what is qualitative research definition

Have a language expert improve your writing

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

• Knowledge Base

Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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

Prevent plagiarism. Run a free check.

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

Receive feedback on language, structure, and formatting

Professional editors proofread and edit your paper by focusing on:

• Academic style
• Vague sentences
• Style consistency

See an example

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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.

Bhandari, P. (2023, June 22). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved August 30, 2024, from https://www.scribbr.com/methodology/qualitative-research/

Is this article helpful?

Pritha Bhandari

Other students also liked, qualitative vs. quantitative research | differences, examples & methods, how to do thematic analysis | step-by-step guide & examples, what is your plagiarism score.

• Privacy Policy

Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

You may also like

Quantitative Research – Methods, Types and...

Descriptive Research Design – Types, Methods and...

Experimental Design – Types, Methods, Guide

Survey Research – Types, Methods, Examples

Qualitative Research Methods

Explanatory Research – Types, Methods, Guide

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
• Next: Choose an approach >>
• Choose an approach
• Find studies
• Learn methods
• Getting Started
• Get software
• Get data for secondary analysis
• Network with researchers

• Last Updated: Aug 9, 2024 2:09 PM
• URL: https://guides.library.stanford.edu/qualitative_research

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.

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.

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

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.

• 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 numerically. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.
• Qualitative research gathers non-numerical data (words, images, sounds) to explore subjective experiences and attitudes, often via observation and interviews. It aims to produce detailed descriptions and uncover new insights about the studied phenomenon.

On This Page:

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

• Mixed methods research
• 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

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

What is qualitative research?

Qualitative research is a process of naturalistic inquiry that seeks an in-depth understanding of social phenomena within their natural setting. It focuses on the "why" rather than the "what" of social phenomena and relies on the direct experiences of human beings as meaning-making agents in their every day lives. Rather than by logical and statistical procedures, qualitative researchers use multiple systems of inquiry for the study of human phenomena including biography, case study, historical analysis, discourse analysis, ethnography, grounded theory, and phenomenology.

University of Utah College of Nursing, (n.d.). What is qualitative research? [Guide] Retrieved from  https://nursing.utah.edu/research/qualitative-research/what-is-qualitative-research.php#what 

The following video will explain the fundamentals of qualitative research.

• << Previous: What is Quantitative Research?
• Next: Quantitative vs Qualitative >>
• Last Updated: Aug 19, 2024 2:09 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 Research Definition

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

• Share on Twitter Share on Twitter
• Share on Facebook Share on Facebook
• Share on LinkedIn Share on LinkedIn

Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full  editorial guidelines .

Table of Contents

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

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

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

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

Quantium Data Analytics

Explore the power of data and its ability to power breakthrough possibilities for individuals, organisations and societies with this free job simulation from Quantium.

Avg. Time: 4 to 5 hours

Skills you’ll build: Data validation, data visualisation, data wrangling, programming, data analysis, commercial thinking, statistical testing, presentation skills

Who Uses Qualitative Research?

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

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

Other careers that may involve qualitative research include: 

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

Electronic Arts Product Management

Learn how product managers leverage qualitative and other types of research to build and improve products in this free job simulation from EA.

Avg. Time: 1 to 2 hours

Skills you’ll build: Critical thinking, problem solving, performance metrics, written communication, project planning

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

Grounded Theory

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

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

Action Research

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

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

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

Phenomenological Research

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

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

GE Aerospace Human Resources

Learn the research and conflict resolution skills necessary for a career in human resources in this free job simulation from GE.

Avg. Time: 3 to 4 hours

Skills you’ll build: Feedback giving, communication skills, empowering with insights, basics of lean, process mapping, continuous improvement tools, dataset handling in Excel

Ethnography

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

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

Case Studies

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

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

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

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

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

Find your career fit

See what career path is right for you with our free career quiz!

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

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

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

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

JPMorgan Quantitative Research

Discover how bankers use quantitative methods to analyze businesses and industry trends with this free job simulation.

Avg. Time: 6 to 7 hours

Skills you’ll build: Programming, data analysis, Python, critical thinking, statistics, dynamic programming

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

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

Grow your skills and explore your career options with Forage’s free job simulations .

Image credit: Canva

Related Posts

6 negotiation skills to level up your work life, how to build conflict resolution skills: case studies and examples, what is github uses and getting started, upskill with forage.

Top companies are hiring now!

18 Qualitative Research Examples

Chris Drew (PhD)

Dr. Chris Drew is the founder of the Helpful Professor. He holds a PhD in education and has published over 20 articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education. [Image Descriptor: Photo of Chris]

Learn about our Editorial Process

Qualitative research is an approach to scientific research that involves using observation to gather and analyze non-numerical, in-depth, and well-contextualized datasets.

It serves as an integral part of academic, professional, and even daily decision-making processes (Baxter & Jack, 2008).

Methods of qualitative research encompass a wide range of techniques, from in-depth personal encounters, like ethnographies (studying cultures in-depth) and autoethnographies (examining one’s own cultural experiences), to collection of diverse perspectives on topics through methods like interviewing focus groups (gatherings of individuals to discuss specific topics).

Qualitative Research Examples

1. ethnography.

Definition: Ethnography is a qualitative research design aimed at exploring cultural phenomena. Rooted in the discipline of anthropology , this research approach investigates the social interactions, behaviors, and perceptions within groups, communities, or organizations.

Ethnographic research is characterized by extended observation of the group, often through direct participation, in the participants’ environment. An ethnographer typically lives with the study group for extended periods, intricately observing their everyday lives (Khan, 2014).

It aims to present a complete, detailed and accurate picture of the observed social life, rituals, symbols, and values from the perspective of the study group.

Example of Ethnographic Research

Title: “ The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity “

Citation: Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Overview: This study by Evans (2010) provides a rich narrative of young adult male identity as experienced in everyday life. The author immersed himself among a group of young men, participating in their activities and cultivating a deep understanding of their lifestyle, values, and motivations. This research exemplified the ethnographic approach, revealing complexities of the subjects’ identities and societal roles, which could hardly be accessed through other qualitative research designs.

Read my Full Guide on Ethnography Here

2. Autoethnography

Definition: Autoethnography is an approach to qualitative research where the researcher uses their own personal experiences to extend the understanding of a certain group, culture, or setting. Essentially, it allows for the exploration of self within the context of social phenomena.

Unlike traditional ethnography, which focuses on the study of others, autoethnography turns the ethnographic gaze inward, allowing the researcher to use their personal experiences within a culture as rich qualitative data (Durham, 2019).

The objective is to critically appraise one’s personal experiences as they navigate and negotiate cultural, political, and social meanings. The researcher becomes both the observer and the participant, intertwining personal and cultural experiences in the research.

Example of Autoethnographic Research

Title: “ A Day In The Life Of An NHS Nurse “

Citation: Osben, J. (2019). A day in the life of a NHS nurse in 21st Century Britain: An auto-ethnography. The Journal of Autoethnography for Health & Social Care. 1(1).

Overview: This study presents an autoethnography of a day in the life of an NHS nurse (who, of course, is also the researcher). The author uses the research to achieve reflexivity, with the researcher concluding: “Scrutinising my practice and situating it within a wider contextual backdrop has compelled me to significantly increase my level of scrutiny into the driving forces that influence my practice.”

Read my Full Guide on Autoethnography Here

3. Semi-Structured Interviews

Definition: Semi-structured interviews stand as one of the most frequently used methods in qualitative research. These interviews are planned and utilize a set of pre-established questions, but also allow for the interviewer to steer the conversation in other directions based on the responses given by the interviewee.

In semi-structured interviews, the interviewer prepares a guide that outlines the focal points of the discussion. However, the interview is flexible, allowing for more in-depth probing if the interviewer deems it necessary (Qu, & Dumay, 2011). This style of interviewing strikes a balance between structured ones which might limit the discussion, and unstructured ones, which could lack focus.

Example of Semi-Structured Interview Research

Title: “ Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review “

Citation: Puts, M., et al. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Overview: Puts et al. (2014) executed an extensive systematic review in which they conducted semi-structured interviews with older adults suffering from cancer to examine the factors influencing their adherence to cancer treatment. The findings suggested that various factors, including side effects, faith in healthcare professionals, and social support have substantial impacts on treatment adherence. This research demonstrates how semi-structured interviews can provide rich and profound insights into the subjective experiences of patients.

4. Focus Groups

Definition: Focus groups are a qualitative research method that involves organized discussion with a selected group of individuals to gain their perspectives on a specific concept, product, or phenomenon. Typically, these discussions are guided by a moderator.

During a focus group session, the moderator has a list of questions or topics to discuss, and participants are encouraged to interact with each other (Morgan, 2010). This interactivity can stimulate more information and provide a broader understanding of the issue under scrutiny. The open format allows participants to ask questions and respond freely, offering invaluable insights into attitudes, experiences, and group norms.

Example of Focus Group Research

Title: “ Perspectives of Older Adults on Aging Well: A Focus Group Study “

Citation: Halaweh, H., Dahlin-Ivanoff, S., Svantesson, U., & Willén, C. (2018). Perspectives of older adults on aging well: a focus group study. Journal of aging research .

Overview: This study aimed to explore what older adults (aged 60 years and older) perceived to be ‘aging well’. The researchers identified three major themes from their focus group interviews: a sense of well-being, having good physical health, and preserving good mental health. The findings highlight the importance of factors such as positive emotions, social engagement, physical activity, healthy eating habits, and maintaining independence in promoting aging well among older adults.

5. Phenomenology

Definition: Phenomenology, a qualitative research method, involves the examination of lived experiences to gain an in-depth understanding of the essence or underlying meanings of a phenomenon.

The focus of phenomenology lies in meticulously describing participants’ conscious experiences related to the chosen phenomenon (Padilla-Díaz, 2015).

In a phenomenological study, the researcher collects detailed, first-hand perspectives of the participants, typically via in-depth interviews, and then uses various strategies to interpret and structure these experiences, ultimately revealing essential themes (Creswell, 2013). This approach focuses on the perspective of individuals experiencing the phenomenon, seeking to explore, clarify, and understand the meanings they attach to those experiences.

Example of Phenomenology Research

Title: “ A phenomenological approach to experiences with technology: current state, promise, and future directions for research ”

Citation: Cilesiz, S. (2011). A phenomenological approach to experiences with technology: Current state, promise, and future directions for research. Educational Technology Research and Development, 59 , 487-510.

Overview: A phenomenological approach to experiences with technology by Sebnem Cilesiz represents a good starting point for formulating a phenomenological study. With its focus on the ‘essence of experience’, this piece presents methodological, reliability, validity, and data analysis techniques that phenomenologists use to explain how people experience technology in their everyday lives.

6. Grounded Theory

Definition: Grounded theory is a systematic methodology in qualitative research that typically applies inductive reasoning . The primary aim is to develop a theoretical explanation or framework for a process, action, or interaction grounded in, and arising from, empirical data (Birks & Mills, 2015).

In grounded theory, data collection and analysis work together in a recursive process. The researcher collects data, analyses it, and then collects more data based on the evolving understanding of the research context. This ongoing process continues until a comprehensive theory that represents the data and the associated phenomenon emerges – a point known as theoretical saturation (Charmaz, 2014).

Example of Grounded Theory Research

Title: “ Student Engagement in High School Classrooms from the Perspective of Flow Theory “

Citation: Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158–176.

Overview: Shernoff and colleagues (2003) used grounded theory to explore student engagement in high school classrooms. The researchers collected data through student self-reports, interviews, and observations. Key findings revealed that academic challenge, student autonomy, and teacher support emerged as the most significant factors influencing students’ engagement, demonstrating how grounded theory can illuminate complex dynamics within real-world contexts.

7. Narrative Research

Definition: Narrative research is a qualitative research method dedicated to storytelling and understanding how individuals experience the world. It focuses on studying an individual’s life and experiences as narrated by that individual (Polkinghorne, 2013).

In narrative research, the researcher collects data through methods such as interviews, observations , and document analysis. The emphasis is on the stories told by participants – narratives that reflect their experiences, thoughts, and feelings.

These stories are then interpreted by the researcher, who attempts to understand the meaning the participant attributes to these experiences (Josselson, 2011).

Example of Narrative Research

Title: “Narrative Structures and the Language of the Self”

Citation: McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative . American Psychological Association.

Overview: In this innovative study, McAdams et al. (2006) employed narrative research to explore how individuals construct their identities through the stories they tell about themselves. By examining personal narratives, the researchers discerned patterns associated with characters, motivations, conflicts, and resolutions, contributing valuable insights about the relationship between narrative and individual identity.

8. Case Study Research

Definition: Case study research is a qualitative research method that involves an in-depth investigation of a single instance or event: a case. These ‘cases’ can range from individuals, groups, or entities to specific projects, programs, or strategies (Creswell, 2013).

The case study method typically uses multiple sources of information for comprehensive contextual analysis. It aims to explore and understand the complexity and uniqueness of a particular case in a real-world context (Merriam & Tisdell, 2015). This investigation could result in a detailed description of the case, a process for its development, or an exploration of a related issue or problem.

Example of Case Study Research

Title: “ Teacher’s Role in Fostering Preschoolers’ Computational Thinking: An Exploratory Case Study “

Citation: Wang, X. C., Choi, Y., Benson, K., Eggleston, C., & Weber, D. (2021). Teacher’s role in fostering preschoolers’ computational thinking: An exploratory case study. Early Education and Development , 32 (1), 26-48.

Overview: This study investigates the role of teachers in promoting computational thinking skills in preschoolers. The study utilized a qualitative case study methodology to examine the computational thinking scaffolding strategies employed by a teacher interacting with three preschoolers in a small group setting. The findings highlight the importance of teachers’ guidance in fostering computational thinking practices such as problem reformulation/decomposition, systematic testing, and debugging.

Read about some Famous Case Studies in Psychology Here

9. Participant Observation

Definition: Participant observation has the researcher immerse themselves in a group or community setting to observe the behavior of its members. It is similar to ethnography, but generally, the researcher isn’t embedded for a long period of time.

The researcher, being a participant, engages in daily activities, interactions, and events as a way of conducting a detailed study of a particular social phenomenon (Kawulich, 2005).

The method involves long-term engagement in the field, maintaining detailed records of observed events, informal interviews, direct participation, and reflexivity. This approach allows for a holistic view of the participants’ lived experiences, behaviours, and interactions within their everyday environment (Dewalt, 2011).

Example of Participant Observation Research

Title: Conflict in the boardroom: a participant observation study of supervisory board dynamics

Citation: Heemskerk, E. M., Heemskerk, K., & Wats, M. M. (2017). Conflict in the boardroom: a participant observation study of supervisory board dynamics. Journal of Management & Governance , 21 , 233-263.

Overview: This study examined how conflicts within corporate boards affect their performance. The researchers used a participant observation method, where they actively engaged with 11 supervisory boards and observed their dynamics. They found that having a shared understanding of the board’s role called a common framework, improved performance by reducing relationship conflicts, encouraging task conflicts, and minimizing conflicts between the board and CEO.

10. Non-Participant Observation

Definition: Non-participant observation is a qualitative research method in which the researcher observes the phenomena of interest without actively participating in the situation, setting, or community being studied.

This method allows the researcher to maintain a position of distance, as they are solely an observer and not a participant in the activities being observed (Kawulich, 2005).

During non-participant observation, the researcher typically records field notes on the actions, interactions, and behaviors observed , focusing on specific aspects of the situation deemed relevant to the research question.

This could include verbal and nonverbal communication , activities, interactions, and environmental contexts (Angrosino, 2007). They could also use video or audio recordings or other methods to collect data.

Example of Non-Participant Observation Research

Title: Mental Health Nurses’ attitudes towards mental illness and recovery-oriented practice in acute inpatient psychiatric units: A non-participant observation study

Citation: Sreeram, A., Cross, W. M., & Townsin, L. (2023). Mental Health Nurses’ attitudes towards mental illness and recovery‐oriented practice in acute inpatient psychiatric units: A non‐participant observation study. International Journal of Mental Health Nursing .

Overview: This study investigated the attitudes of mental health nurses towards mental illness and recovery-oriented practice in acute inpatient psychiatric units. The researchers used a non-participant observation method, meaning they observed the nurses without directly participating in their activities. The findings shed light on the nurses’ perspectives and behaviors, providing valuable insights into their attitudes toward mental health and recovery-focused care in these settings.

11. Content Analysis

Definition: Content Analysis involves scrutinizing textual, visual, or spoken content to categorize and quantify information. The goal is to identify patterns, themes, biases, or other characteristics (Hsieh & Shannon, 2005).

Content Analysis is widely used in various disciplines for a multitude of purposes. Researchers typically use this method to distill large amounts of unstructured data, like interview transcripts, newspaper articles, or social media posts, into manageable and meaningful chunks.

When wielded appropriately, Content Analysis can illuminate the density and frequency of certain themes within a dataset, provide insights into how specific terms or concepts are applied contextually, and offer inferences about the meanings of their content and use (Duriau, Reger, & Pfarrer, 2007).

Example of Content Analysis

Title: Framing European politics: A content analysis of press and television news .

Citation: Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50 (2), 93-109.

Overview: This study analyzed press and television news articles about European politics using a method called content analysis. The researchers examined the prevalence of different “frames” in the news, which are ways of presenting information to shape audience perceptions. They found that the most common frames were attribution of responsibility, conflict, economic consequences, human interest, and morality.

Read my Full Guide on Content Analysis Here

12. Discourse Analysis

Definition: Discourse Analysis, a qualitative research method, interprets the meanings, functions, and coherence of certain languages in context.

Discourse analysis is typically understood through social constructionism, critical theory , and poststructuralism and used for understanding how language constructs social concepts (Cheek, 2004).

Discourse Analysis offers great breadth, providing tools to examine spoken or written language, often beyond the level of the sentence. It enables researchers to scrutinize how text and talk articulate social and political interactions and hierarchies.

Insight can be garnered from different conversations, institutional text, and media coverage to understand how topics are addressed or framed within a specific social context (Jorgensen & Phillips, 2002).

Example of Discourse Analysis

Title: The construction of teacher identities in educational policy documents: A critical discourse analysis

Citation: Thomas, S. (2005). The construction of teacher identities in educational policy documents: A critical discourse analysis. Critical Studies in Education, 46 (2), 25-44.

Overview: The author examines how an education policy in one state of Australia positions teacher professionalism and teacher identities. While there are competing discourses about professional identity, the policy framework privileges a  narrative that frames the ‘good’ teacher as one that accepts ever-tightening control and regulation over their professional practice.

Read my Full Guide on Discourse Analysis Here

13. Action Research

Definition: Action Research is a qualitative research technique that is employed to bring about change while simultaneously studying the process and results of that change.

This method involves a cyclical process of fact-finding, action, evaluation, and reflection (Greenwood & Levin, 2016).

Typically, Action Research is used in the fields of education, social sciences , and community development. The process isn’t just about resolving an issue but also developing knowledge that can be used in the future to address similar or related problems.

The researcher plays an active role in the research process, which is normally broken down into four steps: 

• developing a plan to improve what is currently being done
• implementing the plan
• observing the effects of the plan, and
• reflecting upon these effects (Smith, 2010).

Example of Action Research

Title: Using Digital Sandbox Gaming to Improve Creativity Within Boys’ Writing

Citation: Ellison, M., & Drew, C. (2020). Using digital sandbox gaming to improve creativity within boys’ writing. Journal of Research in Childhood Education , 34 (2), 277-287.

Overview: This was a research study one of my research students completed in his own classroom under my supervision. He implemented a digital game-based approach to literacy teaching with boys and interviewed his students to see if the use of games as stimuli for storytelling helped draw them into the learning experience.

Read my Full Guide on Action Research Here

14. Semiotic Analysis

Definition: Semiotic Analysis is a qualitative method of research that interprets signs and symbols in communication to understand sociocultural phenomena. It stems from semiotics, the study of signs and symbols and their use or interpretation (Chandler, 2017).

In a Semiotic Analysis, signs (anything that represents something else) are interpreted based on their significance and the role they play in representing ideas.

This type of research often involves the examination of images, sounds, and word choice to uncover the embedded sociocultural meanings. For example, an advertisement for a car might be studied to learn more about societal views on masculinity or success (Berger, 2010).

Example of Semiotic Research

Title: Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia

Citation: Symes, C. (2023). Shielding the learned body: a semiotic analysis of school badges in New South Wales, Australia. Semiotica , 2023 (250), 167-190.

Overview: This study examines school badges in New South Wales, Australia, and explores their significance through a semiotic analysis. The badges, which are part of the school’s visual identity, are seen as symbolic representations that convey meanings. The analysis reveals that these badges often draw on heraldic models, incorporating elements like colors, names, motifs, and mottoes that reflect local culture and history, thus connecting students to their national identity. Additionally, the study highlights how some schools have shifted from traditional badges to modern logos and slogans, reflecting a more business-oriented approach.

15. Qualitative Longitudinal Studies

Definition: Qualitative Longitudinal Studies are a research method that involves repeated observation of the same items over an extended period of time.

Unlike a snapshot perspective, this method aims to piece together individual histories and examine the influences and impacts of change (Neale, 2019).

Qualitative Longitudinal Studies provide an in-depth understanding of change as it happens, including changes in people’s lives, their perceptions, and their behaviors.

For instance, this method could be used to follow a group of students through their schooling years to understand the evolution of their learning behaviors and attitudes towards education (Saldaña, 2003).

Example of Qualitative Longitudinal Research

Title: Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study

Citation: Hackett, J., Godfrey, M., & Bennett, M. I. (2016). Patient and caregiver perspectives on managing pain in advanced cancer: a qualitative longitudinal study.  Palliative medicine ,  30 (8), 711-719.

Overview: This article examines how patients and their caregivers manage pain in advanced cancer through a qualitative longitudinal study. The researchers interviewed patients and caregivers at two different time points and collected audio diaries to gain insights into their experiences, making this study longitudinal.

Read my Full Guide on Longitudinal Research Here

16. Open-Ended Surveys

Definition: Open-Ended Surveys are a type of qualitative research method where respondents provide answers in their own words. Unlike closed-ended surveys, which limit responses to predefined options, open-ended surveys allow for expansive and unsolicited explanations (Fink, 2013).

Open-ended surveys are commonly used in a range of fields, from market research to social studies. As they don’t force respondents into predefined response categories, these surveys help to draw out rich, detailed data that might uncover new variables or ideas.

For example, an open-ended survey might be used to understand customer opinions about a new product or service (Lavrakas, 2008).

Contrast this to a quantitative closed-ended survey, like a Likert scale, which could theoretically help us to come up with generalizable data but is restricted by the questions on the questionnaire, meaning new and surprising data and insights can’t emerge from the survey results in the same way.

Example of Open-Ended Survey Research

Title: Advantages and disadvantages of technology in relationships: Findings from an open-ended survey

Citation: Hertlein, K. M., & Ancheta, K. (2014). Advantages and disadvantages of technology in relationships: Findings from an open-ended survey.  The Qualitative Report ,  19 (11), 1-11.

Overview: This article examines the advantages and disadvantages of technology in couple relationships through an open-ended survey method. Researchers analyzed responses from 410 undergraduate students to understand how technology affects relationships. They found that technology can contribute to relationship development, management, and enhancement, but it can also create challenges such as distancing, lack of clarity, and impaired trust.

