qualitative research is to quantitative research as

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• Qualitative vs. Quantitative Research | Differences, Examples & Methods

Qualitative vs. Quantitative Research | Differences, Examples & Methods

Published on April 12, 2019 by Raimo Streefkerk . Revised on June 22, 2023.

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

Quantitative research is at risk for research biases including information bias , omitted variable bias , sampling bias , or selection bias . Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs. quantitative research, how to analyze qualitative and quantitative data, other interesting articles, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyze data, and they allow you to answer different kinds of research questions.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observational studies or case studies , your data can be represented as numbers (e.g., using rating scales or counting frequencies) or as words (e.g., with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which different types of variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations : Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups : Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organization for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis )
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: “on a scale from 1-5, how satisfied are your with your professors?”

You can perform statistical analysis on the data and draw conclusions such as: “on average students rated their professors 4.4”.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: “How satisfied are you with your studies?”, “What is the most positive aspect of your study program?” and “What can be done to improve the study program?”

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analyzed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analyzing quantitative data

Quantitative data is based on numbers. Simple math or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores ( means )
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analyzing qualitative data

Qualitative data is more difficult to analyze than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analyzing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

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

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

Research bias

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

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

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

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

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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

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

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

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

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

Streefkerk, R. (2023, June 22). Qualitative vs. Quantitative Research | Differences, Examples & Methods. Scribbr. Retrieved April 12, 2024, from https://www.scribbr.com/methodology/qualitative-quantitative-research/

Is this article helpful?

Raimo Streefkerk

Other students also liked, what is quantitative research | definition, uses & methods, what is qualitative research | methods & examples, mixed methods research | definition, guide & examples, what is your plagiarism score.

Qualitative vs Quantitative Research Methods & Data Analysis

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, 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. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded.

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

• Bipolar Disorder
• Therapy Center
• When To See a Therapist
• Types of Therapy
• Best Online Therapy
• Best Couples Therapy
• Best Family Therapy
• Managing Stress
• Sleep and Dreaming
• Understanding Emotions
• Self-Improvement
• Healthy Relationships
• Student Resources
• Personality Types
• Guided Meditations
• Verywell Mind Insights
• 2023 Verywell Mind 25
• Mental Health in the Classroom
• Editorial Process
• Meet Our Review Board
• Crisis Support

Quantitative vs. Qualitative Research in Psychology

Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

• Key Differences

Quantitative Research Methods

Qualitative research methods.

• How They Relate

In psychology and other social sciences, researchers are faced with an unresolved question: Can we measure concepts like love or racism the same way we can measure temperature or the weight of a star? Social phenomena⁠—things that happen because of and through human behavior⁠—are especially difficult to grasp with typical scientific models.

At a Glance

Psychologists rely on quantitative and quantitative research to better understand human thought and behavior.

• Qualitative research involves collecting and evaluating non-numerical data in order to understand concepts or subjective opinions.
• Quantitative research involves collecting and evaluating numerical data. 

This article discusses what qualitative and quantitative research are, how they are different, and how they are used in psychology research.

Qualitative Research vs. Quantitative Research

In order to understand qualitative and quantitative psychology research, it can be helpful to look at the methods that are used and when each type is most appropriate.

Psychologists rely on a few methods to measure behavior, attitudes, and feelings. These include:

• Self-reports , like surveys or questionnaires
• Observation (often used in experiments or fieldwork)
• Implicit attitude tests that measure timing in responding to prompts

Most of these are quantitative methods. The result is a number that can be used to assess differences between groups.

However, most of these methods are static, inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" answer rather than a "why" answer.

Sometimes, researchers are more interested in the "why" and the "how." That's where qualitative methods come in.

Qualitative research is about speaking to people directly and hearing their words. It is grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective," and that how humans make meaning is just as important as how much they score on a standardized test.

Used to develop theories

Takes a broad, complex approach

Answers "why" and "how" questions

Explores patterns and themes

Used to test theories

Takes a narrow, specific approach

Answers "what" questions

Explores statistical relationships

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte (which maintains that factual knowledge obtained by observation is trustworthy) that it became a "scientific method."

The scientific method follows this general process. A researcher must:

• Generate a theory or hypothesis (i.e., predict what might happen in an experiment) and determine the variables needed to answer their question
• Develop instruments to measure the phenomenon (such as a survey, a thermometer, etc.)
• Develop experiments to manipulate the variables
• Collect empirical (measured) data
• Analyze data

Quantitative methods are about measuring phenomena, not explaining them.

Quantitative research compares two groups of people. There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the researcher a sense of how the various data points relate to one another.

Basic Assumptions

Quantitative methods assume:

• That the world is measurable
• That humans can observe objectively
• That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research have shown, people behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender , social class, or sexual orientation .

Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies across large groups of people, but they can never describe every case or every experience. In other words, there are always outliers.

Correlation and Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

• The study was a true experiment.
• The independent variable can be manipulated (for example, researchers cannot manipulate gender, but they can change the primer a study subject sees, such as a picture of nature or of a building).
• The dependent variable can be measured through a ratio or a scale.

So when you read a report that "gender was linked to" something (like a behavior or an attitude), remember that gender is NOT a cause of the behavior or attitude. There is an apparent relationship, but the true cause of the difference is hidden.

Pitfalls of Quantitative Research

Quantitative methods are one way to approach the measurement and understanding of human and social phenomena. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give a general idea, respondents have to choose between only a few responses. This can make it difficult to understand the subtleties of different experiences.

Quantitative methods can be helpful when making objective comparisons between groups or when looking for relationships between variables. They can be analyzed statistically, which can be helpful when looking for patterns and relationships.

Qualitative data are not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts, and characteristics. This approach uses interviews, written texts, art, photos, and other materials to make sense of human experiences and to understand what these experiences mean to people.

While quantitative methods ask "what" and "how much," qualitative methods ask "why" and "how."

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree that some questions are too complex or impossible to answer with standardized instruments.

These methods also accept that it is impossible to be completely objective in observing phenomena. Researchers have their own thoughts, attitudes, experiences, and beliefs, and these always color how people interpret results.

Qualitative Approaches

There are many different approaches to qualitative research, with their own philosophical bases. Different approaches are best for different kinds of projects. For example:

• Case studies and narrative studies are best for single individuals. These involve studying every aspect of a person's life in great depth.
• Phenomenology aims to explain experiences. This type of work aims to describe and explore different events as they are consciously and subjectively experienced.
• Grounded theory develops models and describes processes. This approach allows researchers to construct a theory based on data that is collected, analyzed, and compared to reach new discoveries.
• Ethnography describes cultural groups. In this approach, researchers immerse themselves in a community or group in order to observe behavior.

Qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research.

Some researchers specialize in a single method, but others specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

There is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants).

The insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

Relationship Between Qualitative and Quantitative Research

It might sound like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs. However, this could not be further from the truth.

These two general methods complement each other. By using both, researchers can gain a fuller, more comprehensive understanding of a phenomenon.

For example, a psychologist wanting to develop a new survey instrument about sexuality might and ask a few dozen people questions about their sexual experiences (this is qualitative research). This gives the researcher some information to begin developing questions for their survey (which is a quantitative method).

After the survey, the same or other researchers might want to dig deeper into issues brought up by its data. Follow-up questions like "how does it feel when...?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Qualitative and quantitative methods both play an important role in psychology. Where quantitative methods can help answer questions about what is happening in a group and to what degree, qualitative methods can dig deeper into the reasons behind why it is happening. By using both strategies, psychology researchers can learn more about human thought and behavior.

Gough B, Madill A. Subjectivity in psychological science: From problem to prospect . Psychol Methods . 2012;17(3):374-384. doi:10.1037/a0029313

Pearce T. “Science organized”: Positivism and the metaphysical club, 1865–1875 . J Hist Ideas . 2015;76(3):441-465.

Adams G. Context in person, person in context: A cultural psychology approach to social-personality psychology . In: Deaux K, Snyder M, eds. The Oxford Handbook of Personality and Social Psychology . Oxford University Press; 2012:182-208.

Brady HE. Causation and explanation in social science . In: Goodin RE, ed. The Oxford Handbook of Political Science. Oxford University Press; 2011. doi:10.1093/oxfordhb/9780199604456.013.0049

Chun Tie Y, Birks M, Francis K. Grounded theory research: A design framework for novice researchers .  SAGE Open Med . 2019;7:2050312118822927. doi:10.1177/2050312118822927

Reeves S, Peller J, Goldman J, Kitto S. Ethnography in qualitative educational research: AMEE Guide No. 80 . Medical Teacher . 2013;35(8):e1365-e1379. doi:10.3109/0142159X.2013.804977

Salkind NJ, ed. Encyclopedia of Research Design . Sage Publishing.

Shaughnessy JJ, Zechmeister EB, Zechmeister JS.  Research Methods in Psychology . McGraw Hill Education.

By Anabelle Bernard Fournier Anabelle Bernard Fournier is a researcher of sexual and reproductive health at the University of Victoria as well as a freelance writer on various health topics.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Qualitative vs Quantitative Research | Examples & Methods

Qualitative vs Quantitative Research | Examples & Methods

Published on 4 April 2022 by Raimo Streefkerk . Revised on 8 May 2023.

When collecting and analysing data, quantitative research deals with numbers and statistics, while qualitative research  deals with words and meanings. Both are important for gaining different kinds of knowledge.

Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions. Qualitative research Qualitative research is expressed in words . It is used to understand concepts, thoughts or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood.

Table of contents

The differences between quantitative and qualitative research, data collection methods, when to use qualitative vs quantitative research, how to analyse qualitative and quantitative data, frequently asked questions about qualitative and quantitative research.

Quantitative and qualitative research use different research methods to collect and analyse data, and they allow you to answer different kinds of research questions.

Prevent plagiarism, run a free check.

Quantitative and qualitative data can be collected using various methods. It is important to use a data collection method that will help answer your research question(s).

Many data collection methods can be either qualitative or quantitative. For example, in surveys, observations or case studies , your data can be represented as numbers (e.g. using rating scales or counting frequencies) or as words (e.g. with open-ended questions or descriptions of what you observe).

However, some methods are more commonly used in one type or the other.

Quantitative data collection methods

• Surveys :  List of closed or multiple choice questions that is distributed to a sample (online, in person, or over the phone).
• Experiments : Situation in which variables are controlled and manipulated to establish cause-and-effect relationships.
• Observations: Observing subjects in a natural environment where variables can’t be controlled.

Qualitative data collection methods

• Interviews : Asking open-ended questions verbally to respondents.
• Focus groups: Discussion among a group of people about a topic to gather opinions that can be used for further research.
• Ethnography : Participating in a community or organisation for an extended period of time to closely observe culture and behavior.
• Literature review : Survey of published works by other authors.

A rule of thumb for deciding whether to use qualitative or quantitative data is:

• Use quantitative research if you want to confirm or test something (a theory or hypothesis)
• Use qualitative research if you want to understand something (concepts, thoughts, experiences)

For most research topics you can choose a qualitative, quantitative or mixed methods approach . Which type you choose depends on, among other things, whether you’re taking an inductive vs deductive research approach ; your research question(s) ; whether you’re doing experimental , correlational , or descriptive research ; and practical considerations such as time, money, availability of data, and access to respondents.

Quantitative research approach

You survey 300 students at your university and ask them questions such as: ‘on a scale from 1-5, how satisfied are your with your professors?’

You can perform statistical analysis on the data and draw conclusions such as: ‘on average students rated their professors 4.4’.

Qualitative research approach

You conduct in-depth interviews with 15 students and ask them open-ended questions such as: ‘How satisfied are you with your studies?’, ‘What is the most positive aspect of your study program?’ and ‘What can be done to improve the study program?’

Based on the answers you get you can ask follow-up questions to clarify things. You transcribe all interviews using transcription software and try to find commonalities and patterns.

Mixed methods approach

You conduct interviews to find out how satisfied students are with their studies. Through open-ended questions you learn things you never thought about before and gain new insights. Later, you use a survey to test these insights on a larger scale.

It’s also possible to start with a survey to find out the overall trends, followed by interviews to better understand the reasons behind the trends.

Qualitative or quantitative data by itself can’t prove or demonstrate anything, but has to be analysed to show its meaning in relation to the research questions. The method of analysis differs for each type of data.

Analysing quantitative data

Quantitative data is based on numbers. Simple maths or more advanced statistical analysis is used to discover commonalities or patterns in the data. The results are often reported in graphs and tables.

Applications such as Excel, SPSS, or R can be used to calculate things like:

• Average scores
• The number of times a particular answer was given
• The correlation or causation between two or more variables
• The reliability and validity of the results

Analysing qualitative data

Qualitative data is more difficult to analyse than quantitative data. It consists of text, images or videos instead of numbers.

Some common approaches to analysing qualitative data include:

• Qualitative content analysis : Tracking the occurrence, position and meaning of words or phrases
• Thematic analysis : Closely examining the data to identify the main themes and patterns
• Discourse analysis : Studying how communication works in social contexts

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.

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

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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 .

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

Streefkerk, R. (2023, May 08). Qualitative vs Quantitative Research | Examples & Methods. Scribbr. Retrieved 9 April 2024, from https://www.scribbr.co.uk/research-methods/quantitative-qualitative-research/

Is this article helpful?

Raimo Streefkerk

Qualitative Research : Definition

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

Events and Workshops

• Introduction to NVivo Have you just collected your data and wondered what to do next? Come join us for an introductory session on utilizing NVivo to support your analytical process. This session will only cover features of the software and how to import your records. Please feel free to attend any of the following sessions below: April 25th, 2024 12:30 pm - 1:45 pm Green Library - SVA Conference Room 125 May 9th, 2024 12:30 pm - 1:45 pm Green Library - SVA Conference Room 125 May 30th, 2024 12:30 pm - 1:45 pm Green Library - SVA Conference Room 125
• Next: Choose an approach >>
• Choose an approach
• Find studies
• Learn methods
• Get software
• Get data for secondary analysis
• Network with researchers

• Last Updated: Apr 2, 2024 10:41 AM
• URL: https://guides.library.stanford.edu/qualitative_research

• How it works

Qualitative Vs Quantitative Research – A Comprehensive Guide

Published by Carmen Troy at August 13th, 2021 , Revised On September 20, 2023

What is Quantitative Research?

Quantitative research is associated with numerical data or data that can be measured. It is used to study a large group of population. The information is gathered by performing statistical, mathematical, or computational techniques.

Quantitative research isn’t simply based on  statistical analysis or quantitative techniques but rather uses a certain approach to theory to address research hypotheses or questions, establish an appropriate research methodology, and draw findings & conclusions .

Characteristics of Quantitative Research

Some most commonly employed quantitative research strategies include data-driven dissertations, theory-driven studies, and reflection-driven research. Regardless of the chosen approach, there are some common quantitative research features as listed below.

• Quantitative research tests or builds on other researchers’ existing theories whilst taking a reflective or extensive route.
• Quantitative research aims to test the research hypothesis or answer established research questions.
• It is primarily justified by positivist or post-positivist research paradigms.
• The  research design can be relationship-based, quasi-experimental, experimental, or descriptive.
• It draws on a small sample to make generalisations to a wider population using probability sampling techniques.
• Quantitative data is gathered according to the established research questions using research vehicles such as structured observation, structured interviews, surveys, questionnaires, and laboratory results.
• The researcher uses  statistical analysis tools and techniques to measure variables and gather inferential or descriptive data. In some cases, your tutor or dissertation committee members might find it easier to verify your study results with numbers and statistical analysis.
• The study results’ accuracy is based on external and internal validity and authenticity of the data used.
• Quantitative research answers research questions or tests the hypothesis using charts, graphs, tables, data, and statements.
• It underpins  research questions or hypotheses and findings to make conclusions.
• The researcher can provide recommendations for future research and expand or test existing theories.

What is Qualitative Research?

Qualitative research is a type of scientific research where a researcher collects evidence to seek answers to a  question . It is associated with studying human behavior from an informative perspective. It aims at obtaining in-depth details of the problem.

As the term suggests,  qualitative research  is based on qualitative research methods, including participants’ observations, focus groups, and unstructured interviews.

Qualitative research is very different in nature when compared to quantitative research. It takes an established path towards the  research process , how  research questions  are set up, how existing theories are built upon, what research methods are employed, and how the  findings  are unveiled to the readers.

You may adopt conventional methods, including phenomenological research, narrative-based research, grounded theory research, ethnographies, case studies, and auto-ethnographies.

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Characteristics of Qualitative Research

Again, regardless of the chosen approach to qualitative research, your dissertation will have unique key features as listed below.

• The research questions that you aim to answer will expand or even change as the  dissertation writing process continues . This aspect of the research is typically known as an emergent design where the research objectives evolve with time.
• Qualitative research may use existing theories to cultivate new theoretical understandings or fall back on existing theories to support the research process. However, the original goal of testing a certain theoretical understanding remains the same.
• It can be based on various research models, such as critical theory, constructivism, and interpretivism.
• The chosen research design largely influences the analysis and discussion of results and the choices you make . Research design depends on the adopted research path: phenomenological research, narrative-based research, grounded theory-based research, ethnography, case study-based research, or auto-ethnography.
• Qualitative research answers research questions with theoretical sampling, where data gathered from the organisation or people are studied.
• It involves various research methods to gather qualitative data from participants belonging to the field of study. As indicated previously, some of the most notable qualitative research methods include participant observation, focus groups, and unstructured interviews.
• It incorporates an  inductive process where the researcher analyses and understands the data through his own eyes and judgments to identify concepts and themes that comprehensively depict the researched material.
• The key quality characteristics of qualitative research are transferability, conformity, confirmability, and reliability.
• Results and discussions are largely based on narratives, case study and personal experiences, which help detect inconsistencies, observations, processes, and ideas.
• Qualitative research discusses theoretical concepts obtained from the results whilst taking research questions and/or hypotheses to  draw general  conclusions .

Confused between qualitative and quantitative methods of data analysis? No idea what discourse and content analysis are?

We hear you.

• Whether you want a full dissertation written or need help forming a dissertation proposal, we can help you with both.
• Get different dissertation services at ResearchProspect and score amazing grades!

When to Use Qualitative and Quantitative Research Model?

• The research  title, research questions,  hypothesis , objectives, and study area generally determine the dissertation’s best research method.
• If the primary aim of your research is to test a hypothesis, validate an existing theory or perhaps measure some variables, then the quantitative research model will be the more appropriate choice because it might be easier for you to convince your supervisor or members of the dissertation committee with the use of statistics and numbers.
• On the other hand, oftentimes, statistics and a collection of numbers are not the answer, especially where there is a need to understand meanings, experiences, and beliefs.
• If your research questions or hypothesis can be better addressed through people’s observations and experiences, you should consider qualitative data.
• If you select an inappropriate research method, you will not prove your findings’ accuracy, and your dissertation will be pretty much meaningless. To prove that your research is authentic and reliable, choose a research method that best suits your study’s requirements.
• In the sections that follow, we explain the most commonly employed research methods for the dissertation, including quantitative, qualitative, and mixed research methods.

Now that you know the unique differences between quantitative and qualitative research methods, you may want to learn a bit about primary and secondary research methods.

Here is an article that will help you  distinguish between primary and secondary research  and decide whether you need to use quantitative and/or qualitative methods of primary research in your dissertation.

Alternatively, you can base your dissertation on secondary research, which is descriptive and explanatory.

Limitations of Quantitative and Qualitative Research

What is quantitative research, what is qualitative research.

Qualitative research is a type of scientific research where a researcher collects evidence to seek answers to a question . It is associated with studying human behavior from an informative perspective. It aims at obtaining in-depth details of the problem.

Qualitative or quantitative, which research type should I use?

The research title, research questions, hypothesis , objectives, and study area generally determine the dissertation’s best research method.

You May Also Like

A hypothesis is a research question that has to be proved correct or incorrect through hypothesis testing – a scientific approach to test a hypothesis.

In historical research, a researcher collects and analyse the data, and explain the events that occurred in the past to test the truthfulness of observations.

Descriptive research is carried out to describe current issues, programs, and provides information about the issue through surveys and various fact-finding methods.

USEFUL LINKS

LEARNING RESOURCES

COMPANY DETAILS

• How It Works

Root out friction in every digital experience, super-charge conversion rates, and optimize digital self-service

Uncover insights from any interaction, deliver AI-powered agent coaching, and reduce cost to serve

Increase revenue and loyalty with real-time insights and recommendations delivered to teams on the ground

Know how your people feel and empower managers to improve employee engagement, productivity, and retention

Take action in the moments that matter most along the employee journey and drive bottom line growth

Whatever they’re are saying, wherever they’re saying it, know exactly what’s going on with your people

Get faster, richer insights with qual and quant tools that make powerful market research available to everyone

Run concept tests, pricing studies, prototyping + more with fast, powerful studies designed by UX research experts

Track your brand performance 24/7 and act quickly to respond to opportunities and challenges in your market

Explore the platform powering Experience Management

• Free Account
• For Digital
• For Customer Care
• For Human Resources
• For Researchers
• Financial Services
• All Industries

Popular Use Cases

• Customer Experience
• Employee Experience
• Employee Exit Interviews
• Net Promoter Score
• Voice of Customer
• Customer Success Hub
• Product Documentation
• Training & Certification
• XM Institute
• Popular Resources
• Customer Stories

Market Research

• Artificial Intelligence
• Partnerships
• Marketplace

The annual gathering of the experience leaders at the world’s iconic brands building breakthrough business results, live in Salt Lake City.

• English/AU & NZ
• Español/Europa
• Español/América Latina
• Português Brasileiro
• REQUEST DEMO
• Experience Management
• Qualitative Vs Quantitative Research

Try Qualtrics for free

Qualitative vs quantitative research.

13 min read You’ll use both quantitative and qualitative research methods to gather data in your research projects. So what do qualitative and quantitative mean exactly, and how can you best use them to gain the most accurate insights?

What is qualitative research?

Qualitative research is all about language, expression, body language and other forms of human communication. That covers words, meanings and understanding. Qualitative research is used to describe WHY. Why do people feel the way they do, why do they act in a certain way, what opinions do they have and what motivates them?

Qualitative data is used to understand phenomena – things that happen, situations that exist, and most importantly the meanings associated with them. It can help add a ‘why’ element to factual, objective data.

Qualitative research gives breadth, depth and context to questions, although its linguistic subtleties and subjectivity can mean that results are trickier to analyze than quantitative data.

This qualitative data is called unstructured data by researchers. This is because it has not traditionally had the type of structure that can be processed by computers, until today. It has, until recently at least, been exclusively accessible to human brains. And although our brains are highly sophisticated, they have limited processing power. What can help analyze this structured data to assist computers and the human brain?

Free eBook: Quantitative and qualitative research design

What is quantitative research?

Quantitative data refers to numerical information. Quantitative research gathers information that can be counted, measured, or rated numerically – AKA quantitative data. Scores, measurements, financial records, temperature charts and receipts or ledgers are all examples of quantitative data.

Quantitative data is often structured data, because it follows a consistent, predictable pattern that computers and calculating devices are able to process with ease. Humans can process it too, although we are now able to pass it over to machines to process on our behalf. This is partly what has made quantitative data so important historically, and why quantitative data – sometimes called ‘hard data’ – has dominated over qualitative data in fields like business, finance and economics.

It’s easy to ‘crunch the numbers’ of quantitative data and produce results visually in graphs, tables and on data analysis dashboards. Thanks to today’s abundance and accessibility of processing power, combined with our ability to store huge amounts of information, quantitative data has fuelled the Big Data phenomenon, putting quantitative methods and vast amounts of quantitative data at our fingertips.

As we’ve indicated, quantitative and qualitative data are entirely different and mutually exclusive categories. Here are a few of the differences between them.

1. Data collection

Data collection methods for quantitative data and qualitative data vary, but there are also some places where they overlap.

2. Data analysis

Quantitative data suits statistical analysis techniques like linear regression, T-tests and ANOVA. These are quite easy to automate, and large quantities of quantitative data can be analyzed quickly.

Analyzing qualitative data needs a higher degree of human judgement, since unlike quantitative data, non numerical data of a subjective nature has certain characteristics that inferential statistics can’t perceive. Working at a human scale has historically meant that qualitative data is lower in volume – although it can be richer in insights.

3. Strengths and weaknesses

When weighing up qualitative vs quantitative research, it’s largely a matter of choosing the method appropriate to your research goals. If you’re in the position of having to choose one method over another, it’s worth knowing the strengths and limitations of each, so that you know what to expect from your results.

Qualitative vs quantitative – the role of research questions

How do you know whether you need qualitative or quantitative research techniques? By finding out what kind of data you’re going to be collecting.

You’ll do this as you develop your research question, one of the first steps to any research program. It’s a single sentence that sums up the purpose of your research, who you’re going to gather data from, and what results you’re looking for.

As you formulate your question, you’ll get a sense of the sort of answer you’re working towards, and whether it will be expressed in numerical data or qualitative data.

For example, your research question might be “How often does a poor customer experience cause shoppers to abandon their shopping carts?” – this is a quantitative topic, as you’re looking for numerical values.

Or it might be “What is the emotional impact of a poor customer experience on regular customers in our supermarket?” This is a qualitative topic, concerned with thoughts and feelings and answered in personal, subjective ways that vary between respondents.

Here’s how to evaluate your research question and decide which method to use:

• Qualitative research:

Use this if your goal is to understand something – experiences, problems, ideas.

For example, you may want to understand how poor experiences in a supermarket make your customers feel. You might carry out this research through focus groups or in depth interviews (IDI’s). For a larger scale research method you could start  by surveying supermarket loyalty card holders, asking open text questions, like “How would you describe your experience today?” or “What could be improved about your experience?” This research will provide context and understanding that quantitative research will not.

• Quantitative research:

Use this if your goal is to test or confirm a hypothesis, or to study cause and effect relationships. For example, you want to find out what percentage of your returning customers are happy with the customer experience at your store. You can collect data to answer this via a survey.

For example, you could recruit 1,000 loyalty card holders as participants, asking them, “On a scale of 1-5, how happy are you with our store?” You can then make simple mathematical calculations to find the average score. The larger sample size will help make sure your results aren’t skewed by anomalous data or outliers, so you can draw conclusions with confidence.

Qualitative and quantitative research combined?

Do you always have to choose between qualitative or quantitative data?

In some cases you can get the best of both worlds by combining both quantitative and qualitative data.You could use pre quantitative data to understand the landscape of your research. Here you can gain insights around a topic and propose a hypothesis. Then adopt a quantitative research method to test it out. Here you’ll discover where to focus your survey appropriately or to pre-test your survey, to ensure your questions are understood as you intended. Finally, using a round of qualitative research methods to bring your insights and story to life. This mixed methods approach is becoming increasingly popular with businesses who are looking for in depth insights.

For example, in the supermarket scenario we’ve described, you could start out with a qualitative data collection phase where you use focus groups and conduct interviews with customers. You might find suggestions in your qualitative data that customers would like to be able to buy children’s clothes in the store.

