during labour and delivery, and more manoeuvring was expected of them (as midwives) as they had to adjust their performance and some procedures. The midwives also reported challenges in providing holistic care to women with mobility disabilities during pregnancy, labour and puerperium. Konig-Bachmann et al. [ 35 ] reiterate that caring for women with disabilities requires a level of flexibility, adaptation beyond routine procedures, and demands a high degree of improvisation from healthcare providers to ensure high-quality care. Morrison et al. [ 36 ] also found that healthcare providers reported difficulties with equipment when providing healthcare for women with physical disabilities; particularly the beds being too high for them to access. Smeltzer et al. [ 37 ] similarly allude to the importance of educating and training clinicians to equip them with knowledge and technical skills to provide more effective care to women with physical disabilities.

The midwives also shared that labour and deliveries were further complicated by some women with mobility disabilities not being able to cooperate due to the pain they experienced; others could not change position due to their disability. In a study by Sonalkar et al., [ 38 ] healthcare providers described the gynaecologic examination as challenging to complete as it required patience and the ability to be adaptable to different methods and positioning. Similarly, Konig-Bachmann et al. [ 35 ] indicate that in order to provide high-quality care for women with disabilities, healthcare providers need to exercise strong flexibility, adapt beyond routine procedures, and engage in a high degree of improvisation. Byrnes and Hickey [ 39 ] concur with this study’s findings and state that due to mobility restrictions, it may be difficult to assess the fundal height and foetal growth in women with physical disabilities.

Some midwives reported their caregiving role was emotionally draining as they felt sorry and pitied the women with mobility disabilities; thus, they needed to show compassion and reassure them. According to Mgwili et al., [ 40 ] psychoanalytic thinkers associate pity among staff members upon first contact with a physically disabled person as being instigated by personal feelings, stimulated by the disability. The midwives in this study stated they needed to be more patient and adjust their approach to caring for these women. Tarasoff [ 41 ] and Schildberger et al. [ 42 ] reiterated that healthcare providers seemed uncomfortable with women’s disability, consequently failing to offer needed support. According to Sonalkar et al., [ 38 ] healthcare providers reported there would be less fear and concern about hurting women with disabilities if midwives had increased training. Similarly, Mitra et al. [ 43 ] mentioned that healthcare providers had a general lack of confidence in their ability to provide adequate maternity care for women with physical disabilities.

Another theme was midwives’ challenges in providing competent and quality care for women with mobility disabilities due to a lack of equipment, including special beds and examination tables to meet these women’s needs. The examination, labour and delivery beds were too high and could not be adjusted for the women to get on by themselves, or even with the assistance of a midwife. In addition, the midwives reported there was no prenatal ward or waiting huts where they could place these women during the latent phase of labour. The midwives further emphasised there were no special toilets for women with mobility disabilities, which made it hazardous and difficult for them. Mitra et al. [ 43 ] concur on the barriers to providing maternity care to women with physical disabilities presented from health professionals’ perspectives. The authors indicated that participants from their study reported inaccessible equipment, including examination tables, as a barrier, making it more difficult and time-consuming to care for women with physical disabilities. In addition, Sonalkar et al. [ 38 ] said healthcare providers shared their concern about the lack of adjustable examination tables and transfer equipment, thus presenting a barrier to equitable care for women with disabilities.

Midwives further reported a lack of guidelines and protocols. This resulted in everyone making their own decisions and doing as they saw fit in caring for these women, and, in most instances, not recording the disability at all during antenatal care and admission into labour records. They often only discovered that the woman had a mobility disability at a later stage, when they were in labour. Sonalkar et al. [ 38 ] reported that healthcare providers felt frustrated and overwhelmed by the uncertainty of whether they made the correct decisions when caring for women with physical disabilities due to the lack of guidelines forcing them to use their own judgement. Mitra et al. [ 43 ] determined that most healthcare providers reported a lack of maternity practice guidelines for women with physical disabilities. Also, healthcare providers highlighted the importance of learning about disabilities and having a better understanding of a condition, particularly if it is likely to be exacerbated during pregnancy [ 44 ]. The need to make and read the notes on these women’s antenatal care cards or reports was emphasised.