17. Naturalistic Observation

Definition: Naturalistic Observation is a type of qualitative research method that involves observing individuals in their natural environments without interference or manipulation by the researcher.

Naturalistic observation is often used when conducting research on behaviors that cannot be controlled or manipulated in a laboratory setting (Kawulich, 2005).

It is frequently used in the fields of psychology, sociology, and anthropology. For instance, to understand the social dynamics in a schoolyard, a researcher could spend time observing the children interact during their recess, noting their behaviors, interactions, and conflicts without imposing their presence on the children’s activities (Forsyth, 2010).

Example of Naturalistic Observation Research

Title: Dispositional mindfulness in daily life: A naturalistic observation study

Citation: Kaplan, D. M., Raison, C. L., Milek, A., Tackman, A. M., Pace, T. W., & Mehl, M. R. (2018). Dispositional mindfulness in daily life: A naturalistic observation study. PloS one , 13 (11), e0206029.

Overview: In this study, researchers conducted two studies: one exploring assumptions about mindfulness and behavior, and the other using naturalistic observation to examine actual behavioral manifestations of mindfulness. They found that trait mindfulness is associated with a heightened perceptual focus in conversations, suggesting that being mindful is expressed primarily through sharpened attention rather than observable behavioral or social differences.

Read my Full Guide on Naturalistic Observation Here

18. Photo-Elicitation

Definition: Photo-elicitation utilizes photographs as a means to trigger discussions and evoke responses during interviews. This strategy aids in bringing out topics of discussion that may not emerge through verbal prompting alone (Harper, 2002).

Traditionally, Photo-Elicitation has been useful in various fields such as education, psychology, and sociology. The method involves the researcher or participants taking photographs, which are then used as prompts for discussion.

For instance, a researcher studying urban environmental issues might invite participants to photograph areas in their neighborhood that they perceive as environmentally detrimental, and then discuss each photo in depth (Clark-Ibáñez, 2004).

Example of Photo-Elicitation Research

Title: Early adolescent food routines: A photo-elicitation study

Citation: Green, E. M., Spivak, C., & Dollahite, J. S. (2021). Early adolescent food routines: A photo-elicitation study. Appetite, 158 .

Overview: This study focused on early adolescents (ages 10-14) and their food routines. Researchers conducted in-depth interviews using a photo-elicitation approach, where participants took photos related to their food choices and experiences. Through analysis, the study identified various routines and three main themes: family, settings, and meals/foods consumed, revealing how early adolescents view and are influenced by their eating routines.

Features of Qualitative Research

Qualitative research is a research method focused on understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

Some key features of this method include:

• Naturalistic Inquiry: Qualitative research happens in the natural setting of the phenomena, aiming to understand “real world” situations (Patton, 2015). This immersion in the field or subject allows the researcher to gather a deep understanding of the subject matter.
• Emphasis on Process: It aims to understand how events unfold over time rather than focusing solely on outcomes (Merriam & Tisdell, 2015). The process-oriented nature of qualitative research allows researchers to investigate sequences, timing, and changes.
• Interpretive: It involves interpreting and making sense of phenomena in terms of the meanings people assign to them (Denzin & Lincoln, 2011). This interpretive element allows for rich, nuanced insights into human behavior and experiences.
• Holistic Perspective: Qualitative research seeks to understand the whole phenomenon rather than focusing on individual components (Creswell, 2013). It emphasizes the complex interplay of factors, providing a richer, more nuanced view of the research subject.
• Prioritizes Depth over Breadth: Qualitative research favors depth of understanding over breadth, typically involving a smaller but more focused sample size (Hennink, Hutter, & Bailey, 2020). This enables detailed exploration of the phenomena of interest, often leading to rich and complex data.

Qualitative vs Quantitative Research

Qualitative research centers on exploring and understanding the meaning individuals or groups attribute to a social or human problem (Creswell, 2013).

It involves an in-depth approach to the subject matter, aiming to capture the richness and complexity of human experience.

Examples include conducting interviews, observing behaviors, or analyzing text and images.

There are strengths inherent in this approach. In its focus on understanding subjective experiences and interpretations, qualitative research can yield rich and detailed data that quantitative research may overlook (Denzin & Lincoln, 2011).

Additionally, qualitative research is adaptive, allowing the researcher to respond to new directions and insights as they emerge during the research process.

However, there are also limitations. Because of the interpretive nature of this research, findings may not be generalizable to a broader population (Marshall & Rossman, 2014). Well-designed quantitative research, on the other hand, can be generalizable.

Moreover, the reliability and validity of qualitative data can be challenging to establish due to its subjective nature, unlike quantitative research, which is ideally more objective.

Compare Qualitative and Quantitative Research Methodologies in This Guide Here

In conclusion, qualitative research methods provide distinctive ways to explore social phenomena and understand nuances that quantitative approaches might overlook. Each method, from Ethnography to Photo-Elicitation, presents its strengths and weaknesses but they all offer valuable means of investigating complex, real-world situations. The goal for the researcher is not to find a definitive tool, but to employ the method best suited for their research questions and the context at hand (Almalki, 2016). Above all, these methods underscore the richness of human experience and deepen our understanding of the world around us.

Angrosino, M. (2007). Doing ethnographic and observational research. Sage Publications.

Areni, C. S., & Kim, D. (1994). The influence of in-store lighting on consumers’ examination of merchandise in a wine store. International Journal of Research in Marketing, 11 (2), 117-125.

Barker, C., Pistrang, N., & Elliott, R. (2016). Research Methods in Clinical Psychology: An Introduction for Students and Practitioners. John Wiley & Sons.

Baxter, P. & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The Qualitative Report, 13 (4), 544-559.

Berger, A. A. (2010). The Objects of Affection: Semiotics and Consumer Culture. Palgrave Macmillan.

Bevan, M. T. (2014). A method of phenomenological interviewing. Qualitative health research, 24 (1), 136-144.

Birks, M., & Mills, J. (2015). Grounded theory: A practical guide . Sage Publications.

Bryman, A. (2015) . The SAGE Handbook of Qualitative Research. Sage Publications.

Chandler, D. (2017). Semiotics: The Basics. Routledge.

Charmaz, K. (2014). Constructing grounded theory. Sage Publications.

Cheek, J. (2004). At the margins? Discourse analysis and qualitative research. Qualitative Health Research, 14(8), 1140-1150.

Clark-Ibáñez, M. (2004). Framing the social world with photo-elicitation interviews. American Behavioral Scientist, 47(12), 1507-1527.

Creswell, J. W. (2013). Research Design: Qualitative, Quantitative and Mixed Methods Approaches. Sage Publications.

Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

Crowe, S., Cresswell, K., Robertson, A., Huby, G., Avery, A., & Sheikh, A. (2011). The case study approach. BMC Medical Research Methodology, 11(100), 1-9.

Denzin, N. K., & Lincoln, Y. S. (2011). The Sage Handbook of Qualitative Research. Sage.

Dewalt, K. M., & Dewalt, B. R. (2011). Participant observation: A guide for fieldworkers. Rowman Altamira.

Doody, O., Slevin, E., & Taggart, L. (2013). Focus group interviews in nursing research: part 1. British Journal of Nursing, 22(1), 16-19.

Durham, A. (2019). Autoethnography. In P. Atkinson (Ed.), Qualitative Research Methods. Oxford University Press.

Duriau, V. J., Reger, R. K., & Pfarrer, M. D. (2007). A content analysis of the content analysis literature in organization studies: Research themes, data sources, and methodological refinements. Organizational Research Methods, 10(1), 5-34.

Evans, J. (2010). The Everyday Lives of Men: An Ethnographic Investigation of Young Adult Male Identity. Peter Lang.

Farrall, S. (2006). What is qualitative longitudinal research? Papers in Social Research Methods, Qualitative Series, No.11, London School of Economics, Methodology Institute.

Fielding, J., & Fielding, N. (2008). Synergy and synthesis: integrating qualitative and quantitative data. The SAGE handbook of social research methods, 555-571.

Fink, A. (2013). How to conduct surveys: A step-by-step guide . SAGE.

Forsyth, D. R. (2010). Group Dynamics . Wadsworth Cengage Learning.

Fugard, A. J. B., & Potts, H. W. W. (2015). Supporting thinking on sample sizes for thematic analyses: A quantitative tool. International Journal of Social Research Methodology, 18 (6), 669–684.

Glaser, B. G., & Strauss, A. L. (1967). The discovery of grounded theory: Strategies for qualitative research. Aldine de Gruyter.

Gray, J. R., Grove, S. K., & Sutherland, S. (2017). Burns and Grove’s the Practice of Nursing Research E-Book: Appraisal, Synthesis, and Generation of Evidence. Elsevier Health Sciences.

Greenwood, D. J., & Levin, M. (2016). Introduction to action research: Social research for social change. SAGE.

Harper, D. (2002). Talking about pictures: A case for photo elicitation. Visual Studies, 17 (1), 13-26.

Heinonen, T. (2012). Making Sense of the Social: Human Sciences and the Narrative Turn. Rozenberg Publishers.

Heisley, D. D., & Levy, S. J. (1991). Autodriving: A photoelicitation technique. Journal of Consumer Research, 18 (3), 257-272.

Hennink, M. M., Hutter, I., & Bailey, A. (2020). Qualitative Research Methods . SAGE Publications Ltd.

Hsieh, H. F., & Shannon, S. E. (2005). Three Approaches to Qualitative Content Analysis. Qualitative Health Research, 15 (9), 1277–1288.

Jorgensen, D. L. (2015). Participant Observation. In Emerging Trends in the Social and Behavioral Sciences: An Interdisciplinary, Searchable, and Linkable Resource. John Wiley & Sons, Inc.

Jorgensen, M., & Phillips, L. (2002). Discourse Analysis as Theory and Method . SAGE.

Josselson, R. (2011). Narrative research: Constructing, deconstructing, and reconstructing story. In Five ways of doing qualitative analysis . Guilford Press.

Kawulich, B. B. (2005). Participant observation as a data collection method. Forum: Qualitative Social Research, 6 (2).

Khan, S. (2014). Qualitative Research Method: Grounded Theory. Journal of Basic and Clinical Pharmacy, 5 (4), 86-88.

Koshy, E., Koshy, V., & Waterman, H. (2010). Action Research in Healthcare . SAGE.

Krippendorff, K. (2013). Content Analysis: An Introduction to its Methodology. SAGE.

Lannon, J., & Cooper, P. (2012). Humanistic Advertising: A Holistic Cultural Perspective. International Journal of Advertising, 15 (2), 97–111.

Lavrakas, P. J. (2008). Encyclopedia of survey research methods. SAGE Publications.

Lieblich, A., Tuval-Mashiach, R., & Zilber, T. (2008). Narrative research: Reading, analysis and interpretation. Sage Publications.

Mackey, A., & Gass, S. M. (2015). Second language research: Methodology and design. Routledge.

Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Sage publications.

McAdams, D. P., Josselson, R., & Lieblich, A. (2006). Identity and story: Creating self in narrative. American Psychological Association.

Merriam, S. B., & Tisdell, E. J. (2015). Qualitative Research: A Guide to Design and Implementation. Jossey-Bass.

Mick, D. G. (1986). Consumer Research and Semiotics: Exploring the Morphology of Signs, Symbols, and Significance. Journal of Consumer Research, 13 (2), 196-213.

Morgan, D. L. (2010). Focus groups as qualitative research. Sage Publications.

Mulhall, A. (2003). In the field: notes on observation in qualitative research. Journal of Advanced Nursing, 41 (3), 306-313.

Neale, B. (2019). What is Qualitative Longitudinal Research? Bloomsbury Publishing.

Nolan, L. B., & Renderos, T. B. (2012). A focus group study on the influence of fatalism and religiosity on cancer risk perceptions in rural, eastern North Carolina. Journal of religion and health, 51 (1), 91-104.

Padilla-Díaz, M. (2015). Phenomenology in educational qualitative research: Philosophy as science or philosophical science? International Journal of Educational Excellence, 1 (2), 101-110.

Parker, I. (2014). Discourse dynamics: Critical analysis for social and individual psychology . Routledge.

Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice . Sage Publications.

Polkinghorne, D. E. (2013). Narrative configuration in qualitative analysis. In Life history and narrative. Routledge.

Puts, M. T., Tapscott, B., Fitch, M., Howell, D., Monette, J., Wan-Chow-Wah, D., Krzyzanowska, M., Leighl, N. B., Springall, E., & Alibhai, S. (2014). Factors influencing adherence to cancer treatment in older adults with cancer: a systematic review. Annals of oncology, 25 (3), 564-577.

Qu, S. Q., & Dumay, J. (2011). The qualitative research interview . Qualitative research in accounting & management.

Ali, J., & Bhaskar, S. B. (2016). Basic statistical tools in research and data analysis. Indian Journal of Anaesthesia, 60 (9), 662–669.

Rosenbaum, M. S. (2017). Exploring the social supportive role of third places in consumers’ lives. Journal of Service Research, 20 (1), 26-42.

Saldaña, J. (2003). Longitudinal Qualitative Research: Analyzing Change Through Time . AltaMira Press.

Saldaña, J. (2014). The Coding Manual for Qualitative Researchers. SAGE.

Shernoff, D. J., Csikszentmihalyi, M., Shneider, B., & Shernoff, E. S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18 (2), 158-176.

Smith, J. A. (2015). Qualitative Psychology: A Practical Guide to Research Methods . Sage Publications.

Smith, M. K. (2010). Action Research. The encyclopedia of informal education.

Sue, V. M., & Ritter, L. A. (2012). Conducting online surveys . SAGE Publications.

Van Auken, P. M., Frisvoll, S. J., & Stewart, S. I. (2010). Visualising community: using participant-driven photo-elicitation for research and application. Local Environment, 15 (4), 373-388.

Van Voorhis, F. L., & Morgan, B. L. (2007). Understanding Power and Rules of Thumb for Determining Sample Sizes. Tutorials in Quantitative Methods for Psychology, 3 (2), 43–50.

Wodak, R., & Meyer, M. (2015). Methods of Critical Discourse Analysis . SAGE.

Zuber-Skerritt, O. (2018). Action research for developing educational theories and practices . Routledge.

• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 10 Reasons you’re Perpetually Single
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 20 Montessori Toddler Bedrooms (Design Inspiration)
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 21 Montessori Homeschool Setups
• Chris Drew (PhD) https://helpfulprofessor.com/author/chris-drew-phd-2/ 101 Hidden Talents Examples

Leave a Comment Cancel Reply

Your email address will not be published. Required fields are marked *

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
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

[What Is Qualitative Research?]

Affiliation.

• 1 Graduate School of Education and Human Development, Nagoya University.
• PMID: 28566568
• DOI: 10.1248/yakushi.16-00224-1

The article is an in-depth explanation of qualitative research, an approach increasingly prevalent among today's research communities. After discussing its present spread within the health sciences, the author addresses: 1. Its definition. 2. Its characteristics, as well as its theoretical and procedural background. 3. Its procedures. 4. Differences between qualitative and quantitative approaches. 5. Mixed methods incorporating quantitative research. And in conclusion: 6. The importance of establishing an epistemological perspective in qualitative research.

Keywords: data collection; qualitative data analysis; qualitative research; research design; research question; theorization.

PubMed Disclaimer

Similar articles

• Qualitative research in healthcare: an introduction to grounded theory using thematic analysis. Chapman AL, Hadfield M, Chapman CJ. Chapman AL, et al. J R Coll Physicians Edinb. 2015;45(3):201-5. doi: 10.4997/JRCPE.2015.305. J R Coll Physicians Edinb. 2015. PMID: 26517098 Review.
• A student's perspective of managing data collection in a complex qualitative study. Dowse EM, van der Riet P, Keatinge DR. Dowse EM, et al. Nurse Res. 2014 Nov;22(2):34-9. doi: 10.7748/nr.22.2.34.e1302. Nurse Res. 2014. PMID: 25423940
• [The mixed design in nursing sciences or when a question of research calls for qualitative and quantitative strategies]. Bourgault P, Gallagher F, Michaud C, Saint-Cyr-Tribble D. Bourgault P, et al. Rech Soins Infirm. 2010 Dec;(103):20-8. Rech Soins Infirm. 2010. PMID: 21322192 French.
• The use of triangulation in qualitative research. Carter N, Bryant-Lukosius D, DiCenso A, Blythe J, Neville AJ. Carter N, et al. Oncol Nurs Forum. 2014 Sep;41(5):545-7. doi: 10.1188/14.ONF.545-547. Oncol Nurs Forum. 2014. PMID: 25158659
• [A call for qualitative research in Orthodontics]. Yitschaky O, Hofnung T, Zini A. Yitschaky O, et al. Refuat Hapeh Vehashinayim (1993). 2015 Jan;32(1):30-6, 61. Refuat Hapeh Vehashinayim (1993). 2015. PMID: 25799792 Review. Hebrew.
• Composition and influencing factors of professionals' capacity in public health emergency rescues: a qualitative study. Zhong F, Lin Y, Chen Y, Gao Y, Zhu X. Zhong F, et al. Front Public Health. 2024 May 9;12:1338839. doi: 10.3389/fpubh.2024.1338839. eCollection 2024. Front Public Health. 2024. PMID: 38784573 Free PMC article.
• Screening and management of osteoporosis: a survey of knowledge, attitude, and practice among healthcare professionals in Egypt-a study by the Egyptian Academy of Bone Health. Elwakil W, El Gaafary M, El Miedany Y. Elwakil W, et al. Osteoporos Int. 2024 Jan;35(1):93-103. doi: 10.1007/s00198-023-06914-4. Epub 2023 Sep 18. Osteoporos Int. 2024. PMID: 37721557 Free PMC article.
• Improving the Management of Children with Fevers by Healers in Native Rural Areas in the South of Ecuador. Bautista-Valarezo E, Espinosa ME, Arce Guerrero NE, Verhoeven V, Hendrickx K, Michels NRM. Bautista-Valarezo E, et al. Int J Environ Res Public Health. 2023 Feb 22;20(5):3923. doi: 10.3390/ijerph20053923. Int J Environ Res Public Health. 2023. PMID: 36900933 Free PMC article.
• Cognitive and Emotional Changes in Peer Educators of Type 2 Diabetes Patients After Starting Peer-Support Activities. Aoto H, Kobayashi N, Tokushima Y, Tanimura C, Fukada M, Nagata A, Otani S, Morita T, Inoue K, Hanaki K, Kageyama S, Kurozawa Y. Aoto H, et al. Yonago Acta Med. 2022 Nov 28;65(4):303-314. doi: 10.33160/yam.2022.11.007. eCollection 2022 Nov. Yonago Acta Med. 2022. PMID: 36474901 Free PMC article.
• Moving beyond superficial communication to collaborative communication: learning processes and outcomes of interprofessional education in actual medical settings. Ito M, Hida T, Goto K, Goto M, Kanada Y, Ohtsuki M. Ito M, et al. Fujita Med J. 2020;6(4):93-101. doi: 10.20407/fmj.2019-026. Epub 2020 Jul 14. Fujita Med J. 2020. PMID: 35111529 Free PMC article.

Publication types

• Search in MeSH

LinkOut - more resources

Full text sources.

• J-STAGE, Japan Science and Technology Information Aggregator, Electronic
• Medical Online, Meteo Inc

Other Literature Sources

• scite Smart Citations
• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Chapter 2 --  Designing a Qualitative Study

General frameworks hold qualitative research together.

One undertakes qualitative research in a natural setting where the researcher is an instrument of data collection who gathers words or pictures, analyzes them inductively, focuses on the meaning of participants, and describes a process that is expressive and persuasive in language.

Dezin and Lincoln (1994) define research:

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 our 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 meaning in individuals' lives.

Creswell's definition of Qualitative Research:

Qualitative research is an inquiry process of understanding based on distinct methodological traditions of inquiry that explore a social or human problem.  The researcher builds a complex, holistic picture, analyzes words, reports detailed views of informants, and conducts the study in a natural setting.

The difference between the two types of research is that quantitative researchers work with a few variables and many cases whereas qualitative researchers rely on a few cases and many variables.

To undertake qualitative research requires a strong commitment to study a problem and demands time and resources.

Qualitative inquiry is for the researcher who is willing to do the following:

• Select a qualitative study because of the nature of the research question (question often starts with how or what so that initial forays into the topic describe what is going on).
• Choose a qualitative study because the topic needs to be explored (variables cannot be easily identified).
• Use a qualitative study because of the need to present a detailed view of the topic.
• Choose a qualitative approach in order to study individuals in their natural setting.
• Select qualitative approach because of interest in writhing in a literary style.
• Employ a qualitative study because of sufficient time and resources to spend on extensive data collection in the field and detailed data analysis of "text" information.
• Select a qualitative approach because audiences are receptive to qualitative research.
• Employ a qualitative approach to emphasize the researcher's role as an active learner who can tell the story from the participants' view rather than an "expert" who passes judgment on participants.

The qualitative approach to design contains several unique features:

Given these phases in the design, one uses a set of assumptions that guide the study.

These assumptions speak to our understanding of knowledge.  Knowledge is within the meanings people make of it.

We begin by posing a problem, a research issue, to which we would like an answer.

The topics about which we write are emotion laden, close to the people, and practical.

We ask open-ended question, wanting to listen to the participants we are studying and shaping the questions after we "explore" and we refrain from assuming the role of the expert researcher with the "best" questions.

Four basic types of information:

• Observations
• Audio-visual materials

The backbone of qualitative research is extensive collection of data, typically from multiple sources of information.  At this stage we consciously consider ethical issues.

Perhaps qualitative studies do not have endings, only questions.

Characteristics of a "good" qualitative study:

No set format exists for planning a study.  Several writers suggest general topics to be included in a written plan.

The complete study contains data findings and a discussion as well as the problem or issue, research questions, methodology, and verification or validity.

"Given the multiple perspectives on qualitative research, it is helpful to establish some common ground before preceding to examine the varieties of qualitative traditions.  Qualitative research is complex, involving fieldwork for prolonged periods of time, collecting words and pictures, analyzing this information inductively while focusing on participant views, and writing about the process using expressive and persuasive language.  Moreover, researchers frame this approach within traditions of inquiry, and they engage in research to examine how or what types of questions, to explore a topic, to develop a detailed view, to take advantage of access to information, to write in expressive and persuasive language, to spend time in the field and to reach audiences receptive to qualitative approaches.  In designing a study, one works with broad philosophical assumptions; possible frameworks, problems, and questions; and data collection through techniques such as interviews, observations, documents, and audio-visual materials.  Reducing the data into small categories or themes comes next, as does storing them and representing them for the reader in the narrative.  The narrative assumes many forms--a theory, a description, a detailed view, an abstract model--and we know whether the narrative rings true using criteria about rigor, the philosophical assumptions of the design, detailed methods and approaches, and persuasive and engaging writhing.  The narrative will, in the end, reflect the creativity of the writer, although the plan for the study, the proposal, might follow several of the procedures being discussed in the literature.  In the next chapter, we see how five authors shape these central elements of good qualitative research using a lens of a tradition of inquiry--the traditions of a biography, a phenomenology, a ground theory study, an ethnography, and a case study."

Cresswell, J. W. (1997). Qualitative Inquiry and Research Design: Choosing Among the Five Traditions. Thousand Oaks:  Sage Publications.