In response, the supermarket might pilot a children’s clothing range. Targeted quantitative research could then reveal whether or not those stores selling children’s clothes achieve higher customer satisfaction scores and a rise in profits for clothing.

Together, qualitative and quantitative data, combined with statistical analysis, have provided important insights about customer experience, and have proven the effectiveness of a solution to business problems.

Qualitative vs quantitative question types

As we’ve noted, surveys are one of the data collection methods suitable for both quantitative and qualitative research. Depending on the types of questions you choose to include, you can generate qualitative and quantitative data. Here we have summarized some of the survey question types you can use for each purpose.

Qualitative data survey questions

There are fewer survey question options for collecting qualitative data, since they all essentially do the same thing – provide the respondent with space to enter information in their own words. Qualitative research is not typically done with surveys alone, and researchers may use a mix of qualitative methods. As well as a survey, they might conduct in depth interviews, use observational studies or hold focus groups.

Open text ‘Other’ box (can be used with multiple choice questions)

Text box (space for short written answer)

Essay box (space for longer, more detailed written answers)

Quantitative data survey questions

These questions will yield quantitative data – i.e. a numerical value.

Net Promoter Score (NPS)

Likert Scale

Radio buttons (respondents choose just one option)

Check boxes (respondents can choose multiple options)

Sliding scale

Star rating

Analyzing data (quantitative or qualitative) using technology

We are currently at an exciting point in the history of qualitative analysis. Digital analysis and other methods that were formerly exclusively used for quantitative data are now used for interpreting non numerical data too.

A rtificial intelligence programs can now be used to analyze open text, and turn qualitative data into structured and semi structured quantitative data that relates to qualitative data topics such as emotion and sentiment, opinion and experience.

Research that in the past would have meant qualitative researchers conducting time-intensive studies using analysis methods like thematic analysis can now be done in a very short space of time. This not only saves time and money, but opens up qualitative data analysis to a much wider range of businesses and organizations.

The most advanced tools can even be used for real-time statistical analysis, forecasting and prediction, making them a powerful asset for businesses.

Qualitative or quantitative – which is better for data analysis?

Historically, quantitative data was much easier to analyze than qualitative data. But as we’ve seen, modern technology is helping qualitative analysis to catch up, making it quicker and less labor-intensive than before.

That means the choice between qualitative and quantitative studies no longer needs to factor in ease of analysis, provided you have the right tools at your disposal. With an integrated platform like Qualtrics, which incorporates data collection, data cleaning, data coding and a powerful suite of analysis tools for both qualitative and quantitative data, you have a wide range of options at your fingertips.

Related resources

Qualitative research questions 11 min read, qualitative research design 12 min read, primary vs secondary research 14 min read, business research methods 12 min read, qualitative research interviews 11 min read, market intelligence 10 min read, marketing insights 11 min read, request demo.

Ready to learn more about Qualtrics?

Quantitative and Qualitative Research

• I NEED TO . . .

What is Quantitative Research?

• What is Qualitative Research?
• Quantitative vs Qualitative
• Step 1: Accessing CINAHL
• Step 2: Create a Keyword Search
• Step 3: Create a Subject Heading Search
• Step 4: Repeat Steps 1-3 for Second Concept
• Step 5: Repeat Steps 1-3 for Quantitative Terms
• Step 6: Combining All Searches
• Step 7: Adding Limiters
• Step 8: Save Your Search!
• What Kind of Article is This?
• More Research Help This link opens in a new window

Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is  imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014).  The SAGE encyclopedia of action research  (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017).  The SAGE encyclopedia of communication research methods  (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design?  What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used.  You will need to know how to decipher which design type is used.  The following video will help you determine the quantitative design type.

• << Previous: I NEED TO . . .
• Next: What is Qualitative Research? >>
• Last Updated: Dec 8, 2023 10:05 PM
• URL: https://libguides.uta.edu/quantitative_and_qualitative_research

University of Texas Arlington Libraries 702 Planetarium Place · Arlington, TX 76019 · 817-272-3000

• Internet Privacy
• Accessibility
• Problems with a guide? Contact Us.

Qualitative Vs. Quantitative Research — A step-wise guide to conduct research

A research study includes the collection and analysis of data. In quantitative research, the data are analyzed with numbers and statistics, and in qualitative research, the data analyzed are non-numerical and perceive the meaning of social reality.

What Is Qualitative Research?

Qualitative research observes and describes a phenomenon to gain a deeper understanding of a subject. It is also used to generate hypotheses for further studies. In general, qualitative research is explanatory and helps understands how an individual perceives non-numerical data, like video, photographs, or audio recordings. The qualitative data is collected from diary accounts or interviews and analyzed by grounded theory or thematic analysis.

When to Use Qualitative Research?

Qualitative research is used when the outcome of the research study is to disseminate knowledge and understand concepts, thoughts, and experiences. This type of research focuses on creating ideas and formulating theories or hypotheses .

Benefits of Qualitative Research

• Unlike quantitative research, which relies on numerical data, qualitative research relies on data collected from interviews, observations, and written texts.
• It is often used in fields such as sociology and anthropology, where the goal is to understand complex social phenomena.
• Qualitative research is considered to be more flexible and adaptive, as it is used to study a wide range of social aspects.
• Additionally, qualitative research often leads to deeper insights into the research study. This helps researchers and scholars in designing their research methods .

Qualitative Research Example

In research, to understand the culture of a pharma company, one could take an ethnographic approach. With an experience in the company, one could gather data based on the —

• Field notes with observations, and reflections on one’s experiences of the company’s culture
• Open-ended surveys for employees across all the company’s departments via email to find out variations in culture across teams and departments
• Interview sessions with employees and gather information about their experiences and perspectives.

What Is Quantitative Research?

Quantitative research is for testing hypotheses and measuring relationships between variables. It follows the process of objectively collecting data and analyzing it numerically, to determine and control variables of interest. This type of research aims to test causal relationships between variables and provide generalized results. These results determine if the theory proposed for the research study could be accepted or rejected.

When to Use Quantitative Research?

Quantitative research is used when a research study needs to confirm or test a theory or a hypothesis. When a research study is focused on measuring and quantifying data, using a quantitative approach is appropriate. It is often used in fields such as economics, marketing, or biology, where researchers are interested in studying trends and relationships between variables .

Benefits of Quantitative Research

• Quantitative data is interpreted with statistical analysis . The type of statistical study is based on the principles of mathematics and it provides a fast, focused, scientific and relatable approach.
• Quantitative research creates an ability to replicate the test and results of research. This approach makes the data more reliable and less open to argument.
• After collecting the quantitative data, expected results define which statistical tests are applicable and results provide a quantifiable conclusion for the research hypothesis
• Research with complex statistical analysis is considered valuable and impressive. Quantitative research is associated with technical advancements like computer modeling and data-based decisions.

Quantitative Research Example

An organization wishes to conduct a customer satisfaction (CSAT) survey by using a survey template. From the survey, the organization can acquire quantitative data and metrics on the brand or the organization based on the customer’s experience. Various parameters such as product quality, pricing, customer experience, etc. could be used to generate data in the form of numbers that is statistically analyzed.

Data Collection Methods

1. qualitative data collection methods.

Qualitative data is collected from interview sessions, discussions with focus groups, case studies, and ethnography (scientific description of people and cultures with their customs and habits). The collection methods involve understanding and interpreting social interactions.

Qualitative research data also includes respondents’ opinions and feelings, which is conducted face-to-face mostly in focus groups. Respondents are asked open-ended questions either verbally or through discussion among a group of people, related to the research topic implemented to collect opinions for further research.

2. Quantitative Data Collection Methods

Quantitative research data is acquired from surveys, experiments, observations, probability sampling, questionnaire observation, and content review. Surveys usually contain a list of questions with multiple-choice responses relevant to the research topic under study. With the availability of online survey tools, researchers can conduct a web-based survey for quantitative research.

Quantitative data is also assimilated from research experiments. While conducting experiments, researchers focus on exploring one or more independent variables and studying their effect on one or more dependent variables.

A Step-wise Guide to Conduct Qualitative and Quantitative Research

• Understand the difference between types of research — qualitative, quantitative, or mixed-methods-based research.
• Develop a research question or hypothesis. This research approach will define which type of research one could choose.
• Choose a method for data collection. Depending on the process of data collection, the type of research could be determined.
• Analyze and interpret the collected data. Based on the analyzed data, results are reported.
• If observed results are not equivalent to expected results, consider using an unbiased research approach or choose both qualitative and quantitative research methods for preferred results.

Qualitative Vs. Quantitative Research – A Comparison

With an awareness of qualitative vs. quantitative research and the different data collection methods , researchers could use one or both types of research approaches depending on their preferred results. Moreover, to implement unbiased research and acquire meaningful insights from the research study, it is advisable to consider both qualitative and quantitative research methods .

Through this article, you would have understood the comparison between qualitative and quantitative research. However, if you have any queries related to qualitative vs. quantitative research, do comment below or email us.

Well explained and easy to understand.

Rate this article Cancel Reply

Your email address will not be published.

Enago Academy's Most Popular Articles

• Reporting Research

Choosing the Right Analytical Approach: Thematic analysis vs. content analysis for data interpretation

In research, choosing the right approach to understand data is crucial for deriving meaningful insights.…

Demystifying the Role of Confounding Variables in Research

In the realm of scientific research, the pursuit of knowledge often involves complex investigations, meticulous…

Research Interviews: An effective and insightful way of data collection

Research interviews play a pivotal role in collecting data for various academic, scientific, and professional…

Planning Your Data Collection: Designing methods for effective research

Planning your research is very important to obtain desirable results. In research, the relevance of…

• Manuscripts & Grants
• Trending Now

Unraveling Research Population and Sample: Understanding their role in statistical inference

Research population and sample serve as the cornerstones of any scientific inquiry. They hold the…

6 Steps to Evaluate the Effectiveness of Statistical Hypothesis Testing

How to Use Creative Data Visualization Techniques for Easy Comprehension of…

Sign-up to read more

Subscribe for free to get unrestricted access to all our resources on research writing and academic publishing including:

• 2000+ blog articles
• 50+ Webinars
• 10+ Expert podcasts
• 50+ Infographics
• 10+ Checklists
• Research Guides

We hate spam too. We promise to protect your privacy and never spam you.

I am looking for Editing/ Proofreading services for my manuscript Tentative date of next journal submission:

What should universities' stance be on AI tools in research and academic writing?

• Reviews / Why join our community?
• For companies
• Frequently asked questions

Qualitative Research

What is qualitative research.

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

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

• Transcript loading…

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

Qualitative Research Focuses on the “Why”

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

Qualitative research

Quantitative Research

You Aim to Determine

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

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

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

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

Number of Representative Users

Often around 5

Ideally 30+

Level of Contact with Users

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

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

Statistically

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

Reliable – given enough test users

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

Qualitative Research Methods You Can Use to Get Behind Your Users

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

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

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

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

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

Usability testing

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

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

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

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

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

Qualitative Research – How to Get Reliable Results

Some helpful points to remember are:

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

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

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

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

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

Learn More about Qualitative Research

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

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

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

Explore additional insights into qualitative research here .

Literature on Qualitative Research

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

Learn more about Qualitative Research

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

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

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

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

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

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

All open-source articles on Qualitative Research

How to do a thematic analysis of user interviews.

• 1.2k shares
• 3 years ago

How to Visualize Your Qualitative User Research Results for Maximum Impact

• 2 years ago

Creating Personas from User Research Results

Best Practices for Qualitative User Research

Card Sorting

Contextual Interviews and How to Handle Them

Understand the User’s Perspective through Research for Mobile UX

• 10 mths ago

Ethnography

7 simple ways to get better results from ethnographic research.

Semi-structured qualitative studies

Pros and cons of conducting user interviews.

Workshops to Establish Empathy and Understanding from User Research Results

How to Moderate User Interviews

• 4 years ago

Question Everything

Adding Quality to Your Design Research with an SSQS Checklist

• 8 years ago

Open Access—Link to us!

We believe in Open Access and the  democratization of knowledge . Unfortunately, world-class educational materials such as this page are normally hidden behind paywalls or in expensive textbooks.

If you want this to change , cite this page , link to us, or join us to help us democratize design knowledge !

Privacy Settings

Our digital services use necessary tracking technologies, including third-party cookies, for security, functionality, and to uphold user rights. Optional cookies offer enhanced features, and analytics.

Experience the full potential of our site that remembers your preferences and supports secure sign-in.

Governs the storage of data necessary for maintaining website security, user authentication, and fraud prevention mechanisms.

Enhanced Functionality

Saves your settings and preferences, like your location, for a more personalized experience.

Referral Program

We use cookies to enable our referral program, giving you and your friends discounts.

Error Reporting

We share user ID with Bugsnag and NewRelic to help us track errors and fix issues.

Optimize your experience by allowing us to monitor site usage. You’ll enjoy a smoother, more personalized journey without compromising your privacy.

Analytics Storage

Collects anonymous data on how you navigate and interact, helping us make informed improvements.

Differentiates real visitors from automated bots, ensuring accurate usage data and improving your website experience.

Lets us tailor your digital ads to match your interests, making them more relevant and useful to you.

Advertising Storage

Stores information for better-targeted advertising, enhancing your online ad experience.

Personalization Storage

Permits storing data to personalize content and ads across Google services based on user behavior, enhancing overall user experience.

Advertising Personalization

Allows for content and ad personalization across Google services based on user behavior. This consent enhances user experiences.

Enables personalizing ads based on user data and interactions, allowing for more relevant advertising experiences across Google services.

Receive more relevant advertisements by sharing your interests and behavior with our trusted advertising partners.

Enables better ad targeting and measurement on Meta platforms, making ads you see more relevant.

Allows for improved ad effectiveness and measurement through Meta’s Conversions API, ensuring privacy-compliant data sharing.

LinkedIn Insights

Tracks conversions, retargeting, and web analytics for LinkedIn ad campaigns, enhancing ad relevance and performance.

LinkedIn CAPI

Enhances LinkedIn advertising through server-side event tracking, offering more accurate measurement and personalization.

Google Ads Tag

Tracks ad performance and user engagement, helping deliver ads that are most useful to you.

Share the knowledge!

Share this content on:

or copy link

Cite according to academic standards

Simply copy and paste the text below into your bibliographic reference list, onto your blog, or anywhere else. You can also just hyperlink to this page.

New to UX Design? We’re Giving You a Free ebook!

Download our free ebook The Basics of User Experience Design to learn about core concepts of UX design.

In 9 chapters, we’ll cover: conducting user interviews, design thinking, interaction design, mobile UX design, usability, UX research, and many more!

When Does a Researcher Choose a Quantitative, Qualitative, or Mixed Research Approach?

• Published: 26 November 2021
• Volume 53 , pages 113–131, ( 2022 )

Cite this article

• Feyisa Mulisa   ORCID: orcid.org/0000-0002-0738-6554 1  

8624 Accesses

9 Citations

3 Altmetric

Explore all metrics

In educational studies, the paradigm war over quantitative and qualitative research approaches has raged for more than half a century. The focus in the late twentieth century was on the distinction between the two approaches, and the motivation was to retain one of the approaches’ supremacy. Since the early twenty-first century, there has been a growing interest in situating in the middle position and combining both approaches into a single study or a series of studies. Despite these signs of progress, when it comes to using the appropriate research approach at the right time, beginner educational researchers remain perplexed. This paper, therefore, provides useful guidelines that facilitate the choice of quantitative, qualitative, or mixed research approaches in educational inquiry. To achieve this objective, this article comprises three distinct and underlying areas of interest, which have been structured into three sections. The first section highlights the distinctions between quantitative and qualitative research approaches. The second section discusses the paradigm views that underpin the choice of a particular research approach. Finally, an effort has been made to determine the appropriate time to opt for any of the research approaches that facilitate successful educational investigations. Since truth and the means used to discover it are both dynamic, it is also essential to foresight innovative approaches to research with distinguishing features of applications to educational research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Social Learning Theory—Albert Bandura

The use of cronbach’s alpha when developing and reporting research instruments in science education.

Keith S. Taber

Theories of Motivation in Education: an Integrative Framework

Detlef Urhahne & Lisette Wijnia

Åkerblad, L., Seppänen-Järvelä, R., & Haapakoski, K. (2021). Integrative strategies in mixed methods research. Journal of Mixed Methods Research, 15 (2), 152–170. https://doi.org/10.1177/1558689820957125

Article   Google Scholar  

Allwood, C. M. (2012). The distinction between qualitative and quantitative research methods is problematic. Quality and Quantity, 46 (5), 1417–1429. https://doi.org/10.1007/s11135-011-9455-8

Amaratugna, D., Baldry, D., Sarshar, M., & Newton, R. (2002). Quantitative and qualitative research in the built environment: Application of “mixed” research approach. Work Study, 51 (1), 17–31. https://doi.org/10.1108/00438020210415488

Antwi, S. K., & Hamza, K. (2015). Quantitative and qualitative research paradigms in business research: A philosophical reflections. European Journal of Business and Management, 7 (3), 217–225.

Google Scholar  

Bailey, L. F. (2014). The origin and success of qualitative research. International Journal of Market Research, 56 (2), 167–184. https://doi.org/10.2501/IJMR-2014-013

Belk, R. W. (2013). Qualitative versus quantitative research in marketing. Revista de Negócios, 18 (1), 5–9. https://doi.org/10.7867/1980-4431.2013v18n1p5-9

Brinkmann, S., Jacobsen, M. H., Kristiansen, S., Brinkmann, S., Jacobsen, M. H., & Kristiansen, S. (2014). Historical overview of qualitative research in the social sciences. In The Oxford handbook of qualitative research (pp. 16–42). https://doi.org/10.1093/oxfordhb/9780199811755.013.017

Burke Johnson, R., & Onwuegbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33 (7), 14–26.

Choy, L. T. (2014). The strengths and weaknesses of research methodology: Comparison and complimentary between qualitative and quantitative approaches. IOSR Journal of Humanities and Social Science, 19 (4), 99–104.

Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge.

Creswell, J. W. (2009). Research design: Qualitative, quantitative and mixed methods approaches (3rd ed.). Sage Publications, Inc.

Creswell, J. W. (2013). Steps in conducting a scholarly mixed methods study . http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1047&context=dberspeakers

Curry, L. A., Nembhard, I. M., & Bradley, E. H. (2009). Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 119 , 1442–1452. https://doi.org/10.1161/CIRCULATIONAHA.107.742775

Daniel, E. (2016). The usefulness of qualitative and quantitative approaches and methods in researching problem-solving ability in science education curriculum. Journal of Education and Practice, 7 (15), 91–100.

Dawadi, S. (2017). Are quantitative and qualitative approaches to educational research compatible? The Warwick ELT , 3 (6). https://thewarwickeltezine.wordpress.com/2017/05/31/291/

Ejnavarzala, H. (2019). Epistemology–ontology relations in social research: A review. Sociological Bulletin, 68 (1), 94–104. https://doi.org/10.1177/0038022918819369

Fagan, M. B. (2010). Social construction revisited: Epistemology and scientific practice. Philosophy of Science, 77 (1), 92–116.

Farrell, E. (2020). Researching lived experience in education: Misunderstood or missed opportunity? International Journal of Qualitative Methods, 19 , 1–8. https://doi.org/10.1177/1609406920942066

Fassinger, R., & Morrow, S. L. (2013). Toward best practices in quantitative, qualitative, and mixed-method research: A social justice perspective. Journal of Social Action in Counseling Psychology, 5 (2), 69–83.

Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11 (3), 255–274. https://doi.org/10.3102/01623737011003255

Gunasekare, U. (2015). Mixed research method as the third research paradigm: A literature review. International Journal of Science and Research, 4 (8), 363–367.

Hodkinson, P. (2004). Research as a form of work: Expertise, community and methodological objectivity. British Educational Research Journal, 30 (1), 9–26. https://doi.org/10.1080/01411920310001629947

Howitt, D., & Cramer, D. (2011). Introduction to research methods in psychology (3rd ed.). Pearson Education Limited.

Johnson, R. B., & Christensen, L. (2014). Educational research: Quantitative, qualitative and mixed approaches (5th ed.). Sage Publications, Inc.

Johnson, R. B., & Christensen, L. (2020). Educational research: Quantitative, qualitative, and mixed approaches (7th ed.). Sage Publications, Inc.

Khaldi, K. (2017). Quantitative, qualitative or mixed research: Which research paradigm to use? Journal of Educational and Social Research, 7 (2), 15–24. https://doi.org/10.5901/jesr.2017.v7n2p15

Krivokapic-skoko, B., & O’neill, G. (2011). Beyond the qualitative-quantitative distinction: Some innovative methods for business and management research. International Journal of Multiple Research Approaches, 5 (5), 290–300. https://doi.org/10.5172/mra.2011.5.3.290

Lee, A. S., & Baskerville, R. L. (2003). Generalizing generalizability in information systems research. Information Systems Research . https://doi.org/10.1287/isre.14.3.221.16560

Levers, M. J. D. (2013). Philosophical paradigms, grounded theory, and perspectives on emergence. SAGE Open, 3 (4), 1–6. https://doi.org/10.1177/2158244013517243

Lobe, B., Morgan, D., & Hoffman, K. A. (2020). Qualitative data collection in an era of social distancing. International Journal of Qualitative Methods, 19 , 1–8. https://doi.org/10.1177/1609406920937875

Mack, L. (2010). The philosophical underpinnings of educational research. Polyglossia, 19 , 5–11.

Madill, A., & Gough, B. (2008). Qualitative research and its place in psychological science. Psychological Methods, 13 (3), 254–271. https://doi.org/10.1037/a0013220

Marshall, M. N. (1996). Sampling for qualitative research. Family Practice, 13 (6), 522–525.

Maxwell, J. A., & Reybold, L. E. (2015). Qualitative research. In International encyclopedia of the social & behavioral sciences (2nd ed., Vol. 19, pp. 685–689). Elsevier. https://doi.org/10.1016/B978-0-08-097086-8.10558-6

Mertens, D. M. (2012). What comes first? The paradigm or the approach? Journal of Mixed Methods Research, 6 (4), 255–257. https://doi.org/10.1177/1558689812461574

Meyer, D. K., & Schutz, P. A. (2020). Why talk about qualitative and mixed methods in educational psychology? Introduction to special issue. Educational Psychologist, 55 (4), 193–196. https://doi.org/10.1080/00461520.2020.1796671

Morgan, D. L. (2007). Paradigms lost and pragmatism regained: Methodological implications of combining qualitative and quantitative methods. Journal of Mixed Methods Research, 1 (1), 48–76. https://doi.org/10.1177/2345678906292462

Morgan, D. L., & Nica, A. (2020). Iterative thematic inquiry: A new method for analyzing qualitative data. International Journal of Qualitative Methods, 19 , 1–11. https://doi.org/10.1177/1609406920955118

Östlund, U., Kidd, L., Wengström, Y., & Rowa-Dewar, N. (2011). Combining qualitative and quantitative research within mixed method research designs: A methodological review. International Journal of Nursing Studies, 48 (3), 369–383. https://doi.org/10.1016/j.ijnurstu.2010.10.005

Poli, R. (2018). A note on the classification of future-related methods. European Journal of Futures Research, 6 (1), 1–7. https://doi.org/10.1186/s40309-018-0145-9

Rahman, M. S. (2016). The advantages and disadvantages of using qualitative and quantitative approaches and methods in language “Testing and Assessment” research: A literature review. Journal of Education and Learning, 6 (1), 102. https://doi.org/10.5539/jel.v6n1p102

Sale, J. E. M., Lohfeld, L. H., & Brazil, K. (2002). Revisiting the quantitative-qualitative debate: Implications for mixed methods research. Quality & Quantity, 36 , 43–53. https://doi.org/10.1023/A:1014301607592

Salvador, J. T. (2016). Exploring quantitative and qualitative methodologies: A guide to novice nursing researchers. European Scientific Journal, 12 (18), 107–122. https://doi.org/10.19044/esj.2016.v12n18p107

Shannon-Baker, P. (2016). Making paradigms meaningful in mixed methods research. Journal of Mixed Methods Research, 10 (4), 319–334. https://doi.org/10.1177/1558689815575861

Symonds, J. E., & Gorard, S. (2010). Death of mixed methods? Or the rebirth of research as a craft. Evaluation & Research in Education, 23 (2), 121–136. https://doi.org/10.1080/09500790.2010.483514

Taylor, P., & Kanis, H. (2004). The quantitative-qualitative research dichotomy revisited. Theoretical Issues in Ergonomics Science, 5 (6), 507–516. https://doi.org/10.1080/1463922041233130303418

Techo, V. P. (2016). Research methods-quantitative, qualitative, and mixed methods . Horizons University. https://doi.org/10.13140/RG.2.1.1262.4886

Wohlfart, O. (2020). “Digging Deeper?”: Insights from a novice researcher. International Journal of Qualitative Methods, 19 , 1–5. https://doi.org/10.1177/1609406920963778

Yin, R. K. (2011). Qualitative research from start to finish . The Guilford Press.

Download references

No funding was received for this article.

Author information

Authors and affiliations.

Institute of Education and Behavioral Sciences, Ambo University, Ambo, Ethiopia

Feyisa Mulisa

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Feyisa Mulisa .

Ethics declarations

Conflict of interest.

Not applicable.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Mulisa, F. When Does a Researcher Choose a Quantitative, Qualitative, or Mixed Research Approach?. Interchange 53 , 113–131 (2022). https://doi.org/10.1007/s10780-021-09447-z

Download citation

Received : 29 March 2021

Accepted : 18 November 2021

Published : 26 November 2021

Issue Date : March 2022

DOI : https://doi.org/10.1007/s10780-021-09447-z

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Quantitative research
• Qualitative research
• Mixed research
• Research approaches
• Research paradigm
• Find a journal
• Publish with us
• Track your research

• Open access
• Published: 01 April 2024

“They seemed to be like cogs working in different directions”: a longitudinal qualitative study on Long COVID healthcare services in the United Kingdom from a person-centred lens

• Chao Fang 1 ,
• Sarah Akhtar Baz 2 ,
• Laura Sheard 2 &
• J. D. Carpentieri 3  

BMC Health Services Research volume  24 , Article number:  406 ( 2024 ) Cite this article

250 Accesses

5 Altmetric

Metrics details

The COVID-19 pandemic has presented significant challenges to the already over-stretched healthcare system in the United Kingdom (UK). These challenges are particularly pronounced for people living with the novel condition of Long COVID (LC) as they often face persistent and fluctuating symptoms, encountering prolonged uncertainty when seeking medical support. Despite a growing understanding of the healthcare challenges associated with LC, existing qualitative studies have predominantly focused on individual experiences rather than examining the structural aspects of healthcare.

A longitudinal qualitative study with 80 participants and 12 healthcare practitioners was conducted in the UK to explore the healthcare experiences of those with LC. In total, 178 interviews (with attrition) were collected across two rounds, from November 2021 to March 2022, and from June to October 2022.