Due to the lack of clear guidelines and protocols in caring for women with mobility disabilities, the midwives reported they sometimes admitted the woman into the labour ward regardless of the stage of labour, while other midwives did not and wanted them to walk around and come back for admission once they are in the active phase of labour. Furthermore, the midwives explained they often referred these women for caesarean sections right away, regardless of whether the woman could deliver normally due to mere panic from just seeing the disability or based on a previous record of surgery. Smeltzer et al. [ 45 ] researched obstetric clinicians’ experiences and educational preparation in caring for pregnant women with physical disabilities, and they agree on the lack of knowledge among health professionals caring for women with mobility disability.

Devkota et al. [ 46 ] also agree regarding midwives’ inefficiency in providing quality care for women with mobility disabilities. They claim healthcare providers often struggle to understand women with disabilities’ needs as they are not formally trained to provide services to this population. These healthcare providers were found to be undertrained in specific skills that would equip them to provide better and more targeted services for women with disabilities.

Consequent to the challenges in providing holistic care to women with mobility disabilities during pregnancy, labour and puerperium, midwives experienced challenges in allowing significant others to support these women. They reported that as much as they needed assistance caring for these women, and as much as the women would prefer to have their family members or significant others assisting them, this is not possible due to the lack of privacy, especially in public health facilities. Walsh-Gallager et al.’s [ 13 ] study on the ambiguity of disabled women’s experiences of pregnancy, childbirth and motherhood resonate with this study’s findings. The authors reported that women with disabilities’ partners were denied access or had their visits curtailed on several occasions due to inflexible hospital visiting policies. Redshaw et al. [ 47 ] reiterated the same in their study; disabled women were less likely to say their companion or partner was welcome to visit, let alone provide any form of assistance. In addition, a study by Bassoumah and Mohammad [ 48 ] reported that women with disabilities were denied their spouses’ support while receiving maternity care. Byrnes and Hickey [ 39 ] also concur that every effort should be made to allow women with disabilities who are in labour to receive support from significant others, and they should be active partners in the labour process.

Limitations

The study was limited to two of the four regions of Eswatini, namely Hhohho and Manzini; hence, the results could not be generalised for the whole country. The study also only focused on mobility disabilities due to time constraints and limited funds. Future research could be conducted to cover all other forms of disabilities.

This study focused on midwives’ lived experiences caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini. In-depth phenomenological interviews were conducted, the findings were analysed, and themes were established. The findings illustrate that midwives experienced challenges caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini. There is a need to develop and implement guidelines to empower midwives with knowledge and skill to provide support and holistic maternity care, and enact protocols. They should also have access to appropriate equipment and infrastructure specifically tailored towards promoting optimal health for women with mobility disabilities.

Data availability

The data analysed is available from the corresponding author upon reasonable request.

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Acknowledgements

The authors would like to acknowledge the midwives in the Hhohho and Manzini regions of Eswatini who participated in the study and provided their own experiences of providing maternity care to women with mobility disabilities during pregnancy, labour and puerperium.

The research received funding from the University of Johannesburg Postgraduate Supervisor-linked Bursary.

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F.N.M conducted the research and wrote the manuscript. A.M.T supervised, reviewed, and finalised the manuscript. A.G.W.N co-supervised the study and edited the manuscript for final submission.

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Ethical clearance to conduct this study was obtained from the University of Johannesburg Faculty of Health Sciences Higher Degrees Committee (ref. no. HDC-01-50-2018), University of Johannesburg Faculty of Health Research Ethics Committee (ref. no. REC-01-82-2018) and the Eswatini National Health Research Review Board (ref. no. NHRRB982/2018). Participation in this study was voluntary, and informed consent was obtained from participants before the interviews commenced.

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Temane, A.M., Magagula, F.N. & Nolte, A.G.W. Midwives’ lived experiences of caring for women with mobility disabilities during pregnancy, labour and puerperium in Eswatini: a qualitative study. BMC Women's Health 24 , 207 (2024). https://doi.org/10.1186/s12905-024-03032-z

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Received : 18 August 2023

Accepted : 18 March 2024

Published : 01 April 2024

DOI : https://doi.org/10.1186/s12905-024-03032-z

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