What is Qualitative in Research

• December 2021
• Qualitative Sociology 44(2)

• University of St.Gallen

• University of Stavanger (UiS)

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations
• Kurnia Kurnia
• Pratiwi Samad
• Abdul Wahab
• Ahmad Nur Budi Utama
• Rike Setiawati
• Ade Irma Suryani

• Zuvyati Aryani Tlonaen

• Andrew Carnegie Stewart
• Harriet Dunbar-Morris

• Qual Sociol

• Gary Alan Fine

• Japonica Brown-Saracino

• Mario L. Small

• Eviatar Zerubavel

• Karl R. Popper

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

• Media Center
• Not yet translated

Qualitative Research

What is qualitative research.

Qualitative research is a methodology focused on collecting and analyzing descriptive, non-numerical data to understand complex human behavior, experiences, and social phenomena. This approach utilizes techniques such as interviews, focus groups, and observations to explore the underlying reasons, motivations, and meanings behind actions and decisions. Unlike quantitative research, which focuses on measuring and quantifying data, qualitative research delves into the 'why' and 'how' of human behavior, providing rich, contextual insights that reveal deeper patterns and relationships.

The Basic Idea

Theory, meet practice.

TDL is an applied research consultancy. In our work, we leverage the insights of diverse fields—from psychology and economics to machine learning and behavioral data science—to sculpt targeted solutions to nuanced problems.

Ever heard of the saying “quality over quantity”? Well, some researchers feel the same way!

Imagine you are conducting a study looking at consumer behavior for buying potato chips. You’re interested in seeing which factors influence a customer’s choice between purchasing Doritos and Pringles. While you could conduct quantitative research and measure the number of bags purchased, this data alone wouldn’t explain why consumers choose one chip brand over the other; it would just tell you what they are purchasing. To gather more meaningful data, you may conduct interviews or surveys, asking people about their chip preferences and what draws them to one brand over another. Is it the taste of the chips? The font or color of the bag? This qualitative approach dives deeper to uncover why one potato chip is more popular than the other and can help companies make the adjustments that count.

Qualitative research, as seen in the example above, can provide greater insight into behavior, going beyond numbers to understand people’s experiences, attitudes, and perceptions. It helps us to grasp the meaning behind decisions, rather than just describing them. As human behavior is often difficult to qualify, qualitative research is a useful tool for solving complex problems or as a starting point to generate new ideas for research. Qualitative methods are used across all types of research—from consumer behavior to education, healthcare, behavioral science, and everywhere in between!

At its core, qualitative research is exploratory—rather than coming up with a hypothesis and gathering numerical data to support it, qualitative research begins with open-ended questions. Instead of asking “Which chip brand do consumers buy more frequently?”, qualitative research asks “Why do consumers choose one chip brand over another?”. Common methods to obtain qualitative data include focus groups, unstructured interviews, and surveys. From the data gathered, researchers then can make hypotheses and move on to investigating them. 

It’s important to note that qualitative and quantitative research are not two opposing methods, but rather two halves of a whole. Most of the best studies leverage both kinds of research by collecting objective, quantitative data, and using qualitative research to gain greater insight into what the numbers reveal.

You may have heard the world is made up of atoms and molecules, but it’s really made up of stories. When you sit with an individual that’s been here, you can give quantitative data a qualitative overlay. – William Turner, 16th century British scientist 1

Quantitative Research: A research method that involves collecting and analyzing numerical data to test hypotheses, identify patterns, and predict outcomes.

Exploratory Research: An initial study used to investigate a problem that is not clearly defined, helping to clarify concepts and improve research design.

Positivism: A scientific approach that emphasizes empirical evidence and objectivity, often involving the testing of hypotheses based on observable data. 2 

Phenomenology: A research approach that emphasizes the first-person point of view, placing importance on how people perceive, experience, and interpret the world around them. 3

Social Interaction Theory: A theoretical perspective that people make sense of their social worlds by the exchange of meaning through language and symbols. 4

Critical Theory: A worldview that there is no unitary or objective “truth” about people that can be discovered, as human experience is shaped by social, cultural, and historical contexts that influences reality and society. 5

Empirical research: A method of gaining knowledge through direct observation and experimentation, relying on real-world data to test theories. 

Paradigm shift: A fundamental change in the basic assumptions and methodologies of a scientific discipline, leading to the adoption of a new framework. 2

Interpretive/descriptive approach: A methodology that focuses on understanding the meanings people assign to their experiences, often using qualitative methods.

Unstructured interviews: A free-flowing conversation between researcher and participant without predetermined questions that must be asked to all participants. Instead, the researcher poses questions depending on the flow of the interview. 6

Focus Group: Group interviews where a researcher asks questions to guide a conversation between participants who are encouraged to share their ideas and information, leading to detailed insights and diverse perspectives on a specific topic.

Grounded theory : A qualitative methodology that generates a theory directly from data collected through iterative analysis.

When social sciences started to emerge in the 17th and 18th centuries, researchers wanted to apply the same quantitative approach that was used in the natural sciences. At this time, there was a predominant belief that human behavior could be numerically analyzed to find objective patterns and would be generalizable to similar people and situations. Using scientific means to understand society is known as a positivist approach. However, in the early 20th century, both natural and social scientists started to criticize this traditional view of research as being too reductive. 2  

In his book, The Structure of Scientific Revolutions, American philosopher Thomas Kuhn identified that a major paradigm shift was starting to occur. Earlier methods of science were being questioned and replaced with new ways of approaching research which suggested that true objectivity was not possible when studying human behavior. Rather, the importance of context meant research on one group could not be generalized to all groups. 2 Numbers alone were deemed insufficient for understanding the environment surrounding human behavior which was now seen as a crucial piece of the puzzle. Along with this paradigm shift, Western scholars began to take an interest in ethnography , wanting to understand the customs, practices, and behaviors of other cultures. 

Qualitative research became more prominent throughout the 20th century, expanding beyond anthropology and ethnography to being applied across all forms of research; in science, psychology, marketing—the list goes on. Paul Felix Lazarsfield, Austrian-American sociologist and mathematician often known as the father of qualitative research, popularized new methods such as unstructured interviews and group discussions. 7 During the 1940s, Lazarfield brought attention to the fact that humans are not always rational decision-makers, making them difficult to understand through numerical data alone.

The 1920s saw the invention of symbolic interaction theory, developed by George Herbert Mead. Symbolic interaction theory posits society as the product of shared symbols such as language. People attach meanings to these symbols which impacts the way they understand and communicate with the world around them, helping to create and maintain a society. 4 Critical theory was also developed in the 1920s at the University of Frankfurt Institute for Social Research. Following the challenge of positivism, critical theory is a worldview that there is no unitary or objective “truth” about people that can be discovered, as human experience is shaped by social, cultural, and historical contexts. By shedding light on the human experience, it hopes to highlight the role of power, ideology, and social structures in shaping humans, and using this knowledge to create change. 5

Other formalized theories were proposed during the 20th century, such as grounded theory , where researchers started gathering data to form a hypothesis, rather than the other way around. This represented a stark contrast to positivist approaches that had dominated the 17th and 18th centuries.

The 1950s marked a shift toward a more interpretive and descriptive approach which factored in how people make sense of their subjective reality and attach meaning to it. 2 Researchers began to recognize that the why of human behavior was just as important as the what . Max Weber, a German sociologist, laid the foundation of the interpretive approach through the concept of Verstehen (which in English translates to understanding), emphasizing the importance of interpreting the significance people attach to their behavior. 8 With the shift to an interpretive and descriptive approach came the rise of phenomenology, which emphasizes first-person experiences by studying how individuals perceive, experience, and interpret the world around them. 

Today, in the age of big data, qualitative research has boomed, as advancements in digital tools allow researchers to gather vast amounts of data (both qualitative and quantitative), helping us better understand complex social phenomena. Social media patterns can be analyzed to understand public sentiment, consumer behavior, and cultural trends to grasp how people attach subjective meaning to their reality. There is even an emerging field of digital ethnography which is entirely focused on how humans interact and communicate in virtual environments!

Thomas Kuhn

American philosopher who suggested that science does not evolve through merely an addition of knowledge by compiling new learnings onto existing theories, but instead undergoes paradigm shifts where new theories and methodologies replace old ones. In this way, Kuhn suggested that science is a reflection of a community at a particular point in time. 9

Paul Felix Lazarsfeld

Often referred to as the father of qualitative research, Austrian-American sociologist and mathematician Paul Lazarsfield helped to develop modern empirical methods of conducting research in the social sciences such as surveys, opinion polling, and panel studies. Lazarsfeld was best known for combining qualitative and quantitative research to explore America's voting habits and behaviors related to mass communication, such as newspapers, magazines, and radios. 10  

German sociologist and political economist known for his sociological approach of “Verstehen” which emphasized the need to understand individuals or groups by exploring the meanings that people attach to their decisions. While previously, qualitative researchers in ethnography acted like an outside observer to explain behavior from their point of view, Weber believed that an empathetic understanding of behavior, that explored both intent and context, was crucial to truly understanding behavior. 11  

George Herbert Mead

Widely recognized as the father of symbolic interaction theory, Mead was an American philosopher and sociologist who took an interest in how spoken language and symbols contribute to one’s idea of self, and to society at large. 4

Consequences

Humans are incredibly complex beings, whose behaviors cannot always be reduced to mere numbers and statistics. Qualitative research acknowledges this inherent complexity and can be used to better capture the diversity of human and social realities. 

Qualitative research is also more flexible—it allows researchers to pivot as they uncover new insights. Instead of approaching the study with predetermined hypotheses, oftentimes, researchers let the data speak for itself and are not limited by a set of predefined questions. It can highlight new areas that a researcher hadn’t even thought of exploring. 

By providing a deeper explanation of not only what we do, but why we do it, qualitative research can be used to inform policy-making, educational practices, healthcare approaches, and marketing tactics. For instance, while quantitative research tells us how many people are smokers, qualitative research explores what, exactly, is driving them to smoke in the first place. If the research reveals that it is because they are unaware of the gravity of the consequences, efforts can be made to emphasize the risks, such as by placing warnings on cigarette cartons. 

Finally, qualitative research helps to amplify the voices of marginalized or underrepresented groups. Researchers who embrace a true “Verstehen” mentality resist applying their own worldview to the subjects they study, but instead seek to understand the meaning people attach to their own behaviors. In bringing forward other worldviews, qualitative research can help to shift perceptions and increase awareness of social issues. For example, while quantitative research may show that mental health conditions are more prevalent for a certain group, along with the access they have to mental health resources, qualitative research is able to explain the lived experiences of these individuals and uncover what barriers they are facing to getting help. This qualitative approach can support governments and health organizations to better design mental health services tailored to the communities they exist in.

Controversies

Qualitative research aims to understand an individual’s lived experience, which although provides deeper insights, can make it hard to generalize to a larger population. While someone in a focus group could say they pick Doritos over Pringles because they prefer the packaging, it’s difficult for a researcher to know if this is universally applicable, or just one person’s preference. 12 This challenge makes it difficult to replicate qualitative research because it involves context-specific findings and subjective interpretation. 

Moreover, there can be bias in sample selection when conducting qualitative research. Individuals who put themselves forward to be part of a focus group or interview may hold strong opinions they want to share, making the insights gathered from their answers not necessarily reflective of the general population.13 People may also give answers that they think researchers are looking for leading to skewed results, which is a common example of the observer expectancy effect . 

However, the bias in this interaction can go both ways. While researchers are encouraged to embrace “Verstehen,” there is a possibility that they project their own views onto their participants. For example, if an American researcher is studying eating habits in China and observes someone burping, they may attribute this behavior to rudeness—when in fact, burping can be a sign that you have enjoyed your meal and it is a compliment to the chef. One way to mitigate this risk is through thick description , noting a great amount of contextual detail in their observations. Another way to minimize the researcher’s bias on their observations is through member checking , returning results to participants to check if they feel they accurately capture their experience.

Another drawback of qualitative research is that it is time-consuming. Focus groups and unstructured interviews take longer and are more difficult to logistically arrange, and the data gathered is harder to analyze as it goes beyond numerical data. While advances in technology alleviate some of these labor-intensive processes, they still require more resources. 

Many of these drawbacks can be mitigated through a mixed-method approach, combining both qualitative and quantitative research. Qualitative research can be a good starting point, giving depth and contextual understanding to a behavior, before turning to quantitative data to see if the results are generalizable. Or, the opposite direction can be used—quantitative research can show us the “what,” identifying patterns and correlations, and researchers can then better understand the “why” behind behavior by leveraging qualitative methods. Triangulation —using multiple datasets, methods, or theories—is another way to help researchers avoid bias. 

Linking Adult Behaviors to Childhood Experiences

In the mid-1980s, an obesity program at the KP San Diego Department of Preventive Medicine had a high dropout rate. What was interesting is that a majority of the dropouts were successfully losing weight, posing the question of why they were leaving the program in the first place. In this instance, greater investigation was required to understand the why behind their behaviors.

Researchers conducted in-depth interviews with almost 200 dropouts, finding that many of them had experienced childhood abuse that had led to obesity. In this unfortunate scenario, obesity was a consequence of another problem, rather than the root problem itself. This led Dr. Vincent J. Felitti, who was working for the department, to launch the Adverse Childhood Experiences (ACE) Study, aimed at exploring how childhood experiences impact adult health status. 

Felitti and the Department of Preventive Medicine studied over 17,000 adults with health plans that revealed a strong relationship between emotional experiences as children and negative health behaviors as adults, such as obesity, smoking, and intravenous drug use. This study demonstrates the importance of qualitative research to uncover correlations that would not be discovered by merely looking at numerical data. 14  

Understanding Voter Turnout

Voting is usually considered an important part of political participation in a democracy. However, voter turnout is an issue in many countries, including the US. While quantitative research can tell us how many people vote, it does not provide insights into why people choose to vote or not.

With this in mind, Dawn Merdelin Johnson, a PhD student in philosophy at Walden University, explored how public corruption has impacted voter turnout in Cook County, Illinois. Johnson conducted semi-structured telephone interviews to understand factors that contribute to low voter turnout and the impact of public corruption on voting behaviors. Johnson found that public corruption leads to voters believing public officials prioritize their own well-being over the good of the people, leading to distrust in candidates and the overall political system, and thus making people less likely to vote. Other themes revealed that to increase voter turnout, voting should be more convenient and supply more information about the candidates to help people make more informed decisions.

From these findings, Johnson suggested that the County could experience greater voter turnout through the development of an anti-corruption agency, improved voter registration and maintenance, and enhanced voting accessibility. These initiatives would boost voting engagement and positively impact democratic participation. 15

Related TDL Content

Applying behavioral science in an organization.

At its core, behavioral science is about uncovering the reasons behind why people do what they do. That means that the role of a behavioral scientist can be quite broad, but has many important applications. In this article, Preeti Kotamarthi explains how behavioral science supports different facets of the organization, providing valuable insights for user design, data science, and product marketing. 

Increasing HPV Vaccination in Rural Kenya

While HPV vaccines are an effective method of preventing cervical cancer, there is low intake in low and middle-income countries worldwide. Qualitative research can uncover the social and behavioral barriers to increasing HPV vaccination, revealing that misinformation, skepticism, and fear prevent people from getting the vaccine. In this article, our writer Annika Steele explores how qualitative insights can inform a two-part intervention strategy to increase HPV vaccination rates.

• Versta Research. (n.d.). Bridging the quantitative-qualitative gap . Versta Research. Retrieved August 17, 2024, from https://verstaresearch.com/newsletters/bridging-the-quantitative-qualitative-gap/
• Merriam, S. B., & Tisdell, E. J. (2015). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass.
• Smith, D. W. (2018). Phenomenology. In E. N. Zalta (Ed.), Stanford Encyclopedia of Philosophy . Retrieved from https://plato.stanford.edu/entries/phenomenology/#HistVariPhen
• Nickerson, C. (2023, October 16). Symbolic interaction theory . Simply Psychology. https://www.simplypsychology.org/symbolic-interaction-theory.html
• DePoy, E., & Gitlin, L. N. (2016). Introduction to research (5th ed.). Elsevier.
• ATLAS.ti. (n.d.). Unstructured interviews . ATLAS.ti. Retrieved August 17, 2024, from https://atlasti.com/research-hub/unstructured-interviews
• O'Connor, O. (2020, August 14). The history of qualitative research . Medium. https://oliconner.medium.com/the-history-of-qualitative-research-f6e07c58e439
• Sociology Institute. (n.d.). Max Weber: Interpretive sociology & legacy . Sociology Institute. Retrieved August 18, 2024, from https://sociology.institute/introduction-to-sociology/max-weber-interpretive-sociology-legacy
• Kuhn, T. S. (2012). The structure of scientific revolutions (4th ed.). University of Chicago Press.
• Encyclopaedia Britannica. (n.d.). Paul Felix Lazarsfeld . Encyclopaedia Britannica. Retrieved August 17, 2024, from https://www.britannica.com/biography/Paul-Felix-Lazarsfeld
• Nickerson, C. (2019). Verstehen in Sociology: Empathetic Understanding . Simply Psychology. Retrieved August 18, 2024, from: https://www.simplypsychology.org/verstehen.html
• Omniconvert. (2021, October 4). Qualitative research: Definition, methodology, limitations, and examples . Omniconvert. https://www.omniconvert.com/blog/qualitative-research-definition-methodology-limitation-examples/
• Vaughan, T. (2021, August 5). 10 advantages and disadvantages of qualitative research . Poppulo. https://www.poppulo.com/blog/10-advantages-and-disadvantages-of-qualitative-research
• Felitti, V. J. (2002). The relation between adverse childhood experiences and adult health: Turning gold into lead. The Permanente Journal, 6 (1), 44–47. https://www.thepermanentejournal.org/doi/10.7812/TPP/02.994
• Johnson, D. M. (2024). Voters' perception of public corruption and low voter turnout: A qualitative case study of Cook County (Doctoral dissertation). Walden University.

About the Author

Emilie Rose Jones

Emilie currently works in Marketing & Communications for a non-profit organization based in Toronto, Ontario. She completed her Masters of English Literature at UBC in 2021, where she focused on Indigenous and Canadian Literature. Emilie has a passion for writing and behavioural psychology and is always looking for opportunities to make knowledge more accessible. 

We are the leading applied research & innovation consultancy

Our insights are leveraged by the most ambitious organizations.

I was blown away with their application and translation of behavioral science into practice. They took a very complex ecosystem and created a series of interventions using an innovative mix of the latest research and creative client co-creation. I was so impressed at the final product they created, which was hugely comprehensive despite the large scope of the client being of the world's most far-reaching and best known consumer brands. I'm excited to see what we can create together in the future.

Heather McKee

BEHAVIORAL SCIENTIST

GLOBAL COFFEEHOUSE CHAIN PROJECT

OUR CLIENT SUCCESS

Annual revenue increase.

By launching a behavioral science practice at the core of the organization, we helped one of the largest insurers in North America realize $30M increase in annual revenue .

Increase in Monthly Users

By redesigning North America's first national digital platform for mental health, we achieved a 52% lift in monthly users and an 83% improvement on clinical assessment.

Reduction In Design Time

By designing a new process and getting buy-in from the C-Suite team, we helped one of the largest smartphone manufacturers in the world reduce software design time by 75% .

Reduction in Client Drop-Off

By implementing targeted nudges based on proactive interventions, we reduced drop-off rates for 450,000 clients belonging to USA's oldest debt consolidation organizations by 46%

Randomized Controlled Trial

Psychological theories.

Automatic Thinking

Eager to learn about how behavioral science can help your organization?

Get new behavioral science insights in your inbox every month..

• MS in the Learning Sciences
• Tuition & Financial Aid

Qualitative vs. quantitative data analysis: How do they differ?

Learning analytics have become the cornerstone for personalizing student experiences and enhancing learning outcomes. In this data-informed approach to education there are two distinct methodologies: qualitative and quantitative analytics. These methods, which are typical to data analytics in general, are crucial to the interpretation of learning behaviors and outcomes. This blog will explore the nuances that distinguish qualitative and quantitative research, while uncovering their shared roles in learning analytics, program design and instruction.

What is qualitative data?

Qualitative data is descriptive and includes information that is non numerical. Qualitative research is used to gather in-depth insights that can't be easily measured on a scale like opinions, anecdotes and emotions. In learning analytics qualitative data could include in depth interviews, text responses to a prompt, or a video of a class period. 1

What is quantitative data?

Quantitative data is information that has a numerical value. Quantitative research is conducted to gather measurable data used in statistical analysis. Researchers can use quantitative studies to identify patterns and trends. In learning analytics quantitative data could include test scores, student demographics, or amount of time spent in a lesson. 2

Key difference between qualitative and quantitative data

It's important to understand the differences between qualitative and quantitative data to both determine the appropriate research methods for studies and to gain insights that you can be confident in sharing.

Data Types and Nature

Examples of qualitative data types in learning analytics:

• Observational data of human behavior from classroom settings such as student engagement, teacher-student interactions, and classroom dynamics
• Textual data from open-ended survey responses, reflective journals, and written assignments
• Feedback and discussions from focus groups or interviews
• Content analysis from various media

Examples of quantitative data types:

• Standardized test, assessment, and quiz scores
• Grades and grade point averages
• Attendance records
• Time spent on learning tasks
• Data gathered from learning management systems (LMS), including login frequency, online participation, and completion rates of assignments

Methods of Collection

Qualitative and quantitative research methods for data collection can occasionally seem similar so it's important to note the differences to make sure you're creating a consistent data set and will be able to reliably draw conclusions from your data.

Qualitative research methods

Because of the nature of qualitative data (complex, detailed information), the research methods used to collect it are more involved. Qualitative researchers might do the following to collect data:

• Conduct interviews to learn about subjective experiences
• Host focus groups to gather feedback and personal accounts
• Observe in-person or use audio or video recordings to record nuances of human behavior in a natural setting
• Distribute surveys with open-ended questions

Quantitative research methods

Quantitative data collection methods are more diverse and more likely to be automated because of the objective nature of the data. A quantitative researcher could employ methods such as:

• Surveys with close-ended questions that gather numerical data like birthdates or preferences
• Observational research and record measurable information like the number of students in a classroom
• Automated numerical data collection like information collected on the backend of a computer system like button clicks and page views

Analysis techniques

Qualitative and quantitative data can both be very informative. However, research studies require critical thinking for productive analysis.

Qualitative data analysis methods

Analyzing qualitative data takes a number of steps. When you first get all your data in one place you can do a review and take notes of trends you think you're seeing or your initial reactions. Next, you'll want to organize all the qualitative data you've collected by assigning it categories. Your central research question will guide your data categorization whether it's by date, location, type of collection method (interview vs focus group, etc), the specific question asked or something else. Next, you'll code your data. Whereas categorizing data is focused on the method of collection, coding is the process of identifying and labeling themes within the data collected to get closer to answering your research questions. Finally comes data interpretation. To interpret the data you'll take a look at the information gathered including your coding labels and see what results are occurring frequently or what other conclusions you can make. 3

Quantitative analysis techniques

The process to analyze quantitative data can be time-consuming due to the large volume of data possible to collect. When approaching a quantitative data set, start by focusing in on the purpose of your evaluation. Without making a conclusion, determine how you will use the information gained from analysis; for example: The answers of this survey about study habits will help determine what type of exam review session will be most useful to a class. 4

Next, you need to decide who is analyzing the data and set parameters for analysis. For example, if two different researchers are evaluating survey responses that rank preferences on a scale from 1 to 5, they need to be operating with the same understanding of the rankings. You wouldn't want one researcher to classify the value of 3 to be a positive preference while the other considers it a negative preference. It's also ideal to have some type of data management system to store and organize your data, such as a spreadsheet or database. Within the database, or via an export to data analysis software, the collected data needs to be cleaned of things like responses left blank, duplicate answers from respondents, and questions that are no longer considered relevant. Finally, you can use statistical software to analyze data (or complete a manual analysis) to find patterns and summarize your findings. 4

Qualitative and quantitative research tools

From the nuanced, thematic exploration enabled by tools like NVivo and ATLAS.ti, to the statistical precision of SPSS and R for quantitative analysis, each suite of data analysis tools offers tailored functionalities that cater to the distinct natures of different data types.