Embracing a person-centred framework that recognises and nurtures interconnected individual, relational, and existential needs, we investigated healthcare experiences related to LC across primary, secondary, and specialist integrated care. Using this perspective, we identified three overarching themes. Theme 1 addresses the persistent hurdle of accessing primary care as the initial point of contact for LC healthcare; Theme 2 underscores the complexity of navigating secondary care; and Theme 3 encapsulates the distinctive challenges of developing LC integrated care. These themes are interlinked, as people with LC often had to navigate or struggle between the various systems, with practitioners seeking to collaborate across the breadth of their professional responsibilities.

From a person-centred approach, we were able to identify the needs of those affected by lasting LC symptoms and comprehend how health services intricately influence these needs. The focus on healthcare systems also captures the nuanced impact that continuing healthcare struggles can have on people’s identity. As such, our findings provide evidence to inform a more effective and sustainable delivery of person-centred care for people with LC across various healthcare settings and over time.

Peer Review reports

The COVID-19 pandemic has presented significant challenges to healthcare in the United Kingdom (UK). At the peak of the pandemic in 2020–21, the Office for National Statistics (ONS) estimated that over 10% of the UK population suffered from persistent symptoms 12 weeks post-infection [ 1 ]. According to the latest ONS statistics from March 2023, around 1.9 million people (2.9% of the UK population) self-reported Long COVID (LC) symptoms [ 2 ]. These symptoms can encompass respiratory, cognitive and cardiovascular issues. Commonly reported issues include fatigue, breathlessness, brain fog and pain, while others also encounter hair loss, skin rashes and sensory dysfunction [ 3 ]. Managing LC symptoms is often closely connected to its multisystemic and often changing nature, requiring ongoing support for symptom management and recovery [ 4 ]. While understandings of and treatments for LC as a new illness are fast-evolving, healthcare provision in the UK continues to lag [ 5 ]. Extensive literature has painted a troubling picture of fragmented healthcare for LC: people living with LC (PLwLC) often have to do the “hard and heavy work of managing symptoms and accessing care” [ 6 ] and thus face various challenges arising from their disrupted health and identity [ 7 , 8 ].

The UK healthcare system has been scrutinised by waves of PLwLC across different levels2. A scoping review on potential LC pathways [ 9 ] suggests that LC related healthcare has been predominantly offered in primary care, yet accessing it remains a significant hurdle for many [ 10 , 11 ]. Even when admitted into healthcare, they also faced considerable barriers in navigating said systems to obtain more specialised (often secondary) care for their symptoms4,7. To meet the unique needs of PLwLC and to optimise healthcare resources dedicated care pathways have been established across the UK since December 2020 [ 12 ]. These pathways, including Long COVID clinics in England and similar services in Wales, Scotland, and Northern Ireland, aim to offer tailored care that addresses the multifaceted challenges (e.g., physical, mental and social) individuals face during their LC trajectories. However, these pathways are limited due to lacking accessibility and holistic care [ 13 ]. The dilemmas between the needs of PLwLC’s and the constraints of healthcare provision have reflected a “perfect storm” in a “healthcare system which has faced years of austerity, budget caps, increasing waiting times, pressurised services, backlogs, and workface shortages” [ 14 ].

These healthcare dilemmas for LC have so far been captured as experienced by individuals . Drawing upon individual narratives (e.g., both the general public living with PLwLC 4,6,7 and healthcare professionals with LC4 [ 15 ],), current literature has often explored healthcare as a vague (broad) construct, asserting that people with LC were “let down, fought against and negotiated with”6,8,10. In other words, LC healthcare has been primarily examined through subjective feelings and the experiences of individuals. Various theoretical frames have been used to explore both the complexity of dilemmas facing LC healthcare and the potential solutions for these. Researchers have employed lenses such as “candidacy” [ 16 ], “legitimation” [ 17 ], “epistemic injustice”8 and “sick role” [ 18 ] to capture both the challenges and the agency of PLwLC’s interactions with healthcare. While the focus on individual encounters in healthcare is valuable, from a health service research perspective, it is also important to understand barriers and enablers for LC healthcare from a more systematic and structural perspective. As such, these understandings can contribute to more explicitly identifying gaps in care provision, offering evidence to further shape healthcare development for LC in the longer term.

To enhance the understandings of PLwLC’ needs and how these are supported, undermined and overlooked in healthcare systems, we argue that adopting a person-centred lens is valuable. Person-centredness, as both a theoretical and practical framework, has long been a cornerstone of healthcare. It prioritises the individual needs and values of patients throughout their healthcare journey. Research has suggested that developing healthcare provision with a person-centred lens can contribute to improved health outcomes and reduced care expenditure [ 19 , 20 ]. This is particularly important in the UK as the healthcare services are free at the point of delivery and the National Health Service (NHS) is responsible for providing comprehensive healthcare to the whole population across a range of interconnected care settings, including primary, specialist, acute/emergency care and integrated care pathways [ 21 ].

In the context of this universal healthcare, the values of person-centred approaches have been interpreted and implemented in a multitude of ways, aiming to treat patients as a person whose ‘‘choice" and "rights" are holistically and consistently addressed20. This focus of person-centred care also entails an empowering dimension, ensuring patients are equipped with sufficient knowledge and skills, and are confident in managing their own health19, [ 22 ]. Healthcare in the UK thus far has actively sought to promote patients’ individual wishes, dignity and autonomy across all the processes of care planning, treatment and decision-making [ 23 ]. Person-centred needs have also been closely examined in the rich matrix of patients’ family, social, cultural and religious circumstances to support their relational being20,22. Meanwhile, there is also an increasing focus on patients’ existential needs in healthcare settings particularly for those with terminal and chronic illnesses, in response to deeper fears of losing fundamental resilience and meaning due to compounded health-related losses [ 24 ]. More importantly, these individual, relational and existential components of person-centred care are often emphasised not as separated but interconnected entities in healthcare provision21,23. As such, person-centred care presents a holistic and systemic approach to addressing the multifaceted and interconnected needs of people with health conditions throughout their healthcare experiences24.

Despite efforts to integrate person-centred care into the UK healthcare system, persistent gaps, primarily attributed to funding and staff shortages, hinder its implementation, leading to increased waiting times and reliance on self-management or private healthcare. Regional disparities, inequalities, and factors such as racism, age, gender, and cultural differences further obstruct healthcare engagement with patients' multifaceted needs. These challenges to the implementation of person-centred healthcare in the UK have been further exacerbated by the COVID-19 pandemic5. The unprecedented crisis has heavily drained the already over-stretched public health resources, amplifying existing issues such as staff shortages, data sharing, inter-organisational coordination and inequalities14. As a result, enacting person-centred care may become even more complicated in varied healthcare settings [ 25 ]. The COVID-19 pandemic has also presented unique circumstances, confronting the competing agendas of prioritising individual care and public health interests. As such, person-centred care is a useful lens to explore how individual needs are shaped by standardised (and highly pressurised) healthcare structures. This lens can be particularly beneficial for critically understanding healthcare services for people with LC, as living with such novel and persistent symptoms may require both acute care and prolonged support alongside their illness trajectories. Ultimately, we aim to understand not only the quality of health care provision but also to more adequately clarify how LC patients’ needs are supported/undermined in (intersection with) health systems over time. These understandings will help to inform the continuing development of holistic healthcare for LC and other similar chronic or novel health conditions in the UK and internationally.

We conducted a longitudinal qualitative study to understand the evolving needs of PLwLC in the UK and the evolution of healthcare in response to this. The interviews were conducted at two times between 2021–2022, respectively November 2021–March 2022, June–October 2022 (each participant had their two interviews approximately 6 months apart). The findings of the first round of interviews have been previously published10,31.

Research design

Our study was designed to conduct three phases of interviews over 2021–2023, talking to both people living with LC and healthcare practitioners. This article reports upon our findings from the initial two phases which extensively explored healthcare experiences (the third phase, conducted in early 2023, focused on resilience). Our aim in this study was to capture an ongoing picture of LC experiences and healthcare across the UK. We also placed a specific focus on a region in northern England characterised by great levels of deprivation (to as region A to project the confidentiality of our participants). This geographical focus allowed us to further contest social and racial inequalities in healthcare, which were exacerbated during the COVID-19 pandemic [ 26 ]. Our investigation examined experiences and development of LC health services from both cross-sectional and longitudinal perspectives. Cross-sectionally, by combining data from both PLwLC as (potential) health services users and healthcare professionals as services providers, we aimed to gain a fuller understanding of how people with LC are (or not) supported as a ‘person’ in health services at that time19. Longitudinally, we then tracked how person-centred healthcare for LC was developed over time in the fast-evolving context of LC as a social and medical experience.

To better understand provision and experience of LC healthcare across diverse circumstances, we used purposeful sampling to recruit participants with self-identified LC from nationally and regionally representative cohort studies. This approach enabled us to not rely on health records for recruitment, as such not only reaching those within healthcare systems (and thus on health records) but also PLwLC who have not accessed healthcare for a variety of reasons. Focusing on self-identified LC symptoms provided us access to people who have not been formally diagnosed with COVID and LC, whose voices often remain unheard due to early testing limitations and healthcare access issues. Our sampling strategy also expanded our research scope by including PLwLC who may not have a strong online presence or digital literacy, unlike many earlier studies recruiting from self-selecting online groups7,16. This inclusive sampling strategy allowed us to engage with people residing in diverse, often overlooked, social and community settings to explore their healthcare experiences of living with LC10.

Participants living with LC were recruited in two ways. Firstly, 40 participants were recruited from five UK national cohort studies (Fig.  1 ). Specific COVID-19 surveys from these cohort studies identified cohort members who reported COVID-19 related symptoms for over 4 weeks, with a focus on those indicating symptoms for over 8 weeks. Recruitment concluded upon reaching the target of 40 interviews. Secondly, 40 interviews were collected in Region A. A similar recruitment approach was used (Fig.  1 ) , identifying 21 participants, who are parents of children born in a general hospital in Region A between March 2007 and December 2010. The remaining 19 participants were recruited from the wider local community through community workers and snowball sampling, to gain a more diverse demographic sample. Both our national and region-specific recruitment oversampled individuals with greater socioeconomic deprivation and from ethnic minorities to reach people who may be underrepresented in other LC studies. In the first phase of interview collection, we conducted in-depth interviews with 80 socially and ethnically diverse participants across varied age groups, including two participants in the 70–79 age group and their partner in a dyad interview (Table  1 ). 73 participants, including the two with their partner, remained for our second phase of interviews (9% attrition rate). Over the two phases, around 25% of PLwLC recovered, 25% improved but had minor symptoms, and the remaining half continued to experience significant and sometimes worsening symptoms (these are estimates due to some participants that their symptoms intersected with other health conditions).

Participating cohort studies

To enrich our picture of LC health services, particularly from the perspective of providers, we included healthcare and public health professionals in our study. We adopted an inclusive approach, aiming to engage interdisciplinary professionals from different healthcare sections supporting LC (e.g., primary and specialist care). We concentrated on sampling practitioners in the metropolitan region A, including the city and surrounding areas. This strategy allowed us to explore how inequalities, such as poverty and racism, may disproportionally contribute to the healthcare challenges facing PLwLC. We also paid attention to the provision of the LC pathway in Region A, one of longest-running pathways in the UK [ 27 ], particularly within the limited timeframe of our study. Using our team’s existing connections as well as snowballing, 12 practitioners were recruited from 7 different care settings in the first phase of interviews (Table  2 ). In phase 2, we talked to 13 healthcare professionals, including 9 remaining from the first phase and 4 new recruits due to job changes and the development of new services.

All the interviews with PLwLC and practitioners were conducted remotely, either online by Zoom or telephone (apart from with two PLwLC who had hearing accessibility issues). The interviews ranged from 30 to 110 min in length and averaged around 45 min.

Data analysis

We adopted a reflexive thematic analysis approach to interpret the rich data10. Given the longitudinal nature of our study, the data analysis presented in this paper focused on "changes" in healthcare both from an individual and structural perspective (by talking to both PLwLC and practitioners). As such, we “ground the interviews in an exploration of processes and changes which look both backwards and forwards in time [ 28 ](p.194)”, to explore the construction of person-centred healthcare in response to the novel and often complex condition of LC in the UK. To gain in-depth and critical insights into LC healthcare, we analysed the longitudinal qualitative data at three levels, namely, “description”, “analysis” and “interpretation” [ 29 ]. These levels aimed to understand “if/what changes had occurred”, “how/why these changes might have happened” and “what is the meaning and impact of these changes”.

Following these guiding questions, we conducted a three-step analysis (Fig.  2 ). Firstly, we generated and compared initial codes from both phases to describe the provision and development of LC healthcare over time. Based on step 1, we moved to step 2, incorporating a person-centred lens24 to analyse essential features of these developments and the systematic interconnections amongst these changes. Finally, in step 3 we interpreted how these changes address/overlook PLwLC as a ‘person’ from a holistic and consistent perspective. Throughout the analysis, we considered changes both at the individual and the collective levels to more fully capture changes in LC healthcare and the impact on individual experiences. During this threefold longitudinal analysis, we also carefully relate, contrast and further incorporate narratives from both PLwLC (service users) and practitioners (service providers) to explore the intersections between broader healthcare structures (e.g., operation, implementation and care delivery) and the localised experiences of PLwLC’s multifaceted and persistent needs.

An illustrate of our coding process

We present our findings on LC healthcare services in the UK broadly through three dimensions of the health system: primary, secondary and LC specialist care. While acknowledging that services also exist between and outside these systems, we briefly mention them to provide a broader view of LC healthcare. Figure  2 shows three overarching themes: theme 1 reports continued hurdles in accessing the first point of contact for LC healthcare; theme 2 highlights the complexity in progressing through secondary care; theme 3 captures unique challenges to the propagation of integrated LC care pathway. These themes are used to capture a systemic view of how people with LC are (or are not) supported in a person-centred manner. Our findings and the three dimensions of healthcare they encompass are interconnected. As we found, people were often bounced between these systems; practitioners also sought to cooperate across their own remit with practitioners from diverse fields.

The person-centred lens here is used as an overarching framework providing a consistent thread to understand the quality of healthcare for PLwLC. This lens focuses on multifaceted needs, including individual, relational, and existential aspects, all of which are interconnected, shaping their health experiences and identity in nuanced ways. As such, we examined how these needs are address/overlooked both within specific and across healthcare systems, exploring how person-centred lens can inform healthcare services, to more holistically (multifaceted needs) and consistently (across settings and time), to support LC. To protect participants’ confidentiality, pseudonyms are used throughout below.

Theme 1: continued hurdles to accessing primary care and to entering healthcare systems

Ongoing access barriers.

Primary care as the first point of contact with healthcare is often the principal gateway for people to enter health systems [ 30 ]. A predominant message voiced by our participants across the two phases of interviews is the significant barriers in accessing primary care, particularly general practice (GP) services, including not getting an appointment, receiving inadequate care and having to be persistent. Research has found that the COVID-19 pandemic has created a “perfect storm” to exacerbate the already pressurised primary care services10,14.

During the first phase of interviews in 2021–22, over 70% of our 80 LC participants faced significant challenges in securing GP appointments for their acute and persistent COVID-19 symptoms. Reported access barriers included “waiting on the phone for over two hours”, “making 100 calls on a Monday morning”, as well as “being turned away by receptionists or nurses before seeing a GP”. The struggle with access is vividly captured by Barry’s experience:

Barry: “ You’re almost like a leper going to the GP, just can’t get to the surgery… I just can’t see a doctor. It’s all done like this. You know, sometimes just done over the phone, it’s not even a video. ” (Male, White British, 60s, phase 1)

The situation had not improved significantly later in 2022, the rate of participants in phase 2 experiencing GP access barriers remained high, with over 65% affected. This continued delay and inaccessibility was also acknowledged by the GPs who we interviewed in both phases, reflecting long-standing issues related to budget caps, backlogs and workforce shortages in primary care. The ongoing hurdles in obtaining basic medical support, as well as clarification and reassurance, led to increased frustration and health-related anxieties among many of our LC participant:

Susan: “ You don’t know the fact that maybe you haven’t had treatment or things haven’t been picked up, maybe will impact your long-term health because you’ve been waiting for so long. I think that’s also the thing, have I missed the time to get some treatment or something? ”. (Female, White British, 50s,)

Alternative to GP care

Due to the ongoing barriers to accessing primary care, many LC participants had trouble accessing NHS healthcare for medical support, leading them to explore alternative ways to address their health concerns. They often resorted to self-management, using methods like painkillers, supplements, exercise, and meditation to cope with their symptoms. Some sought advice for LC symptoms from resources like the Internet (particularly online self-help groups) and local communities, including pharmacists. Only a small number of participants (just seven in phase 1 and five in phase 2 interviews, respectively) were able to access private GP services.

Despite ongoing barriers to accessing primary care, some participants, particularly those with urgent symptoms, turned to emergency care for faster and more immediate access to healthcare. However, emergency care often provided one-off support without follow-up, leaving participants like Sara without continuous assistance for their ongoing struggles:

Sara: “ I went to hospital and had x-ray, blood tests done and they said ‘you’ve got a blood clot, we think it’s on your lung but we need to book you for a CT scan’… [following the scan] I came home and they gave me some blood thinning tablets and after about 10 days I had a CT scan. Whatever it was the blood clot was not there anymore. They said that ‘there’s some damage on the lungs’. So they gave me some inhalers and I got to go home. After that I wasn’t well at all… They could clearly see that but what the long effect is we don’t know. But I’ve not been back to the GP to find out, the only follow-up appointment I was offered was in hospital with the blood clot.” (Female, British Pakistani, 30s, phase 1)

In addition, community-based care, such as physiotherapy, was another avenue for alternative care; however, access to it often had to be gained through primary care. When asked about how physiotherapists identify people with needs related to LC symptoms, Luke, who was a PLwLC and a volunteer in a local therapy centre, said (this issue remained in phase 2 interviews):

Luke : “That’s what we’re waiting on the hospital to do for us. And we haven’t had any referrals yet. I don’t know what the hold-up is. We’ve not, we are all geared up ready for them, but we haven’t had anybody come through.” (Male, White British, 60s, phase 1)

The above experiences underscore the ongoing call to emphasise the significant role of primary care in LC healthcare9,30. Nonetheless, due to persistent access barriers and/or previous negative healthcare experiences, approximately half of our participants felt “exhausted” and had to “give up” trying to engage with their GP and enter the healthcare system. The number remained persistent in phase 2, further fuelling people’s anxiety and worries about their symptoms.

Increasing awareness of LC

Despite a rather disheartening picture depicted above, we also observed improvements in primary care for PLwLC during our two-phase interviews (November 2021 – October 2022). In phase 2, some of our LC participants reported increased awareness of LC as a novel medical condition among professionals. These improvements in primary care were also supported by accounts from primary care practitioners, with one GP mentioning that she had more information to draw upon to recognise and empathise with patients’ LC symptoms:

“ I’ve seen patterns I suppose of what people have had. So certainly right at the beginning, it was all the lost your taste and smell and you’re going to have a cough and breathlessness, particularly kind of neuro type symptoms. Those kind of things I can reassure patients that I’ve seen and that people generally tend to get better, so you get a bit more idea of what kind of symptoms are coming.” (GP 1, phase 2)

While some patients experienced improved support, or at least understanding from their GP, this increased awareness of their condition was not regionally/nationally consistent. According to a GP we interviewed, this discrepancy may be attributed to the lack of “systemic training and knowledge” about LC, especially during the early days of the pandemic, for primary care practitioners. In other words, whether and how to support LC was often dependent on practitioners’ own wishes/opinions/understandings. As a result, a contrasting picture was observed, with a few patients reporting improved primary care while many others still found the improvement limited. Craig shared that although his GP acknowledged his LC symptoms, she tended to be "reactive" rather than "proactive" in providing support.

Craig: “ She took note of it [LC], obviously, we’d had it– but didn’t prescribe or didn’t expand on the conversation. She was just more reactive as opposed to proactive on it.” (Male, White British, 50s, phase 2)

This ongoing inadequacy and disparities in LC support from primary care may contribute to the exacerbation of people’s worries and even desperation. During our phase 2 interviews, some participants expressed the sentiment that “there is nothing they [GPs] can do”, with a few opting to forgo primary care in favour of alternative forms of support.

As illustrated in the theme above , we identified barriers in LC primary care, termed "de-personalisation" by one PLwLC participant. While this phenomenon was not unique to primary care and was also observed in secondary and specialist care settings, it was particularly significant as it created a sense of neglect at the gateway to the health system. Many participants with prolonged and often 'mysterious' LC symptoms faced various hurdles in accessing primary care for initial clarification and support. Even those, who gained access, often struggled with limited understanding and support from practitioners as the first contact point with professional healthcare. This could further illegitimatise their experiences and failed to validate their suffering. Despite ongoing efforts to improve LC support in primary care, the continued uncertainties around the condition seemingly caused significant emotional distress, including frustration, anxiety and fears, related to both healthcare access and their illness. Participants often likened the differentiated progress in primary care to a "postcode lottery", adding to the uncertainty they felt about their healthcare.

Failing to meet the individual and relational needs of PLwLC in primary care may have further implications for their existential needs [ 31 ]. These continued multifaceted uncertainties may hinder their ability to access clinical and social support to understand and adapt to this novel health condition. These experiences can be particularly existential, as exemplified by Susan's concerns about her shattered health and future due to limited healthcare access. Without sufficient clarification and reassurance from reliable medical resources, PLwLC may struggle to retain meaning and purpose as they navigate their ongoing life with the illness31.

Theme 2: complexity in navigating secondary care

Specialised but fragmented care.

Secondary care, compared to primary care, tended to provide more specialised support for many of the often-complicated symptoms faced by PLwLC. However, due to the limited availability of secondary care and the ongoing issues around access to primary care, only 17 out of 80 participants had access to secondary care in phase 1 (e.g., for cardiological, respiratory, neurological and mental health complications). In phase 2, the situation remained largely similar, with 14 participants being discharged due to their improved conditions while 5 more with worsened symptoms were being referred to secondary care. While these participants appreciated the targeted care they received, they also felt that the highly specialised nature of secondary care sometimes could restrict their chance to access more holistic and integrated care. Lucy found her fatigue and brain fog symptoms were not adequately addressed by varied specialists:

Lucy: “ The thing I found the most difficult about the healthcare system is that they don’t see things as a round so that you know you kind of go and see a few different specialists and one’s looking at your lungs, and one’s looking at your head, and one’s looking at your heart but nobody’s pulling all together and sitting down and going, this is what we think. There’s no, you’re not really sure what the journey is or what they’re trying to find out, what the conclusion is.” (Female, White British, 50s, phase 1)

The above situation was not particularly better in phase 2 as Lucy and her peers still struggled to access what she described as ‘holistic care’. This over-specialisation could also be attributed to a lack of communication across healthcare settings. A GP reported her frustration, saying, “ I want to know as a GP that my patients have been worked up for properly. I have to ask secondary care [for updates] because it’s out of my hands” (phase 1 interview).

The inconsistency within and beyond secondary care for PLwLC could also cause frustration. In our study, only a few participants, such as Heather, who had a certain level of healthcare knowledge and communication skills, could navigate the highly specialised and fragmented care systems, often employing extreme persistence at the cost of becoming known as “infamous”:

Heather: “ I phoned [hospital A] the next day because although it's another hospital called [hospital B] in [location C], it was through [hospital A] that I had to try and weave my way through. And thankfully, I'd taken so many phone numbers when my husband was at [hospital A], I managed to go through to a specialist and say, ‘I can't get through to your booking clerk, but I need to do this’, and because we're infamous now I think, [laughs], I managed to get – she got me an emergency appointment for the afternoon. ” (Female, White British, 60s, phase 1)

Heather’s situation in phase 2 was “slightly better but not significantly”. After enduring prolonged struggles while navigating secondary care and beyond, Heather expressed that “ they [healthcare professionals, such as specialists, paramedics and receptionists] seemed to be like cogs working in different directions ”. This disintegration of care provision was not unexpected to our participants working in secondary care. A respiratory consultant highlighted that " this is not just a problem for Long COVID, but a broader issue " due to a lack of funding and staff (phase 2).

Importance of being in the system

Despite the barriers to accessing holistic and consistent secondary care, our LC participants predominately emphasised the importance of being in the healthcare system (particularly secondary care after GP referrals). Those referred/admitted to secondary care (e.g., hospitalisation, specialist care), often had positive healthcare experiences. For instance, Patrick entered secondary care via hospitalisation for his acute COVID-19 symptoms. Whilst he had to wait for and navigate various specialist care pathways over a lengthy period after hospital discharge, he still found the support he received “helpful” for his LC recovery:

Patrick: “ They [the hospital] were very supportive – after I left hospital there was in total about seven or eight months of follow-up support. I had the general nurse, the general consultant because they were worried about strokes and they were worried about different things, neurosurgeon, a lot of different people doing bloods. So I had to have the different people signed off and occupational psychiatry had to sign me off etc. So bit by bit they all signed me off until I got out and then even thereafter each function needed to monitor you afterwards. So I had a lung specialist because my lung was damaged. I had a haematologist, so different functions… Definitely, I mean the support helped me recover .” (Male, British Indian, 50s, phase 1).

Such support in secondary care was afforded by concentrated resources and the highly specialised nature of treatment, ensuring patients are “healthy enough” to be discharged and referred back to primary care9. Therefore, many of our participants were determined to enter the specialised secondary care system. This struggle was particularly evident in Gemma’s persistence, expressed across the two interviews, as she wanted her “ Long COVID to be logged in the NHS ” for referral and further examinations/treatment of her multisystemic symptoms of fatigue, pain and sensory issues (Female, white British, 63).

These attempts to enter and move forward through the system however were often obstructed by barriers in secondary care, and sometimes connected to primary care, reflecting broader issues in the UK public healthcare system. A service manager reported ongoing efforts to clear referral delays at her hospital over the two interviews, highlighting both the healthcare access barriers and the impact on the wellbeing of PLwLC:

“ Sometimes there are delays in getting the bloods and things like that, I think there is a huge barrier to people even getting an appointment with their GP to get referred and that can lead to a lot of helplessness and hopelessness for people like, what’s the point and will I get any help anyway? That’s a huge barrier, I hope that people know that widely in society what’s available and I think the challenge is each local commissioning area have a different pathway .” (Service manager 1, phase 2)

Increased challenges to address blurred boundaries between LC and other health conditions

Secondary care faces ongoing challenges due to the novel and rapidly evolving symptoms of LC. Our conversations with participants during 2021–22 revealed that LC symptoms often develop alongside other pre-existing health issues, creating complications that can be challenging to address even with highly specialised care. Some interviewees expressed frustration with the lack of adequate support available to manage their LC symptoms alongside other health concerns. For example, Linda's hospital admission, reported in her phase 1 interview, was unable to determine whether her throat problem was related to LC or another underlying condition. In the second interview, she continued to express her concerns about changing LC symptoms and her desire for more specialised/personalised healthcare.

Linda: “ Obviously, symptoms are still coming up and changing, so it’s not that you’re living with long term symptoms that are the same, that actually symptoms are changing, and new symptoms are coming along, that weren’t there a year ago; which is very odd… That’s why you want to get to be seen [by specialists], so if they start to see something worrying coming out, that you’re on a list somewhere. At the moment I don’t feel I’m on a list anywhere of people that are suffering from this .” (Female, white British, 30s, phase 2).

The above accounts highlight the importance of healthcare providers addressing the interconnected nature of LC symptoms and other health issues for more effective care. For instance, in a phase 2 interview with a hospital service manager, a respiratory care service shifted to acknowledge that the symptoms of middle aged PLwLC could potentially be compounded by LC and menopause:

“ We’re realise that women who are of menopausal age those have been affected more by post COVID as well. We’ve done some training sessions on the menopause and post COVID to try and again make people more aware.” (Service manager 2, phase 2)

Despite the positive developments observed in region A, the majority of participating PLwLC faced persistent barriers in accessing specialist care for their increasingly interwoven symptoms between LC and other conditions. In some cases, due to the specialised nature of secondary care, PLwLC with complex and unknown symptoms could face exclusion from the healthcare system. Penny was one of those who was already ‘in the system’ due to pre-existing health issues, but had to re-enter specialist care via the aforementioned challenging primary care routes for her LC-related pains that intersected with her previous conditions:

Penny: “ Like my rheumatoid I know when I’m having a flare up, I visit the consultant and I have a good back-up with the rheumatoid team. If I’m having a flare up or something’s wrong, I know that I phone up, the rheumatoid team and they help me and they support me… The thing [joint pain] with Covid is basically I don’t know what I’m supposed to be looking for and nobody’s actually said anything, so I get confused sometimes when I feel ill, I don’t think of Long Covid and just think, oh maybe I’ve got a chest infection or something else. Then you go to your GP and they say Long Covid and then you don’t know what it is .” (Female, white British, 60s, phase 2).

The findings in this theme illustrated the difficulties our LC participants faced in navigating support for their complex symptoms within the complicated secondary care system. Being “in the system” was essential for our participants access to various specialised medical resources, but the challenges persisted in supporting LC as a novel condition within an already strained healthcare system. While primary care serves as the gateway to the health system, secondary care is where patients seek improvement, if not full recovery, of their medical conditions5,9. As demonstrated earlier, the lack of holistic and consistent support in specialist care could undermine the physical, emotional, social, and financial aspects of PLwLC in an ongoing manner. The slow progress in secondary care may gradually erode people’s hope to recover through receiving specialised (often as perceived “more advanced”) support. Such experiences in secondary care might have an existential dimension, as captured by Dorothy’s reflections on her vulnerability and even mortality in phase 2 interview: “ this is the final curtain, this is the last, ‘cos you think, well this isn’t getting any better, I don’t know what this is ” (Female, white British, 60 s).

Theme 3: unique challenges to promote LC integrated care pathways

Still limited coverage.

To provide PLwLC with more specialised and integrated care, a variety of LC clinics in England and similar services in the rest of the UK have been established. The NHS plan for improving long COVID services published in 2022 highlighted the accomplishments of developing new services and outlined plans to cut waiting times, improve care quality and reduce health inequalities12. However, our study found that these pathways were largely unknown and challenging to access for people with LC. In phase 1, only 4 out of 80 participants had accessed LC clinics through GP referrals, and this only increased to 5 in phase 2. A major contributing factor to this issue was the prevalence of barriers encountered when trying to enter and navigate healthcare systems. For example, Christine had initial difficulties accessing her GP and faced a lengthy process of medical examinations before being referred to a LC clinic (female, white British, 50 s). By her second interview, she had been on the LC clinic waiting list for over a year, despite her proactive efforts to communicate with her GP and the clinic.

The limited access also lay in a lack of awareness about LC integrated/specialised care. Approximately one third of our participants with LC in phase 1 had never heard of LC clinics or other similar services. Despite being provided with information about the integrated care pathways, many participants’ knowledge remained largely limited in phase 2. This was due to the scarcity of publicly accessible information about the specialised services and difficulties in accessing them (or the healthcare systems more generally):

Malcolm: “ I haven’t heard about a Long COVID clinic or something like that in this area if there was something I think she would have said, or if you could see, the nurse would have said, do you want to go to a clinic? But there’s nothing .” (Male, white British, 70s, phase 2).

As seen above, inadequate information for primary care practitioners was another contributor to the limited access to LC integrated care pathways. This issue was reiterated by a GP who had to rely on her patients for information about the support offered in LC clinics:

“ I was relying on my patients, I was like, tell me what the Long COVID clinic is like and come back to me. And then I can tell the next person ”. (GP 1, phase 1)

The situation improved in phase 2 interview as this GP could access notes via NHS systems from the LC clinics about support details for her patients, but she still struggled to stay updated on the fast-evolving LC care pathways due to a lack of direct communication from the local LC clinics.

Tendency to develop a pathway towards holistic and consistent care

A rapidly evolving picture was captured across the two phases of interviews, highlighting how LC integrated pathways were developed from initially highly specialised medical care (e.g., often centred around respiratory care) towards the provision of increasingly holistic support. In phase 1, two out of the four participants who reported having access to LC integrated care pathways, found that LC clinics tended to "apply existing medical models to a new illness", be "led by respiratory specialists", and "focus on 'clinically severe and visible' symptoms" (e.g., organ damage, lung issues). One of them, Lucy, called for a “One-Stop-Shop” for more integrated and holistic care:

“ A one-stop-shop where you can, say, ‘this is Long COVID, this is what people have experienced, this is what doctors can do, this is what they can’t do, this is what people have found helpful, this is what’s available’ would be really helpful. It just seems so random, what people are getting and aren’t getting .” (Female, White British, 50s, phase 1)

While acknowledging the heavily clinical focus of LC care pathways, practitioners also emphasised the evolving support for the holistic wellbeing of people with LC. In phase 1, a LC clinic coordinator reported the development of a comprehensive psychology-led course to empower patients to better identify their needs and manage their symptoms. Notably, there were further enhancements addressing existential needs during phase 2. A hierarchical framework of identity roles was adopted to address patients' awareness of identity loss and mortality to (re)develop a ‘flexible and resilient self’, assisting them in prioritising the recovery of their primary identity and well-being.

Improvements can also be observed in service providers' efforts to offer follow-up care that specifically addresses the fluctuating nature of LC symptoms. For instance, the previously mentioned care pathway coordinator discussed the potential for self-referral to the LC clinic. Similarly, a rehabilitation coordinator introduced their plan to implement "Patient-Initiated Follow-Ups" to empower patients to play a more active role in seeking specialised care consistently, while acknowledging their limited capacity:

“ What we’re just at the point of starting to offer are the Patient Initiated Follow-Ups, so once they’ve been through the groups that we feel have been appropriate and they’ve gone through them all once, it’s then about some sort of self-management and then offering them to see how you go on. If you feel you need to come back to us, you initiate another follow-up with us. But as I say, we’ve still got patients working through and we are not quite yet, but that’s our intention .” (Rehabilitation coordinator 1, phase 2)

Uncertainties in funding security

Positive changes in LC care pathways were indeed observed over the two 2021–2022 interview rounds. However, significant uncertainty lingered regarding funding sustainability for specialised care for this persistent condition. This uncertainty was not unique to LC specialised care but reflected broader NHS resource challenges, with stretched and fragmented resources10,25.

Healthcare professionals in region A voiced concerns about long-term funding. Almost half of them noted how funding constraints affected daily operations, service reach, capacity, and future planning for LC specialised services. A manager for specialised medicine highlighted the persistently limited availability of funding for expanding and even maintaining the services. In phase 1 in early 2022, she underscored the challenges of prioritising funding over the LC patients’ real needs, further creating a highly uncertain future for service provision:

“All these patients, that we’ve just talked about ending up within the community and getting referred back in, they’re not funded. We haven’t got any funding for increased activity related to Long COVID. We’ve got at the moment recovery money which means we can put on extra activity and have extra sessions for the consultants that can be funded. But long term it’s very difficult to predict how long this is going to go on for. We keep stopping and starting activity depending on spikes, so we don’t know what our backlog is going to look like and we don’t know what the long-term implications are going to be.” (Specialised medicine manager, phase 1)

In the second interview in late 2022, these situations had not improved and, in some cases, had deteriorated. Both this manager and other service providers highlighted the potential for long-term funding insecurity to disrupt LC specialised care in a multitude of ways, affecting staff retention, consistency and coordination:

“It’s much harder to recruit to temporary contracts and secondment, it’s destabilising for the service where you take the person from because it’s really hard for them to fill that vacancy… we are three separate Trusts working together and it’s quite complicated then because each Trust has their own policies and procedures that aren’t necessarily the same. Everyone still has a contract with one Trust and just follow those procedures from their Trust which might be different from their colleagues’ procedures. So those things are quite challenging.” (Service manager 1, phase 2)

The funding uncertainties prompted some creative approaches to sustain LC specialised care within the constrained financial parameters. Some practitioners disclosed plans to secure additional funding. Some other managers and commissioners also deliberated the possibility of integrating LC specialised care into existing post-viral/chronic illness pathways, aiming for more consistent and potentially comprehensive care (e.g., drawing lessons from other health conditions).

To sum up, healthcare is comprised of various systems, including primary (community), secondary, and specialised care. Theoretically specialised healthcare aligns well with the philosophy of person-centred care, as both emphasise the importance of tailoring treatment and care plans to meet patients' specific and holistic needs23. While the specialised pathways showed some improvements towards a more holistic approach to LC, significant gaps persist. These gaps hinder the integration of LC specialised care into the healthcare system to address LC's multifaceted and persistent nature effectively. These gaps primarily result from limited access to LC specialised care, driven by funding insecurity and subsequent workforce shortages, often intertwined with issues in primary and secondary care systems. This fragmentation was exemplified by the experience of Lucy (Female, White British, 50s), who initially received physical therapy from a LC clinic but faced discontinuation and challenges accessing follow-up support within primary and secondary care systems.

Our study reveals persistent challenges in seeking support within the UK healthcare system for PLwLC, leading to continued barriers, delays, and disruptions in accessing treatment and understanding their complex symptoms. This extends our prior work on healthcare access issues and the extensive impact of LC on PLwLC’s wellbeing10,31. It deepens our understandings of how the lingering struggles in the under-resourced and complex UK healthcare system may not only undermine PLwLC’s health needs but can also cause enduring disruptions to their identity as a holistic being.

Living with highly individualised LC conditions, our participants had to exert significant, and often repeated, efforts to access primary care (the gateway to the healthcare system). They also needed to demonstrate persistence and, at times, sheer determination in navigating the highly specialised and often inconsistent care provided through secondary care and LC specialist care pathways. While the study period between 2021–2022 revealed some practical and structural improvements (e.g., increased understanding from healthcare workers, provision of more holistic care), long-standing systemic issues, including limited access, a shortage of available treatments, and disconnections between these services, remained significant obstacles14. These obstacles further hindered many participants from accessing medical care for their distressing symptoms based on their desires and preferences. In essence, their fundamental needs for physical and emotional comfort as a person was not fully acknowledged and supported22. The insights into these multi-level issues also resonate with key actions outlined in the Long COVID: the NHS plan for 2021/22 to expand LC health support and equity through enhanced services and care coordination within and across primary and specialist care [ 32 ].

Capturing the voices of our participants facing ongoing struggles of “being turned away” and even “being abandoned” by health services, our study highlights the vital relational and existential dimensions of healthcare in the context of LC. For many, interacting with healthcare professionals was not merely about addressing physical symptoms, but also finding an accessible and trustworthy source to make sense of their suffering and adapt to their changed lives more generally. The persistent challenges in addressing relational needs within and across the various health systems were also closely linked to their longing for meaning to justify their existence in the face of their compromised health and with a fractured body. Lack of validation from healthcare and reassurance from practitioners could elevate the risk of existential encounters with meaninglessness, particularly a profound sense of anxiety being disconnected from both their once-familiar past and their greatly uncertain future31. These multifaceted and deeply painful struggles affirm the NHS plan for improving long COVID services , aiming to enhance healthcare capacity and prioritise holistic and continuous care for PLwLC in a more interdisciplinary and inter-systematic manner12.

Our findings also further expand on the scope of person-centredness in healthcare, moving beyond individual perspectives of dignity, choice, and autonomy to emphasise a more relational approach that situates individuals' healthcare needs within a rich matrix of relationships and socio-cultural beliefs [ 33 , 34 ]. The evolving concept of person-centred care now places a greater emphasis on its holistic nature. This calls for a thorough consideration of each patient's unique experiences, acknowledging and supporting their life histories, social contexts, and the relationships that matter to them34. It also emphasises the importance of preserving and respecting patients’ cherished personhood, thereby preventing any unintentional harm to these esteemed facets of their existence.

This holistic perspective is particularly relevant to our study as our participants shared their experience of feeling that they had lost part, if not all, of themselves as a person to their complex and persistent symptoms31. Considering the extended and often unpredictable illness trajectories associated with LC, failing to provide person-centred healthcare could pose a substantial challenge to PLwLC’s ability to alleviate clinical distress and, more importantly, to find meaning in enduring suffering. Essentially, our study highlights the pressing need for person-centred care in managing chronic illnesses like LC, especially in the absence of immediate and efficient treatments. To truly support individuals in their health journeys, healthcare for LC should holistically address their multifaceted and interconnected needs, ensuring a consistent sense of identity. As such, our findings underscore the practical importance of person-centred healthcare in assisting PLwLC to gain security, understanding, and the ability to live with their health conditions as an integral part of their ongoing lives.

By examining the healthcare needs of our participants across primary, secondary, and specialised care pathways, our study enhances the holistic nature of person-centred care at a structural level. LC, along with the broader challenges posed by the COVID-19 pandemic, has exacerbated the conflicting priorities between individual care and public health interests9. Our findings regarding the fragmentation and inconsistency in care highlight the conceptual and empirical significance of incorporating a comprehensive approach to healthcare structures to ensure person-centred care23. As strongly voiced by PLwLC, their healthcare struggles often went beyond a single health system and were encountered across various provisions. The narratives shared by healthcare professionals reveal both macro systemic issues (e.g., funding supply, design and priorities of health services at different levels) and micro structural barriers (e.g., lack of inter-organisational cooperation) that impede holistic care provision to PLwLC. To better view PLwLC as a whole and living person, it is essential to bridge the gaps and inconsistencies within and across various healthcare systems. This extends beyond LC healthcare to other chronic conditions, such as chronic fatigue syndrome. Existing literature on chronic illness has highlighted empowerment as a key approach to ensure consistent holistic care for patients [ 35 ]. Building upon this, our findings suggest the significance of further integrating patients into and across different health systems for stable (e.g., funding and workforce security), continuing (e.g., consistency in care) and flexible (e.g., training and understanding) care to address PLwLC’s needs and identity through a more person centred lens.

Finally, the longitudinal focus of our study captures both the evolving healthcare needs of our participants and the importance/challenges of aligning healthcare infrastructures to address these changes. Methodologically, we generated a rich set of qualitative data spanning across 2021–22, providing insights into the fluidity of individual healthcare needs, broader health systems and also the relationships between them28. Our research method, designed to track changes over time, has made substantial contributions on two fronts. Conceptually, it has greatly expanded our comprehension of the evolving healthcare needs of individuals, exposing the often complex (e.g., changing or increasing) intersections between conditions like LC and other health issues. This underscores the imperative nature of adopting a holistic and person-centred approach to care, one that recognises the interconnectedness of various health dimensions, both concurrently, across different aspects of life and longitudinally over time. On a practical level, our study has underscored the critical necessity for healthcare providers to regularly review and adapt care plans to accommodate these dynamic shifts in patient needs. This highlights the vital importance of flexibility and responsiveness in healthcare strategies, particularly in chronic illness management.

Limitations and implications

While our study offers valuable insights into the challenges and complexities of person-centred healthcare for LC, there are several limitations to consider. Firstly, limited information was reported by our participants on LC community-based care, such as physiotherapy and rehabilitation services, as well as tertiary care. These areas require further exploration to comprehensively address the diverse healthcare needs of LC suffers. Secondly, our study's focus on healthcare professionals in region A may not fully represent the healthcare experiences and developments in other geographic locations, warranting future research in more diverse settings. Additionally, whilst we engaged with a socio-economically and ethnically diverse sample, the absence of Black minority participants in our study highlights the further need for research that captures the unique healthcare experiences within this group and beyond. Lastly, our study generated rich data, underscoring the importance of future research to further explore the multifaceted challenges and opportunities in person-centred care for LC and to potentially extend these findings to inform care for other chronic conditions.

Availability of data and materials

The data that support the findings of this study are available on request from the corresponding author. The data will be submitted to the UK Data Service following the completion of the CONVALESCENCE study.

Abbreviations

General Practitioner

National Health Service

Office for National Statistics

People Living with Long COVID

United Kingdom

Office for National Statistics. Technical article: Updated estimates of the prevalence of post-acute symptoms among people with coronavirus (COVID-19) in the UK: 26 April 2020 to 1 August 2021. London: Office for National Statistics; 2021. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/articles/technicalarticleupdatedestimatesoftheprevalenceofpostacutesymptomsamongpeoplewithcoronaviruscovid19intheuk/26april2020to1august2021

Office for National Statistics. Prevalence of ongoing symptoms following coronavirus (COVID-19) infection in the UK: 30 March 2023. London: Office for National Statistics; 2022. https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/conditionsanddiseases/bulletins/prevalenceofongoingsymptomsfollowingcoronaviruscovid19infectionintheuk/30march2023

Lopez-Leon S, Wegman-Ostrosky T, Perelman C, et al. More than 50 long-term effects of COVID-19: a systematic review and meta-analysis. Sci Rep. 2021;11:16144. https://doi.org/10.1038/s41598-021-95565-8 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Taylor AK, Kingstone T, Briggs TA, et al. “Reluctant pioneer”: A qualitative study of doctors’ experiences as patients with long COVID. Health Expect. 2021;24:833–42. https://doi.org/10.1111/hex.13223 .

Article   PubMed   PubMed Central   Google Scholar  

Moynihan R, Sanders S, Michaleff ZA, et al. Impact of COVID-19 pandemic on utilisation of healthcare services: a systematic review. BMJ Open. 2021;11: e045343. https://doi.org/10.1136/bmjopen-2020-045343 .

Article   PubMed   Google Scholar  

Kingstone T, Taylor AK, O’Donnell CA, Atherton H, Blane DN, Chew-Graham CA. Finding the “right” GP: a qualitative study of the experiences of people with long-COVID. BJGP Open. 2020;4(5):bjgpopen20X101143. https://doi.org/10.3399/bjgpopen20X101143 .

Ladds E, Rushforth A, Wieringa S, et al. Persistent symptoms after Covid-19: qualitative study of 114 “long Covid” patients and draft quality principles for services. BMC Health Serv Res. 2020;20:1144. https://doi.org/10.1186/s12913-020-06001-y .

Ireson J, Taylor A, Richardson E, Greenfield B, Jones G. Exploring invisibility and epistemic injustice in Long Covid-A citizen science qualitative analysis of patient stories from an online Covid community. Health Expect. 2022;25(4):1753–65. https://doi.org/10.1111/hex.13518 .

Wolf S, Zechmeister-Koss I, Erdös J. Possible long COVID healthcare pathways: a scoping review. BMC Health Serv Res. 2022;22:1076. https://doi.org/10.1186/s12913-022-08384-6 .

Baz SA, Fang C, Carpentieri JD, Sheard L. ‘I don’t know what to do or where to go’. Experiences of accessing healthcare support from the perspectives of people living with Long Covid and healthcare professionals: a qualitative study in Bradford, UK. Health Expect. 2023;26:542–54. https://doi.org/10.1111/hex.13687 .

Maxwell E. Living with COVID-19. A dynamic review of the evidence around ongoing COVID-19 symptoms (often called long covid). Natl Inst Health Res. 2020;31:197–200. https://doi.org/10.3310/themedreview_41169 .

Article   Google Scholar  

NHS England. The NHS plan for improving long COVID services. London: NHS; 2022. https://www.england.nhs.uk/wp-content/uploads/2022/07/C1607_The-NHS-plan-for-improving-long-COVID-services_July-2022.pdf

Dean E. What happens inside a long covid clinic? BMJ. 2023;382:1791. https://doi.org/10.1136/bmj.p1791 .

Bambra C, Lynch J, Smith KE. The Unequal Pandemic: COVID-19 and Health Inequalities. Bristol UK: Policy Press; 2021.

Book   Google Scholar  

Ladds E, Rushforth A, Wieringa S, et al. Developing services for long COVID: lessons from a study of wounded healers. Clin Med (Lond). 2021;21(1):59–65. https://doi.org/10.7861/clinmed.2020-0962 .

Maclean A, Hunt K, et al. Negotiation of collective and individual candidacy for long Covid healthcare in the early phases of the Covid-19 pandemic: Validated, diverted and rejected candidacy. SSM Qualitative research in health. 2023;3: 100207. https://doi.org/10.1016/j.ssmqr.2022.100207 .

Rushforth A, Ladds E, Wieringa S, Taylor S, Husain L, Greenhalgh T. Long Covid - The illness narratives. Soc Sci Med. 2021;286:114326. https://doi.org/10.1016/j.socscimed.2021.114326 .

Wang Y, Bao S, Chen Y. The Illness Experience of Long COVID Patients: A Qualitative Study Based on the Online Q&A Community Zhihu. Int J Environ Res Public Health. 2022;19(16):9827. https://doi.org/10.3390/ijerph19169827 .

Thomas K, Gray SM. Population-based, person-centred end-of-life care: time for a rethink. Br J Gen Pract. 2018;68(668):116–7. https://doi.org/10.3399/bjgp18X694925 .

Coulter A, Oldham J. Person-centred care: what is it and how do we get there? Future Hosp J. 2016;3(2):114–6. https://doi.org/10.7861/futurehosp.3-2-114 .

Anderson M, Pitchforth E, Edwards N, Alderwick H, McGuire A, Mossialos E. United Kingdom: Health System Review. Health Syst Transit. 2022;24(1):1–194.

PubMed   Google Scholar  

Entwistle V, Watt I. Treating patients as persons: a capabilities approach to support delivery of person-centered care. Am J Bioeth. 2013;13(8):29–39.

NHS Health Education England. Person-Centred Approaches: Empowering people in their lives and communities to enable an upgrade in prevention, wellbeing, health, care and support. 2017. https://www.skillsforhealth.org.uk/images/pdf/Person-Centred-Approaches-Framework.pdf?s=form#:~:text=A%20person%2Dcentred%20approach%20puts,of%20what%20matters%20to%20people .

Fang C, Tanaka M. An exploration of person-centred approach in end-of-life care policies in England and Japan. BMC Palliat Care. 2022;21:68. https://doi.org/10.1186/s12904-022-00965-w .

Curnow E, Tyagi V, Salisbury L, et al. Person-Centered Healthcare Practice in a Pandemic Context: An Exploration of People’s Experience of Seeking Healthcare Support. Front Rehabil Sci. 2021;2: 726210. https://doi.org/10.3389/fresc.2021.726210 .

Lockyer B, Islam S, Rahman A, et al. Understanding COVID-19 misinformation and vaccine hesitancy in context: Findings from a qualitative study involving citizens in Bradford. UK Health Expect. 2021;24(4):1158–67. https://doi.org/10.1111/hex.13240 .

NHS England. Long COVID patients to get help at more than 60 clinics. https://www.england.nhs.uk/2020/12/long-covid-patients-to-get-help-at-more-than-60-clinics/

Neale B, Flowerdew J. Time, texture and childhood: The contours of longitudinal qualitative research. Int J Soc Res Methodol. 2003;6(3):189–99. https://doi.org/10.1080/1364557032000091798 .

Saldaña J. Longitudinal qualitative research: Analyzing change through time. Walnut Creet, California: Rowman Altamira; 2003.

Google Scholar  

Greenhalgh T, Sivan M, et al. Long covid—an update for primary care. BMJ. 2022;378:e072117. https://doi.org/10.1136/bmj-2022-072117 .

Fang C, Baz SA, Sheard L, Carpentieri J. ‘I am just a shadow of who I used to be’—Exploring existential loss of identity among people living with chronic conditions of Long COVID. Sociol Health Illn. 2023;46(1):59–77. https://doi.org/10.1111/1467-9566.13690 .

NHS England. Long COVID: the NHS plan for 2021/22. 2022. https://www.england.nhs.uk/coronavirus/wp-content/uploads/sites/52/2021/06/C1312-long-covid-plan-june-2021.pdf

Pringle Jan, et al. Dignity and patient-centred care for people with palliative care needs in the acute hospital setting: A systematic review. Palliat Med. 2015;29(8):675–94.

Nolan M, Davies S, et al. Beyond ‘person-centred’care: a new vision for gerontological nursing. J Clin Nurs. 2004;13:45–53.

Stepanian N, Larsen MH, Mendelsohn JB, et al. Empowerment interventions designed for persons living with chronic disease - a systematic review and meta-analysis of the components and efficacy of format on patient-reported outcomes. BMC Health Serv Res. 2023;23:911. https://doi.org/10.1186/s12913-023-09895-6- .

Download references

Acknowledgements

We would like to acknowledge the following people and organisations for their kind support of this project: (1) the 80 participants who kindly shared their thoughts, feelings and experiences with us, (2) the Centre for Longitudinal Studies at University College London (who manage the five UK national cohort studies), (3) the region A cohort study maintenance team and researchers who supported the study and recruitment process, (4) Professor Nishi Chaturvedi who is the Principal Investigator of the broader CONVALESCENCE Long COVID study.

Characterisation, determinants, mechanisms and consequences of the long-term effects of COVID-19: providing the evidence base for health care services (CONVALESCENCE) was funded by NIHR (COV-LT-0009) and UKRI (MC_PC_20051). This research team is working on the Qualitative component of the work package, a qualitative longitudinal study.

Author information

Authors and affiliations.

Department of Sociology, Social Policy and Criminology, University of Liverpool, Liverpool, UK

Department of Health Sciences, University of York, York, UK

Sarah Akhtar Baz & Laura Sheard

Department of Education, Practice and Society, Institute of Education, University College London, London, UK

J. D. Carpentieri

You can also search for this author in PubMed   Google Scholar

Contributions

All four authors contributed to the conceptualisation and design of this article. CF developed and drafted the overall structure of the article. SB contributed to data collection and analysis. SB, LS, and JC reviewed the manuscript. All authors approved the final version to be submitted for publication.

Corresponding author

Correspondence to Chao Fang .

Ethics declarations

Ethics approval and consent to participate.