Qualitative research software:

NVivo: NVivo is qualitative data analysis software that can do everything from transcribe recordings to create word clouds and evaluate uploads for different sentiments and themes. NVivo is just one tool from the company Lumivero, which offers whole suites of data processing software. 5

ATLAS.ti: Similar to NVivo, ATLAS.ti allows researchers to upload and import data from a variety of sources to be tagged and refined using machine learning and presented with visualizations and ready for insert into reports. 6

SPSS: SPSS is a statistical analysis tool for quantitative research, appreciated for its user-friendly interface and comprehensive statistical tests, which makes it ideal for educators and researchers. With SPSS researchers can manage and analyze large quantitative data sets, use advanced statistical procedures and modeling techniques, predict customer behaviors, forecast market trends and more. 7

R: R is a versatile and dynamic open-source tool for quantitative analysis. With a vast repository of packages tailored to specific statistical methods, researchers can perform anything from basic descriptive statistics to complex predictive modeling. R is especially useful for its ability to handle large datasets, making it ideal for educational institutions that generate substantial amounts of data. The programming language offers flexibility in customizing analysis and creating publication-quality visualizations to effectively communicate results. 8

Applications in Educational Research

Both quantitative and qualitative data can be employed in learning analytics to drive informed decision-making and pedagogical enhancements. In the classroom, quantitative data like standardized test scores and online course analytics create a foundation for assessing and benchmarking student performance and engagement. Qualitative insights gathered from surveys, focus group discussions, and reflective student journals offer a more nuanced understanding of learners' experiences and contextual factors influencing their education. Additionally feedback and practical engagement metrics blend these data types, providing a holistic view that informs curriculum development, instructional strategies, and personalized learning pathways. Through these varied data sets and uses, educators can piece together a more complete narrative of student success and the impacts of educational interventions.

Master Data Analysis with an M.S. in Learning Sciences From SMU

Whether it is the detailed narratives unearthed through qualitative data or the informative patterns derived from quantitative analysis, both qualitative and quantitative data can provide crucial information for educators and researchers to better understand and improve learning. Dive deeper into the art and science of learning analytics with SMU's online Master of Science in the Learning Sciences program . At SMU, innovation and inquiry converge to empower the next generation of educators and researchers. Choose the Learning Analytics Specialization to learn how to harness the power of data science to illuminate learning trends, devise impactful strategies, and drive educational innovation. You could also find out how advanced technologies like augmented reality (AR), virtual reality (VR), and artificial intelligence (AI) can revolutionize education, and develop the insight to apply embodied cognition principles to enhance learning experiences in the Learning and Technology Design Specialization , or choose your own electives to build a specialization unique to your interests and career goals.

For more information on our curriculum and to become part of a community where data drives discovery, visit SMU's MSLS program website or schedule a call with our admissions outreach advisors for any queries or further discussion. Take the first step towards transforming education with data today.

• Retrieved on August 8, 2024, from nnlm.gov/guides/data-glossary/qualitative-data
• Retrieved on August 8, 2024, from nnlm.gov/guides/data-glossary/quantitative-data
• Retrieved on August 8, 2024, from cdc.gov/healthyyouth/evaluation/pdf/brief19.pdf
• Retrieved on August 8, 2024, from cdc.gov/healthyyouth/evaluation/pdf/brief20.pdf
• Retrieved on August 8, 2024, from lumivero.com/solutions/
• Retrieved on August 8, 2024, from atlasti.com/
• Retrieved on August 8, 2024, from ibm.com/products/spss-statistics
• Retrieved on August 8, 2024, from cran.r-project.org/doc/manuals/r-release/R-intro.html#Introduction-and-preliminaries

Return to SMU Online Learning Sciences Blog

Southern Methodist University has engaged Everspring , a leading provider of education and technology services, to support select aspects of program delivery.

This will only take a moment

• Number System and Arithmetic
• Trigonometry
• Probability
• Mensuration
• Linear Algebra
• CBSE Class 8 Maths Formulas
• CBSE Class 9 Maths Formulas
• CBSE Class 10 Maths Formulas
• CBSE Class 11 Maths Formulas
• Qualitative Data

Qualitative data is defined as data that approximates and characterizes. Qualitative data can be observed and recorded. In the field of analysis, the terms “qualitative data” and “quantitative data” are used frequently. Quantitative and Qualitative are the two sides of the coin named “Data in Statistics” but as many people are familiar with quantitative data (i.e., numerical data of various sorts), qualitative data is often less understood. Understanding the qualitative data is essential for researchers, analysts, decision-makers, or anyone who wants to gain deep insights into people’s behaviors, attitudes, and experiences.

Qualitative data represents information and concepts that are not quantified numerically. They are typically acquired through sources like interviews, focus groups, personal diaries, lab notebooks, maps, photographs, and other observational or printed materials.

In this article, we have tried to explain Qualitative data with different approaches to its analysis, and also learn about the advantages and disadvantages of Qualitative Data.

Types of Data in Statistics

The grouping of data can be based on the quantitative and qualitative aspects of the gathered information, and data can be classified into the following types:

• Quantitative Data

Types of Data

Qualitative Data in Statistics

Qualitative Data uses variables to represent labels or characteristics of entities or objects, such as movie genres or travel methods. The labels cannot be represented in numerical form, and their numerical values may not hold any significance. Qualitative data is also known as categorical data it is expressed through indicators and deals with perceptions. 

Qualitative data cannot be averaged, and aggregate methods like mean or average do not hold for non-numerical data. Qualitative data can be grouped based on categories, and it is useful in determining the frequency of traits or characteristics. For instance, the color of hair can be categorized into three main colors, being, black-brown or blonde. It deals with perceptions. Qualitative data is useful in determining the particular frequency of traits or characteristics.

Qualitative Data Examples

There are several examples of Qualitative Data in the real world, some of these examples are:

• Interview transcripts: Data collected from survey forms after the interviews can provide rich qualitative data that describes the opinions, attitudes, and experiences of participants.
• Observation notes: When observing a behavior or phenomenon, recorded data of that phenomenon is also an example of qualitative data as it can tell us about the characteristics, context, and nuances of the observed phenomenon.
• Open-ended survey responses: In a survey, there are some open-ended questions sometimes to know about the participant’s experiences, perceptions, and opinions on a given topic. This data is also an example of qualitative data.

Features of Qualitative Data

The features or characteristics of the qualitative data are as follows.

• Qualitative data is descriptive in nature i.e., it describes and explains the phenomenon in-depth, and often provides rich contextual information as well.
• Qualitative data is non-numerical in nature, i.e., it is in the form of notes, photos, and survey forms.
• As this data is descriptive and non-numerical, it can be interpreted by different people differently, thus the analysis of this kind of data varies with the researcher.
• In Qualitative data collection, collected data is not very specific. It has open-ended responses and detailed answers and experiences provided by the participants.

Types of Qualitative Data

Qualitative data can be further categorized into the following types:

Nominal Data

Ordinal data.

Let’s understand these types in detail as follows.

Nominal data is represented using names, as indicated by their Latin origin. It includes named or labeled data and does not take numerical values into consideration. For example, different movie or series genres, such as horror, sci-fi, and rom-com, are nominal categorical data. They are labeled in different forms.

Ordinal qualitative data uses a certain scale or measure to group data into categories or groups. The data is generally ordered or measured, but the scale used to represent the data may not be standard or specific. This type of data includes numerical values and displays properties of both categorical data and numerical data. Categorical data can be analyzed by making groups, and it can be visually represented using bar graphs. Ordinal categorical data can be illustrated using surveys that use numbers to compute comparison data belonging to groups under categorical variables.

Qualitative Data Analysis

Analysis of data is a much more crucial part than the collection of it as data in itself without analysis didn’t tell us anything about the phenomenon for which it is collected. As for the analysis of Qualitative Data, there can be two main approaches:

Deductive Approach

Inductive approach.

The deductive approach to qualitative data analysis starts with the preconceived ideas or concepts for which we collect data and analyze it to see if the evidence supports or nullifies these preconceived ideas. Some steps involved in using the deductive approach to qualitative data analysis:

• The first step in this approach is to develop a theoretical framework based on thorough research, which further will be proved by the data or not.
• After the completion of the framework or hypothesis, we collect the data using various means.
• After the collection of data, we use programming languages to code Machine Learning models to find the patterns which are relevant to our hypothesis.
• After all this, we analyze the results and draw a conclusion on whether our hypothesis is correct or not or if it needs much more data to conclude.

The inductive approach to qualitative data analysis starts with the collection of data and works its way towards identifying patterns, and themes. It is an approach researchers explore various different themes and concludes the results as the hypothesis with the evidence from the data. Unlike the deductive approach, here researchers always arise at a conclusion with some correct hypothesis.

The following are some steps involved in using the inductive approach to qualitative data analysis:

• In this approach, we first collect the data using various methods such as interviews, observations, and various focus groups. This data is usually in the form of audio recordings, transcripts, notes, or photos.
• After the collection of data, basic coding procedures start which helps us identify and label the segments of data which represents similar idea and concepts.
• After the labeling and identification of data are complete, some basic patterns arise in the data, which need further research and pattern finding where the Machine Learning models are used.
• After all the research data is used as evidence to publish the findings of the research. Now a hypothesis or framework is developed using all the themes and patterns to support the framework.

Difference between Nominal and Ordinal Data

Some key differences between both types of Qualitative Data can be listed in the following table:

Advantages and Disadvantages of Qualitative Data

There are advantages and disadvantages to using Qualitative Data, as data is very rich in nature so a collection of this type of data is very useful for many cases, but there are some disadvantages of it as well. Let’s dive into the advantages and disadvantages of Qualitative Data in detail.

Advantages of Qualitative Data

Some advantages of Qualitative Data are as follows:

• Richness and depth of data: Qualitative data provides a rich and in-depth understanding of the phenomenon being studied and can also reveal complex relationships, social norms, and cultural practices.
• Flexibility: Qualitative research is flexible, which means that researchers can adapt their methods of collection, amount and type of data collected, and analysis to the specific needs of the study. 
• Participant perspectives: Qualitative data is often collected through interviews, which provide the researcher with the opportunity to understand participants’ perspectives. 
• Uncovering hidden phenomena: Qualitative data is particularly useful when researchers want to explore new or under-researched topics. This type of data can reveal previously unknown phenomena or provide insight into existing topics.

Disadvantages of Qualitative Data

Some disadvantages of Qualitative Data are as follows:

• Subjectivity: As qualitative data is often collected through interviews or observations, that’s why the researcher’s own biases and beliefs can influence the data and that can lead to subjective interpretations of the data.
• Small sample sizes : Qualitative research typically involves small sample sizes, which can limit the generalizability of the findings. 
• Time-consuming: Qualitative research can be time-consuming, particularly when compared to quantitative research as all the steps in this type of data are time-consuming from collection to analysis.
• Difficulty in data analysis: Qualitative data is often complex and difficult to analyze. Researchers need to be skilled in data analysis and interpretation to ensure that their findings are accurate and reliable.
• Different Types of Data
• Difference Between Qualitative and Quantitative Data

Sample Questions on Qualitative Data

Question 1: To which category, the game data for the game “name, place animal or thing” will belong?

Qualitative data will be used to illustrate the type of data used to represent the names for the places, animals, things. 

Question 2: Which type of data is used by the evaluator to grade the students using a range of marks?

The marks are expressed in the range, or using perfect integrals. Ordinal data is used to represent the range of data distribution used by the evaluator.  

Question 3: The following table depicts the percentage of people who prefer a certain movie genre. Can you represent this categorical data using a pie chart?

Sports Percentage of students Calculation of Angle [Angle = (Percentage / 100) x 360°] Angle Cricket 25% Angle = (25/100) x 360° 90° Table Tennis 35% Angle = (35/100) x 360° 126° Football 40% Angle = (40/100) x 360° 144° Thus, pie chart of the given qualitative data is as follows:

Question 4: The following bar graph depicts the ordinal categorical data of the mobile phone company according to price range.

Answer the following questions according to the bar graph

• What is the total price if someone buys all three brands of phones?
• Find the average price of all the phones.

Based on the observations made from the bar graph: Total number of students = 30k + 55k + 45k = 130k Average of the price of all the Phones = (30 + 55 + 45)/3 = 130/3 = 46.67 k

Practice Problems

• In a survey, respondents were asked to select their favorite color from the options: Red, Blue, Green, and Yellow. Which type of qualitative data is represented by this survey?
• A study categorizes students based on their participation in extracurricular activities: Sports, Arts, Music, and None. What type of qualitative data is this?
• A teacher records the performance of students in a class as “Excellent,” “Good,” “Average,” or “Poor.” What type of data is being collected?
• A research survey asks participants to select their preferred mode of transportation: Car, Bike, Bus, or Walk. Identify the type of qualitative data represented.
• In a focus group, participants are asked to rank their satisfaction with a product as “Very Satisfied,” “Satisfied,” “Neutral,” “Dissatisfied,” or “Very Dissatisfied.” What type of qualitative data does this represent?
• A company’s HR department categorizes employees based on their job titles: Manager, Engineer, Technician, and Clerk. What type of data is this?
• A fashion survey asks respondents to choose their preferred clothing style: Casual, Formal, or Sportswear. Which type of qualitative data is being collected?
• A restaurant categorizes its menu items by cuisine type: Italian, Chinese, Indian, and Mexican. What type of qualitative data does this represent?
• A political survey asks participants to identify their political affiliation as Democrat, Republican, Independent, or Other. What type of data is this?
• A marketing research study segments customers based on their loyalty to a brand as “Loyal,” “Occasional,” or “New.” What type of qualitative data is being collected?

Qualitative data is a type of non-numeric information that categorizes and describes various things, making it easier to find patterns and trends. It’s critical for examining a community’s behavior, tastes, and features. For instance, insights can be gained when qualitative analyses are done on data classified into nominal or ordinal categories. This method has gained popularity in areas such as marketing research and social sciences.

Qualitative Data – FAQs

What is qualitative or categorical data.

Qualitative data is the non-numerical data which describes the qualities, characteristics, and other descriptive information about the phenomenon or the subject for which data is collected.

What are Some Examples of Qualitative Data?

Some examples of qualitative data include survey forms of interviews or focus groups, observational notes, photographs, and other forms of non-numerical data.

What are Some Common Methods for Collecting Qualitative Data?

Qualitative Data is often collected through observation, interviews, focus groups, and other forms of subjective data collection methods .

How is Qualitative Data Analyzed?

Qualitative data is typically analyzed using two approaches which are covered in detail in this article. Deductive Approach Inductive Approach

What are the Advantages of Qualitative Data?

Some advantages of use of qualitative data are: Qualitative data provides in-depth information about a subject or phenomenon.  It can also provide rich descriptions of the context and social interactions surrounding the subject or phenomenon.  Qualitative data can be more flexible in terms of data collection and analysis methods, allowing for more creative and iterative approaches to research.

What are the Disadvantages of Qualitative Data?

Some disadvantages of use of qualitative data are: Qualitative data can be time-consuming and resource-intensive to collect and analyze.  As qualitative data is subjective and interpretive, there may be concerns about the reliability and validity of the data.  Qualitative data may also be less generalizable than quantitative data, as it is often focused on specific contexts and perspectives.

Please Login to comment...

Similar reads.

• Mathematics
• School Learning
• Math-Concepts
• Best 10 IPTV Service Providers in Germany
• Python 3.13 Releases | Enhanced REPL for Developers
• IPTV Anbieter in Deutschland - Top IPTV Anbieter Abonnements
• Best SSL Certificate Providers in 2024 (Free & Paid)
• Content Improvement League 2024: From Good To A Great Article

Improve your Coding Skills with Practice

What kind of Experience do you want to share?

• Usability testing

Run remote usability tests on any digital product to deep dive into your key user flows

• Product analytics

Learn how users are behaving on your website in real time and uncover points of frustration

• Research repository

A tool for collaborative analysis of qualitative data and for building your research repository and database.

• Trymata Blog

How-to articles, expert tips, and the latest news in user testing & user experience

• Knowledge Hub

Detailed explainers of Trymata’s features & plans, and UX research terms & topics

• Plans & Pricing

Get paid to test

• User Experience (UX) testing
• User Interface (UI) testing
• Ecommerce testing
• Remote usability testing
• Plans & Pricing
• Customer Stories

How do you want to use Trymata?

Conduct user testing, desktop usability video.

You’re on a business trip in Oakland, CA. You've been working late in downtown and now you're looking for a place nearby to grab a late dinner. You decided to check Zomato to try and find somewhere to eat. (Don't begin searching yet).

• Look around on the home page. Does anything seem interesting to you?
• How would you go about finding a place to eat near you in Downtown Oakland? You want something kind of quick, open late, not too expensive, and with a good rating.
• What do the reviews say about the restaurant you've chosen?
• What was the most important factor for you in choosing this spot?
• You're currently close to the 19th St Bart station, and it's 9PM. How would you get to this restaurant? Do you think you'll be able to make it before closing time?
• Your friend recommended you to check out a place called Belly while you're in Oakland. Try to find where it is, when it's open, and what kind of food options they have.
• Now go to any restaurant's page and try to leave a review (don't actually submit it).

What was the worst thing about your experience?

It was hard to find the bart station. The collections not being able to be sorted was a bit of a bummer

What other aspects of the experience could be improved?

Feedback from the owners would be nice

What did you like about the website?

The flow was good, lots of bright photos

What other comments do you have for the owner of the website?

I like that you can sort by what you are looking for and i like the idea of collections

You're going on a vacation to Italy next month, and you want to learn some basic Italian for getting around while there. You decided to try Duolingo.

• Please begin by downloading the app to your device.
• Choose Italian and get started with the first lesson (stop once you reach the first question).
• Now go all the way through the rest of the first lesson, describing your thoughts as you go.
• Get your profile set up, then view your account page. What information and options are there? Do you feel that these are useful? Why or why not?
• After a week in Italy, you're going to spend a few days in Austria. How would you take German lessons on Duolingo?
• What other languages does the app offer? Do any of them interest you?

I felt like there could have been a little more of an instructional component to the lesson.

It would be cool if there were some feature that could allow two learners studying the same language to take lessons together. I imagine that their screens would be synced and they could go through lessons together and chat along the way.

Overall, the app was very intuitive to use and visually appealing. I also liked the option to connect with others.

Overall, the app seemed very helpful and easy to use. I feel like it makes learning a new language fun and almost like a game. It would be nice, however, if it contained more of an instructional portion.

All accounts, tests, and data have been migrated to our new & improved system!

Use the same email and password to log in:

Legacy login: Our legacy system is still available in view-only mode, login here >

What’s the new system about? Read more about our transition & what it-->

What is Reflexivity in Qualitative Research? Definition, Process and Examples

Conduct End-to-End User Testing & Research

What is Reflexivity in Qualitative Research?

Reflexivity in qualitative research is defined as the practice of self-awareness and critical examination of the researcher’s influence on the research process. It involves acknowledging and addressing the researcher’s positionality, biases, values, and experiences that may shape the study’s design, data collection, and interpretation. Reflexivity is grounded in the understanding that researchers are not neutral observers but actively contribute to the construction of knowledge through their interactions with participants and engagement with the data.

The first aspect of reflexivity involves recognizing the researcher’s subjectivity and the potential impact of their background, beliefs, and experiences on the research. Researchers bring their own perspectives to the study, influencing everything from the formulation of research questions to the interpretation of findings. By acknowledging this subjectivity, researchers can take steps to minimize bias and enhance the transparency and validity of their research.

Secondly, reflexivity prompts researchers to document and critically reflect on their decision-making processes throughout the research journey. This includes considerations of how personal beliefs and experiences may shape the framing of questions during interviews, the selection of participants, and the interpretation of data. Maintaining a reflexive journal or diary allows researchers to capture insights into their evolving awareness and potential biases.

Furthermore, reflexivity encourages an ongoing dialogue between the researcher and the data. As researchers engage with participants and analyze qualitative data, they continuously reflect on how their own perspectives may influence the interpretation of findings. This iterative process enables a deeper understanding of the complex dynamics at play and allows for adjustments in the research approach as needed.

Reflexivity in qualitative research encompasses several key characteristics that highlight the self-awareness and critical reflection of the researcher throughout the research process. These characteristics contribute to the transparency, rigor, and ethical conduct of qualitative studies:

• Reflexivity involves recognizing and acknowledging the subjectivity of the researcher. Researchers are aware that their personal experiences, beliefs, and background can shape the research process, influencing decisions from the formulation of research questions to data interpretation.
• Researchers engage in the documentation of their personal biases, assumptions, and values. This involves maintaining a reflexive journal or diary where researchers record their reflections on how their own perspectives may impact various aspects of the research, including participant interactions and data analysis.
• Reflexivity promotes ongoing critical self-reflection, encouraging researchers to examine their own role in shaping the research. This includes considering how personal biases might affect interactions with participants, the framing of interview questions, and the interpretation of qualitative data.
• Researchers reflect on the power dynamics inherent in the research process, acknowledging their position of authority and influence. This awareness extends to how the researcher’s background and societal privileges may impact interactions with participants, potentially influencing the participants’ responses.
• Reflexivity emphasizes transparency in reporting, requiring researchers to be explicit about their own roles and perspectives. This transparency extends to research publications, ensuring that readers understand the researcher’s positionality and potential influences on the study’s outcomes.
• Researchers may adapt research methods in response to ongoing reflections and insights gained during the study. Reflexivity allows for flexibility in the research design, enabling adjustments to data collection and analysis approaches as the researcher gains deeper insights into their own biases and the dynamics at play.
• Reflexivity includes a consideration of ethical implications. Researchers actively think about the ethical dimensions of their decisions, from obtaining informed consent to protecting participant confidentiality. Ethical considerations are intertwined with reflexive practices to ensure the well-being and rights of participants.
• Engaging in a dialogue with colleagues is a key characteristic of reflexivity. Researchers seek input and feedback from peers, mentors, or other experts to enrich their reflections. Collaborative discussions contribute to a more comprehensive understanding of the researcher’s positionality and its potential impact on the research.
• Reflexivity is an iterative process that evolves throughout the research journey. Researchers continuously revisit and refine their reflections as they engage with participants, analyze data, and interpret findings. This iterative approach allows for a dynamic and responsive research process.
• Ultimately, the key characteristic of reflexivity is its contribution to the trustworthiness of qualitative research. By actively acknowledging and addressing the researcher’s influence, reflexivity enhances the credibility, dependability, and transferability of study findings.

These characteristics collectively underscore the importance of reflexivity as an integral part of qualitative research, ensuring that researchers navigate their own subjectivity with transparency and diligence.