This study has been ethically reviewed and approved by University College London Institute of Education Research Ethics Committee (ref: REC 1554) and University of York Health Sciences Research Governance Committee (ref: HSRGC/2021/466/B). We have also received permission from the participating cohort studies to conduct this study with their cohort members. All participants provided their informed consent prior to data collection and were informed that their anonymised data will be used in publications. The study was conducted according to the guidelines of the Declaration of Helsinki.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary material 1., supplementary material 2., supplementary material 3., supplementary material 4., rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Fang, C., Baz, S.A., Sheard, L. et al. “They seemed to be like cogs working in different directions”: a longitudinal qualitative study on Long COVID healthcare services in the United Kingdom from a person-centred lens. BMC Health Serv Res 24 , 406 (2024). https://doi.org/10.1186/s12913-024-10891-7

Download citation

Received : 17 November 2023

Accepted : 22 March 2024

Published : 01 April 2024

DOI : https://doi.org/10.1186/s12913-024-10891-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Chronic illness
• Person-centred care
• Health services
• Longitudinal
• Qualitative

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List

What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

2 Seminar for Sociology, Universität St. Gallen, St. Gallen, Switzerland

3 Department of Media and Social Sciences, University of Stavanger, Stavanger, Norway

What is qualitative research? If we look for a precise definition of qualitative research, and specifically for one that addresses its distinctive feature of being “qualitative,” the literature is meager. In this article we systematically search, identify and analyze a sample of 89 sources using or attempting to define the term “qualitative.” Then, drawing on ideas we find scattered across existing work, and based on Becker’s classic study of marijuana consumption, we formulate and illustrate a definition that tries to capture its core elements. We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. This formulation is developed as a tool to help improve research designs while stressing that a qualitative dimension is present in quantitative work as well. Additionally, it can facilitate teaching, communication between researchers, diminish the gap between qualitative and quantitative researchers, help to address critiques of qualitative methods, and be used as a standard of evaluation of qualitative research.

If we assume that there is something called qualitative research, what exactly is this qualitative feature? And how could we evaluate qualitative research as good or not? Is it fundamentally different from quantitative research? In practice, most active qualitative researchers working with empirical material intuitively know what is involved in doing qualitative research, yet perhaps surprisingly, a clear definition addressing its key feature is still missing.

To address the question of what is qualitative we turn to the accounts of “qualitative research” in textbooks and also in empirical work. In his classic, explorative, interview study of deviance Howard Becker ( 1963 ) asks ‘How does one become a marijuana user?’ In contrast to pre-dispositional and psychological-individualistic theories of deviant behavior, Becker’s inherently social explanation contends that becoming a user of this substance is the result of a three-phase sequential learning process. First, potential users need to learn how to smoke it properly to produce the “correct” effects. If not, they are likely to stop experimenting with it. Second, they need to discover the effects associated with it; in other words, to get “high,” individuals not only have to experience what the drug does, but also to become aware that those sensations are related to using it. Third, they require learning to savor the feelings related to its consumption – to develop an acquired taste. Becker, who played music himself, gets close to the phenomenon by observing, taking part, and by talking to people consuming the drug: “half of the fifty interviews were conducted with musicians, the other half covered a wide range of people, including laborers, machinists, and people in the professions” (Becker 1963 :56).

Another central aspect derived through the common-to-all-research interplay between induction and deduction (Becker 2017 ), is that during the course of his research Becker adds scientifically meaningful new distinctions in the form of three phases—distinctions, or findings if you will, that strongly affect the course of his research: its focus, the material that he collects, and which eventually impact his findings. Each phase typically unfolds through social interaction, and often with input from experienced users in “a sequence of social experiences during which the person acquires a conception of the meaning of the behavior, and perceptions and judgments of objects and situations, all of which make the activity possible and desirable” (Becker 1963 :235). In this study the increased understanding of smoking dope is a result of a combination of the meaning of the actors, and the conceptual distinctions that Becker introduces based on the views expressed by his respondents. Understanding is the result of research and is due to an iterative process in which data, concepts and evidence are connected with one another (Becker 2017 ).

Indeed, there are many definitions of qualitative research, but if we look for a definition that addresses its distinctive feature of being “qualitative,” the literature across the broad field of social science is meager. The main reason behind this article lies in the paradox, which, to put it bluntly, is that researchers act as if they know what it is, but they cannot formulate a coherent definition. Sociologists and others will of course continue to conduct good studies that show the relevance and value of qualitative research addressing scientific and practical problems in society. However, our paper is grounded in the idea that providing a clear definition will help us improve the work that we do. Among researchers who practice qualitative research there is clearly much knowledge. We suggest that a definition makes this knowledge more explicit. If the first rationale for writing this paper refers to the “internal” aim of improving qualitative research, the second refers to the increased “external” pressure that especially many qualitative researchers feel; pressure that comes both from society as well as from other scientific approaches. There is a strong core in qualitative research, and leading researchers tend to agree on what it is and how it is done. Our critique is not directed at the practice of qualitative research, but we do claim that the type of systematic work we do has not yet been done, and that it is useful to improve the field and its status in relation to quantitative research.

The literature on the “internal” aim of improving, or at least clarifying qualitative research is large, and we do not claim to be the first to notice the vagueness of the term “qualitative” (Strauss and Corbin 1998 ). Also, others have noted that there is no single definition of it (Long and Godfrey 2004 :182), that there are many different views on qualitative research (Denzin and Lincoln 2003 :11; Jovanović 2011 :3), and that more generally, we need to define its meaning (Best 2004 :54). Strauss and Corbin ( 1998 ), for example, as well as Nelson et al. (1992:2 cited in Denzin and Lincoln 2003 :11), and Flick ( 2007 :ix–x), have recognized that the term is problematic: “Actually, the term ‘qualitative research’ is confusing because it can mean different things to different people” (Strauss and Corbin 1998 :10–11). Hammersley has discussed the possibility of addressing the problem, but states that “the task of providing an account of the distinctive features of qualitative research is far from straightforward” ( 2013 :2). This confusion, as he has recently further argued (Hammersley 2018 ), is also salient in relation to ethnography where different philosophical and methodological approaches lead to a lack of agreement about what it means.

Others (e.g. Hammersley 2018 ; Fine and Hancock 2017 ) have also identified the treat to qualitative research that comes from external forces, seen from the point of view of “qualitative research.” This threat can be further divided into that which comes from inside academia, such as the critique voiced by “quantitative research” and outside of academia, including, for example, New Public Management. Hammersley ( 2018 ), zooming in on one type of qualitative research, ethnography, has argued that it is under treat. Similarly to Fine ( 2003 ), and before him Gans ( 1999 ), he writes that ethnography’ has acquired a range of meanings, and comes in many different versions, these often reflecting sharply divergent epistemological orientations. And already more than twenty years ago while reviewing Denzin and Lincoln’ s Handbook of Qualitative Methods Fine argued:

While this increasing centrality [of qualitative research] might lead one to believe that consensual standards have developed, this belief would be misleading. As the methodology becomes more widely accepted, querulous challengers have raised fundamental questions that collectively have undercut the traditional models of how qualitative research is to be fashioned and presented (1995:417).

According to Hammersley, there are today “serious treats to the practice of ethnographic work, on almost any definition” ( 2018 :1). He lists five external treats: (1) that social research must be accountable and able to show its impact on society; (2) the current emphasis on “big data” and the emphasis on quantitative data and evidence; (3) the labor market pressure in academia that leaves less time for fieldwork (see also Fine and Hancock 2017 ); (4) problems of access to fields; and (5) the increased ethical scrutiny of projects, to which ethnography is particularly exposed. Hammersley discusses some more or less insufficient existing definitions of ethnography.

The current situation, as Hammersley and others note—and in relation not only to ethnography but also qualitative research in general, and as our empirical study shows—is not just unsatisfactory, it may even be harmful for the entire field of qualitative research, and does not help social science at large. We suggest that the lack of clarity of qualitative research is a real problem that must be addressed.

Towards a Definition of Qualitative Research

Seen in an historical light, what is today called qualitative, or sometimes ethnographic, interpretative research – or a number of other terms – has more or less always existed. At the time the founders of sociology – Simmel, Weber, Durkheim and, before them, Marx – were writing, and during the era of the Methodenstreit (“dispute about methods”) in which the German historical school emphasized scientific methods (cf. Swedberg 1990 ), we can at least speak of qualitative forerunners.

Perhaps the most extended discussion of what later became known as qualitative methods in a classic work is Bronisław Malinowski’s ( 1922 ) Argonauts in the Western Pacific , although even this study does not explicitly address the meaning of “qualitative.” In Weber’s ([1921–-22] 1978) work we find a tension between scientific explanations that are based on observation and quantification and interpretative research (see also Lazarsfeld and Barton 1982 ).

If we look through major sociology journals like the American Sociological Review , American Journal of Sociology , or Social Forces we will not find the term qualitative sociology before the 1970s. And certainly before then much of what we consider qualitative classics in sociology, like Becker’ study ( 1963 ), had already been produced. Indeed, the Chicago School often combined qualitative and quantitative data within the same study (Fine 1995 ). Our point being that before a disciplinary self-awareness the term quantitative preceded qualitative, and the articulation of the former was a political move to claim scientific status (Denzin and Lincoln 2005 ). In the US the World War II seem to have sparked a critique of sociological work, including “qualitative work,” that did not follow the scientific canon (Rawls 2018 ), which was underpinned by a scientifically oriented and value free philosophy of science. As a result the attempts and practice of integrating qualitative and quantitative sociology at Chicago lost ground to sociology that was more oriented to surveys and quantitative work at Columbia under Merton-Lazarsfeld. The quantitative tradition was also able to present textbooks (Lundberg 1951 ) that facilitated the use this approach and its “methods.” The practices of the qualitative tradition, by and large, remained tacit or was part of the mentoring transferred from the renowned masters to their students.

This glimpse into history leads us back to the lack of a coherent account condensed in a definition of qualitative research. Many of the attempts to define the term do not meet the requirements of a proper definition: A definition should be clear, avoid tautology, demarcate its domain in relation to the environment, and ideally only use words in its definiens that themselves are not in need of definition (Hempel 1966 ). A definition can enhance precision and thus clarity by identifying the core of the phenomenon. Preferably, a definition should be short. The typical definition we have found, however, is an ostensive definition, which indicates what qualitative research is about without informing us about what it actually is :

Qualitative research 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)

Flick claims that the label “qualitative research” is indeed used as an umbrella for a number of approaches ( 2007 :2–4; 2002 :6), and it is not difficult to identify research fitting this designation. Moreover, whatever it is, it has grown dramatically over the past five decades. In addition, courses have been developed, methods have flourished, arguments about its future have been advanced (for example, Denzin and Lincoln 1994) and criticized (for example, Snow and Morrill 1995 ), and dedicated journals and books have mushroomed. Most social scientists have a clear idea of research and how it differs from journalism, politics and other activities. But the question of what is qualitative in qualitative research is either eluded or eschewed.

We maintain that this lacuna hinders systematic knowledge production based on qualitative research. Paul Lazarsfeld noted the lack of “codification” as early as 1955 when he reviewed 100 qualitative studies in order to offer a codification of the practices (Lazarsfeld and Barton 1982 :239). Since then many texts on “qualitative research” and its methods have been published, including recent attempts (Goertz and Mahoney 2012 ) similar to Lazarsfeld’s. These studies have tried to extract what is qualitative by looking at the large number of empirical “qualitative” studies. Our novel strategy complements these endeavors by taking another approach and looking at the attempts to codify these practices in the form of a definition, as well as to a minor extent take Becker’s study as an exemplar of what qualitative researchers actually do, and what the characteristic of being ‘qualitative’ denotes and implies. We claim that qualitative researchers, if there is such a thing as “qualitative research,” should be able to codify their practices in a condensed, yet general way expressed in language.

Lingering problems of “generalizability” and “how many cases do I need” (Small 2009 ) are blocking advancement – in this line of work qualitative approaches are said to differ considerably from quantitative ones, while some of the former unsuccessfully mimic principles related to the latter (Small 2009 ). Additionally, quantitative researchers sometimes unfairly criticize the first based on their own quality criteria. Scholars like Goertz and Mahoney ( 2012 ) have successfully focused on the different norms and practices beyond what they argue are essentially two different cultures: those working with either qualitative or quantitative methods. Instead, similarly to Becker ( 2017 ) who has recently questioned the usefulness of the distinction between qualitative and quantitative research, we focus on similarities.

The current situation also impedes both students and researchers in focusing their studies and understanding each other’s work (Lazarsfeld and Barton 1982 :239). A third consequence is providing an opening for critiques by scholars operating within different traditions (Valsiner 2000 :101). A fourth issue is that the “implicit use of methods in qualitative research makes the field far less standardized than the quantitative paradigm” (Goertz and Mahoney 2012 :9). Relatedly, the National Science Foundation in the US organized two workshops in 2004 and 2005 to address the scientific foundations of qualitative research involving strategies to improve it and to develop standards of evaluation in qualitative research. However, a specific focus on its distinguishing feature of being “qualitative” while being implicitly acknowledged, was discussed only briefly (for example, Best 2004 ).

In 2014 a theme issue was published in this journal on “Methods, Materials, and Meanings: Designing Cultural Analysis,” discussing central issues in (cultural) qualitative research (Berezin 2014 ; Biernacki 2014 ; Glaeser 2014 ; Lamont and Swidler 2014 ; Spillman 2014). We agree with many of the arguments put forward, such as the risk of methodological tribalism, and that we should not waste energy on debating methods separated from research questions. Nonetheless, a clarification of the relation to what is called “quantitative research” is of outmost importance to avoid misunderstandings and misguided debates between “qualitative” and “quantitative” researchers. Our strategy means that researchers, “qualitative” or “quantitative” they may be, in their actual practice may combine qualitative work and quantitative work.

In this article we accomplish three tasks. First, we systematically survey the literature for meanings of qualitative research by looking at how researchers have defined it. Drawing upon existing knowledge we find that the different meanings and ideas of qualitative research are not yet coherently integrated into one satisfactory definition. Next, we advance our contribution by offering a definition of qualitative research and illustrate its meaning and use partially by expanding on the brief example introduced earlier related to Becker’s work ( 1963 ). We offer a systematic analysis of central themes of what researchers consider to be the core of “qualitative,” regardless of style of work. These themes – which we summarize in terms of four keywords: distinction, process, closeness, improved understanding – constitute part of our literature review, in which each one appears, sometimes with others, but never all in the same definition. They serve as the foundation of our contribution. Our categories are overlapping. Their use is primarily to organize the large amount of definitions we have identified and analyzed, and not necessarily to draw a clear distinction between them. Finally, we continue the elaboration discussed above on the advantages of a clear definition of qualitative research.

In a hermeneutic fashion we propose that there is something meaningful that deserves to be labelled “qualitative research” (Gadamer 1990 ). To approach the question “What is qualitative in qualitative research?” we have surveyed the literature. In conducting our survey we first traced the word’s etymology in dictionaries, encyclopedias, handbooks of the social sciences and of methods and textbooks, mainly in English, which is common to methodology courses. It should be noted that we have zoomed in on sociology and its literature. This discipline has been the site of the largest debate and development of methods that can be called “qualitative,” which suggests that this field should be examined in great detail.

In an ideal situation we should expect that one good definition, or at least some common ideas, would have emerged over the years. This common core of qualitative research should be so accepted that it would appear in at least some textbooks. Since this is not what we found, we decided to pursue an inductive approach to capture maximal variation in the field of qualitative research; we searched in a selection of handbooks, textbooks, book chapters, and books, to which we added the analysis of journal articles. Our sample comprises a total of 89 references.

In practice we focused on the discipline that has had a clear discussion of methods, namely sociology. We also conducted a broad search in the JSTOR database to identify scholarly sociology articles published between 1998 and 2017 in English with a focus on defining or explaining qualitative research. We specifically zoom in on this time frame because we would have expect that this more mature period would have produced clear discussions on the meaning of qualitative research. To find these articles we combined a number of keywords to search the content and/or the title: qualitative (which was always included), definition, empirical, research, methodology, studies, fieldwork, interview and observation .

As a second phase of our research we searched within nine major sociological journals ( American Journal of Sociology , Sociological Theory , American Sociological Review , Contemporary Sociology , Sociological Forum , Sociological Theory , Qualitative Research , Qualitative Sociology and Qualitative Sociology Review ) for articles also published during the past 19 years (1998–2017) that had the term “qualitative” in the title and attempted to define qualitative research.

Lastly we picked two additional journals, Qualitative Research and Qualitative Sociology , in which we could expect to find texts addressing the notion of “qualitative.” From Qualitative Research we chose Volume 14, Issue 6, December 2014, and from Qualitative Sociology we chose Volume 36, Issue 2, June 2017. Within each of these we selected the first article; then we picked the second article of three prior issues. Again we went back another three issues and investigated article number three. Finally we went back another three issues and perused article number four. This selection criteria was used to get a manageable sample for the analysis.

The coding process of the 89 references we gathered in our selected review began soon after the first round of material was gathered, and we reduced the complexity created by our maximum variation sampling (Snow and Anderson 1993 :22) to four different categories within which questions on the nature and properties of qualitative research were discussed. We call them: Qualitative and Quantitative Research, Qualitative Research, Fieldwork, and Grounded Theory. This – which may appear as an illogical grouping – merely reflects the “context” in which the matter of “qualitative” is discussed. If the selection process of the material – books and articles – was informed by pre-knowledge, we used an inductive strategy to code the material. When studying our material, we identified four central notions related to “qualitative” that appear in various combinations in the literature which indicate what is the core of qualitative research. We have labeled them: “distinctions”, “process,” “closeness,” and “improved understanding.” During the research process the categories and notions were improved, refined, changed, and reordered. The coding ended when a sense of saturation in the material arose. In the presentation below all quotations and references come from our empirical material of texts on qualitative research.

Analysis – What is Qualitative Research?

In this section we describe the four categories we identified in the coding, how they differently discuss qualitative research, as well as their overall content. Some salient quotations are selected to represent the type of text sorted under each of the four categories. What we present are examples from the literature.

Qualitative and Quantitative

This analytic category comprises quotations comparing qualitative and quantitative research, a distinction that is frequently used (Brown 2010 :231); in effect this is a conceptual pair that structures the discussion and that may be associated with opposing interests. While the general goal of quantitative and qualitative research is the same – to understand the world better – their methodologies and focus in certain respects differ substantially (Becker 1966 :55). Quantity refers to that property of something that can be determined by measurement. In a dictionary of Statistics and Methodology we find that “(a) When referring to *variables, ‘qualitative’ is another term for *categorical or *nominal. (b) When speaking of kinds of research, ‘qualitative’ refers to studies of subjects that are hard to quantify, such as art history. Qualitative research tends to be a residual category for almost any kind of non-quantitative research” (Stiles 1998:183). But it should be obvious that one could employ a quantitative approach when studying, for example, art history.

The same dictionary states that quantitative is “said of variables or research that can be handled numerically, usually (too sharply) contrasted with *qualitative variables and research” (Stiles 1998:184). From a qualitative perspective “quantitative research” is about numbers and counting, and from a quantitative perspective qualitative research is everything that is not about numbers. But this does not say much about what is “qualitative.” If we turn to encyclopedias we find that in the 1932 edition of the Encyclopedia of the Social Sciences there is no mention of “qualitative.” In the Encyclopedia from 1968 we can read:

Qualitative Analysis. For methods of obtaining, analyzing, and describing data, see [the various entries:] CONTENT ANALYSIS; COUNTED DATA; EVALUATION RESEARCH, FIELD WORK; GRAPHIC PRESENTATION; HISTORIOGRAPHY, especially the article on THE RHETORIC OF HISTORY; INTERVIEWING; OBSERVATION; PERSONALITY MEASUREMENT; PROJECTIVE METHODS; PSYCHOANALYSIS, article on EXPERIMENTAL METHODS; SURVEY ANALYSIS, TABULAR PRESENTATION; TYPOLOGIES. (Vol. 13:225)

Some, like Alford, divide researchers into methodologists or, in his words, “quantitative and qualitative specialists” (Alford 1998 :12). Qualitative research uses a variety of methods, such as intensive interviews or in-depth analysis of historical materials, and it is concerned with a comprehensive account of some event or unit (King et al. 1994 :4). Like quantitative research it can be utilized to study a variety of issues, but it tends to focus on meanings and motivations that underlie cultural symbols, personal experiences, phenomena and detailed understanding of processes in the social world. In short, qualitative research centers on understanding processes, experiences, and the meanings people assign to things (Kalof et al. 2008 :79).

Others simply say that qualitative methods are inherently unscientific (Jovanović 2011 :19). Hood, for instance, argues that words are intrinsically less precise than numbers, and that they are therefore more prone to subjective analysis, leading to biased results (Hood 2006 :219). Qualitative methodologies have raised concerns over the limitations of quantitative templates (Brady et al. 2004 :4). Scholars such as King et al. ( 1994 ), for instance, argue that non-statistical research can produce more reliable results if researchers pay attention to the rules of scientific inference commonly stated in quantitative research. Also, researchers such as Becker ( 1966 :59; 1970 :42–43) have asserted that, if conducted properly, qualitative research and in particular ethnographic field methods, can lead to more accurate results than quantitative studies, in particular, survey research and laboratory experiments.

Some researchers, such as Kalof, Dan, and Dietz ( 2008 :79) claim that the boundaries between the two approaches are becoming blurred, and Small ( 2009 ) argues that currently much qualitative research (especially in North America) tries unsuccessfully and unnecessarily to emulate quantitative standards. For others, qualitative research tends to be more humanistic and discursive (King et al. 1994 :4). Ragin ( 1994 ), and similarly also Becker, ( 1996 :53), Marchel and Owens ( 2007 :303) think that the main distinction between the two styles is overstated and does not rest on the simple dichotomy of “numbers versus words” (Ragin 1994 :xii). Some claim that quantitative data can be utilized to discover associations, but in order to unveil cause and effect a complex research design involving the use of qualitative approaches needs to be devised (Gilbert 2009 :35). Consequently, qualitative data are useful for understanding the nuances lying beyond those processes as they unfold (Gilbert 2009 :35). Others contend that qualitative research is particularly well suited both to identify causality and to uncover fine descriptive distinctions (Fine and Hallett 2014 ; Lichterman and Isaac Reed 2014 ; Katz 2015 ).

There are other ways to separate these two traditions, including normative statements about what qualitative research should be (that is, better or worse than quantitative approaches, concerned with scientific approaches to societal change or vice versa; Snow and Morrill 1995 ; Denzin and Lincoln 2005 ), or whether it should develop falsifiable statements; Best 2004 ).

We propose that quantitative research is largely concerned with pre-determined variables (Small 2008 ); the analysis concerns the relations between variables. These categories are primarily not questioned in the study, only their frequency or degree, or the correlations between them (cf. Franzosi 2016 ). If a researcher studies wage differences between women and men, he or she works with given categories: x number of men are compared with y number of women, with a certain wage attributed to each person. The idea is not to move beyond the given categories of wage, men and women; they are the starting point as well as the end point, and undergo no “qualitative change.” Qualitative research, in contrast, investigates relations between categories that are themselves subject to change in the research process. Returning to Becker’s study ( 1963 ), we see that he questioned pre-dispositional theories of deviant behavior working with pre-determined variables such as an individual’s combination of personal qualities or emotional problems. His take, in contrast, was to understand marijuana consumption by developing “variables” as part of the investigation. Thereby he presented new variables, or as we would say today, theoretical concepts, but which are grounded in the empirical material.

Qualitative Research

This category contains quotations that refer to descriptions of qualitative research without making comparisons with quantitative research. Researchers such as Denzin and Lincoln, who have written a series of influential handbooks on qualitative methods (1994; Denzin and Lincoln 2003 ; 2005 ), citing Nelson et al. (1992:4), argue that because qualitative research is “interdisciplinary, transdisciplinary, and sometimes counterdisciplinary” it is difficult to derive one single definition of it (Jovanović 2011 :3). According to them, in fact, “the field” is “many things at the same time,” involving contradictions, tensions over its focus, methods, and how to derive interpretations and findings ( 2003 : 11). Similarly, others, such as Flick ( 2007 :ix–x) contend that agreeing on an accepted definition has increasingly become problematic, and that qualitative research has possibly matured different identities. However, Best holds that “the proliferation of many sorts of activities under the label of qualitative sociology threatens to confuse our discussions” ( 2004 :54). Atkinson’s position is more definite: “the current state of qualitative research and research methods is confused” ( 2005 :3–4).

Qualitative research is about interpretation (Blumer 1969 ; Strauss and Corbin 1998 ; Denzin and Lincoln 2003 ), or Verstehen [understanding] (Frankfort-Nachmias and Nachmias 1996 ). It is “multi-method,” involving the collection and use of a variety of empirical materials (Denzin and Lincoln 1998; Silverman 2013 ) and approaches (Silverman 2005 ; Flick 2007 ). It focuses not only on the objective nature of behavior but also on its subjective meanings: individuals’ own accounts of their attitudes, motivations, behavior (McIntyre 2005 :127; Creswell 2009 ), events and situations (Bryman 1989) – what people say and do in specific places and institutions (Goodwin and Horowitz 2002 :35–36) in social and temporal contexts (Morrill and Fine 1997). For this reason, following Weber ([1921-22] 1978), it can be described as an interpretative science (McIntyre 2005 :127). But could quantitative research also be concerned with these questions? Also, as pointed out below, does all qualitative research focus on subjective meaning, as some scholars suggest?

Others also distinguish qualitative research by claiming that it collects data using a naturalistic approach (Denzin and Lincoln 2005 :2; Creswell 2009 ), focusing on the meaning actors ascribe to their actions. But again, does all qualitative research need to be collected in situ? And does qualitative research have to be inherently concerned with meaning? Flick ( 2007 ), referring to Denzin and Lincoln ( 2005 ), mentions conversation analysis as an example of qualitative research that is not concerned with the meanings people bring to a situation, but rather with the formal organization of talk. Still others, such as Ragin ( 1994 :85), note that qualitative research is often (especially early on in the project, we would add) less structured than other kinds of social research – a characteristic connected to its flexibility and that can lead both to potentially better, but also worse results. But is this not a feature of this type of research, rather than a defining description of its essence? Wouldn’t this comment also apply, albeit to varying degrees, to quantitative research?

In addition, Strauss ( 2003 ), along with others, such as Alvesson and Kärreman ( 2011 :10–76), argue that qualitative researchers struggle to capture and represent complex phenomena partially because they tend to collect a large amount of data. While his analysis is correct at some points – “It is necessary to do detailed, intensive, microscopic examination of the data in order to bring out the amazing complexity of what lies in, behind, and beyond those data” (Strauss 2003 :10) – much of his analysis concerns the supposed focus of qualitative research and its challenges, rather than exactly what it is about. But even in this instance we would make a weak case arguing that these are strictly the defining features of qualitative research. Some researchers seem to focus on the approach or the methods used, or even on the way material is analyzed. Several researchers stress the naturalistic assumption of investigating the world, suggesting that meaning and interpretation appear to be a core matter of qualitative research.

We can also see that in this category there is no consensus about specific qualitative methods nor about qualitative data. Many emphasize interpretation, but quantitative research, too, involves interpretation; the results of a regression analysis, for example, certainly have to be interpreted, and the form of meta-analysis that factor analysis provides indeed requires interpretation However, there is no interpretation of quantitative raw data, i.e., numbers in tables. One common thread is that qualitative researchers have to get to grips with their data in order to understand what is being studied in great detail, irrespective of the type of empirical material that is being analyzed. This observation is connected to the fact that qualitative researchers routinely make several adjustments of focus and research design as their studies progress, in many cases until the very end of the project (Kalof et al. 2008 ). If you, like Becker, do not start out with a detailed theory, adjustments such as the emergence and refinement of research questions will occur during the research process. We have thus found a number of useful reflections about qualitative research scattered across different sources, but none of them effectively describe the defining characteristics of this approach.

Although qualitative research does not appear to be defined in terms of a specific method, it is certainly common that fieldwork, i.e., research that entails that the researcher spends considerable time in the field that is studied and use the knowledge gained as data, is seen as emblematic of or even identical to qualitative research. But because we understand that fieldwork tends to focus primarily on the collection and analysis of qualitative data, we expected to find within it discussions on the meaning of “qualitative.” But, again, this was not the case.

Instead, we found material on the history of this approach (for example, Frankfort-Nachmias and Nachmias 1996 ; Atkinson et al. 2001), including how it has changed; for example, by adopting a more self-reflexive practice (Heyl 2001), as well as the different nomenclature that has been adopted, such as fieldwork, ethnography, qualitative research, naturalistic research, participant observation and so on (for example, Lofland et al. 2006 ; Gans 1999 ).

We retrieved definitions of ethnography, such as “the study of people acting in the natural courses of their daily lives,” involving a “resocialization of the researcher” (Emerson 1988 :1) through intense immersion in others’ social worlds (see also examples in Hammersley 2018 ). This may be accomplished by direct observation and also participation (Neuman 2007 :276), although others, such as Denzin ( 1970 :185), have long recognized other types of observation, including non-participant (“fly on the wall”). In this category we have also isolated claims and opposing views, arguing that this type of research is distinguished primarily by where it is conducted (natural settings) (Hughes 1971:496), and how it is carried out (a variety of methods are applied) or, for some most importantly, by involving an active, empathetic immersion in those being studied (Emerson 1988 :2). We also retrieved descriptions of the goals it attends in relation to how it is taught (understanding subjective meanings of the people studied, primarily develop theory, or contribute to social change) (see for example, Corte and Irwin 2017 ; Frankfort-Nachmias and Nachmias 1996 :281; Trier-Bieniek 2012 :639) by collecting the richest possible data (Lofland et al. 2006 ) to derive “thick descriptions” (Geertz 1973 ), and/or to aim at theoretical statements of general scope and applicability (for example, Emerson 1988 ; Fine 2003 ). We have identified guidelines on how to evaluate it (for example Becker 1996 ; Lamont 2004 ) and have retrieved instructions on how it should be conducted (for example, Lofland et al. 2006 ). For instance, analysis should take place while the data gathering unfolds (Emerson 1988 ; Hammersley and Atkinson 2007 ; Lofland et al. 2006 ), observations should be of long duration (Becker 1970 :54; Goffman 1989 ), and data should be of high quantity (Becker 1970 :52–53), as well as other questionable distinctions between fieldwork and other methods:

Field studies differ from other methods of research in that the researcher performs the task of selecting topics, decides what questions to ask, and forges interest in the course of the research itself . This is in sharp contrast to many ‘theory-driven’ and ‘hypothesis-testing’ methods. (Lofland and Lofland 1995 :5)

But could not, for example, a strictly interview-based study be carried out with the same amount of flexibility, such as sequential interviewing (for example, Small 2009 )? Once again, are quantitative approaches really as inflexible as some qualitative researchers think? Moreover, this category stresses the role of the actors’ meaning, which requires knowledge and close interaction with people, their practices and their lifeworld.

It is clear that field studies – which are seen by some as the “gold standard” of qualitative research – are nonetheless only one way of doing qualitative research. There are other methods, but it is not clear why some are more qualitative than others, or why they are better or worse. Fieldwork is characterized by interaction with the field (the material) and understanding of the phenomenon that is being studied. In Becker’s case, he had general experience from fields in which marihuana was used, based on which he did interviews with actual users in several fields.

Grounded Theory

Another major category we identified in our sample is Grounded Theory. We found descriptions of it most clearly in Glaser and Strauss’ ([1967] 2010 ) original articulation, Strauss and Corbin ( 1998 ) and Charmaz ( 2006 ), as well as many other accounts of what it is for: generating and testing theory (Strauss 2003 :xi). We identified explanations of how this task can be accomplished – such as through two main procedures: constant comparison and theoretical sampling (Emerson 1998:96), and how using it has helped researchers to “think differently” (for example, Strauss and Corbin 1998 :1). We also read descriptions of its main traits, what it entails and fosters – for instance, an exceptional flexibility, an inductive approach (Strauss and Corbin 1998 :31–33; 1990; Esterberg 2002 :7), an ability to step back and critically analyze situations, recognize tendencies towards bias, think abstractly and be open to criticism, enhance sensitivity towards the words and actions of respondents, and develop a sense of absorption and devotion to the research process (Strauss and Corbin 1998 :5–6). Accordingly, we identified discussions of the value of triangulating different methods (both using and not using grounded theory), including quantitative ones, and theories to achieve theoretical development (most comprehensively in Denzin 1970 ; Strauss and Corbin 1998 ; Timmermans and Tavory 2012 ). We have also located arguments about how its practice helps to systematize data collection, analysis and presentation of results (Glaser and Strauss [1967] 2010 :16).

Grounded theory offers a systematic approach which requires researchers to get close to the field; closeness is a requirement of identifying questions and developing new concepts or making further distinctions with regard to old concepts. In contrast to other qualitative approaches, grounded theory emphasizes the detailed coding process, and the numerous fine-tuned distinctions that the researcher makes during the process. Within this category, too, we could not find a satisfying discussion of the meaning of qualitative research.

Defining Qualitative Research

In sum, our analysis shows that some notions reappear in the discussion of qualitative research, such as understanding, interpretation, “getting close” and making distinctions. These notions capture aspects of what we think is “qualitative.” However, a comprehensive definition that is useful and that can further develop the field is lacking, and not even a clear picture of its essential elements appears. In other words no definition emerges from our data, and in our research process we have moved back and forth between our empirical data and the attempt to present a definition. Our concrete strategy, as stated above, is to relate qualitative and quantitative research, or more specifically, qualitative and quantitative work. We use an ideal-typical notion of quantitative research which relies on taken for granted and numbered variables. This means that the data consists of variables on different scales, such as ordinal, but frequently ratio and absolute scales, and the representation of the numbers to the variables, i.e. the justification of the assignment of numbers to object or phenomenon, are not questioned, though the validity may be questioned. In this section we return to the notion of quality and try to clarify it while presenting our contribution.

Broadly, research refers to the activity performed by people trained to obtain knowledge through systematic procedures. Notions such as “objectivity” and “reflexivity,” “systematic,” “theory,” “evidence” and “openness” are here taken for granted in any type of research. Next, building on our empirical analysis we explain the four notions that we have identified as central to qualitative work: distinctions, process, closeness, and improved understanding. In discussing them, ultimately in relation to one another, we make their meaning even more precise. Our idea, in short, is that only when these ideas that we present separately for analytic purposes are brought together can we speak of qualitative research.

Distinctions

We believe that the possibility of making new distinctions is one the defining characteristics of qualitative research. It clearly sets it apart from quantitative analysis which works with taken-for-granted variables, albeit as mentioned, meta-analyses, for example, factor analysis may result in new variables. “Quality” refers essentially to distinctions, as already pointed out by Aristotle. He discusses the term “qualitative” commenting: “By a quality I mean that in virtue of which things are said to be qualified somehow” (Aristotle 1984:14). Quality is about what something is or has, which means that the distinction from its environment is crucial. We see qualitative research as a process in which significant new distinctions are made to the scholarly community; to make distinctions is a key aspect of obtaining new knowledge; a point, as we will see, that also has implications for “quantitative research.” The notion of being “significant” is paramount. New distinctions by themselves are not enough; just adding concepts only increases complexity without furthering our knowledge. The significance of new distinctions is judged against the communal knowledge of the research community. To enable this discussion and judgements central elements of rational discussion are required (cf. Habermas [1981] 1987 ; Davidsson [ 1988 ] 2001) to identify what is new and relevant scientific knowledge. Relatedly, Ragin alludes to the idea of new and useful knowledge at a more concrete level: “Qualitative methods are appropriate for in-depth examination of cases because they aid the identification of key features of cases. Most qualitative methods enhance data” (1994:79). When Becker ( 1963 ) studied deviant behavior and investigated how people became marihuana smokers, he made distinctions between the ways in which people learned how to smoke. This is a classic example of how the strategy of “getting close” to the material, for example the text, people or pictures that are subject to analysis, may enable researchers to obtain deeper insight and new knowledge by making distinctions – in this instance on the initial notion of learning how to smoke. Others have stressed the making of distinctions in relation to coding or theorizing. Emerson et al. ( 1995 ), for example, hold that “qualitative coding is a way of opening up avenues of inquiry,” meaning that the researcher identifies and develops concepts and analytic insights through close examination of and reflection on data (Emerson et al. 1995 :151). Goodwin and Horowitz highlight making distinctions in relation to theory-building writing: “Close engagement with their cases typically requires qualitative researchers to adapt existing theories or to make new conceptual distinctions or theoretical arguments to accommodate new data” ( 2002 : 37). In the ideal-typical quantitative research only existing and so to speak, given, variables would be used. If this is the case no new distinction are made. But, would not also many “quantitative” researchers make new distinctions?

Process does not merely suggest that research takes time. It mainly implies that qualitative new knowledge results from a process that involves several phases, and above all iteration. Qualitative research is about oscillation between theory and evidence, analysis and generating material, between first- and second -order constructs (Schütz 1962 :59), between getting in contact with something, finding sources, becoming deeply familiar with a topic, and then distilling and communicating some of its essential features. The main point is that the categories that the researcher uses, and perhaps takes for granted at the beginning of the research process, usually undergo qualitative changes resulting from what is found. Becker describes how he tested hypotheses and let the jargon of the users develop into theoretical concepts. This happens over time while the study is being conducted, exemplifying what we mean by process.

In the research process, a pilot-study may be used to get a first glance of, for example, the field, how to approach it, and what methods can be used, after which the method and theory are chosen or refined before the main study begins. Thus, the empirical material is often central from the start of the project and frequently leads to adjustments by the researcher. Likewise, during the main study categories are not fixed; the empirical material is seen in light of the theory used, but it is also given the opportunity to kick back, thereby resisting attempts to apply theoretical straightjackets (Becker 1970 :43). In this process, coding and analysis are interwoven, and thus are often important steps for getting closer to the phenomenon and deciding what to focus on next. Becker began his research by interviewing musicians close to him, then asking them to refer him to other musicians, and later on doubling his original sample of about 25 to include individuals in other professions (Becker 1973:46). Additionally, he made use of some participant observation, documents, and interviews with opiate users made available to him by colleagues. As his inductive theory of deviance evolved, Becker expanded his sample in order to fine tune it, and test the accuracy and generality of his hypotheses. In addition, he introduced a negative case and discussed the null hypothesis ( 1963 :44). His phasic career model is thus based on a research design that embraces processual work. Typically, process means to move between “theory” and “material” but also to deal with negative cases, and Becker ( 1998 ) describes how discovering these negative cases impacted his research design and ultimately its findings.

Obviously, all research is process-oriented to some degree. The point is that the ideal-typical quantitative process does not imply change of the data, and iteration between data, evidence, hypotheses, empirical work, and theory. The data, quantified variables, are, in most cases fixed. Merging of data, which of course can be done in a quantitative research process, does not mean new data. New hypotheses are frequently tested, but the “raw data is often the “the same.” Obviously, over time new datasets are made available and put into use.

Another characteristic that is emphasized in our sample is that qualitative researchers – and in particular ethnographers – can, or as Goffman put it, ought to ( 1989 ), get closer to the phenomenon being studied and their data than quantitative researchers (for example, Silverman 2009 :85). Put differently, essentially because of their methods qualitative researchers get into direct close contact with those being investigated and/or the material, such as texts, being analyzed. Becker started out his interview study, as we noted, by talking to those he knew in the field of music to get closer to the phenomenon he was studying. By conducting interviews he got even closer. Had he done more observations, he would undoubtedly have got even closer to the field.

Additionally, ethnographers’ design enables researchers to follow the field over time, and the research they do is almost by definition longitudinal, though the time in the field is studied obviously differs between studies. The general characteristic of closeness over time maximizes the chances of unexpected events, new data (related, for example, to archival research as additional sources, and for ethnography for situations not necessarily previously thought of as instrumental – what Mannay and Morgan ( 2015 ) term the “waiting field”), serendipity (Merton and Barber 2004 ; Åkerström 2013 ), and possibly reactivity, as well as the opportunity to observe disrupted patterns that translate into exemplars of negative cases. Two classic examples of this are Becker’s finding of what medical students call “crocks” (Becker et al. 1961 :317), and Geertz’s ( 1973 ) study of “deep play” in Balinese society.

By getting and staying so close to their data – be it pictures, text or humans interacting (Becker was himself a musician) – for a long time, as the research progressively focuses, qualitative researchers are prompted to continually test their hunches, presuppositions and hypotheses. They test them against a reality that often (but certainly not always), and practically, as well as metaphorically, talks back, whether by validating them, or disqualifying their premises – correctly, as well as incorrectly (Fine 2003 ; Becker 1970 ). This testing nonetheless often leads to new directions for the research. Becker, for example, says that he was initially reading psychological theories, but when facing the data he develops a theory that looks at, you may say, everything but psychological dispositions to explain the use of marihuana. Especially researchers involved with ethnographic methods have a fairly unique opportunity to dig up and then test (in a circular, continuous and temporal way) new research questions and findings as the research progresses, and thereby to derive previously unimagined and uncharted distinctions by getting closer to the phenomenon under study.

Let us stress that getting close is by no means restricted to ethnography. The notion of hermeneutic circle and hermeneutics as a general way of understanding implies that we must get close to the details in order to get the big picture. This also means that qualitative researchers can literally also make use of details of pictures as evidence (cf. Harper 2002). Thus, researchers may get closer both when generating the material or when analyzing it.

Quantitative research, we maintain, in the ideal-typical representation cannot get closer to the data. The data is essentially numbers in tables making up the variables (Franzosi 2016 :138). The data may originally have been “qualitative,” but once reduced to numbers there can only be a type of “hermeneutics” about what the number may stand for. The numbers themselves, however, are non-ambiguous. Thus, in quantitative research, interpretation, if done, is not about the data itself—the numbers—but what the numbers stand for. It follows that the interpretation is essentially done in a more “speculative” mode without direct empirical evidence (cf. Becker 2017 ).

Improved Understanding

While distinction, process and getting closer refer to the qualitative work of the researcher, improved understanding refers to its conditions and outcome of this work. Understanding cuts deeper than explanation, which to some may mean a causally verified correlation between variables. The notion of explanation presupposes the notion of understanding since explanation does not include an idea of how knowledge is gained (Manicas 2006 : 15). Understanding, we argue, is the core concept of what we call the outcome of the process when research has made use of all the other elements that were integrated in the research. Understanding, then, has a special status in qualitative research since it refers both to the conditions of knowledge and the outcome of the process. Understanding can to some extent be seen as the condition of explanation and occurs in a process of interpretation, which naturally refers to meaning (Gadamer 1990 ). It is fundamentally connected to knowing, and to the knowing of how to do things (Heidegger [1927] 2001 ). Conceptually the term hermeneutics is used to account for this process. Heidegger ties hermeneutics to human being and not possible to separate from the understanding of being ( 1988 ). Here we use it in a broader sense, and more connected to method in general (cf. Seiffert 1992 ). The abovementioned aspects – for example, “objectivity” and “reflexivity” – of the approach are conditions of scientific understanding. Understanding is the result of a circular process and means that the parts are understood in light of the whole, and vice versa. Understanding presupposes pre-understanding, or in other words, some knowledge of the phenomenon studied. The pre-understanding, even in the form of prejudices, are in qualitative research process, which we see as iterative, questioned, which gradually or suddenly change due to the iteration of data, evidence and concepts. However, qualitative research generates understanding in the iterative process when the researcher gets closer to the data, e.g., by going back and forth between field and analysis in a process that generates new data that changes the evidence, and, ultimately, the findings. Questioning, to ask questions, and put what one assumes—prejudices and presumption—in question, is central to understand something (Heidegger [1927] 2001 ; Gadamer 1990 :368–384). We propose that this iterative process in which the process of understanding occurs is characteristic of qualitative research.

Improved understanding means that we obtain scientific knowledge of something that we as a scholarly community did not know before, or that we get to know something better. It means that we understand more about how parts are related to one another, and to other things we already understand (see also Fine and Hallett 2014 ). Understanding is an important condition for qualitative research. It is not enough to identify correlations, make distinctions, and work in a process in which one gets close to the field or phenomena. Understanding is accomplished when the elements are integrated in an iterative process.

It is, moreover, possible to understand many things, and researchers, just like children, may come to understand new things every day as they engage with the world. This subjective condition of understanding – namely, that a person gains a better understanding of something –is easily met. To be qualified as “scientific,” the understanding must be general and useful to many; it must be public. But even this generally accessible understanding is not enough in order to speak of “scientific understanding.” Though we as a collective can increase understanding of everything in virtually all potential directions as a result also of qualitative work, we refrain from this “objective” way of understanding, which has no means of discriminating between what we gain in understanding. Scientific understanding means that it is deemed relevant from the scientific horizon (compare Schütz 1962 : 35–38, 46, 63), and that it rests on the pre-understanding that the scientists have and must have in order to understand. In other words, the understanding gained must be deemed useful by other researchers, so that they can build on it. We thus see understanding from a pragmatic, rather than a subjective or objective perspective. Improved understanding is related to the question(s) at hand. Understanding, in order to represent an improvement, must be an improvement in relation to the existing body of knowledge of the scientific community (James [ 1907 ] 1955). Scientific understanding is, by definition, collective, as expressed in Weber’s famous note on objectivity, namely that scientific work aims at truths “which … can claim, even for a Chinese, the validity appropriate to an empirical analysis” ([1904] 1949 :59). By qualifying “improved understanding” we argue that it is a general defining characteristic of qualitative research. Becker‘s ( 1966 ) study and other research of deviant behavior increased our understanding of the social learning processes of how individuals start a behavior. And it also added new knowledge about the labeling of deviant behavior as a social process. Few studies, of course, make the same large contribution as Becker’s, but are nonetheless qualitative research.

Understanding in the phenomenological sense, which is a hallmark of qualitative research, we argue, requires meaning and this meaning is derived from the context, and above all the data being analyzed. The ideal-typical quantitative research operates with given variables with different numbers. This type of material is not enough to establish meaning at the level that truly justifies understanding. In other words, many social science explanations offer ideas about correlations or even causal relations, but this does not mean that the meaning at the level of the data analyzed, is understood. This leads us to say that there are indeed many explanations that meet the criteria of understanding, for example the explanation of how one becomes a marihuana smoker presented by Becker. However, we may also understand a phenomenon without explaining it, and we may have potential explanations, or better correlations, that are not really understood.

We may speak more generally of quantitative research and its data to clarify what we see as an important distinction. The “raw data” that quantitative research—as an idealtypical activity, refers to is not available for further analysis; the numbers, once created, are not to be questioned (Franzosi 2016 : 138). If the researcher is to do “more” or “change” something, this will be done by conjectures based on theoretical knowledge or based on the researcher’s lifeworld. Both qualitative and quantitative research is based on the lifeworld, and all researchers use prejudices and pre-understanding in the research process. This idea is present in the works of Heidegger ( 2001 ) and Heisenberg (cited in Franzosi 2010 :619). Qualitative research, as we argued, involves the interaction and questioning of concepts (theory), data, and evidence.

Ragin ( 2004 :22) points out that “a good definition of qualitative research should be inclusive and should emphasize its key strengths and features, not what it lacks (for example, the use of sophisticated quantitative techniques).” We define qualitative research as an iterative process in which improved understanding to the scientific community is achieved by making new significant distinctions resulting from getting closer to the phenomenon studied. Qualitative research, as defined here, is consequently a combination of two criteria: (i) how to do things –namely, generating and analyzing empirical material, in an iterative process in which one gets closer by making distinctions, and (ii) the outcome –improved understanding novel to the scholarly community. Is our definition applicable to our own study? In this study we have closely read the empirical material that we generated, and the novel distinction of the notion “qualitative research” is the outcome of an iterative process in which both deduction and induction were involved, in which we identified the categories that we analyzed. We thus claim to meet the first criteria, “how to do things.” The second criteria cannot be judged but in a partial way by us, namely that the “outcome” —in concrete form the definition-improves our understanding to others in the scientific community.

We have defined qualitative research, or qualitative scientific work, in relation to quantitative scientific work. Given this definition, qualitative research is about questioning the pre-given (taken for granted) variables, but it is thus also about making new distinctions of any type of phenomenon, for example, by coining new concepts, including the identification of new variables. This process, as we have discussed, is carried out in relation to empirical material, previous research, and thus in relation to theory. Theory and previous research cannot be escaped or bracketed. According to hermeneutic principles all scientific work is grounded in the lifeworld, and as social scientists we can thus never fully bracket our pre-understanding.

We have proposed that quantitative research, as an idealtype, is concerned with pre-determined variables (Small 2008 ). Variables are epistemically fixed, but can vary in terms of dimensions, such as frequency or number. Age is an example; as a variable it can take on different numbers. In relation to quantitative research, qualitative research does not reduce its material to number and variables. If this is done the process of comes to a halt, the researcher gets more distanced from her data, and it makes it no longer possible to make new distinctions that increase our understanding. We have above discussed the components of our definition in relation to quantitative research. Our conclusion is that in the research that is called quantitative there are frequent and necessary qualitative elements.

Further, comparative empirical research on researchers primarily working with ”quantitative” approaches and those working with ”qualitative” approaches, we propose, would perhaps show that there are many similarities in practices of these two approaches. This is not to deny dissimilarities, or the different epistemic and ontic presuppositions that may be more or less strongly associated with the two different strands (see Goertz and Mahoney 2012 ). Our point is nonetheless that prejudices and preconceptions about researchers are unproductive, and that as other researchers have argued, differences may be exaggerated (e.g., Becker 1996 : 53, 2017 ; Marchel and Owens 2007 :303; Ragin 1994 ), and that a qualitative dimension is present in both kinds of work.

Several things follow from our findings. The most important result is the relation to quantitative research. In our analysis we have separated qualitative research from quantitative research. The point is not to label individual researchers, methods, projects, or works as either “quantitative” or “qualitative.” By analyzing, i.e., taking apart, the notions of quantitative and qualitative, we hope to have shown the elements of qualitative research. Our definition captures the elements, and how they, when combined in practice, generate understanding. As many of the quotations we have used suggest, one conclusion of our study holds that qualitative approaches are not inherently connected with a specific method. Put differently, none of the methods that are frequently labelled “qualitative,” such as interviews or participant observation, are inherently “qualitative.” What matters, given our definition, is whether one works qualitatively or quantitatively in the research process, until the results are produced. Consequently, our analysis also suggests that those researchers working with what in the literature and in jargon is often called “quantitative research” are almost bound to make use of what we have identified as qualitative elements in any research project. Our findings also suggest that many” quantitative” researchers, at least to some extent, are engaged with qualitative work, such as when research questions are developed, variables are constructed and combined, and hypotheses are formulated. Furthermore, a research project may hover between “qualitative” and “quantitative” or start out as “qualitative” and later move into a “quantitative” (a distinct strategy that is not similar to “mixed methods” or just simply combining induction and deduction). More generally speaking, the categories of “qualitative” and “quantitative,” unfortunately, often cover up practices, and it may lead to “camps” of researchers opposing one another. For example, regardless of the researcher is primarily oriented to “quantitative” or “qualitative” research, the role of theory is neglected (cf. Swedberg 2017 ). Our results open up for an interaction not characterized by differences, but by different emphasis, and similarities.

Let us take two examples to briefly indicate how qualitative elements can fruitfully be combined with quantitative. Franzosi ( 2010 ) has discussed the relations between quantitative and qualitative approaches, and more specifically the relation between words and numbers. He analyzes texts and argues that scientific meaning cannot be reduced to numbers. Put differently, the meaning of the numbers is to be understood by what is taken for granted, and what is part of the lifeworld (Schütz 1962 ). Franzosi shows how one can go about using qualitative and quantitative methods and data to address scientific questions analyzing violence in Italy at the time when fascism was rising (1919–1922). Aspers ( 2006 ) studied the meaning of fashion photographers. He uses an empirical phenomenological approach, and establishes meaning at the level of actors. In a second step this meaning, and the different ideal-typical photographers constructed as a result of participant observation and interviews, are tested using quantitative data from a database; in the first phase to verify the different ideal-types, in the second phase to use these types to establish new knowledge about the types. In both of these cases—and more examples can be found—authors move from qualitative data and try to keep the meaning established when using the quantitative data.

A second main result of our study is that a definition, and we provided one, offers a way for research to clarify, and even evaluate, what is done. Hence, our definition can guide researchers and students, informing them on how to think about concrete research problems they face, and to show what it means to get closer in a process in which new distinctions are made. The definition can also be used to evaluate the results, given that it is a standard of evaluation (cf. Hammersley 2007 ), to see whether new distinctions are made and whether this improves our understanding of what is researched, in addition to the evaluation of how the research was conducted. By making what is qualitative research explicit it becomes easier to communicate findings, and it is thereby much harder to fly under the radar with substandard research since there are standards of evaluation which make it easier to separate “good” from “not so good” qualitative research.

To conclude, our analysis, which ends with a definition of qualitative research can thus both address the “internal” issues of what is qualitative research, and the “external” critiques that make it harder to do qualitative research, to which both pressure from quantitative methods and general changes in society contribute.

Acknowledgements

Financial Support for this research is given by the European Research Council, CEV (263699). The authors are grateful to Susann Krieglsteiner for assistance in collecting the data. The paper has benefitted from the many useful comments by the three reviewers and the editor, comments by members of the Uppsala Laboratory of Economic Sociology, as well as Jukka Gronow, Sebastian Kohl, Marcin Serafin, Richard Swedberg, Anders Vassenden and Turid Rødne.