Importance of Reflexivity in Qualitative Research

Reflexivity plays a crucial role in qualitative research and holds significant importance for several reasons. It contributes to the transparency, rigor, and ethical conduct of the research process, ultimately enhancing the credibility and trustworthiness of study findings. Here are key reasons highlighting the importance of reflexivity in qualitative research:

• Reflexivity allows researchers to recognize and address their own biases, assumptions, and preconceptions. By acknowledging and actively engaging with their subjectivity, researchers can minimize the impact of personal perspectives on the research process, reducing the risk of biased interpretations and conclusions.
• Engaging in reflexivity fosters self-awareness among researchers. This heightened awareness extends to the researcher’s own role, positionality, and potential influence on the study. Understanding one’s own biases and motivations enables more conscious decision-making throughout the research journey.
• Reflexivity contributes to more nuanced and thoughtful data interpretation. Researchers who continuously reflect on their own perspectives are better equipped to critically analyze and interpret qualitative data. This depth of interpretation leads to a richer understanding of the complexities inherent in participants’ experiences.
• Reflexivity is intertwined with ethical considerations in qualitative research. Researchers who actively reflect on their own values and ethical stance are more likely to make ethical decisions in the design, implementation, and reporting of the study. This contributes to the protection of participants’ rights and well-being.
• Transparent reporting is a hallmark of reflexive qualitative research. Researchers explicitly communicate their own positions, biases, and reflections in research publications, contributing to the overall trustworthiness of the study. Transparency allows readers to assess the potential impact of the researcher on the research outcomes.
• Reflexivity prompts researchers to consider power dynamics within the research context. This includes acknowledging the researcher’s position of authority and the potential influence on participant responses. By being attuned to power imbalances, researchers can strive for more equitable and respectful interactions.
• The ongoing process of reflexivity allows researchers to adapt research strategies as needed. If reflections reveal potential shortcomings or biases in the original approach, researchers can make adjustments to the research design, data collection methods, or analytical frameworks to ensure a more rigorous and valid study.
• Engaging in reflexivity fosters a collaborative research environment. Researchers who actively seek input and feedback from colleagues contribute to the robustness of the study. Peer review becomes an integral part of the research process, allowing for external perspectives to enrich the overall quality of the research.
• Reflexivity contributes to the overall rigor and validity of qualitative research. By systematically addressing the potential influences of the researcher, the study becomes more methodologically sound, dependable, and capable of producing findings that accurately reflect participants’ experiences.

Best Practices for Applying Reflexivity in Qualitative Research 

Applying reflexivity in qualitative research involves integrating self-awareness, critical reflection, and transparency into the research process. Here are some best practices to effectively incorporate reflexivity into qualitative research:

• Consider your own background, values, and assumptions before formulating research questions or designing the study. Early reflexivity sets the tone for the entire research process.
• Record thoughts, insights, and challenges related to your own biases, reactions to participants, and evolving understandings. This journal serves as a valuable tool for continuous self-reflection.
• Regularly review and update your reflexive notes as the research progresses. 
• Explicitly acknowledge your positionality in research publications. Clearly articulate your background, experiences, and any potential biases. This transparency enhances the credibility of the study and allows readers to assess the potential impact of the researcher on the research outcomes.
• Actively engage in critical self-reflection at key points in the research process. Reflect on your role during participant interactions, the formulation of interview questions, and data analysis. Consider how your own experiences and perspectives may influence interpretations.
• Seek external perspectives through collaboration and peer review. Share your reflexive notes and findings with colleagues or mentors, and encourage open discussions about potential biases or assumptions. External input can provide valuable insights and help refine interpretations.
• Pay attention to power dynamics in the research context. Reflect on how your role as a researcher may influence the dynamics between you and participants. Be attuned to the potential impact of your position on participants’ responses and interactions.
• Implement member checking as a reflexive practice. Share key findings with participants to verify the accuracy and relevance of your interpretations. This not only enhances the validity of the study but also allows participants to contribute to the reflexivity process.
• Be flexible in adapting research strategies based on reflexive insights. If ongoing reflections reveal the need for adjustments in the research design, data collection methods, or analytical approaches, be open to making those changes to enhance the study’s rigor.
• If working within a research team, promote reflexivity in team discussions. Encourage team members to share their reflections and insights. This collaborative approach contributes to a more comprehensive understanding of the researcher’s role and its potential impact.
• Consider cultural sensitivity in your reflexivity. Reflect on how cultural backgrounds, both yours and participants’, may influence interactions and interpretations. Reflexivity is crucial in navigating cultural nuances and avoiding cultural bias.
• Integrate reflexivity with other quality criteria in qualitative research, such as dependability, confirmability, and transferability. Reflexivity enhances these criteria by addressing the researcher’s influence on the study and contributing to the overall rigor of the research.

Interested in learning more about the fields of product, research, and design? Search our articles here for helpful information spanning a wide range of topics!

CX Testing: Methods, Challenges & Best Practices for Success

15 user acceptance testing tools for quality & satisfaction, mobile usability test: from preparation to execution & more, ux research process: a step-by-step guide for you.

Educational resources and simple solutions for your research journey

What is Descriptive Research? Definition, Methods, Types and Examples

Descriptive research is a methodological approach that seeks to depict the characteristics of a phenomenon or subject under investigation. In scientific inquiry, it serves as a foundational tool for researchers aiming to observe, record, and analyze the intricate details of a particular topic. This method provides a rich and detailed account that aids in understanding, categorizing, and interpreting the subject matter.

Descriptive research design is widely employed across diverse fields, and its primary objective is to systematically observe and document all variables and conditions influencing the phenomenon.

After this descriptive research definition, let’s look at this example. Consider a researcher working on climate change adaptation, who wants to understand water management trends in an arid village in a specific study area. She must conduct a demographic survey of the region, gather population data, and then conduct descriptive research on this demographic segment. The study will then uncover details on “what are the water management practices and trends in village X.” Note, however, that it will not cover any investigative information about “why” the patterns exist.

Table of Contents

What is descriptive research?

If you’ve been wondering “What is descriptive research,” we’ve got you covered in this post! In a nutshell, descriptive research is an exploratory research method that helps a researcher describe a population, circumstance, or phenomenon. It can help answer what , where , when and how questions, but not why questions. In other words, it does not involve changing the study variables and does not seek to establish cause-and-effect relationships.

Importance of descriptive research

Now, let’s delve into the importance of descriptive research. This research method acts as the cornerstone for various academic and applied disciplines. Its primary significance lies in its ability to provide a comprehensive overview of a phenomenon, enabling researchers to gain a nuanced understanding of the variables at play. This method aids in forming hypotheses, generating insights, and laying the groundwork for further in-depth investigations. The following points further illustrate its importance:

Provides insights into a population or phenomenon: Descriptive research furnishes a comprehensive overview of the characteristics and behaviors of a specific population or phenomenon, thereby guiding and shaping the research project.

Offers baseline data: The data acquired through this type of research acts as a reference for subsequent investigations, laying the groundwork for further studies.

Allows validation of sampling methods: Descriptive research validates sampling methods, aiding in the selection of the most effective approach for the study.

Helps reduce time and costs: It is cost-effective and time-efficient, making this an economical means of gathering information about a specific population or phenomenon.

Ensures replicability: Descriptive research is easily replicable, ensuring a reliable way to collect and compare information from various sources.

When to use descriptive research design?

Determining when to use descriptive research depends on the nature of the research question. Before diving into the reasons behind an occurrence, understanding the how, when, and where aspects is essential. Descriptive research design is a suitable option when the research objective is to discern characteristics, frequencies, trends, and categories without manipulating variables. It is therefore often employed in the initial stages of a study before progressing to more complex research designs. To put it in another way, descriptive research precedes the hypotheses of explanatory research. It is particularly valuable when there is limited existing knowledge about the subject.

Some examples are as follows, highlighting that these questions would arise before a clear outline of the research plan is established:

• In the last two decades, what changes have occurred in patterns of urban gardening in Mumbai?
• What are the differences in climate change perceptions of farmers in coastal versus inland villages in the Philippines?

Characteristics of descriptive research

Coming to the characteristics of descriptive research, this approach is characterized by its focus on observing and documenting the features of a subject. Specific characteristics are as below.

• Quantitative nature: Some descriptive research types involve quantitative research methods to gather quantifiable information for statistical analysis of the population sample.
• Qualitative nature: Some descriptive research examples include those using the qualitative research method to describe or explain the research problem.
• Observational nature: This approach is non-invasive and observational because the study variables remain untouched. Researchers merely observe and report, without introducing interventions that could impact the subject(s).
• Cross-sectional nature: In descriptive research, different sections belonging to the same group are studied, providing a “snapshot” of sorts.
• Springboard for further research: The data collected are further studied and analyzed using different research techniques. This approach helps guide the suitable research methods to be employed.

Types of descriptive research

There are various descriptive research types, each suited to different research objectives. Take a look at the different types below.

• Surveys: This involves collecting data through questionnaires or interviews to gather qualitative and quantitative data.
• Observational studies: This involves observing and collecting data on a particular population or phenomenon without influencing the study variables or manipulating the conditions. These may be further divided into cohort studies, case studies, and cross-sectional studies:
• Cohort studies: Also known as longitudinal studies, these studies involve the collection of data over an extended period, allowing researchers to track changes and trends.
• Case studies: These deal with a single individual, group, or event, which might be rare or unusual.
• Cross-sectional studies : A researcher collects data at a single point in time, in order to obtain a snapshot of a specific moment.
• Focus groups: In this approach, a small group of people are brought together to discuss a topic. The researcher moderates and records the group discussion. This can also be considered a “participatory” observational method.
• Descriptive classification: Relevant to the biological sciences, this type of approach may be used to classify living organisms.

Descriptive research methods

Several descriptive research methods can be employed, and these are more or less similar to the types of approaches mentioned above.

• Surveys: This method involves the collection of data through questionnaires or interviews. Surveys may be done online or offline, and the target subjects might be hyper-local, regional, or global.
• Observational studies: These entail the direct observation of subjects in their natural environment. These include case studies, dealing with a single case or individual, as well as cross-sectional and longitudinal studies, for a glimpse into a population or changes in trends over time, respectively. Participatory observational studies such as focus group discussions may also fall under this method.

Researchers must carefully consider descriptive research methods, types, and examples to harness their full potential in contributing to scientific knowledge.

Examples of descriptive research

Now, let’s consider some descriptive research examples.

• In social sciences, an example could be a study analyzing the demographics of a specific community to understand its socio-economic characteristics.
• In business, a market research survey aiming to describe consumer preferences would be a descriptive study.
• In ecology, a researcher might undertake a survey of all the types of monocots naturally occurring in a region and classify them up to species level.

These examples showcase the versatility of descriptive research across diverse fields.

Advantages of descriptive research

There are several advantages to this approach, which every researcher must be aware of. These are as follows:

• Owing to the numerous descriptive research methods and types, primary data can be obtained in diverse ways and be used for developing a research hypothesis .
• It is a versatile research method and allows flexibility.
• Detailed and comprehensive information can be obtained because the data collected can be qualitative or quantitative.
• It is carried out in the natural environment, which greatly minimizes certain types of bias and ethical concerns.
• It is an inexpensive and efficient approach, even with large sample sizes

Disadvantages of descriptive research

On the other hand, this design has some drawbacks as well:

• It is limited in its scope as it does not determine cause-and-effect relationships.
• The approach does not generate new information and simply depends on existing data.
• Study variables are not manipulated or controlled, and this limits the conclusions to be drawn.
• Descriptive research findings may not be generalizable to other populations.
• Finally, it offers a preliminary understanding rather than an in-depth understanding.

To reiterate, the advantages of descriptive research lie in its ability to provide a comprehensive overview, aid hypothesis generation, and serve as a preliminary step in the research process. However, its limitations include a potential lack of depth, inability to establish cause-and-effect relationships, and susceptibility to bias.

Frequently asked questions

When should researchers conduct descriptive research.

Descriptive research is most appropriate when researchers aim to portray and understand the characteristics of a phenomenon without manipulating variables. It is particularly valuable in the early stages of a study.

What is the difference between descriptive and exploratory research?

Descriptive research focuses on providing a detailed depiction of a phenomenon, while exploratory research aims to explore and generate insights into an issue where little is known.

What is the difference between descriptive and experimental research?

Descriptive research observes and documents without manipulating variables, whereas experimental research involves intentional interventions to establish cause-and-effect relationships.

Is descriptive research only for social sciences?

No, various descriptive research types may be applicable to all fields of study, including social science, humanities, physical science, and biological science.

How important is descriptive research?

The importance of descriptive research lies in its ability to provide a glimpse of the current state of a phenomenon, offering valuable insights and establishing a basic understanding. Further, the advantages of descriptive research include its capacity to offer a straightforward depiction of a situation or phenomenon, facilitate the identification of patterns or trends, and serve as a useful starting point for more in-depth investigations. Additionally, descriptive research can contribute to the development of hypotheses and guide the formulation of research questions for subsequent studies.

Editage All Access is a subscription-based platform that unifies the best AI tools and services designed to speed up, simplify, and streamline every step of a researcher’s journey. The Editage All Access Pack is a one-of-a-kind subscription that unlocks full access to an AI writing assistant, literature recommender, journal finder, scientific illustration tool, and exclusive discounts on professional publication services from Editage.  

Based on 22+ years of experience in academia, Editage All Access empowers researchers to put their best research forward and move closer to success. Explore our top AI Tools pack, AI Tools + Publication Services pack, or Build Your Own Plan. Find everything a researcher needs to succeed, all in one place –  Get All Access now starting at just $14 a month !    

Related Posts

Back to School – Lock-in All Access Pack for a Year at the Best Price

Journal Turnaround Time: Researcher.Life and Scholarly Intelligence Join Hands to Empower Researchers with Publication Time Insights 

• Open access
• Published: 30 August 2024

Explaining the burden of cultural factors on MS disease: a qualitative study of the experiences of women with multiple sclerosis

• Fahimeh Pourhaji 1 , 5 ,
• Mousa Mahdizadeh Taraghdar 2 ,
• Nooshin Peyman 1 , 4 ,
• Jamshid Jamali 3 , 4 &
• Hadi Tehrani 1 , 4  

BMC Women's Health volume  24 , Article number:  477 ( 2024 ) Cite this article

Metrics details

Multiple sclerosis (MS) is a debilitating, non-traumatic disease that is common among young adults. Cultural factors, as background factors, can affect how patients adapt and their quality of life. This study aimed to explain the burden of cultural factors on Multiple sclerosis.

This study was conducted with a qualitative approach and conventional content analysis among women with Multiple sclerosis in Mashhad. The data were collected through semi-structured interviews with women with MS. Fifteen patients with Multiple sclerosis were selected using purposeful sampling. The Graneheim and Lundman method was used to analyze the collected data. The transferability of the study was evaluated using the Guba and Lincoln criteria. MAXQADA 10 software was used to manage and analyze the data.

In explanation of the cultural factors of patients with Multiple sclerosis, one category (cultural tensions) and five subcategories (forced communication with spouse’s family, definition of women’s role in society, people’s behavior, social beliefs and isolation of the patient) were extracted.

The results obtained in this study show that female MS patients face various concerns. Overcoming these challenges require a change in the attitude of people in the society towards women with MS, which is important in the context of formulating practical policies to create a suitable culture. Adopted policies should aim to internalize the culture of changing society’s views of female MS patients. Therefore, the authors argue that there is a need for cultural policies, followed by the systems implementing these policies to consider the challenges mentioned in this study as a priority for MS patients.

Peer Review reports

Multiple sclerosis (MS) is a chronic inflammatory autoimmune disease of the central nervous system (CNS) [ 1 ]. Multiple sclerosis is usually diagnosed between the ages of 20 and 40 [ 2 ]. The prevalence and incidence of MS is expanding worldwide, and the prevalence of MS is estimated to be 35.9 persons per 100,000 population (2.8 million people) in 2020 [ 3 ]. The probability of MS in women is almost to 2–3 times higher than that in men [ 4 , 5 ]. The prevalence of MS in women and men was estimated to be 44.8/ 100,000 and 16.5/ 100,000, respectively [ 6 ].

People suffering from this disease need to deal with and adapt to its everlasting challenges [ 7 ]. Cultural practices and beliefs of patients affect their coping style with challenges. Due to the abundance and complexity of a person’s relationship with the society and its culture, the influence of cultural factors on human behavior cannot be ignored [ 8 ].

Every culture has certain views, behaviors and beliefs that not only affect people’s way of life, roles and their worldviews, but also affect the health and the numerous illnesses that plagues the people in the society [ 9 ]. Cultural differences can influence the concepts of health and diseases of societies and each society creates ways to treat and manage illnesses based on its culture [ 10 ].

The word “culture” refers to systems of knowledge, concepts, rules and activities that are learnable and are passed down from one generation to another [ 11 ].

Culture influences the ways of describing and understanding patients’ experiences and visible behavioral cues in clinical encounters, symptomatology, clinical manifestations, treatment expectations, adaptation to the disease, and treatment responses [ 12 ].

Psychosocial stressors and cultural characteristics may cause problems in communication and affect the diagnosis and treatment [ 13 ]. Sociocultural norms and beliefs lead people in society to have certain expectations based on specific gender roles for women [ 14 ].

For example, the irrational expectations of the spouse’s family and their great influence on the spouse’s decisions has become the basis for more worries in life [ 15 ]. Studies show that the main notions of the way of doing the housework have not changed much for men and women. They also show that housework and taking care of children are still considered the main duties of women [ 16 ].

On the other hand, the unequal distribution of power, resources and responsibilities between men and women has been institutionalized traditionally and has even taken root in women’s own thoughts and has become a rule. In many societies, women are in charge of nutrition, immunization, cleaning, hygiene, management, organizing ceremonies and celebrations without receiving wages, and women must perform tasks such as cleaning, raising children, cooking, and taking care of their husband [ 17 ]. Having children is considered one of the main goals of marriage [ 18 ]. Therefore, social and cultural norms and beliefs impose significant pressure on women by imposing gender expectations on them [ 14 ].

Considering that MS is more common in women of reproductive age, it may have a significant and long-term effect on women and families who are affected by this condition [ 19 ]. One view about pregnancy and the birth of a baby from a mother with MS is that pregnancy is potentially dangerous for the mother and her baby [ 19 ].

Another common concern in MS patients is sexual dysfunction. Sexual dysfunction is a very common and devastating problem in people with MS [ 20 ]. Young women with MS face challenges in finding a partner, raising a family, and managing their sex lives [ 21 ]. Studies show that patients are very discouraged by the behavior of people around them and their seemingly sympathetic advice [ 22 ]. A major issue in MS employment research is the strong effect of disease status on occupational participation [ 23 ]. Studies show that MS affects the occupational status of patients in various ways. Discrimination in the workplace may result in wrongful termination or failure to provide reasonable accommodations [ 24 , 25 , 26 ].

A qualitative study conducted explained the psychosocial factors of the burden of illness and demonstrated that patients with multiple sclerosis experience stress, agitation, and stigmatization [ 27 ]. However, in addition to the psychosocial challenges, women with MS also experience other challenges. Some of these challenges can be related to beliefs, perceptions, and cultural barriers [ 28 ]. In the long term, insensitivity to cultural aspects can have adverse effects on health and thus perpetuates health inequalities [ 29 ].

Many studies have addressed one or two cultural factors affecting the occurrence or exacerbation of MS; however, due to the diversity and extent of cultural factors, none of them provided integrated classification of these factors and the true contribution of cultural factors on the health outcomes of MS patients is not understood. Since studies have not specifically focused on cultural factors affecting MS, in this study, an attempt was made to understand and classify cultural factors that are effective in exacerbating MS. Cultural beliefs are crucial for providing adequate care and support, and efforts to break cultural barriers also enable better care for people with MS. By addressing this research gap, we can help to develop effective cultural interventions. Which ultimately leads to improving the attitude and reducing the health disparity of MS patients.

This study employed a qualitative approach with conventional content analysis to examine women patients with multiple sclerosis (MS) in Mashhad, Iran, a major city located in the eastern part of the country, during the year 2022.  

Participants and recruitment

In this research, the purposeful sampling method was used and the sampling continued until data saturation was reached.

Considering the maximum diversity in social situations in the city level (from different geographical, urban, and rural areas and different ages), the participants were selected from among 4600 patients admitted to the comprehensive MS center and the MS association. Age, duration of illness, level of education, marital status, and occupation were among the important underlying factors considered in this study.

With official permission, the researcher went to the Comprehensive MS Center and the MS association. She explained the purpose and importance of the research to the officials, and the necessary coordination was conducted with the officials of each department. Then, while communicating with the patient, the researcher explained the objectives, the importance of the research and the conditions of the research to the patients. Participants were allowed to bring their family or caregiver with them during the interview. However, all participants preferred to be interviewed alone. Finally, the patients who wanted to participate in the interview were selected and were interviewed after the necessary coordination.

Inclusion and exclusion criteria

Iranian patients with MS (according to the 2017 McDonald criteria) [ 30 ] and residents of Mashhad, can participate in this study after voluntarily completing and signing the consent form, if at least one year has passed since their MS was diagnosed by a physician. The exclusion criterion was the unwillingness of the participants to continue their cooperation at each stage of the research.

Ethical considerations

Before the interviews, the objectives and importance of the research were explained to the participants. The patients were assured that all information and interviews are only for research purposes and confidentiality and anonymization of information is respected in all stages. The participants’ voices were recorded with their permission. All the stages of this study were conducted following the Helsinki Declaration.

Data collection and analysis

Face-to-face semi-structured interviews were conducted with MS patients to collect data. After twelve patients were interviewed, the data became saturated because no new concepts were obtained from the interviews, and the codes and concepts were repeated. It should be noted that three more interviews were conducted to ensure data saturation. Interviews were conducted by the first author (FP: who is a PhD student in health education and health promotion). The interviewer had experience and interest in conducting interviews on factors related to MS. No of the participants withdrew from the study. Two test interviews were conducted to assess the validity of the tool.

Quantitative and qualitative articles on the cultural factors affecting MS worldwide were reviewed to guide the related questions. The questions were then formulated and revised according to the experiences of the research team. The guide questions are provided in Supplementary File 1 .

For example, in this study, questions were asked such as has this disease affected your relationships with others? If yes, how? Can MS affect others relationship with your? Explain it. What factors cause you worry? Explain it.

At the end of any interview, the researcher asked the participants to talk about any topic they wanted, which the researcher did not mention. The interviews were conducted in the MS Comprehensive Center that was suitable in terms of ventilation, light, and sound.

The interviews were conducted between July and September 2022. Depending on the participant’s tolerance level and environmental factors, the duration of each interview varied from 30 to 63 min. In order for personal thoughts to not affect the process of data collection and analysis, the researcher wrote down her thoughts on paper to avoid emphasizing them.

During the study, the researcher carefully observed the participants’ behaviors in terms of feelings, emotions, and reactions. The researcher then added notes collected during the observations to the interview margins. The researcher provided her contact information to the participants so that wherever the participants felt the need to provide more detailed information to the researcher, they could contact the researcher.