Biographies

is professor of sociology at the Department of Sociology, Uppsala University and Universität St. Gallen. His main focus is economic sociology, and in particular, markets. He has published numerous articles and books, including Orderly Fashion (Princeton University Press 2010), Markets (Polity Press 2011) and Re-Imagining Economic Sociology (edited with N. Dodd, Oxford University Press 2015). His book Ethnographic Methods (in Swedish) has already gone through several editions.

is associate professor of sociology at the Department of Media and Social Sciences, University of Stavanger. His research has been published in journals such as Social Psychology Quarterly, Sociological Theory, Teaching Sociology, and Music and Arts in Action. As an ethnographer he is working on a book on he social world of big-wave surfing.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

• Åkerström M. Curiosity and serendipity in qualitative research. Qualitative Sociology Review. 2013; 9 (2):10–18. [ Google Scholar ]
• Alford, Robert R. 1998. The craft of inquiry. Theories, methods, evidence . Oxford: Oxford University Press.
• Alvesson M, Kärreman D. Qualitative research and theory development . Mystery as method . London: SAGE Publications; 2011. [ Google Scholar ]
• Aspers, Patrik. 2006. Markets in Fashion, A Phenomenological Approach. London Routledge.
• Atkinson P. Qualitative research. Unity and diversity. Forum: Qualitative Social Research. 2005; 6 (3):1–15. [ Google Scholar ]
• Becker HS. Outsiders. Studies in the sociology of deviance . New York: The Free Press; 1963. [ Google Scholar ]
• Becker HS. Whose side are we on? Social Problems. 1966; 14 (3):239–247. [ Google Scholar ]
• Becker HS. Sociological work. Method and substance. New Brunswick: Transaction Books; 1970. [ Google Scholar ]
• Becker HS. The epistemology of qualitative research. In: Richard J, Anne C, Shweder RA, editors. Ethnography and human development. Context and meaning in social inquiry. Chicago: University of Chicago Press; 1996. pp. 53–71. [ Google Scholar ]
• Becker HS. Tricks of the trade. How to think about your research while you're doing it. Chicago: University of Chicago Press; 1998. [ Google Scholar ]
• Becker, Howard S. 2017. Evidence . Chigaco: University of Chicago Press.
• Becker H, Geer B, Hughes E, Strauss A. Boys in White, student culture in medical school. New Brunswick: Transaction Publishers; 1961. [ Google Scholar ]
• Berezin M. How do we know what we mean? Epistemological dilemmas in cultural sociology. Qualitative Sociology. 2014; 37 (2):141–151. [ Google Scholar ]
• Best, Joel. 2004. Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , eds . Charles, Ragin, Joanne, Nagel, and Patricia White, 53-54. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf .
• Biernacki R. Humanist interpretation versus coding text samples. Qualitative Sociology. 2014; 37 (2):173–188. [ Google Scholar ]
• Blumer H. Symbolic interactionism: Perspective and method. Berkeley: University of California Press; 1969. [ Google Scholar ]
• Brady H, Collier D, Seawright J. Refocusing the discussion of methodology. In: Henry B, David C, editors. Rethinking social inquiry. Diverse tools, shared standards. Lanham: Rowman and Littlefield; 2004. pp. 3–22. [ Google Scholar ]
• Brown AP. Qualitative method and compromise in applied social research. Qualitative Research. 2010; 10 (2):229–248. [ Google Scholar ]
• Charmaz K. Constructing grounded theory. London: Sage; 2006. [ Google Scholar ]
• Corte, Ugo, and Katherine Irwin. 2017. “The Form and Flow of Teaching Ethnographic Knowledge: Hands-on Approaches for Learning Epistemology” Teaching Sociology 45(3): 209-219.
• Creswell JW. Research design. Qualitative, quantitative, and mixed method approaches. 3. Thousand Oaks: SAGE Publications; 2009. [ Google Scholar ]
• Davidsson D. The myth of the subjective. In: Davidsson D, editor. Subjective, intersubjective, objective. Oxford: Oxford University Press; 1988. pp. 39–52. [ Google Scholar ]
• Denzin NK. The research act: A theoretical introduction to Ssociological methods. Chicago: Aldine Publishing Company Publishers; 1970. [ Google Scholar ]
• Denzin NK, Lincoln YS. Introduction. The discipline and practice of qualitative research. In: Denzin NK, Lincoln YS, editors. Collecting and interpreting qualitative materials. Thousand Oaks: SAGE Publications; 2003. pp. 1–45. [ Google Scholar ]
• Denzin NK, Lincoln YS. Introduction. The discipline and practice of qualitative research. In: Denzin NK, Lincoln YS, editors. The Sage handbook of qualitative research. Thousand Oaks: SAGE Publications; 2005. pp. 1–32. [ Google Scholar ]
• Emerson RM, editor. Contemporary field research. A collection of readings. Prospect Heights: Waveland Press; 1988. [ Google Scholar ]
• Emerson RM, Fretz RI, Shaw LL. Writing ethnographic fieldnotes. Chicago: University of Chicago Press; 1995. [ Google Scholar ]
• Esterberg KG. Qualitative methods in social research. Boston: McGraw-Hill; 2002. [ Google Scholar ]
• Fine, Gary Alan. 1995. Review of “handbook of qualitative research.” Contemporary Sociology 24 (3): 416–418.
• Fine, Gary Alan. 2003. “ Toward a Peopled Ethnography: Developing Theory from Group Life.” Ethnography . 4(1):41-60.
• Fine GA, Hancock BH. The new ethnographer at work. Qualitative Research. 2017; 17 (2):260–268. [ Google Scholar ]
• Fine GA, Hallett T. Stranger and stranger: Creating theory through ethnographic distance and authority. Journal of Organizational Ethnography. 2014; 3 (2):188–203. [ Google Scholar ]
• Flick U. Qualitative research. State of the art. Social Science Information. 2002; 41 (1):5–24. [ Google Scholar ]
• Flick U. Designing qualitative research. London: SAGE Publications; 2007. [ Google Scholar ]
• Frankfort-Nachmias C, Nachmias D. Research methods in the social sciences. 5. London: Edward Arnold; 1996. [ Google Scholar ]
• Franzosi R. Sociology, narrative, and the quality versus quantity debate (Goethe versus Newton): Can computer-assisted story grammars help us understand the rise of Italian fascism (1919- 1922)? Theory and Society. 2010; 39 (6):593–629. [ Google Scholar ]
• Franzosi R. From method and measurement to narrative and number. International journal of social research methodology. 2016; 19 (1):137–141. [ Google Scholar ]
• Gadamer, Hans-Georg. 1990. Wahrheit und Methode, Grundzüge einer philosophischen Hermeneutik . Band 1, Hermeneutik. Tübingen: J.C.B. Mohr.
• Gans H. Participant Observation in an Age of “Ethnography” Journal of Contemporary Ethnography. 1999; 28 (5):540–548. [ Google Scholar ]
• Geertz C. The interpretation of cultures. New York: Basic Books; 1973. [ Google Scholar ]
• Gilbert N. Researching social life. 3. London: SAGE Publications; 2009. [ Google Scholar ]
• Glaeser A. Hermeneutic institutionalism: Towards a new synthesis. Qualitative Sociology. 2014; 37 :207–241. [ Google Scholar ]
• Glaser, Barney G., and Anselm L. Strauss. [1967] 2010. The discovery of grounded theory. Strategies for qualitative research. Hawthorne: Aldine.
• Goertz G, Mahoney J. A tale of two cultures: Qualitative and quantitative research in the social sciences. Princeton: Princeton University Press; 2012. [ Google Scholar ]
• Goffman E. On fieldwork. Journal of Contemporary Ethnography. 1989; 18 (2):123–132. [ Google Scholar ]
• Goodwin J, Horowitz R. Introduction. The methodological strengths and dilemmas of qualitative sociology. Qualitative Sociology. 2002; 25 (1):33–47. [ Google Scholar ]
• Habermas, Jürgen. [1981] 1987. The theory of communicative action . Oxford: Polity Press.
• Hammersley M. The issue of quality in qualitative research. International Journal of Research & Method in Education. 2007; 30 (3):287–305. [ Google Scholar ]
• Hammersley, Martyn. 2013. What is qualitative research? Bloomsbury Publishing.
• Hammersley M. What is ethnography? Can it survive should it? Ethnography and Education. 2018; 13 (1):1–17. [ Google Scholar ]
• Hammersley M, Atkinson P. Ethnography . Principles in practice . London: Tavistock Publications; 2007. [ Google Scholar ]
• Heidegger M. Sein und Zeit. Tübingen: Max Niemeyer Verlag; 2001. [ Google Scholar ]
• Heidegger, Martin. 1988. 1923. Ontologie. Hermeneutik der Faktizität, Gesamtausgabe II. Abteilung: Vorlesungen 1919-1944, Band 63, Frankfurt am Main: Vittorio Klostermann.
• Hempel CG. Philosophy of the natural sciences. Upper Saddle River: Prentice Hall; 1966. [ Google Scholar ]
• Hood JC. Teaching against the text. The case of qualitative methods. Teaching Sociology. 2006; 34 (3):207–223. [ Google Scholar ]
• James W. Pragmatism. New York: Meredian Books; 1907. [ Google Scholar ]
• Jovanović G. Toward a social history of qualitative research. History of the Human Sciences. 2011; 24 (2):1–27. [ Google Scholar ]
• Kalof L, Dan A, Dietz T. Essentials of social research. London: Open University Press; 2008. [ Google Scholar ]
• Katz J. Situational evidence: Strategies for causal reasoning from observational field notes. Sociological Methods & Research. 2015; 44 (1):108–144. [ Google Scholar ]
• King G, Keohane RO, Sidney S, Verba S. Scientific inference in qualitative research. Princeton: Princeton University Press; 1994. Designing social inquiry. [ Google Scholar ]
• Lamont M. Evaluating qualitative research: Some empirical findings and an agenda. In: Lamont M, White P, editors. Report from workshop on interdisciplinary standards for systematic qualitative research. Washington, DC: National Science Foundation; 2004. pp. 91–95. [ Google Scholar ]
• Lamont M, Swidler A. Methodological pluralism and the possibilities and limits of interviewing. Qualitative Sociology. 2014; 37 (2):153–171. [ Google Scholar ]
• Lazarsfeld P, Barton A. Some functions of qualitative analysis in social research. In: Kendall P, editor. The varied sociology of Paul Lazarsfeld. New York: Columbia University Press; 1982. pp. 239–285. [ Google Scholar ]
• Lichterman, Paul, and Isaac Reed I (2014), Theory and Contrastive Explanation in Ethnography. Sociological methods and research. Prepublished 27 October 2014; 10.1177/0049124114554458.
• Lofland J, Lofland L. Analyzing social settings. A guide to qualitative observation and analysis. 3. Belmont: Wadsworth; 1995. [ Google Scholar ]
• Lofland J, Snow DA, Anderson L, Lofland LH. Analyzing social settings. A guide to qualitative observation and analysis. 4. Belmont: Wadsworth/Thomson Learning; 2006. [ Google Scholar ]
• Long AF, Godfrey M. An evaluation tool to assess the quality of qualitative research studies. International Journal of Social Research Methodology. 2004; 7 (2):181–196. [ Google Scholar ]
• Lundberg G. Social research: A study in methods of gathering data. New York: Longmans, Green and Co.; 1951. [ Google Scholar ]
• Malinowski B. Argonauts of the Western Pacific: An account of native Enterprise and adventure in the archipelagoes of Melanesian New Guinea. London: Routledge; 1922. [ Google Scholar ]
• Manicas P. A realist philosophy of science: Explanation and understanding. Cambridge: Cambridge University Press; 2006. [ Google Scholar ]
• Marchel C, Owens S. Qualitative research in psychology. Could William James get a job? History of Psychology. 2007; 10 (4):301–324. [ PubMed ] [ Google Scholar ]
• McIntyre LJ. Need to know. Social science research methods. Boston: McGraw-Hill; 2005. [ Google Scholar ]
• Merton RK, Barber E. The travels and adventures of serendipity . A Study in Sociological Semantics and the Sociology of Science. Princeton: Princeton University Press; 2004. [ Google Scholar ]
• Mannay D, Morgan M. Doing ethnography or applying a qualitative technique? Reflections from the ‘waiting field‘ Qualitative Research. 2015; 15 (2):166–182. [ Google Scholar ]
• Neuman LW. Basics of social research. Qualitative and quantitative approaches. 2. Boston: Pearson Education; 2007. [ Google Scholar ]
• Ragin CC. Constructing social research. The unity and diversity of method. Thousand Oaks: Pine Forge Press; 1994. [ Google Scholar ]
• Ragin, Charles C. 2004. Introduction to session 1: Defining qualitative research. In Workshop on Scientific Foundations of Qualitative Research , 22, ed. Charles C. Ragin, Joane Nagel, Patricia White. http://www.nsf.gov/pubs/2004/nsf04219/nsf04219.pdf
• Rawls, Anne. 2018. The Wartime narrative in US sociology, 1940–7: Stigmatizing qualitative sociology in the name of ‘science,’ European Journal of Social Theory (Online first).
• Schütz A. Collected papers I: The problem of social reality. The Hague: Nijhoff; 1962. [ Google Scholar ]
• Seiffert H. Einführung in die Hermeneutik. Tübingen: Franke; 1992. [ Google Scholar ]
• Silverman D. Doing qualitative research. A practical handbook. 2. London: SAGE Publications; 2005. [ Google Scholar ]
• Silverman D. A very short, fairly interesting and reasonably cheap book about qualitative research. London: SAGE Publications; 2009. [ Google Scholar ]
• Silverman D. What counts as qualitative research? Some cautionary comments. Qualitative Sociology Review. 2013; 9 (2):48–55. [ Google Scholar ]
• Small ML. “How many cases do I need?” on science and the logic of case selection in field-based research. Ethnography. 2009; 10 (1):5–38. [ Google Scholar ]
• Small, Mario L 2008. Lost in translation: How not to make qualitative research more scientific. In Workshop on interdisciplinary standards for systematic qualitative research, ed in Michelle Lamont, and Patricia White, 165–171. Washington, DC: National Science Foundation.
• Snow DA, Anderson L. Down on their luck: A study of homeless street people. Berkeley: University of California Press; 1993. [ Google Scholar ]
• Snow DA, Morrill C. New ethnographies: Review symposium: A revolutionary handbook or a handbook for revolution? Journal of Contemporary Ethnography. 1995; 24 (3):341–349. [ Google Scholar ]
• Strauss AL. Qualitative analysis for social scientists. 14. Chicago: Cambridge University Press; 2003. [ Google Scholar ]
• Strauss AL, Corbin JM. Basics of qualitative research. Techniques and procedures for developing grounded theory. 2. Thousand Oaks: Sage Publications; 1998. [ Google Scholar ]
• Swedberg, Richard. 2017. Theorizing in sociological research: A new perspective, a new departure? Annual Review of Sociology 43: 189–206.
• Swedberg R. The new 'Battle of Methods'. Challenge January–February. 1990; 3 (1):33–38. [ Google Scholar ]
• Timmermans S, Tavory I. Theory construction in qualitative research: From grounded theory to abductive analysis. Sociological Theory. 2012; 30 (3):167–186. [ Google Scholar ]
• Trier-Bieniek A. Framing the telephone interview as a participant-centred tool for qualitative research. A methodological discussion. Qualitative Research. 2012; 12 (6):630–644. [ Google Scholar ]
• Valsiner J. Data as representations. Contextualizing qualitative and quantitative research strategies. Social Science Information. 2000; 39 (1):99–113. [ Google Scholar ]
• Weber, Max. 1904. 1949. Objectivity’ in social Science and social policy. Ed. Edward A. Shils and Henry A. Finch, 49–112. New York: The Free Press.

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

Published on 11.4.2024 in Vol 26 (2024)

Patients’ Experiences With Digitalization in the Health Care System: Qualitative Interview Study

Authors of this article:

Original Paper

• Christian Gybel Jensen 1 * , MA   ; 
• Frederik Gybel Jensen 1 * , MA   ; 
• Mia Ingerslev Loft 1, 2 * , MSc, PhD  

1 Department of Neurology, Rigshospitalet, Copenhagen, Denmark

2 Institute for People and Technology, Roskilde University, Roskilde, Denmark

*all authors contributed equally

Corresponding Author:

Mia Ingerslev Loft, MSc, PhD

Department of Neurology

Rigshospitalet

Inge Lehmanns Vej 8

Phone: 45 35457076

Email: [email protected]

Background: The digitalization of public and health sectors worldwide is fundamentally changing health systems. With the implementation of digital health services in health institutions, a focus on digital health literacy and the use of digital health services have become more evident. In Denmark, public institutions use digital tools for different purposes, aiming to create a universal public digital sector for everyone. However, this digitalization risks reducing equity in health and further marginalizing citizens who are disadvantaged. Therefore, more knowledge is needed regarding patients’ digital practices and experiences with digital health services.

Objective: This study aims to examine digital practices and experiences with public digital health services and digital tools from the perspective of patients in the neurology field and address the following research questions: (1) How do patients use digital services and digital tools? (2) How do they experience them?

Methods: We used a qualitative design with a hermeneutic approach. We conducted 31 semistructured interviews with patients who were hospitalized or formerly hospitalized at the department of neurology in a hospital in Denmark. The interviews were audio recorded and subsequently transcribed. The text from each transcribed interview was analyzed using manifest content analysis.

Results: The analysis provided insights into 4 different categories regarding digital practices and experiences of using digital tools and services in health care systems: social resources as a digital lifeline, possessing the necessary capabilities, big feelings as facilitators or barriers, and life without digital tools. Our findings show that digital tools were experienced differently, and specific conditions were important for the possibility of engaging in digital practices, including having access to social resources; possessing physical, cognitive, and communicative capabilities; and feeling motivated, secure, and comfortable. These prerequisites were necessary for participants to have positive experiences using digital tools in the health care system. Those who did not have these prerequisites experienced challenges and, in some cases, felt left out.

Conclusions: Experiences with digital practices and digital health services are complex and multifaceted. Engagement in digital practices for the examined population requires access to continuous assistance from their social network. If patients do not meet requirements, digital health services can be experienced as exclusionary and a source of concern. Physical, cognitive, and communicative difficulties might make it impossible to use digital tools or create more challenges. To ensure that digitalization does not create inequities in health, it is necessary for developers and institutions to be aware of the differences in digital health literacy, focus on simplifying communication with patients and next of kin, and find flexible solutions for citizens who are disadvantaged.

Introduction

In 2022, the fourth most googled question in Denmark was, “Why does MitID not work?” [ 1 ]. MitID (My ID) is a digital access tool that Danes use to enter several different private and public digital services, from bank accounts to mail from their municipality or the state. MitID is a part of many Danish citizens’ everyday lives because the public sector in Denmark is digitalized in many areas. In recent decades, digitalization has changed how governments and people interact and has demonstrated the potential to change the core functions of public sectors and delivery of public policies and services [ 2 ]. When public sectors worldwide become increasingly digitalized, this transformation extends to the public health sectors as well, and some studies argue that we are moving toward a “digital public health era” that is already impacting the health systems and will fundamentally change the future of health systems [ 3 ]. While health systems are becoming more digitalized, it is important that both patients and digitalized systems adapt to changes in accordance with each other. Digital practices of people can be understood as what people do with and through digital technologies and how people relate to technology [ 4 ]. Therefore, it is relevant to investigate digital practices and how patients perceive and experience their own use of digital tools and services, especially in relation to existing digital health services. In our study, we highlight a broad perspective on experiences with digital practices and particularly add insight into the challenges with digital practices faced by patients who have acute or chronic illness, with some of them also experiencing physical, communicative, or cognitive difficulties.

An international Organization for Economic Cooperation and Development report indicates that countries are digitalized to different extents and in different ways; however, this does not mean that countries do not share common challenges and insights into the implementation of digital services [ 2 ].

In its global Digital Government Index, Denmark is presented as one of the leading countries when it comes to public digitalization [ 2 ]. Recent statistics indicate that approximately 97% of Danish families have access to the internet at home [ 5 ]. The Danish health sector already offers many different digital services, including web-based delivery of medicine, e-consultations, patient-related outcome questionnaires, and seeking one’s own health journal or getting test results through; “Sundhed” [ 6 ] (the national health portal) and “Sundhedsjournalen” (the electronic patient record); or the apps “Medicinkortet” (the shared medication record), “Minlæge” (My Doctor, consisting of, eg, communication with the general practitioner), or “MinSP” (My Health Platform, consisting of, eg, communication with health care staff in hospitals) [ 6 - 8 ].

The Danish Digital Health Strategy from 2018 aims to create a coherent and user-friendly digital public sector for everyone [ 9 ], but statistics indicate that certain groups in society are not as digitalized as others. In particular, the older population uses digital services the least, with 5% of people aged 65 to 75 years and 18% of those aged 75 to 89 years having never used the internet in 2020 [ 5 ]. In parts of the literature, it has been problematized how the digitalization of the welfare state is related to the marginalization of older citizens who are socially disadvantaged [ 10 ]. However, statistics also indicate that the probability of using digital tools increases significantly as a person’s experience of using digital tools increases, regardless of their age or education level [ 5 ].

Understanding the digital practices of patients is important because they can use digital tools to engage with the health system and follow their own health course. Researching experiences with digital practices can be a way to better understand potential possibilities and barriers when patients use digital health services. With patients becoming more involved in their own health course and treatment, the importance of patients’ health literacy is being increasingly recognized [ 11 ]. The World Health Organization defines health literacy as the “achievement of a level of knowledge, personal skills and confidence to take action to improve personal and community health by changing personal lifestyles and living conditions” [ 12 ]. Furthermore, health literacy can be described as “a person’s knowledge and competencies to meet complex demands of health in modern society, ” and it is viewed as a critical step toward patient empowerment [ 11 , 12 ]. In a digitalized health care system, this also includes the knowledge, capabilities, and resources that individuals require to use and benefit from eHealth services, that is, “digital health literacy (eHealth literacy)” [ 13 ]. An eHealth literacy framework created by Norgaard et al [ 13 ] identified that different aspects, for example, the ability to process information and actively engage with digital services, can be viewed as important facets of digital health literacy. This argument is supported by studies that demonstrate how patients with cognitive and communicative challenges experience barriers to the use of digital tools and require different approaches in the design of digital solutions in the health sector [ 14 , 15 ]. Access to digital services and digital literacy is becoming increasingly important determinants of health, as people with digital literacy and access to digital services can facilitate improvement of health and involvement in their own health course [ 16 ].

The need for a better understanding of eHealth literacy and patients’ capabilities to meet public digital services’ demands as well as engage in their own health calls for a deeper investigation into digital practices and the use of digital tools and services from the perspective of patients with varying digital capabilities. Important focus areas to better understand digital practices and related challenges have already been highlighted in various studies. They indicate that social support, assessment of value in digital services, and systemic assessment of digital capabilities are important in the use and implementation of digital tools, and they call for better insight into complex experiences with digital services [ 13 , 17 , 18 ]. Therefore, we aimed to examine digital practices and experiences with public digital health services and digital tools from the perspective of patients, addressing the following research questions: how do patients use digital services and digital tools, and how do they experience them?

We aimed to investigate digital practices and experiences with digital health services and digital tools; therefore, we used a qualitative design and adopted a hermeneutic approach as the point of departure, which means including preexisting knowledge of digital practices but also providing room for new comprehension [ 19 ]. Our interpretive approach is underpinned by the philosophical hermeneutic approach by Gadamer et al [ 19 ], in which they described the interpretation process as a “hermeneutic circle,” where the researcher enters the interpretation process with an open mind and historical awareness of a phenomenon (preknowledge). We conducted semistructured interviews using an interview guide. This study followed the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist [ 20 ].

Setting and Participants

To gain a broad understanding of experiences with public digital health services, a purposive sampling strategy was used. All 31 participants were hospitalized or formerly hospitalized patients in a large neurological department in the capital of Denmark ( Table 1 ). We assessed whether including patients from the neurological field would give us a broad insight into the experiences of digital practices from different perspectives. The department consisted of, among others, 8 inpatient units covering, for example, acute neurology and stroke units, from which the patients were recruited. Patients admitted to a neurological department can have both acute and transient neurological diseases, such as infections in the brain, stroke, or blood clot in the brain from which they can recover completely or have persistent physical and mental difficulties, or experience chronic neurological and progressive disorders such as Parkinson disease and dementia. Some patients hospitalized in neurological care will have communicative and cognitive difficulties because of their neurological disorders. Nursing staff from the respective units helped the researchers (CGJ, FGJ, and MIL) identify patients who differed in terms of gender, age, and severity of neurological illness. Some patients (6/31, 19%) had language difficulties; however, a speech therapist assessed them as suitable participants. We excluded patients with severe cognitive difficulties and those who were not able to speak the Danish language. Including patients from the field of neurology provided an opportunity to study the experience of digital health practice from various perspectives. Hence, the sampling strategy enabled the identification and selection of information-rich participants relevant to this study [ 21 ], which is the aim of qualitative research. The participants were invited to participate by either the first (CGJ) or last author (MIL), and all invited participants (31/31, 100%) chose to participate.

All 31 participants were aged between 40 to 99 years, with an average age of 71.75 years ( Table 1 ). Out of the 31 participants, 10 (32%) had physical disabilities or had cognitive or communicative difficulties due to sequela in relation to neurological illness or other physical conditions.

Data Collection

The 31 patient interviews were conducted over a 2-month period between September and November 2022. Of the 31 patients, 20 (65%) were interviewed face-to-face at the hospital in their patient room upon admission and 11 (35%) were interviewed on the phone after being discharged. The interviews had a mean length of 20.48 minutes.

We developed a semistructured interview guide ( Table 2 ). The interview questions were developed based on the research aim, findings from our preliminary covering of literature in the field presented in the Introduction section, and identified gaps that we needed to elaborate on to be able to answer our research question [ 22 ]. The semistructured interview guide was designed to support the development of a trusting relationship and ensure the relevance of the interviews’ content [ 22 ]. The questions served as a prompt for the participants and were further supported by questions such as “please tell me more” and “please elaborate” throughout the interview, both to heighten the level of detail and to verify our understanding of the issues at play. If the participant had cognitive or communicative difficulties, communication was supported using a method called Supported Communication for Adults with Aphasia [ 23 ] during the interview.

The interviews were performed by all authors (CGJ, FGJ, and MIL individually), who were skilled in conducting interviews and qualitative research. The interviewers are not part of daily clinical practice but are employed in the department of neurology from where the patients were recruited. All interviews were audio recorded and subsequently transcribed verbatim by all 3 authors individually.

a PRO: patient-related outcome.