A qualitative data analysis was performed using the five-step approach proposed by Graneheim and Lundman. In the first stage, immediately after completing the interviews, the recorded interviews were written on paper to create the primary data. In the second step, the texts were read several times to obtain a general understanding of their content. In the third step, the textual content is divided to determine semantic units and basic codes. In the fourth step, to obtain more comprehensive categories, the primary codes were classified based on their similarities and differences. In the fifth stage, the main subject of each category was determined [ 31 ]. First, the voices of participants were voluntarily recorded using a mobile phone recorder. Data backup was ensured by using two voice recorders. After each interview, the recorded interviews were transcribed on paper and were read several times. In the next step, handwritten transcripts were typed in Word 2016 as the primary research data. Typed interviews were analyzed using MAXQDA version 10 software. In the next step, the important sentences and phrases were first determined, and then the words and sentences (semantic units) were coded by the researcher, and open codes were formed. After the initial codes were extracted, those that were semantically and conceptually similar or related were classified into a category and formed a subcategory of a single topic with a higher level of abstraction. After the formation of more comprehensive categories, the analysis process continued to create the main and subcategories. To check the created codes, an independent researcher also checked the codes, and if there was an unresolved difference between the first and second researchers, the third researcher entered to resolve the difference (Fig.  1 ).

Methodological considerations

Validity, verifiability, transferability, and reliability are the four standards of Lincoln and Guba that were considered to strengthen the data [ 32 , 33 ]. To validate the data, interviews were conducted with various patients. The extracted codes and texts were shared with several interviewees. To review the transcribed interviews, several meetings were held with the team leader.

To ensure the correctness of data, some of the codes and free subsets were checked by experts. In addition, part of the interpretation of the participants was checked by the participants themselves and corrections were made wherever needed.

To assure the transferability of the data, a purposeful sampling method was used, and sampling was performed with maximum diversity and continued until data saturation. The researchers increased the transferability of the data by providing a detailed and step-by-step description of how to conduct the research process, and also described the characteristics of the studied population in order for other researchers to follow the research process. To check the reliability, the research team revised the process in two steps. In the first stage, partial reliability control was carried out and that the researchers checked the categories and coding instructions after working with 10–50% of the data. In the second step, the general reliability was examined by listing the final category at the end of the task (Fig.  1 ).

Flowchart of methodological steps

Tis study was performed through semi-structured interviews with 15 patients with MS. Participants ranged in age from 27 to 52 years with a mean age of 37.13 years old and standard deviation (± 7.49). Participant’s duration of the disease ranged in from 3 to 22 years with a mean of 9.99 and standard deviation (± 6.46). (Table  1 ).

Analysis of the 15 interviews resulted in 138 extracted codes, and after exclusion of the duplicate codes, a total of 22 main codes remained. These codes were classified into five sub-categories (Obligatory communication with the spouse’s family, definition of women’s role in society, people’s behavior, societal beliefs and patient isolation) and one main categories (cultural tensions). More complete results can be seen in Table  2 .

In the following, we will describe each of the categories.

Main category: cultural tensions

First subcategory: obligatory communication with the spouse’s family.

The participants reported that obligatory communication with the spouse’s family such as unwanted participation in parties, tolerating snide comments and remarks for the sake of their spouse, keeping the spouse’s family happy, recurring arguments, jealousy, turning their husband against them, and constant judgments were associated with worsening symptoms.

Participant No. 7 (Duration of illness 3 years): “… my husband doesn’t know about my illness, I don’t want him to know about my illness, because I’m afraid that my husband will tell his family, I haven’t visited my husband’s family for a long time, because communicating with them bothers me. Fortunately, now that I don’t see them anymore I feel much better. That’s why I’m calm. That’s the only reason. When I look back, I ask myself why did I make such a mistake! I ask myself, when they create so many problems for me and my children, why did I go and see them in the first place? Why did I keep telling myself that no, you should go visit them for the sake of your husband?”

Participant No. 8 (Duration of illness 13 years): “…there are many people who get on my nerves, like in the beginning my mother-in-law used to tease me a lot. It’s because of my mother-in-law’s behavior that I’m not well and that I’ve reached this point. Whenever I went to their house I used to come back sad and crying. Now it’s been forty days since the last time I went to their house. The last time, she said something to me again that made me very upset, my husband wanted us to go to his mother’s house but I said I won’t come to their house anymore, you go. There are some people whom you cannot break your relationship with. My mother-in-law disregards my illness, even though she knows that I am sick, she still speaks her mind.”

Second subcategory: definition of women’s role in society

In this context, the participants consider societal beliefs about women’s roles such as taking care of their husband and children, housekeeping, being an income generator, keeping up appearances, meeting the expectations of the family, and having adequate sexual activities to be effective.

Participant No. 11 (Duration of illness 5 years): “… I have four children; I don’t have time to exercise at all. All day long, I am doing housework, taking care of children and cooking. I told my husband: One of the patients is participating in training classes, exercise classes, flower-making classes and goes out of the house sometimes and her condition has improved a lot, but he said to me: If I were that woman’s husband, I would definitely divorce her.” my husband believes that the wife’s job is doing housework.”

Participant No. 3 (Duration of illness 3 years): “… I tried very hard to always have good and perfect marital life, because my husband cares a lot about sexual matters. Sometimes I am not physically and mentally ready to have sex, but I know that I am obligated to have sex with my husband. Because if I say that I don’t want to have sex, my husband says: It’s because of your MS that you have a lower sex drive.”

Third subcategory: people’s behavior

In this context, the participants consider people’s behavior such as pitying the patient, changes in people’s views, and backbiting the patient’s family members to be effective.

Participant No. 4 (Duration of illness 9 years): “…we are like other people, we don’t like being pitied by others and people changing their behavior because of our illness, we are just like them, we are people, we have a life, only our condition has become a little more difficult, that’s all.”

Participant No. 7 (Duration of illness 12 years): “… I don’t have any expectations from the people around me, people are bad, if they find out that you have a problem, they take advantage of you.

Fourth subcategory: societal beliefs

In this context, the participants consider societal beliefs such as the belief that the patient should not get married nor get pregnant, the patient being a burden, and not having a place in society to be effective factors.

Participant No. 10 (Duration of illness 3 years): “…for now, my husband said: go and take the appropriate medicine and treatment, when your body reaches a stable state, then we will have a baby. It is not advisable to have a baby now. Of course, I’m also afraid, everyone also says it won’t be too late to have a baby, you should wait for a while.”

Participant No. 2 (Duration of illness 13 years): “… but one of the main reasons for choosing Cinnovex was that it was free, because I did not want my husband to pay for these issues. My husband does not say that he won’t pay, but I would be very upset if I became a burden on my husband.”

Participant No. 14 (Duration of illness 5 years): “… Everyone thinks of ideal things when getting married, and everyone wants to choose a beautiful, healthy, and rich girl for their son. I am very worried. If you say you are sick before marriage, they refuse to marry you.”

Fifth subcategory: patient isolation

In this context, participants consider behaviors that lead to patient isolation such as reduced participation, ignoring the patient, and lack of trust in the patient, to be effective factors.

Participant No. 2 (Duration of illness 13 years): “…I didn’t tell the company that I was sick. If a private company knows that you are sick, they won’t hire you. Private companies are so conservative because of insurance issues, and most of the people there do not have a positive attitude and they aren’t fun people to work with, everyone is looking for their own interests and they might even take advantage of your illness, for example, the moment something bad happens, they will say that this lady has a problem and she is not fit for working in this company.”

Participant No. 7 (Duration of illness 12 years): “… I am his big sister, but without telling me anything, they went to propose for my brother, and they preferred not to include me. Then they said: We were afraid that something would be said during the proposal that would upset you. We didn’t tell you anything, for your own sake. But it was pretty clear that they didn’t want me, who is sick and stutters because of my MS, to go to the proposal with them. They thought to themselves that if the girl’s family saw my condition, they wouldn’t let their daughter marry my brother.”

Participant No. 5 (Duration of illness 13 years): “… I was very stressed at work and my boss was very pushy about whether the work was done correctly or not. It was as if he did not trust my performance. Last time there was a fierce fight between us which made me leave the company, and again in the next company, there were still many challenges that were bothering me.”

This study aimed to explain the burden of cultural factors on Multiple sclerosis. Based on the results, one main category (cultural tensions) and five subcategories (obligatory communication with the spouse’s family, definition of women’s role in society, people’s behavior, societal beliefs and patient isolation) were constructed.

The results of this study showed that female MS patients are often forced to communicate with their spouse’s family in order to keep their spouse satisfied and prevent marital disputes. This obligatory communication may impose a lot of psychological pressure on them, which can lead to the exacerbation of the disease.

The behaviors of the spouse’s family, such as their interferences, jealousy, selfishness, gossips, vilification, insults, disrespect and their objections to the lack of sociability of the husband and wife cause consequences such as increasing worries, increasing tension between spouses, and the emergence and onset of depression symptoms [ 34 , 35 ]. The results of Datta’s study showed that conflict with the husband’s family and especially the mother-in-law is a fundamental issue in the topic of marital conflicts [ 36 ]. A dissatisfying relationship with one’s mother-in-law is an important risk factor for married women, which endangers their health [ 37 ].

The results of this study showed that female MS patients, due to the societal expectations of women’s role, are often forcing themselves to act a certain way in order to keep their husbands happy and avoid marital disputes. This forced relationship may impose a lot of psychological pressure on them, which leads to the exacerbation of their disease.

The main views of men and women about how to do housework have not changed much, and housework and taking care of children are still considered the main duties of women [ 38 ].

The role of women has changed due to economic conditions and social demands, women have to endure tremendous pressure to get a job similar to their men counterparts, while having to maintain an active role in their personal life [ 39 ].

Work-life balance is a key issue in all types of jobs due to dual-career families becoming more common and stressful jobs with long hours becoming the norm. Work life integrated with personal life creates stress [ 40 ].

People with MS, considering the types of sexual dysfunction and its indirect effects on mental health, quality of life and intimate relationships, may see sexual dysfunction as the most negative feature of this disease [ 41 ].

The results of this study showed that female patients with MS often experience changes in the views and behaviors of those around them, and these behavioral changes are disturbing and lead to the exacerbation of their disease.

A study showed that being pitied by others is an uncomfortable situation that is characterized by a lack of understanding of the situation [ 42 ]. Another study showed that most patients notice a change in other people’s opinions of them after the diagnosis [ 43 ].

The results of a study showed that the patients’ families believed that because of the label of the disease, in addition to the patient themselves, the families are also treated differently. They felt that they were judged negatively and were simply ignored [ 44 ].

The results of a study showed that the support of the surrounding people should be such that it does not cause the patients to be dependent on them or create a feeling of being pitied in the patients, so that they can find the identity and purpose of their lives in post-illness conditions [ 45 ].

According to our study, the exposure of female MS patients to societal beliefs increases negative feelings, such as avoiding marriage and feeling like a burden, and these negative feelings are the basis for the exacerbation of the disease.

Women would avoid having children due to the false belief that it would worsen the overall course of the disease [ 46 ].

MS is diagnosed in adulthood and is more common in women. Therefore, many women with this disease are discouraged from starting a family when their disease is diagnosed [ 47 ].

Although pregnancy has been shown to have no effect on MS and MS to have no effect on pregnancy, some women may still be discouraged by some family members and health professionals [ 19 ].

Some patients expressed their discomfort with feeling like a burden and that their family is wasting a lot of time and money on them [ 48 ].

The importance of raising the awareness of family and community members about their possible negative influence on the MS patients and encouraging them to review their behaviors to prevent putting more pressure on the patients, should be emphasized [ 49 ].

Not considering a specific position for these people in society creates difficult and unfortunate conditions for them, especially those who had strong personalities and were influential members of society before contracting the disease [ 50 ].

Patients with physical disabilities believe that their functional limitations cause problems for their caregivers and significant others. Feeling like a burden may lead to distress and complicate the relationship with the caregiver [ 51 , 52 ].

Considering that many women with MS are vulnerable to societal beliefs, it is necessary to formulate policies to change these beliefs so that society can take a step towards positive changes, and to reduce the frequency of these behaviors.

The results of this study showed that female MS patients are ignored by others during the disease, and the trust of others in their abilities decreases. This Distrust may impose a lot of psychological pressure on them, which leads to the exacerbation of their disease.

The results of studies show that many MS patients face a challenging work life. A higher proportion of people with MS report unemployment, part-time employment or reduced working hours, and lower income compared to the general population [ 23 , 53 ].

MS is associated with work difficulties, reduced working hours or their involvement and participation in their workplace, being transferred to jobs or other departments that is below their skill or knowledge level due to their employers’ impression that they are unable to handle the stress or the pressure of such works, and termination of voluntary and involuntary work or unemployment [ 54 ]. Greiton et al. found that the gender of women with MS was associated with their rate of unemployment [ 55 ].

Negative encounters such as discrimination and uncertainty from colleagues, managers or supervisors, and work organizations contribute to job transfer and termination, while positive support is associated with organizational embeddedness and job continuity [ 56 , 57 ].

Women with disabilities have also historically faced double discrimination due to their physical disability and gender, and have been ignored in many parts of society [ 58 ]. Simmons et al.‘s study showed that many MS sufferers have difficulty keeping jobs, even in good economic times [ 59 ].

Most of the participants were dissatisfied with the normalization of the disease for the doctors, followed by their superficial response to the patient and the lack of sufficient attention to the patient, and this issue had reduced their motivation to pursue treatment and follow medical recommendations [ 60 , 61 ].

Research limitations

The results of this study are limited to explaining the burden of cultural factors on disease worsening in women with MS in the Iranian culture. Therefore, to benefit from the findings of this study, it is necessary to conduct similar investigations in other fields and cultures. Although the researcher tried his best to be neutral during the interviews. However, this important principle may not have been inadvertently observed. Finally, more research is needed to provide complete insight into the cultural factors associated with MS.

The results obtained in this study show that female MS patients face concerns. Overcoming these challenges require a change in the attitude of people in the society towards women with MS, which is important in the context of formulating practical policies to create a suitable culture. Adopted policies should aim to internalize the culture of changing society’s views of female MS patients.

Therefore, the authors argue that there is a need for cultural policies, followed by the systems implementing these policies to consider the challenges mentioned in this study as a priority for MS patients.

Data availability

The data sets used and/or analyzed during the current study was available from the corresponding author on reasonable request.

Abbreviations

• Multiple sclerosis

Central Nervous System

Preiningerova JL, Jiraskova Zakostelska Z, Srinivasan A, Ticha V, Kovarova I, Kleinova P, et al. Multiple Scler Microbiome Biomolecules. 2022;12(3):433. https://doi.org/10.3390/biom12030433 .

Article   CAS   Google Scholar  

Krysko KM, Bove R, Dobson R, Jokubaitis V, Hellwig K. Treatment of women with multiple sclerosis planning pregnancy. Curr Treat Options Neurol. 2021;23(4):1–19. https://doi.org/10.1007/s11940-021-00666-4 . 2021.

Barzegar M, Vaheb S, Mirmosayyeb O, Ashtari F, Afshari-Safavi A, Adibi I, et al. Prevalence and incidence of multiple sclerosis in Isfahan, Iran between 1996 and 2021: a population-based study. Multiple Scler Relat Disorders. 2024;84:105479. https://doi.org/10.1016/j.msard.2024.105479 .

Article   Google Scholar  

Azami M, YektaKooshali MH, Shohani M, Khorshidi A, Mahmudi L. Epidemiology of multiple sclerosis in Iran: a systematic review and meta-analysis. PLoS ONE. 2019;14(4):e0214738. https://doi.org/10.1371/journal.pone.0214738 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Walton C, King R, Rechtman L, Kaye W, Leray E, Marrie RA, et al. Rising prevalence of multiple sclerosis worldwide: insights from the Atlas of MS. Multiple Scler J. 2020;26(14):1816–21. https://doi.org/10.1177/1352458520970841 .

Azami M, YektaKooshali MH, Shohani M, Khorshidi A, Mahmudi L. Epidemiology of multiple sclerosis in Iran: a systematic review and meta-analysis. https://doi.org/10.1371/journal.pone.0214738

Faraji F, Khosravi S, Sajadi M, Farahani Z, Rafiei F. Effect of self-care education on social adaptability in patients with multiple sclerosis. Iran Red Crescent Med J. 2018;20(1):e55634. https://doi.org/10.5812/ircmj.55634 .

Klimczuk A, Stefanovska-Petkovska M, Asfour H, De Luca V, Illario M, Tziraki-Segal C et al. Creating a Culture of Health in Planning and Implementing Innovative Strategies Addressing Non-communicable Chronic Diseases. Perspectives and Theories of Social Innovation for Ageing Population. 2020. https://doi.org/10.3389/fsoc.2019.00009

Falvo DR. Effective patient education: a guide to increased compliance. Jones & Bartlett Learning; 2004.

Dressler WW, Oths KS. Cultural determinants of health behavior. Handb Health Behav Res. 1997;1:359–78.

Google Scholar  

Birukou A, Blanzieri E, Giorgini P, Giunchiglia F. A formal definition of culture. Models Intercultural Collab Negot. 2013;1–26. https://doi.org/10.1007/978-94-007-5574-1_1 .

Edition F. Diagnostic and statistical manual of mental disorders. Am Psychiatric Assoc. 2013;21(21):591–643.

Siahkal SF, Javadifar N, Najafian M, Iravani M, Zakerkish M, Heshmati R. The psychosocial challenges associated with gestational diabetes mellitus: a systematic review of qualitative studies. Prim Care Diabetes. 2022;16(1):11–26. https://doi.org/10.1016/j.pcd.2021.09.003 .

Rehman S, Roomi MA. Emerald Article: gender and work-life balance: a phenomenological study of women entrepreneurs in Pakistan. https://doi.org/10.1108/14626001211223865

Ahmadi K, Mahdi Nabipoor Ashrafi S, Ali Kimiaee S, Afzali MH. Effect of family problem-solving on marital satisfaction. J Appl Sci. 2010;10(8):682–7. https://doi.org/10.3923/jas.2010.682.687 .

Thompson L, Walker AJ. Gender in families: women and men in marriage, work, and parenthood. J. Marriage Fam.1989:845 – 71. https://doi.org/10.2307/353201 . Journal of Marriage and the Family.

Makama GA. Patriarchy and gender inequality in Nigeria: the way forward. Eur Sci J. 2013;9(17).

Ghaffari F, Motaghi Z. Factors affecting Childbearing based on women’s perspectives: a qualitative study. Navid No. 2021;23(76):33–43.

Payne D, McPherson KM. Becoming mothers. Multiple sclerosis and motherhood: a qualitative study. Disabil Rehabil. 2010;32(8):629–38. https://doi.org/10.3109/09638280903204708 .

Article   PubMed   Google Scholar  

Calabrò RS, Russo M, Dattola V, De Luca R, Leo A, Grisolaghi J, et al. Sexual function in young individuals with multiple sclerosis: does disability matter? J Neurosci Nurs. 2018;50(3):161–6. https://doi.org/10.1097/JNN.0000000000000367 .

Bronner G, Elran E, Golomb J, Korczyn A. Female sexuality in multiple sclerosis: the multidimensional nature of the problem and the intervention. Acta Neurol Scand. 2010;121(5):289–301. https://doi.org/10.1111/j.1600-0404.2009.01314.x .

Masoudi R, Abedi H, Abedi P, Mohammadianinejad SE. The perspectives of Iranian patients with multiple sclerosis on continuity of care: a qualitative study. J Nurs Res. 2015;23(2):145–52. https://doi.org/10.1097/JNR.0000000000000070 .

Vijayasingham L, Mairami FF. Employment of patients with multiple sclerosis: the influence of psychosocial–structural coping and context. Degener Neurol Neuromuscul Dis. 2018;8:15. https://doi.org/10.2147/DNND.S131729 .

Article   PubMed   PubMed Central   Google Scholar  

Smith MM, Arnett PA. Factors related to employment status changes in individuals with multiple sclerosis. Mult Scler Int. 2005;11(5):602–9. https://doi.org/10.1191/1352458505ms1204oa .

Benedict RH, Rodgers JD, Emmert N, Kininger R, Weinstock-Guttman B. Negative work events and accommodations in employed multiple sclerosis patients. Mult Scler Int. 2014;20(1):116–9. https://doi.org/10.1177/1352458513494492 .

Kordovski VM, Frndak SE, Fisher CS, Rodgers J, Weinstock-Guttman B, Benedict RH. Identifying employed multiple sclerosis patients at-risk for job loss: when do negative work events pose a threat? Mult Scler Relat Disord. 2015;4(5):409–13. https://doi.org/10.1016/j.msard.2015.07.005 .

Pourhaji F, Peyman N, Taraghdar MM, Jamali J, Tehrani H. Explaining the burden of psychosocial factors on the worsening symptoms of MS: a qualitative study of patients’ experiences. BMC Neurol. 2023;23(1):98. https://doi.org/10.1186/s12883-023-03148-z .

Obiwuru O, Joseph S, Liu L, Palomeque A, Tarlow L, Langer-Gould AM, et al. Perceptions of multiple sclerosis in hispanic americans: need for targeted messaging. Int J MS care. 2017;19(3):131–9. https://doi.org/10.7224/1537-2073.2015-081 .

Rocque R, Leanza Y. A systematic review of patients’ experiences in communicating with primary care physicians: intercultural encounters and a balance between vulnerability and integrity. PLoS ONE. 2015;10(10):e0139577. https://doi.org/10.1371/journal.pone.0139577 .

Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–73. https://doi.org/10.1016/S1474-4422(17)30470-2 .

Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. 2004;24(2):105–12. https://doi.org/10.1016/j.nedt.2003.10.001 .

Article   CAS   PubMed   Google Scholar  

Loh J. Inquiry into issues of trustworthiness and quality in narrative studies: a perspective. Qualitative Rep. 2013;18(33).

Shenton AK. Strategies for ensuring trustworthiness in qualitative research projects. Educ Inform. 2004;22(2):63–75.

Ghasemi S, Etemadi O, Ahmadi SA. The relationship between negative interactions of couple and family in law with intimacy and marital conflict in women. Family Pathol Couns Enrich J. 2015;1(1):1–13.

Marchand JF, Hock E. Avoidance and attacking conflict-resolution strategies among married couples: relations to depressive symptoms and marital satisfaction. Fam Relat. 2000;49(2):201–6. https://doi.org/10.1111/j.1741-3729.2000.00201.x .

Datta P, Poortinga YH, Marcoen A. Parent care by Indian and Belgian caregivers in their roles of daughter/daughter-in-law. J Cross-Cult Psychol. 2003;34(6):736–49. https://doi.org/10.1177/0022022103258589 .

Chung W, Kim R. Are married men healthier than single women? A gender comparison of the health effects of marriage and marital satisfaction in East Asia. PLoS ONE. 2015;10(7):e0134260. https://doi.org/10.1371/journal.pone.0134260 .

Thompson L, Walker AJ. Gender in families: women and men in marriage, work, and parenthood. J Marriage Fam. 1989;845–71. https://doi.org/10.2307/353201 .

Delina G, Raya RP. A study on work-life balance in working women. Int j Commer bus Manag. 2013;2(5):274–82.

Bharat S. Women, work, and family in urban India: towards new families. Psychol Hum Social Development: Lessons Diverse Cultures. 2003;155(169).

Delaney KE, Donovan J. Multiple sclerosis and sexual dysfunction: a need for further education and interdisciplinary care. NeuroRehabilitation. 2017;41(2):317–29. https://doi.org/10.3233/NRE-172200 .

Sinclair S, Beamer K, Hack TF, McClement S, Raffin Bouchal S, Chochinov HM, et al. Sympathy, empathy, and compassion: a grounded theory study of palliative care patients’ understandings, experiences, and preferences. Palliat Med. 2017;31(5):437–47. https://doi.org/10.1177/0269216316663499 .

Cadden MH, Arnett PA, Tyry TM, Cook JE. Judgment hurts: the psychological consequences of experiencing stigma in multiple sclerosis. Soc Sci Med. 2018;208:158–64. https://doi.org/10.1016/j.socscimed.2018.01.015 .

Karamlou S, Borjali A, Mottaghipour Y, Sadeghi MS. Components of stigma experience in families of patients with severe psychiatric disorders: a qualitative study. J Family Res. 2015;11(2):187–202.

Hosseini Z, Homayuni A, Etemadifar M. Barriers to quality of life in patients with multiple sclerosis: a qualitative study. BMC Neurol. 2022;22(1):174. https://doi.org/10.1186/s12883-022-02700-7 .

Vukusic S, Marignier R. Multiple sclerosis and pregnancy in the’treatment era’. Nat Rev Neurol. 2015;11(5):9–280. https://doi.org/10.1038/nrneurol.2015.53 .

Dobson R, Dassan P, Roberts M, Giovannoni G, Nelson-Piercy C, Brex PA. UK consensus on pregnancy in multiple sclerosis:‘Association of British neurologists’ guidelines. Pract Neurol. 2019;19(2):106–14. https://doi.org/10.1136/practneurol-2018-002060 .

Svendsen B, Grytten N, Bø L, Aarseth H, Smedal T, Myhr K-M. The economic impact of multiple sclerosis to the patients and their families in Norway. Eur J Health Econ. 2018;19:1243–57. https://doi.org/10.1007/s10198-018-0971-5 .

Hamed R. Environmental factors affecting the daily functioning of Jordanian individuals with multiple sclerosis. Int J MS Care. 2012;14(4):169–. https://doi.org/10.7224/1537-2073-14.4.169 .  78.

Kirchner T, Lara S. Stress and depression symptoms in patients with multiple sclerosis: the mediating role of the loss of social functioning. Acta Neurol Scand. 2011;123(6):407–13. https://doi.org/10.1111/j.1600-0404.2010.01422.x .

Wilson KG, Kowal J, Caird SM, Castillo D, McWilliams LA, Heenan A. Self-perceived burden, perceived burdensomeness, and suicidal ideation in patients with chronic pain. Can J pain. 2017;1(1):127–36. https://doi.org/10.1080/24740527.2017.1368009 .

Cousineau N, McDowell I, Hotz S, Hébert P. Measuring chronic patients’ feelings of being a burden to their caregivers: development and preliminary validation of a scale. Med Care. 2003:110–8.

Raggi A, Covelli V, Schiavolin S, Scaratti C, Leonardi M, Willems M. Work-related problems in multiple sclerosis: a literature review on its associates and determinants. Disabil Rehabil. 2016;38(10):936–44. https://doi.org/10.3109/09638288.2015.1070295 .

Vijayasingham L, Jogulu U, Allotey P. Work change in multiple sclerosis as motivated by the pursuit of illness-work-life balance: a qualitative study. Mult Scler Int. 2017;2017. https://doi.org/10.1155/2017/8010912 .

Grytten N, Skår AB, Aarseth JH, Assmus J, Farbu E, Lode K, et al. The influence of coping styles on long-term employment in multiple sclerosis: a prospective study. Mult Scler J. 2017;23(7):1008–17. https://doi.org/10.1177/1352458516667240 .

Vickers M. Why people with MS are really leaving work: from a Clayton’s choice to an ugly passage–a phenomenological study. Rev Disabil Stud. 2008;4(4).

Vickers MH. “For the Crime of Being Different…”. Empl Responsib Rights J. 2012;24(3):177 − 95. https://doi.org/10.1007/s10672-011-9186-y .

Bachari S, Mandani G, Ghasemzadeh R, Shahali S. Identifying barriers to self-advocacy in women with multiple sclerosis in Iran: a qualitative study. Archives Rehabilitation. 2021;22(3):378–93. https://doi.org/10.32598/rj.22.3.3277.1 .

Simmons RD, Tribe KL, McDonald EA. Living with multiple sclerosis: longitudinal changes in employment and the importance of symptom management. J Neurol. 2010;257(6):926–36. https://doi.org/10.1007/s00415-009-5441-7 .

Soundy A, Roskell C, Adams R, Elder T, Dawes H. Understanding health care professional-patient interactions in multiple sclerosis: a systematic review and thematic synthesis. Open J Therapy Rehabilitation. 2016;4(04):187. https://doi.org/10.4236/ojtr.2016.44018 .

Buecken R, Galushko M, Golla H, Strupp J, Hahn M, Ernstmann N, et al. Patients feeling severely affected by multiple sclerosis: how do patients want to communicate about end-of-life issues? Patient Educ Couns. 2012;88(2):318–24. https://doi.org/10.1016/j.pec.2012.03.010 .

Download references

Acknowledgements

This article is a part of the Ph.D. thesis in the field of Health Education and Health Promotion sponsored by Mashhad University of Medical Science and research project approved by Ethics Committee of Mashhad University of Medical Sciences with the code of ethics IR.MUMS. FHMPM.REC.1400.024 (Cod: 992067). The authors of the study express their sincere gratitude to all authorities of the Student Research Committee of Mashhad University of Medical Sciences and MS comprehensive center.

No financial support was received for this study.

Author information

Authors and affiliations.

Department of Health Education and Health Promotion, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran

Fahimeh Pourhaji, Nooshin Peyman & Hadi Tehrani

Department of Medical Surgical Nursing, School of Nursing and Midwifery, Mashhad University of Medical Sciences, Mashhad, Iran

Mousa Mahdizadeh Taraghdar

Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran

Jamshid Jamali

Social Determinant of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran

Nooshin Peyman, Jamshid Jamali & Hadi Tehrani

Student Research Committee, Mashhad University of Medical Sciences, Mashhad, Iran

Fahimeh Pourhaji

You can also search for this author in PubMed   Google Scholar

Contributions

Authors FP, HT, NP, MM and JJ designed the study. FP, HT and NP participated in the conception of the study. FP and HT managed and conducted the statistical analyses and interpreted the data. FP, HT, and NP wrote the first draft and FP, MM, HT and JJ revised it to make the final manuscript. All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Hadi Tehrani .

Ethics declarations

Ethics approval and consent to participate.

The study was approved by the Ethics Committee of Mashhad University of Medical Sciences with the code of ethics IR.MUMS. FHMPM. REC.1400.024 (Cod: 992067). All participants signed informed consent to participate in the study. All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Pourhaji, F., Taraghdar, M.M., Peyman, N. et al. Explaining the burden of cultural factors on MS disease: a qualitative study of the experiences of women with multiple sclerosis. BMC Women's Health 24 , 477 (2024). https://doi.org/10.1186/s12905-024-03328-0

Download citation

Received : 22 August 2023

Accepted : 22 August 2024

Published : 30 August 2024

DOI : https://doi.org/10.1186/s12905-024-03328-0

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

• Cultural factors
• Qualitative study

BMC Women's Health

ISSN: 1472-6874

• General enquiries: [email protected]

• Open access
• Published: 28 August 2024

Facilitators and barriers of midwife-led model of care at public health institutions of dire Dawa city, Eastern Ethiopia, 2022: a qualitative study

• Mickiale Hailu 1 ,
• Aminu Mohammed 1 ,
• Daniel Tadesse 1 ,
• Neil Abdurashid 1 ,
• Legesse Abera 1 ,
• Samrawit Ali 2 ,
• Yesuneh Dejene 2 ,
• Tadesse Weldeamaniel 1 ,
• Meklit Girma 3 ,
• Tekleberhan Hailemariam 1 ,
• Netsanet Melkamu 1 ,
• Tewodros Getnet 1 ,
• Yibekal Manaye 1 ,
• Tariku Derese 1 ,
• Muluken Yigezu 1 ,
• Natnael Dechasa 1 &
• Anteneh Atle 1  

BMC Health Services Research volume  24 , Article number:  998 ( 2024 ) Cite this article

Metrics details

The midwife-led model of care is woman-centered and based on the premise that pregnancy and childbirth are normal life events, and the midwife plays a fundamental role in coordinating care for women and linking with other health care professionals as required. Worldwide, this model of care has made a great contribution to the reduction of maternal and child mortality. For example, the global under-5 mortality rate fell from 42 deaths per 1,000 live births in 2015 to 39 in 2018. The neonatal mortality rate fell from 31 deaths per 1,000 live births in 2000 to 18 deaths per 1,000 in 2018. Even if this model of care has a pivotal role in the reduction of maternal and newborn mortality, in recent years it has faced many challenges.

To explore facilitators and barriers to a midwife-led model of care at a public health institution in Dire Dawa, Eastern Ethiopia, in 2021.

Methodology

: A qualitative approach was conducted at Dire Dawa public health institution from March 1–April 30, 2022. Data was collected using a semi-structured, in-depth interview tool guide, focused group discussions, and key informant interviews. A convenience sampling method was implemented to select study participants, and the data were analyzed thematically using computer-assisted qualitative data analysis software Atlas.ti7. The thematic analysis with an inductive approach goes through six steps: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up.

Two major themes were driven from facilitators of the midwife-led model of care (professional pride and good team spirit), and seven major themes were driven from barriers to the midwife-led model of care (lack of professional development, shortage of resources, unfair risk or hazard payment, limited organizational power of midwives, feeling of demoralization absence of recognition from superiors, lack of work-related security).

The midwifery-led model of care is facing considerable challenges, both pertaining to the management of the healthcare service locally and nationally. A multidisciplinary and collaborative effort is needed to solve those challenges.

Peer Review reports

Introduction

A midwife-led model of care is defined as care where “the midwife is the lead professional in the planning, organization, and delivery of care given to a woman from the initial booking to the postnatal period“ [ 1 ]. Within these models, midwives are, however, in partnership with the woman, the lead professional with responsibility for the assessment of her needs, planning her care, referring her to other professionals as appropriate, and ensuring the provision of maternity services. Most industrialized countries with the lowest mortality and morbidity rates of mothers and infants are those in which midwifery is a valued and integral pillar of the maternity care system [ 2 , 3 , 4 , 5 ].

Over the past 20 years, midwife-led model of care (MLC) has significantly lowered mother and infant mortality across the globe. In 2018, there were 39 deaths for every 1,000 live births worldwide, down from 42 in 2015. From 31 deaths per 1,000 live births in 2000 to 18 deaths per 1,000 in 2018, the neonatal mortality rate (NMR) decreased. The midwifery-led care approach is regarded as the gold standard of care for expectant women in many industrialized nations, including Canada, Australia, the United Kingdom, Sweden, the Netherlands, Norway, and Denmark. Evidence from those nations demonstrates that women and babies who get midwife-led care, as opposed to alternative types of care, experience favorable maternal outcomes, fewer interventions, and lower rates of fetal loss or neonatal death [ 6 , 7 , 8 ].

In Pakistan, the MLC was accompanied by many challenges. Some of the challenges were political threats, a lack of diversity (midwives had no opportunities for collaborating with other midwives outside their institutions), long duty hours and low remuneration, a lack of a career ladder, and a lack of socialization (the health centers are isolated from other parts of the country due to relative geographical inaccessibility, transportation issues, and a lack of infrastructure). Currently, in Pakistan, 276 women die for every 100,000 live births, and the infant mortality rate is 74/1000. But the majority of these deaths are preventable through the midwife-led care model [ 7 ].

The MLC in African countries has faced many challenges. Shortages of resources, work overload, low inter-professional collaboration between health facilities, lack of personal development, lack of a well-functioning referral system, societal challenges, family life troubles, low professional autonomy, and unmanageable workloads are the main challenges [ 8 ].

Due to the aforementioned challenges, Sub Saharan Africa (SSA) is currently experiencing the highest rate of infant mortality (1 in 13) and is responsible for 86% of all maternal fatalities worldwide. As a result, it is imperative to look at the MLC issues in low-income countries, which continue to be responsible for 99% of all maternal and newborn deaths worldwide [ 8 , 9 ].

Ethiopia’s has a Maternal mortality rate (MMR) and NMR of 412 per 100,000 live births and 33 per 1000 live births, respectively, remain high, making Ethiopia one of the largest contributors to the global burden of maternal and newborn deaths, placed 4th and 6th, although MLC could prevent a total of 83% of all neonatal and maternal fatalities in an environment that supports it. The MMR & infant mortality rate (IMR) in the research area were indistinguishable from that, at 150 per 100,000 live births and 67 fatalities per 1,000 live births, respectively [ 10 , 11 , 12 , 13 ].

Since the Federal Ministry of Health is currently viewing midwifery-led care as an essential tool in reducing the maternal mortality ratio and ending preventable deaths of newborns, exploring the facilitators and barriers of MLC may have a great contribution to make in reducing maternal and newborn mortality [ 14 ]. Since there has been no study done in Ethiopia or the study area regarding the facilitators and barriers of MLC, the aim of this research was to explore the facilitators and barriers of MLC in Dire Dawa City public health institutions.

In so doing, the research attempted to address the following research questions:

What were the facilitators for a midwife-led model of care at the Dire Dawa city public health institution?

What were the barriers to a midwife-led model of care at the Dire Dawa city public health institution?

Study setting and design

Institutional based qualitative study was conducted from March 01-April 30, 2022 in Dire Dawa city. Dire Dawa city is one of the federal city administrations in Ethiopia which is located at the distance of 515killo meters away from Addis Ababa (the capital city) to the east. The city administration has 9 urban and 38 rural kebeles (kebeles are the smallest administrative unit in Ethiopia). There are 2 government hospitals, 5 private hospitals, 15 health centers, and 33 health posts. The current metro area population of Dire Dawa city is 426,129.Of which 49.8% of them are males and 50.2% females. The total number of women in reproductive age group (15–49 years) is 52,673 which account 15.4% of the total population. It has hot temperature with a mean of 25 degree centigrade [ 15 ].

Study population and sampling procedure

The source population for this study included all midwives who worked at Dire Dawa City public health facilities as well as key informants from appropriate organizations (the focal person for the Ethiopian Midwives Association and maternal and child health (MCH) team leaders). The study encompassed basically 41 healthcare professionals who worked in Dire Dawa public health institutions in total, and the final sample size was decided based on the saturation of the data or information.

From the total 15 Health centers and 2 Governmental Hospitals found in Dire Dawa city administration, 8 Health centers and 2 Governmental Hospitals were selected by non-probability purposive sampling method. In addition to that a non-probability convenience sampling method was used to select midwives who were working in Dire Dawa city public health institutions and key informants from the relevant organization such as Ethiopian midwives association focal person and MCH team leaders. Midwives who were working for at least six months in the institution were taken as inclusion criteria while those who were working as a free service were excluded from the study.

Data collection tool and procedures

Focus groups, in-depth interviews, and key informant interviews were used in collecting data. A voice recorder, a keynote-keeping, and a semi-structured interview tool were all used to conduct the interviews. Voluntary informed written consent was obtained from the study participant’s before they participated in the study. Then an in-depth interview and focus group discussion were held with midwives chosen from various healthcare organizations. The MCH department heads and the Dire Dawa branch of the Ethiopian Midwife Association served as the key informants. In-depth interview (IDI) and key informant interviews (KII) with participants took place only once and lasted for roughly 50–60 min. In the midwives’ duty room, the interview was held. Six to eight people participated in focus group discussions (FGD), which lasted 90 to 100 min. Two midwives with experience in gathering qualitative data gathered the information.

Data quality control

The qualitative design is prone for bias but open-ended questions were used to avoid acquiescence and 2 day proper training was given for the data collector regarding taking keynotes and recording using a tape recorder. For consistency and possible modification, a pretest was done in one FGD and In-depth interviews at non selected health institutions of Dire Dawa city administrations. A detailed explanation was given for the study participants about the objectives of the study prior to the actual data collections. All (FGDs, key informant interview and In-depth interviews) were taken in a silent place.

Data analysis

Atlas.ti7, a qualitative data analysis program, was used for analyzing the data thematically. An inductive approach to thematic analysis involves six steps: familiarization, coding, generation of themes, review of themes, defining and naming of themes, and writing up. By listening to the taped interview again, the data was transcribed. The participants’ well-spoken verbatim was used to extract and describe the inductive meanings of the statements. The data was then coded after that. Each code describes the concept or emotion made clear in that passage of text. Then we look at the codes we’ve made, search for commonalities, and begin to develop themes. To ensure the data’s accuracy and representation, the generated themes were reviewed. Themes were defined and named, and then the analysis of the data was written up.

Trustworthiness of data

Meeting standards of trustworthiness by addressing credibility, conformability, and transferability ensures the quality of qualitative research. Data triangulation, data collection from various sites and study participants, the use of multiple data collection techniques (IDI, KII, and FGD), multiple peer reviews of the proposal, and the involvement of more than two researchers in the coding, analysis, and interpretation decisions are all instances of the methods that were used in order to fulfill the criteria for credibility. To increase its transferability to various contexts, the study gave details of the context, sample size and sampling method, eligibility criteria, and interview processes. To ensure conformability, the research paths were maintained throughout the study in accordance with the work plan [ 16 , 17 ].

Background characteristics of the study participants

In this study, a total of 41 health care providers who are working in Dire Dawa public health facilities participated in the three FGDs, six KIIs, and fifteen IDIs. The years of experience of study participants range from one year to 12 years. The participants represented a wide age range (30–39 years), and the educational status of the respondents ranged from diploma to master’s degree. (Table  1 )

As shown in Table  2 , from the qualitative analysis of the data, two major themes were driven from facilitators of MLC, and seven major themes were driven from barriers to MLC. (Table  2 ).

Facilitators of midwife-led model of care at a public health institution of Dire Dawa city, Eastern Ethiopia, in 2021

Professional pride.

This study found that saving the lives of mothers and newborns was a strong facilitator. Specifically, it was motivational to have skills within the midwifery domain, such as managing the full continuum of care during pregnancy and labour, supporting women in having normal physiologic births, being able to handle complications, and building relationships with the women and the community, as mentioned below by one of the IDI participants.

“I am so proud since I am a midwife; nothing is more satisfying than seeing a pregnant mother give birth almost without complications. I always see their smile and happiness on their faces , especially in the postpartum period , and they warmly thank me and say , “Here is your child; he or she is yours.” They bless me a lot. Even sometimes , when they sew me in the transport area , cafeteria , or other area , they thank me warmly , and some of them also want to invite me to something else. The sum total of those things motivates me to be in this profession or to provide midwifery care.“ IDI participants.

This finding is also supported by other participants in FGD.

“We have learned and promised to work as midwives. We are proud of our profession , to help women and children’s health. The greatest motivation is that we are midwives , we love the profession , and we are contributing a great role in decreasing maternal and child mortality….” FGD discussant.

Good teamwork

The research revealed that good midwifery teamwork and good social interaction within the staff have become facilitators of MLC. FGD participants share their experiences of working in a team.

“In our facility , all the midwives have good teamwork; we have good communication , and we share client information accurately and timely. In case a severe complication happens , we manage it as a team , and we try to cover the gap if some of our staff are absent. Further from that , we do have good social interactions in the case of weeding , funeral ceremonies , and other social activities. We do have good team spirit; we work as a team in the clinical area , and we also have good social relationships. “If some of our staff gets sick or if she or he has other social issues , the other free staff will cover her or his task.” FGD discussant.

Another participant from IDI also shared the same experience regarding their good teamwork and their social interactions.

“As a maternal and child health team , we do have a good team spirit , not only with midwives but also with other professions. We are not restricted by the ward that we assign. If there is a caseload in any unit , some midwives will volunteer to help the other team. Most of the time in the night , we admit more than 3 or 4 labouring mothers at the same time. Since in our health center only one midwife is assigned in the night , we always call nurses to help us. This is our routine experience.” IDI participants.

Barriers of midwife-led model of care at a public health institution of Dire Dawa city, Eastern Ethiopia, in 2021

Lack of professional development.

This study revealed that insufficient opportunities for further education and updated training were the main barriers for MLC. Even the few trainings and update courses that were actually arranged were unavailable to them, either because they did not meet the criteria seated or because the people who work in administration were selected. Even though opportunities are not arranged for them to upgrade themselves through self-sponsored. One of the participants from IDI narrates her opinion about opportunities for further education as follows:

“Training and updates are not sufficient; currently we are almost working with almost old science. For example , the new obstetrics management protocol for 2021 has been released from the ministry of health , and many things have changed there. But we did not receive any training or even announcements. Even the few trainings and update courses that were truly organized and turned in to us are unavailable since the selection criteria are not fair. As a result , we miss those trainings either because we did not meet the selection criteria or because those who work in administration are prioritized.” IDI participant.

FGD discussants also support this idea. She mentioned that even though opportunities are not arranged for them to upgrade themselves through self-sponsorship,

“There is almost no educational opportunity in our institution. Every year , one or two midwives may get institutional sponsorship. Midwives that will be selected for this opportunity are those who have served for more than five to ten years. Imagine that to get this chance , every midwife is expected to serve five or more years. Not only this , even if staff want to learn or upgrade at governmental or private colleges through self-sponsored programmes , whether at night or in an extension programme , they are not cooperative. Let me share with you my personal experience. Before two years , I personally started my MSc degree at Dire Dawa University in a weekend programme , and I have repeatedly asked the management bodies to let me free on weekends and to compensate me at night or any time from Monday to Friday. Since they refuse to accept my concern , I withdraw from the programme.“ FGD discussant.

Shortage of resource

The finding indicates that a shortage of equipment, staff, and rooms or wards was a challenge for MLC. Midwives claimed they were working with few staff, insufficient essential supplies, and advanced materials. This lack of equipment endangers both the midwives and their patients. One of the participants from IDI narrates her opinion about the shortage of resources as follows:

“Of course there is a shortage of resources in our hospital , like gloves and personal protective devices. Even the few types of medical equipment available , like the autoclave , forceps , vacuum delivery couch , and BP apparatus , are outdated , and some of them are unfunctional. If you see the Bp apparatus we used in ANC , it is digital but full of false positives. When I worked in the ANC , I did not trust it and always brought the analogue one from other wards. This is the routine experience of every staff member.“ IDI participants.

Another participant from IDI also shared the same experience regarding the crowdedness of rooms or wards.

“In our health center , there are no adequate wards or rooms. For example , the delivery ward and postnatal ward are almost in one room. Postnatal mothers and neonates did not get enough rest and sleep because of the sound of laboring mothers. Not only is this , but even the antenatal care and midwifery duty rooms are also very narrow.“ IDI participants.

The study also revealed midwifery staff were pressured to work long hours because they were understaffed, which in turn affected the quality of midwifery care. The experience of a certain midwife is shared as follows:

“I did not think that the management bodies understood the risk and stress that we midwives face. They did not want to consider the risk of midwives even equal to that of other disciplines but lower than the others. For example , in our health centre , during the night , only one midwife is assigned for the next 12 hours , but if you see in the nurse department , two or more nurses are assigned at night in the emergency ward.” IDI participants.

The discussion affirms the fact that being understaffed and not having an adequate allocation of midwife professionals on night shifts are affecting labouring mothers’ ability to get sufficient health midwifery care. The above narration is also supported by the FGD discussant.