Data Analysis

The text from each transcribed interview was analyzed using manifest content analysis, as described by Graneheim and Lundman [ 24 ]. Content analysis is a method of analyzing written, verbal, and visual communication in a systematic way [ 25 ]. Qualitative content analysis is a structured but nonlinear process that requires researchers to move back and forth between the original text and parts of the text during the analysis. Manifest analysis is the descriptive level at which the surface structure of the text central to the phenomenon and the research question is described. The analysis was conducted as a collaborative effort between the first (CGJ) and last authors (MIL); hence, in this inductive circular process, to achieve consistency in the interpretation of the text, there was continued discussion and reflection between the researchers. The transcriptions were initially read several times to gain a sense of the whole context, and we analyzed each interview. The text was initially divided into domains that reflected the lowest degree of interpretation, as a rough structure was created in which the text had a specific area in common. The structure roughly reflected the interview guide’s themes, as guided by Graneheim and Lundman [ 24 ]. Thereafter, the text was divided into meaning units, condensed into text-near descriptions, and then abstracted and labeled further with codes. The codes were categorized based on similarities and differences. During this process, we discussed the findings to reach a consensus on the content, resulting in the final 4 categories presented in this paper.

Ethical Considerations

The interviewees received oral and written information about the study and its voluntary nature before the interviews. Written informed consent was obtained from all participants. Participants were able to opt of the study at any time. Data were anonymized and stored electronically on locked and secured servers. The Ethics Committee of the Capitol Region in Denmark was contacted before the start of the study. This study was registered and approved by the ethics committee and registered under the Danish Data Protection Agency (number P2021-839). Furthermore, the ethical principles of the Declaration of Helsinki were followed for this study.

The analysis provided insights into 4 different categories regarding digital practices and experiences of using digital tools and services in health care systems: social resources as a digital lifeline, possessing the necessary capabilities, big feelings as facilitators or barriers, and life without digital tools.

Social Resources as a Digital Lifeline

Throughout the analysis, it became evident that access to both material and social resources was of great importance when using digital tools. Most participants already possessed and had easy access to a computer, smartphone, or tablet. The few participants who did not own the necessary digital tools told us that they did not have the skills needed to use these tools. For these participants, the lack of material resources was tied particularly to a lack of knowledge and know-how, as they expressed that they would not know where to start after buying a computer—how to set it up, connect it to the internet, and use its many systems.

However, possessing the necessary material resources did not mean that the participants possessed the knowledge and skill to use digital tools. Furthermore, access to material resources was also a question of having access to assistance when needed. Some participants who had access to a computer, smartphone, and tablet and knew how to use these tools still had to obtain help when setting up hardware, updating software, or getting a new device. These participants were confident in their own ability to use digital devices but also relied on family, friends, and neighbors in their everyday use of these tools. Certain participants were explicitly aware of their own use of social resources when expressing their thoughts on digital services in health care systems:

I think it is a blessing and a curse. I think it is both. I would say that if I did not have someone around me in my family who was almost born into the digital world, then I think I would be in trouble. But I feel sorry for those who do not have that opportunity, and I know quite a few who do not. They get upset, and it’s really frustrating. [Woman, age 82 years]

The participants’ use of social resources indicates that learning skills and using digital tools are not solely individual tasks but rather continuously involve engagement with other people, particularly whenever a new unforeseen problem arises or when the participants want a deeper understanding of the tools they are using:

If tomorrow I have to get a new ipad...and it was like that when I got this one, then I had to get XXX to come and help me move stuff and he was sweet to help with all the practical stuff. I think I would have cursed a couple of times (if he hadn’t been there), but he is always helpful, but at the same time he is also pedagogic so I hope that next time he showed me something I will be able to do it. [Man, age 71 years]

For some participants, obtaining assistance from a more experienced family member was experienced as an opportunity to learn, whereas for other participants, their use of public digital services was even tied directly to assistance from a spouse or family member:

My wife, she has access to mine, so if something comes up, she can just go in and read, and we can talk about it afterwards what (it is). [Man, age 85 years]

The participants used social resources to navigate digital systems and understand and interpret communication from the health care system through digital devices. Another example of this was the participants who needed assistance to find, answer, and understand questionnaires from the health care department. Furthermore, social resources were viewed as a support system that made participants feel more comfortable and safer when operating digital tools. The social resources were particularly important when overcoming unforeseen and new challenges and when learning new skills related to the use of digital tools. Participants with physical, cognitive, and communicative challenges also explained how social resources were of great importance in their ability to use digital tools.

Possessing the Necessary Capabilities

The findings indicated that possessing the desire and knowing how to use digital tools are not always enough to engage with digital services successfully. Different health issues can carry consequences for motor skills and mobility. Some of these consequences were visibly affecting how our participants interacted with digital devices, and these challenges were somewhat easy to discover. However, our participants revealed hidden challenges that posed difficulties. In some specific cases, cognitive and communicative inabilities can make it difficult to use digital tools, and this might not always be clear until the individual tries to use a device’s more complex functions. An example of this is that some participants found it easy to turn on a computer and use it to write but difficult to go through security measures on digital services or interpret and understand digital language. Remembering passwords and logging on to systems created challenges, particularly for those experiencing health issues that directly affect memory and cognitive abilities, who expressed concerns about what they were able to do through digital tools:

I think it is very challenging because I would like to use it how I used to before my stroke; (I) wish that everything (digital skills) was transferred, but it just isn’t. [Man, age 80 years]

Despite these challenges, the participants demonstrated great interest in using digital tools, particularly regarding health care services and their own well-being. However, sometimes, the challenges that they experienced could not be conquered merely by motivation and good intentions. Another aspect of these challenges was the amount of extra time and energy that the participants had to spend on digital services. A patient diagnosed with Parkinson disease described how her symptoms created challenges that changed her digital practices:

Well it could for example be something like following a line in the device. And right now it is very limited what I can do with this (iPhone). Now I am almost only using it as a phone, and that is a little sad because I also like to text and stuff, but I also find that difficult (...) I think it is difficult to get an overview. [Woman, age 62 years]

Some participants said that after they were discharged from the hospital, they did not use the computer anymore because it was too difficult and too exhausting , which contributed to them giving up . Using digital tools already demanded a certain amount of concentration and awareness, and some diseases and health conditions affected these abilities further.

Big Feelings as Facilitators or Barriers

The findings revealed a wide range of digital practices in which digital tools were used as a communication device, as an entertainment device, and as a practical and informative tool for ordering medicine, booking consultations, asking health-related questions, or receiving email from public institutions. Despite these different digital practices, repeating patterns and arguments appeared when the participants were asked why they learned to use digital tools or wanted to improve their skills. A repeating argument was that they wanted to “follow the times, ” or as a participant who was still not satisfied with her digital skills stated:

We should not go against the future. [Woman, age 89 years]

The participants expressed a positive view of the technological developments and possibilities that digital devices offered, and they wanted to improve their knowledge and skills related to digital practice. For some participants, this was challenging, and they expressed frustration over how technological developments “moved too fast ,” but some participants interpreted these challenges as a way to “keep their mind sharp. ”

Another recurring pattern was that the participants expressed great interest in using digital services related to the health care system and other public institutions. The importance of being able to navigate digital services was explicitly clear when talking about finding test answers, written electronic messages, and questionnaires from the hospital or other public institutions. Keeping up with developments, communicating with public institutions, and taking an interest in their own health and well-being were described as good reasons to learn to use digital tools.

However, other aspects also affected these learning facilitators. Some participants felt alienated while using digital tools and described the practice as something related to feelings of anxiety, fear, and stupidity as well as something that demanded “a certain amount of courage. ” Some participants felt frustrated with the digital challenges they experienced, especially when the challenges were difficult to overcome because of their physical conditions:

I get sad because of it (digital challenges) and I get very frustrated and it takes a lot of time because I have difficulty seeing when I look away from the computer and have to turn back again to find out where I was and continue there (...) It pains me that I have to use so much time on it. [Man, age 71 years]

Fear of making mistakes, particularly when communicating with public institutions, for example, the health care system, was a common pattern. Another pattern was the fear of misinterpreting the sender and the need to ensure that the written electronic messages were actually from the described sender. Some participants felt that they were forced to learn about digital tools because they cared a lot about the services. Furthermore, fears of digital services replacing human interaction were a recurring concern among the participants. Despite these initial and recurring feelings, some participants learned how to navigate the digital services that they deemed relevant. Another recurring pattern in this learning process was repetition, the practice of digital skills, and consistent assistance from other people. One participant expressed the need to use the services often to remember the necessary skills:

Now I can figure it out because now I’ve had it shown 10 times. But then three months still pass... and then I think...how was it now? Then I get sweat on my forehead (feel nervous) and think; I’m not an idiot. [Woman, age 82 years]

For some participants, learning how to use digital tools demanded time and patience, as challenges had to be overcome more than once because they reappeared until the use of digital tools was more automatized into their everyday lives. Using digital tools and health services was viewed as easier and less stressful when part of everyday routines.

Life Without Digital Tools: Not a Free Choice

Even though some participants used digital tools daily, other participants expressed that it was “too late for them.” These participants did not view it as a free choice but as something they had to accept that they could not do. They wished that they could have learned it earlier in life but did not view it as a possibility in the future. Furthermore, they saw potential in digital services, including digital health care services, but they did not know exactly what services they were missing out on. Despite this lack of knowledge, they still felt sad about the position they were in. One participant expressed what she thought regarding the use of digital tools in public institutions:

Well, I feel alright about it, but it is very, very difficult for those of us who do not have it. Sometimes you can feel left out—outside of society. And when you do not have one of those (computers)...A reference is always made to w and w (www.) and then you can read on. But you cannot do that. [Woman, age 94 years]

The feeling of being left out of society was consistent among the participants who did not use digital tools. To them, digital systems seemed to provide unfair treatment based on something outside of their own power. Participants who were heavily affected by their medical conditions and could not use digital services also felt left out because they saw the advantages of using digital tools. Furthermore, a participant described the feelings connected to the use of digital tools in public institutions:

It is more annoying that it does not seem to work out in my favour. [Woman, age 62 years]

These statements indicated that it is possible for individuals to want to use digital tools and simultaneously find them too challenging. These participants were aware that there are consequences of not using digital tools, and that saddens them, as they feel like they are not receiving the same treatment as other people in society and the health care system.

Principal Findings

The insights from our findings demonstrated that our participants had different digital practices and different experiences with digital tools and services; however, the analysis also highlighted patterns related to how digital services and tools were used. Specific conditions were important for the possibility of digital practice, including having access to social resources; possessing the necessary capabilities; and feeling motivated, secure, and comfortable . These prerequisites were necessary to have positive experiences using digital tools in the health care system, although some participants who lived up to these prerequisites were still skeptical toward digital solutions. Others who did not live up to these prerequisites experienced challenges and even though they were aware of opportunities, this awareness made them feel left out. A few participants even viewed the digital tools as a threat to their participation in society. This supports the notion of Norgaard et al [ 13 ] that the attention paid to digital capability demands from eHealth systems is very important. Furthermore, our findings supported the argument of Hjeltholt and Papazu [ 17 ] that it is important to better understand experiences related to digital services. In our study, we accommodate this request and bring forth a broad perspective on experiences with digital practices; we particularly add insight into the challenges with digital practices for patients who also have acute or chronic illness, with some of them also experiencing physical, communicative, and cognitive difficulties. To our knowledge, there is limited existing literature focusing on digital practices that do not have a limited scope, for example, a focus on perspectives on eHealth literacy in the use of apps [ 26 ] or intervention studies with a focus on experiences with digital solutions, for example, telemedicine during the COVID-19 pandemic [ 27 ]. As mentioned by Hjeltholt et al [ 10 ], certain citizens are dependent on their own social networks in the process of using and learning digital tools. Rasi et al [ 28 ] and Airola et al [ 29 ] argued that digital health literacy is situated and should include the capabilities of the individual’s social network. Our findings support these arguments that access to social resources is an important condition; however, the findings also highlight that these resources can be particularly crucial in the use of digital health services, for example, when interpreting and understanding digital and written electronic messages related to one’s own health course or when dealing with physical, cognitive, and communicative disadvantages. Therefore, we argue that the awareness of the disadvantages is important if we want to understand patients’ digital capabilities, and the inclusion of the next of kin can be evident in unveiling challenges that are unknown and not easily visible or when trying to reach patients with digital challenges through digital means.

Studies by Kayser et al [ 30 ] and Kanoe et al [ 31 ] indicated that patients’ abilities to interpret and understand digital health–related services and their benefits are important for the successful implementation of eHealth services—an argument that our findings support. Health literacy in both digital and physical contexts is important if we want to understand how to better design and implement services. Our participants’ statements support the argument that communication through digital means cannot be viewed as similar to face-to-face communication and that an emphasis on digital health literacy demonstrates how health systems are demanding different capabilities from the patients [ 13 ]. We argue that it is important to communicate the purposes of digital services so that both the patient and their next of kin know why they participate and how it can benefit them. Therefore, it is important to make it as clear as possible that digital health services can benefit the patient and that these services are developed to support information, communication, and dialogue between patients and health professionals. However, our findings suggest that even after interpreting and understanding the purposes of digital health services, some patients may still experience challenges when using digital tools.

Therefore, it is important to understand how and why patients learn digital skills, particularly because both experience with digital devices and estimation of the value of digital tools have been highlighted as key factors for digital practices [ 5 , 18 ]. Our findings indicate that a combination of these factors is important, as recognizing the value of digital tools was not enough to facilitate the necessary learning process for some of our participants. Instead, our participants described the use of digital tools as complex and continuous processes in which automation of skills, assistance from others, and time to relearn forgotten knowledge were necessary and important facilitators for learning and understanding digital tools as well as becoming more comfortable and confident in the use of digital health services. This was particularly important, as it was more encouraging for our participants to learn digital tools when they felt secure, instead of feeling afraid and anxious, a point that Bailey et al [ 18 ] also highlighted. The value of digital solutions and the will to learn were greater when challenges were viewed as something to overcome and learn from instead of something that created a feeling of being stupid. This calls for attention on how to simplify and explain digital tools and services so that users do not feel alienated. Our findings also support the argument that digital health literacy should take into account emotional well-being related to digital practice [ 32 ].

The various perspectives that our participants provided regarding the use of digital tools in the health care system indicate that patients are affected by the use of digital health services and their own capabilities to use digital tools. Murray et al [ 33 ] argued that the use of digital tools in health sectors has the potential to improve health and health delivery by improving efficacy, efficiency, accessibility, safety, and personalization, and our participants also highlighted these positive aspects. However, different studies found that some patients, particularly older adults considered socially vulnerable, have lower digital health literacy [ 10 , 34 , 35 ], which is an important determinant of health and may widen disparities and inequity in health care [ 16 ]. Studies on older adult populations’ adaptation to information and communication technology show that engaging with this technology can be limited by the usability of technology, feelings of anxiety and concern, self-perception of technology use, and the need for assistance and inclusive design [ 36 ]. Our participants’ experiences with digital practices support the importance of these focus areas, especially when primarily older patients are admitted to hospitals. Furthermore, our findings indicate that some older patients who used to view themselves as being engaged in their own health care felt more distanced from the health care system because of digital services, and some who did not have the capabilities to use digital tools felt that they were treated differently compared to the rest of society. They did not necessarily view themselves as vulnerable but felt vulnerable in the specific experience of trying to use digital services because they wished that they were more capable. Moreover, this was the case for patients with physical and cognitive difficulties, as they were not necessarily aware of the challenges before experiencing them. Drawing on the phenomenological and feministic approach by Ahmed [ 37 ], these challenges that make patients feel vulnerable are not necessarily visible to others but can instead be viewed as invisible institutional “walls” that do not present themselves before the patient runs into them. Some participants had to experience how their physical, cognitive, or communicative difficulties affected their digital practice to realize that they were not as digitally capable as they once were or as others in society. Furthermore, viewed from this perspective, our findings could be used to argue that digital capabilities should be viewed as a privilege tied to users’ physical bodies and that digital services in the health care system are indirectly making patients without this privilege vulnerable. This calls for more attention to the inequities that digital tools and services create in health care systems and awareness that those who do not use digital tools are not necessarily indifferent about the consequences. Particularly, in a context such as the Danish one, in which the digital strategy is to create an intertwined and user-friendly public digital sector for everyone, it needs to be understood that patients have different digital capabilities and needs. Although some have not yet had a challenging experience that made them feel vulnerable, others are very aware that they receive different treatment and feel that they are on their own or that the rest of the society does not care about them. Inequities in digital health care, such as these, can and should be mitigated or prevented, and our investigation into the experiences with digital practices can help to show that we are creating standards and infrastructures that deliberately exclude the perspectives of those who are most in need of the services offered by the digital health care system [ 8 ]. Therefore, our findings support the notions that flexibility is important in the implementation of universal public digital services [ 17 ]; that it is important to adjust systems in accordance with patients’ eHealth literacy and not only improve the capabilities of individuals [ 38 ]; and that the development and improvement of digital health literacy are not solely an individual responsibility but are also tied to ways in which institutions organize, design, and implement digital tools and services [ 39 ].

Limitations

This qualitative study provided novel insights into the experiences with public digital health services from the perspective of patients in the Danish context, enabling a deeper understanding of how digital health services and digital tools are experienced and used. This helps build a solid foundation for future interventions aimed at digital health literacy and digital health interventions. However, this study has some limitations. First, the study was conducted in a country where digitalization is progressing quickly, and people, therefore, are accustomed to this pace. Therefore, readers must be aware of this. Second, the study included patients with different neurological conditions; some of their digital challenges were caused or worsened by these neurological conditions and are, therefore, not applicable to all patients in the health system. However, the findings provided insights into the patients’ digital practices before their conditions and other challenges not connected to neurological conditions shared by patients. Third, the study was broad, and although a large number of informants was included, from a qualitative research perspective, we would recommend additional research in this field to develop interventions that target digital health literacy and the use of digital health services.

Conclusions

Experiences with digital tools and digital health services are complex and multifaceted. The advantages in communication, finding information, or navigating through one’s own health course work as facilitators for engaging with digital tools and digital health services. However, this is not enough on its own. Furthermore, feeling secure and motivated and having time to relearn and practice skills are important facilitators. Engagement in digital practices for the examined population requires access to continuous assistance from their social network. If patients do not meet requirements, digital health services can be experienced as exclusionary and a source of concern. Physical, cognitive, and communicative difficulties might make it impossible to use digital tools or create more challenges that require assistance. Digitalization of the health care system means that patients do not have the choice to opt out of using digital services without having consequences, resulting in them receiving a different treatment than others. To ensure digitalization does not create inequities in health, it is necessary for developers and the health institutions that create, design, and implement digital services to be aware of differences in digital health literacy and to focus on simplifying communication with patients and next of kin through and about digital services. It is important to focus on helping individuals meet the necessary conditions and finding flexible solutions for those who do not have the same privileges as others if the public digital sector is to work for everyone.

Acknowledgments

The authors would like to thank all the people who gave their time to be interviewed for the study, the clinical nurse specialists who facilitated interviewing patients, and the other nurses on shift who assisted in recruiting participants.

Conflicts of Interest

None declared.

• Year in search 2022. Google Trends. URL: https://trends.google.com/trends/yis/2022/DK/ [accessed 2024-04-02]
• Digital government index: 2019. Organisation for Economic Cooperation and Development. URL: https://www.oecd-ilibrary.org/content/paper/4de9f5bb-en [accessed 2024-04-02]
• Azzopardi-Muscat N, Sørensen K. Towards an equitable digital public health era: promoting equity through a health literacy perspective. Eur J Public Health. Oct 01, 2019;29(Supplement_3):13-17. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Digital practices. Umeå University. URL: https://www.umu.se/en/humlab/research/digital-practice/ [accessed 2024-04-02]
• It-anvendelse i befolkningen 2020. Danmarks Statistik. URL: https://www.dst.dk/da/Statistik/nyheder-analyser-publ/Publikationer/VisPub?cid=29450 [accessed 2024-04-02]
• Sundhed.dk homepage. Sundhed.dk. URL: https://www.sundhed.dk/borger/ [accessed 2024-04-02]
• Nøhr C, Bertelsen P, Vingtoft S, Andersen SK. Digitalisering af Det Danske Sundhedsvæsen. Odense, Denmark. Syddansk Universitetsforlag; 2019.
• Eriksen J, Ebbesen M, Eriksen KT, Hjermitslev C, Knudsen C, Bertelsen P, et al. Equity in digital healthcare - the case of Denmark. Front Public Health. Sep 6, 2023;11:1225222. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Digital health strategy. Sundhedsdatastyrelsen. URL: https://sundhedsdatastyrelsen.dk/da/english/digital_health_solutions/digital_health_strategy [accessed 2024-04-02]
• Hjelholt M, Schou J, Bojsen LB, Yndigegn SL. Digital marginalisering af udsatte ældre: arbejdsrapport 2. IT-Universitetet i København. 2018. URL: https://egv.dk/images/Projekter/Projekter_2018/EGV_arbejdsrapport_2.pdf [accessed 2024-04-02]
• Sørensen K, Van den Broucke S, Fullam J, Doyle G, Pelikan J, Slonska Z, et al. Health literacy and public health: a systematic review and integration of definitions and models. BMC Public Health. Jan 25, 2012;12(1):80. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Improving health literacy. World Health Organization. URL: https://www.who.int/activities/improving-health-literacy [accessed 2024-04-02]
• Norgaard O, Furstrand D, Klokker L, Karnoe KA, Batterham R, Kayser L, et al. The e-health literacy framework: a conceptual framework for characterizing e-health users and their interaction with e-health systems. Knowl Manag E Learn. 2015;7(4). [ CrossRef ]
• Kramer JM, Schwartz A. Reducing barriers to patient-reported outcome measures for people with cognitive impairments. Arch Phys Med Rehabil. Aug 2017;98(8):1705-1715. [ CrossRef ] [ Medline ]
• Menger F, Morris J, Salis C. Aphasia in an internet age: wider perspectives on digital inclusion. Aphasiology. 2016;30(2-3):112-132. [ CrossRef ]
• Richardson S, Lawrence K, Schoenthaler AM, Mann D. A framework for digital health equity. NPJ Digit Med. Aug 18, 2022;5(1):119. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Hjelholt M, Papazu I. "De har fået NemID, men det er ikke nemt for mig” - Digital rum(me)lighed i den danske velfærdsstat. Social Kritik. 2021;2021-2(163). [ FREE Full text ]
• Bailey C, Sheehan C. Technology, older persons’ perspectives and the anthropological ethnographic lens. Alter. 2009;3(2):96-109. [ CrossRef ]
• Gadamer HG, Weinsheimer HG, Marshall DG. Truth and Method. New York, NY. Crossroad Publishing Company; 1991.
• Tong A, Sainsbury P, Craig J. Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups. Int J Qual Health Care. Dec 16, 2007;19(6):349-357. [ CrossRef ] [ Medline ]
• Polit DF, Beck CT. Nursing Research: Generating and Assessing Evidence for Nursing Practice. Philadelphia, PA. Lippincott Williams & Wilkins, Inc; 2012.
• Kvale S, Brinkmann S. InterViews: Learning the Craft of Qualitative Research Interviewing. Thousand Oaks, CA. SAGE Publications; 2009.
• Kagan A. Supported conversation for adults with aphasia: methods and resources for training conversation partners. Aphasiology. Sep 1998;12(9):816-830. [ CrossRef ]
• Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. Feb 2004;24(2):105-112. [ CrossRef ] [ Medline ]
• Krippendorff K. Content Analysis: An Introduction to Its Methodology. Thousand Oaks, CA. SAGE Publications; 1980.
• Klösch M, Sari-Kundt F, Reibnitz C, Osterbrink J. Patients' attitudes toward their health literacy and the use of digital apps in health and disease management. Br J Nurs. Nov 25, 2021;30(21):1242-1249. [ CrossRef ] [ Medline ]
• Datta P, Eiland L, Samson K, Donovan A, Anzalone AJ, McAdam-Marx C. Telemedicine and health access inequalities during the COVID-19 pandemic. J Glob Health. Dec 03, 2022;12:05051. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Rasi P, Lindberg J, Airola E. Older service users’ experiences of learning to use eHealth applications in sparsely populated healthcare settings in Northern Sweden and Finland. Educ Gerontol. Nov 24, 2020;47(1):25-35. [ CrossRef ]
• Airola E, Rasi P, Outila M. Older people as users and non-users of a video conferencing service for promoting social connectedness and well-being – a case study from Finnish Lapland. Educ Gerontol. Mar 29, 2020;46(5):258-269. [ CrossRef ]
• Kayser L, Kushniruk A, Osborne RH, Norgaard O, Turner P. Enhancing the effectiveness of consumer-focused health information technology systems through eHealth literacy: a framework for understanding users' needs. JMIR Hum Factors. May 20, 2015;2(1):e9. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Karnoe A, Furstrand D, Christensen KB, Norgaard O, Kayser L. Assessing competencies needed to engage with digital health services: development of the ehealth literacy assessment toolkit. J Med Internet Res. May 10, 2018;20(5):e178. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Nielsen AS, Hanna L, Larsen BF, Appel CW, Osborne RH, Kayser L. Readiness, acceptance and use of digital patient reported outcome in an outpatient clinic. Health Informatics J. Jun 03, 2022;28(2):14604582221106000. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Murray E, Hekler EB, Andersson G, Collins LM, Doherty A, Hollis C, et al. Evaluating digital health interventions: key questions and approaches. Am J Prev Med. Nov 2016;51(5):843-851. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Chesser A, Burke A, Reyes J, Rohrberg T. Navigating the digital divide: a systematic review of eHealth literacy in underserved populations in the United States. Inform Health Soc Care. Feb 24, 2016;41(1):1-19. [ CrossRef ] [ Medline ]
• Chesser AK, Keene Woods N, Smothers K, Rogers N. Health literacy and older adults: a systematic review. Gerontol Geriatr Med. Mar 15, 2016;2:2333721416630492. [ FREE Full text ] [ CrossRef ] [ Medline ]
• Mitra S, Singh A, Rajendran Deepam S, Asthana MK. Information and communication technology adoption among the older people: a qualitative approach. Health Soc Care Community. Nov 21, 2022;30(6):e6428-e6437. [ CrossRef ] [ Medline ]
• Ahmed S. How not to do things with words. Wagadu. 2016. URL: https://sites.cortland.edu/wagadu/wp-content/uploads/sites/3/2017/02/v16-how-not-to-do-ahmed.pdf [accessed 2024-04-02]
• Monkman H, Kushniruk AW. eHealth literacy issues, constructs, models, and methods for health information technology design and evaluation. Knowl Manag E Learn. 2015;7(4). [ CrossRef ]
• Brørs G, Norman CD, Norekvål TM. Accelerated importance of eHealth literacy in the COVID-19 outbreak and beyond. Eur J Cardiovasc Nurs. Aug 15, 2020;19(6):458-461. [ FREE Full text ] [ CrossRef ] [ Medline ]

Abbreviations

Edited by A Mavragani; submitted 14.03.23; peer-reviewed by G Myreteg, J Eriksen, M Siermann; comments to author 18.09.23; revised version received 09.10.23; accepted 27.02.24; published 11.04.24.

©Christian Gybel Jensen, Frederik Gybel Jensen, Mia Ingerslev Loft. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 11.04.2024.

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