“In our case , only one midwife is assigned to the labour ward during the night shift. I think this is the main challenge for midwives that needs attention. Let me share with you my experience that happened months before. While I was on night shift , two labouring mothers were fully dilated within three or four minutes. It was very difficult for me , to manage two labouring mothers at the same time. Immediately , I call one of my nurse friends from the emergency department to help me. If my friend was so busy , what could happen to the labouring mother and also to me? This is not only my experience but also the routine experience of other midwives.” FGD discussant.

Unfair risk or hazard payments

It is reported that the compensation amount paid for risk is lower than in other health professions. The health risks are not any less, but the remuneration system failed to capture the need to fairly compensate midwifery professionals. The narration from the FGD discussant regarding unfair payment is mentioned below.

“Only 470 ETB is paid for midwives as risk payments , which is incomparable with the risks that midwives are facing. But contrary to that , the risk payments for nurses (in emergencies) are about 1200 Ethiopian birr (ETB) , and Anesthesia is 1000 ETB. I did not want to compare my profession with other disciplines , but with the lowest cost , how the risk of midwifery cannot be equal to that of nursing and other professions. I did not know whose professionals made such types of unfair decisions and with what scientific background or base this calculation was done . ” FGD discussant.

The above finding is also supported by an IDI participant.

“………………………….Even though the midwifery profession is full of risks , with the current Ethiopian health care system , midwives are being paid the lowest risk payments compared to other disciplines…………….” IDI participants.

Limited organizational power of midwives

Midwives’ interviews reported that limited senior midwifery positions in the health system have become the challenge of midwifery care. This constrains the decision-making power and capability of midwives. This was compounded by limited opportunities for midwifery personnel to address their concerns to the responsible bodies, as stated by one of the key informants.

“Our staff has many concerns , especially professional-related concerns , which can contribute to the quality of midwifery care. Personally , as department head , I have tried to address those concerns in different management meetings at different times. But since the leadership positions are dominated by other disciplines , many of our staff concerns have not been solved yet. But let me tell you my personal prediction… If those concerns are not solved early and if this trend continues , the quality of midwifery care will be in danger.“ Participant from Key Informant.

The above finding is also supported by another IDI participant.

“In our hospital , at every hierarchal and structural level , midwives are not well represented. That is why all of our challenges or concerns have not been solved yet. For example , as a structure in the Dire Dawa Health Office (DDHO) , there is a team of management related to maternal and child health. But unfortunately , those professionals working there are not midwives. I was one of three midwives chosen to meet with Dr. X (former DDHO leader) to discuss this issue. At the time , we were reaching an agreement that two or three midwives would be represented on that team. But since a few months later the leader resigned , the issue has not gotten a solution yet.“ IDI participant.

Feeling of demoralization

One of the main concerns reported by the participants during the interviews was a feeling of demoralization induced by both their clients and their supervisors about barriers to midwifery care. They reported having been verbally abused by their patients, something that made them feel that their hard work was being undermined, as stated by an FGD participant.

“I don’t think there is any midwife who would be happy for anybody to lose their baby , or that there is any midwife who would want a woman to die. These things are accidents , but the patient and leaders will always blame the midwife.” FDG discussant.

A narration from an IDI participant also mentioned the following:

“……….If something happens , like a conflict with the patients or clients , the management is on the patient side. Not only that , the way in which they communicate with us is in an aggressive or disrespectful manner . ” IDI participant.

Absence of recognition or /motivation from superiors

This study revealed that midwives experience a loss of motivation at work due to limited support from their superiors. Their effort is used only for reporting purposes. A midwife from FGD shared her experience as follows.

“In our scenario , till the nearest time , the maternal and child health services are provided in a good way. But this was not easy; it is the cumulative effort of midwives. But unfortunately , only those in managerial positions are recognized. Nothing was done for us despite our efforts. To me , our efforts are used only for reporting purposes.” FGD discussant.

This finding was also supported by IDI participants.

“Even though we have good achievements in the MCH services , there is no motivation mechanism done to motivate midwives.” But if something or a minor mistake happens , they are on the front lines to intimidate us or write a warning letter. Generally , their concern is a report or a number issue. We are tired of such types of scenarios.” IDI participant.

Insufficient of work-related security

One of the main concerns reported by the participants during the interviews was the work related security, which has become a challenge for MLC. The midwives’ work environment was surrounded by insecurity, especially during night shifts, when midwives were facing verbal and even physical attack, as mentioned by participants.

“In the labour ward , especially at night , we face many security-related issues. The families of labouring mothers , especially those who are young , are very aggressive. Sometimes they even want to enter the delivery room. They did not hear what we told them to do , but if they hear any labour sounds from their family , they disturb the whole ward. This leads to verbal abuse , and sometimes we face physical abuse. There may be one or two security personnel at the main gate , but since the delivery ward is far from the main gate , they do not know what is happening in the delivery ward. When things become beyond our scope , we call security guards. Immediately after the security guards go back , similar things will continue. What makes it difficult to manage such situations is that only one midwife is assigned at night , and labouring mothers will not get quality midwifery care.” IDI participant.

FGD discussants also shared their experience that their working environment is full of insecurity.

“In case any complications occur , especially at night , it is very difficult to tell the labouring mother’s family or husband unless we call security personnel. It is not only swearing that we face but also that they intimidate us.” FDG discussant.

Discussions

The aim of this study was to explore facilitators’ and barriers to a midwifery-led model of care at Dire Dawa public health facilities. In this study, professional pride was the main facilitator of the midwifery-led model of care. Another qualitative study that examined the midwifery care challenges and factors that motivate them to remain in their workplace lends confirmation to this conclusion. It was found that a strong feeling of love for their work was the main facilitator’s midwifery-led model of care [ 9 ]. Having a good team spirit was also another facilitator’s midwifery-led model of care in our study. Another study’s findings confirmed this one, which emphasizes that building relationships with the midwives, women, and community was the driving force behind providing midwifery care [ 7 , 18 ].

The midwives in this study expressed a need for additional professional training, updates, and competence as part of their continuing professional development. Similar findings have been reported in the worldwide literature that midwives were struggling for survival due to a lack of limited in-service training opportunities to improve their knowledge and skills [ 19 ]. This phenomenon does not seem to differ between settings in high-, middle-, and low-income countries [ 7 , 9 , 18 ], in which midwives experienced difficult work situations due to a lack of professional development to autonomously manage work tasks, which made them feel frustrated, guilty, and inadequate. As such, this can contribute to distress and burnout, which in turn prevent midwives from being able to provide quality care and can eventually cause them to leave the profession [ 19 ].

Shortages of resources (shortage of staff, lack of physical space, and equipment) were the other reported barriers to midwifery care explored in this study. They reported that they are working in an environment with a shortage of resources, which leads to poor patient outcomes. This finding is supported by many other studies conducted around the globe [ 20 , 21 , 22 , 23 ]. Another qualitative finding, which likewise supports the aforementioned finding, which emphasizes that a shortage of resources was reported as a barrier to providing adequate midwifery care [ 19 ]. Delivery attended by skilled personnel with appropriate supplies and equipment has been found to be strongly associated with a reduction in child and maternal mortality [ 24 ].

The feeling of demoralization and lack of motivation from their superiors were other barriers to midwifery care explored in this study. This finding is concurrent with other studies conducted around the globe [ 19 , 25 , 26 , 28 ]. The above finding is also is in accord with another qualitative narration, which emphasizes that feelings of demoralization and a lack of motivation were the main challenges of midwifery care [ 22 ]. Positive support from supervisors has been demonstrated to be important for the quality of services that health workers are able to deliver. In the World Health Organization’s report on improving performance in healthcare, the WHO stresses that supportive supervision can contribute to the improved performance of health workers [ 27 ].

Unfair risk payment was the other challenge identified by the current study. Even though there is no difference in the risk they face among health professionals, the risk payment for midwives is very low compared to others. This finding was in conformity with another qualitative narration, which emphasizes that the lack of an equitable remuneration system was experienced by the DRC midwives, and it has also been confirmed to be highly problematic in other studies in low- and middle-income settings [ 7 , 8 , 22 , 28 ], leading to serious challenges. In settings where salaries are extremely low or unpredictable, proper remuneration is seen as crucial to worker motivation and the quality of midwifery care [ 29 , 30 ].

The limited organizational power of midwives was another identified challenge of MLC. This finding was in step with other studies that emphasize that limited senior midwifery positions in the health system constrain the decision-making power and capability of midwives. This was compounded by limited opportunities for midwifery personnel to address their concerns to the responsible bodies. Hence, midwives need to take control of their own situations. When midwives are included in customizing their work environments, it has proven to result in improved quality of care for women and newborns around the globe [ 8 , 15 ].

Lack of work-related security was another barrier to MLC explored in this study, in which the midwives’ work environment was surrounded by insecurity, especially during night shifts, when midwives are facing verbal and even physical attack, as mentioned by participants. This finding is supported by many other studies conducted around the globe [ 22 , 23 , 25 , 31 ]. The above finding is also in agreement with another qualitative narration, which emphasizes that the midwives’ work environment was surrounded by insecurity, especially during night shifts due to a lack of available security personnel; they often felt frightened on their way to and from work [ 7 ]. In order for midwives to provide quality care, it is crucial to create supportive work environments by ensuring sufficient pre-conditions, primarily security issues [ 31 ].

Conclusions

The study findings contribute to a better understanding of the facilitators’ and barriers of a midwifery-led model of care in the case of Dire Dawa public health facilities. Professional pride and having good team spirit were the main facilitators of midwifery-led model care. Contrary to that, insufficient professional development, shortage of resources, feeling of demoralization, lack of motivation, limited organizational power of midwives, unfair risk payment, and lack of work-related security were the main barriers to a midwifery-led model of care in the case of Dire Dawa public health facilities. Generally, midwifery care is facing considerable challenges, both pertaining to the management of the healthcare service locally and nationally.

Study implications

The findings of the study have implications for midwifery care practices in Eastern Ethiopia. Addressing these areas could potentially contribute to the reduction of IMR and MMR.

Strengths and limitations

The first strength of the study is that the participants represented different healthcare facilities, both urban and rural, thereby offering deeper and more varied experiences and reflections. A second strength is using a midwife as a moderator. She or he understood the midwives’ situation, thereby making the participants feel more comfortable and willing to share their stories. However, focusing solely on the perspective of the midwives is a limitation.

Recommendations

To overcome the barriers of midwifery care, based on the result of this study and in accordance with the 2020 Triad Statement made by the International Council of Nurses, the International Confederation of Midwives, and the World Health Organization, it is suggested that policymakers, Ethiopian federal ministry of health, Dire dawa health office, and regulators in Dire Dawa city and settings with similar conditions coordinate actions in the following:

To the Ethiopian federal ministry of health (FMOH)

Should strengthen regular and continuous educational opportunities, trainings, and updates for midwives, prioritizing and enforcing policies to include adequate and reasonable remuneration and hazard payment for midwives. Support midwifery leadership at all levels of the health system to contribute to health policy development and decision-making.

To dire Dawa health Bureau

Ensure decent working conditions and an enabling environment for midwives. This includes reasonable working hours, occupational safety, safe staffing levels, and merit-based opportunities for career progression. Special efforts must be made to ensure safe, respectful, and enabling workplaces for midwives operating on the night shift. Midwifery leaders should be involved in management bodies within an appropriate legal framework. Made regular mentorships on the functionality of different diagnostic instruments in respective health facilities.

To Dire Dawa public health facility’s

Create an arena for dialogue and implement a more supportive leadership style at the respective health facilities. Should address professional-related concerns of midwives early. Ensure midwives’ representation at the management bodies. Ensure the selection criteria for educational opportunities and different trainings are fair and inclusive. Ensure the safety and security of midwives, especially those who work night shifts. Should assign adequate staff (midwives and security guards) to the night shifts.

Ethiopian midwifery association

Should influence different stakeholders to solve midwife’s concerns like hazards payment and educational opportunity.

Data availability

All the datasets for this study are available from the corresponding author upon request.

Abbreviations

Focused group discussion

In-depth interview

Infant mortality rate

Key informant interview

Maternal and child health

Midwives led model of care

Neonatal mortality rate

The midwives model of care. Midwives alliance North America, the MANA core documents, 2020.

WHO. Midwife-led care delivers positive pregnancy and birth outcomes. The global health work force alliance,2020.

ICM, Midwifery Led Care, the First Choice for All Women, Netherlands, 2017.

Alba R, Franco R, Patrizia B, Maria CB, Giovanna A, Chiara F, Isabella N. The midwifery-led care model: a continuity of care model in the birth path. Acta Bio Medica: Atenei Parmensis. 2019;90(Suppl 6):41.

Google Scholar  

Dahl B, Heinonen K, Bondas TE. From midwife-dominated to midwifery-led antenatal care: a meta-ethnography. Int J Environ Res Public Health. 2020;17(23):8946.

Article   PubMed   PubMed Central   Google Scholar  

McConville F, Lavender DT. Quality of care and midwifery services to meet the needs of women and newborns. BJOG: Int J Obstet Gynecol. 2014;121.

Shahnaz S, Jan R, Lakhani A, Sikandar R. Factors affecting the midwifery-led service provider model in Pakistan. J Asian Midwives (JAM). 2015;1(2):33–45.

Bogren M, Grahn M, Kaboru BB, Berg M. Midwives’ challenges and factors that motivate them to remain in their workplace in the Democratic Republic of Congo—an interview study. Hum Resour Health. 2020;18:1–0.

Article   Google Scholar  

Bremnes HS, Wiig ÅK, Abeid M, Darj E. Challenges in day-to-day midwifery practice; a qualitative study from a regional referral hospital in Dar Es Salaam. Tanzan Global Health Action. 2018;11(1):1453333.

Yigzaw T, Abebe F, Belay L, Assaye Y, Misganaw E, Kidane A, Ademie D, van Roosmalen J, Stekelenburg J, Kim YM. Quality of midwife-provided intrapartum care in Amhara regional state, Ethiopia. BMC Pregnancy Childbirth. 2017;17:1–2.

Federal Democratic Republic of Ethiopia Mini Demographic and Health Survey. 2019 Ethiopian Public Health Institution, Addis Ababa The DHS Program ICF Rockville, Maryland, USA May 2021.

Federal Democratic Republic of Ethiopia. Demographic and Health Survey 2016 Central Statistical Agency Addis Ababa, Ethiopia The DHS Program ICF Rockville, Maryland, USA July 2017.

UNICEF for every child. Situation Analysis of children and women. Dire Dawa Administration; 2020.

Federal Ministry of. Health, Midwifery care process,2021.

Dire Dawa administration Regional Health Bureau. 2017 six months report [unpublished].

Shenton AK. Strategies for ensuring trustworthiness in qualitative research projects. Educ Inform. 2004;22(2):63–75.

Irene K, Albine M, Series. Practical guidance to qualitative research. Trustworthiness and publishing. Eur J Gen Pract. 2018;24(1):120–4.

Behruzi R, Hatem M, Fraser W, Goulet L, Ii M, Misago C. Facilitators and barriers in the humanization of childbirth practice in Japan. BMC Pregnancy Childbirth. 2010;10:1–8.

Adatara P, Amooba PA, Afaya A, Salia SM, Avane MA, Kuug A, Maalman RS, Atakro CA, Attachie IT, Atachie C. Challenges experienced by midwives working in rural communities in the Upper East Region of Ghana: a qualitative study. BMC Pregnancy Childbirth. 2021;21:1–8.

Roets L. Independent midwifery practice: opportunities and challenges. Afr J Phys Health Educ Recreation Dance. 2014;20(3):1209–24.

Mselle LT, Moland KM, Mvungi A, Evjen-Olsen B, Kohi TW. Why give birth in health facility? Users’ and providers’ accounts of poor quality of birth care in Tanzania. BMC Health Serv Res. 2013;13:1–2.

Bogren M, Erlandsson K, Byrskog U. What prevents midwifery quality care in Bangladesh? A focus group enquiry with midwifery students. BMC Health Serv Res. 2018;18(1):639.

Mtegha MB, Chodzaza E, Chirwa E, Kalembo FW, Zgambo M. Challenges experienced by newly qualified nurse-midwives transitioning to practice in selected midwifery settings in northern Malawi. BMC Nurs. 2022;21(1):236.

Floyd L. Helping midwives in Ghana to reduce maternal mortality. Afr J Midwifery Women’s Health. 2013;7(1):34–8.

Filby A, McConville F, Portela A. What prevents quality midwifery care? A systematic mapping of barriers in low and middle income countries from the provider perspective. PLoS ONE. 2016;11(5):e0153391.

Prytherch H, Kagoné M, Aninanya GA, Williams JE, Kakoko DC, Leshabari MT, Yé M, Marx M, Sauerborn R. Motivation and incentives of rural maternal and neonatal health care providers: a comparison of qualitative findings from Burkina Faso, Ghana and Tanzania. BMC Health Serv Res. 2013;13:1–5.

World Health Organization. The world health report 2000: health systems: improving performance. World Health Organization; 2000.

Oyetunde MO, Nkwonta CA. Quality issues in midwifery: a critical analysis of midwifery in Nigeria within the context of the International Confederation of Midwives (ICM) global standards. Int J Nurs Midwifery. 2014;6(3):40–8.

Kruk ME, Gage AD, Arsenault C, Jordan K, Leslie HH, Roder-DeWan S, Adeyi O, Barker P, Daelmans B, Doubova SV, English M. High-quality health systems in the Sustainable Development goals era: time for a revolution. Lancet Global Health. 2018;6(11):e1196–252.

Article   PubMed   Google Scholar  

Mathauer I, Imhoff I. Health worker motivation in Africa: the role of non-financial incentives and human resource management tools. Hum Resour Health. 2006;4:1–7.

World Health Organization. Global strategy on human resources for health: workforce 2030.

Download references

Acknowledgements

We are very grateful to Dire Dawa University for the financial support for this study and to the College of Medicine and Health for its monitoring ship. All study participants for their willingness to respond to our questionnaire.

this work has been funded by Dire Dawa University for data collection purposes. The Dire Dawa University College of Medicine and Health Sciences was involved in the project through monitoring and evaluation of the work from the beginning to the result submission. However, this organization was not involved in the design, analysis, critical review of its intellectual content, or manuscript preparation, and its budget did not include publication.

Author information

Authors and affiliations.

College of Medicine and Health Sciences, Dire Dawa University, Dire Dawa, Ethiopia

Mickiale Hailu, Aminu Mohammed, Daniel Tadesse, Neil Abdurashid, Legesse Abera, Tadesse Weldeamaniel, Tekleberhan Hailemariam, Netsanet Melkamu, Tewodros Getnet, Yibekal Manaye, Tariku Derese, Muluken Yigezu, Natnael Dechasa & Anteneh Atle

College of Health Sciences, Wachemo University, Hossana, Ethiopia

Samrawit Ali & Yesuneh Dejene

College of Health Sciences, Mekelle University, Mekelle, Ethiopia

Meklit Girma

You can also search for this author in PubMed   Google Scholar

Contributions

MH developed the study proposal, served as the primary lead for study implementation and data analysis/interpretation, and was a major contributor in writing and revising all drafts of the paper. AM, DT, NA, LA, and SA supported study implementation and data analysis, and contributed to writing the initial draft of the paper. YD, TW, MG, TH and, NM supported study recruitment and contributed to writing the final draft of the paper. TG, YM, TD, MY, ND and, AA conceptualized, acquired funding, and led protocol development for the study, co-led study implementation and data analysis/interpretation, and was a major contributor in writing and revising all drafts of the paper. All authors contributed to its content. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Mickiale Hailu .

Ethics declarations

Ethics approval and consent to participate.

All methods were followed in accordance with relevant guidelines and regulations. The institutional review board of Dire Dawa University has also examined and evaluated it for its methodological approach and ethical concerns. Ethical clearance was obtained from Dire Dawa University Institutional Review Board and an official letter from research affairs directorate office of Dire Dawa University was submitted to Dire Dawa health office and it was distributed to selected health institutions. Voluntary informed written consent was obtained from the study participant’s right after the objectives of the study were explained to the study participants and confidentiality of the study participants was assured throughout the study period. Participants were informed that they have the right to terminate the discussion (interview) or they can’t answer any questions they didn’t want to answer.

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.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/ .

Reprints and permissions

About this article

Cite this article.

Hailu, M., Mohammed, A., Tadesse, D. et al. Facilitators and barriers of midwife-led model of care at public health institutions of dire Dawa city, Eastern Ethiopia, 2022: a qualitative study. BMC Health Serv Res 24 , 998 (2024). https://doi.org/10.1186/s12913-024-11417-x

Download citation

Received : 03 September 2023

Accepted : 09 August 2024

Published : 28 August 2024

DOI : https://doi.org/10.1186/s12913-024-11417-x

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

• Continuous midwifery care model
• Obstetric care by midwives
• Barriers to obstetric care
• Facilitators to obstetric care

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

Exploring Solitary Waves and Nonlinear Dynamics in the Fractional Chaffee–Infante Equation: A Study Beyond Conventional Diffusion Models

• Published: 29 August 2024
• Volume 23 , article number  270 , ( 2024 )

Cite this article

• Xiao Zhang 1 ,
• Taher A. Nofal 2 ,
• Aleksander Vokhmintsev 3 , 4 &
• Mostafa M. A. Khater 4 , 5 , 6  

The current study examines the (2 + 1)-dimensional fractional Chaffee–Infante (FCI) model, which is a nonlinear evolution equation that characterizes the processes of pattern generation, reaction-diffusion, and nonlinear wave propagation. The construction of analytical solutions involves the use of analytical methods, namely the Khater III and improved Kudryashov schemes. The He’s Variational Iteration method is employed as a numerical approach to validate the accuracy of the obtained solutions. The main objective of this study is to get novel analytical and numerical solutions for the FCI model, with the intention of gaining a deeper understanding of the system’s dynamics and its possible implications in the fields of fluid mechanics, plasma physics, and optical fiber communications. The study makes a valuable contribution to the area of nonlinear science via the use of innovative analytical and numerical methodologies in the FCI model. This research enhances our comprehension of pattern creation, reaction–diffusion phenomena, and the propagation of nonlinear waves in diverse physical scenarios.

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

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Data availability

Data will be made available on request.

Attia, R.A.M., Alfalqi, S.H., Alzaidi, J.F., Vokhmintsev, A., Khater, M.M.A.: Transcending classical diffusion models: nonlinear dynamics and solitary waves in the fractional Chaffee–Infante equation. Opt. Quant. Electron. 56 (6), 1033 (2024)

Article   Google Scholar  

Arshed, S., Akram, G., Sadaf, M., Irfan, M., Inc, M.: Extraction of exact soliton solutions of (2+1)-dimensional Chaffee–Infante equation using two exact integration techniques. Opt. Quant. Electron. 56 (6), 988 (2024)

Zhu, C., Al-Dossari, M., Rezapour, S., Gunay, B.: On the exact soliton solutions and different wave structures to the (2+1) dimensional Chaffee–Infante equation. Results Phys. 57 , 107431 (2024)

Tetik, D., Akbulut, A., çelik, N.: Applications of two kinds of Kudryashov methods for time fractional (2 + 1) dimensional Chaffee–Infante equation and its stability analysis. Opt. Quant. Electron. 56 (4), 640 (2024)

Faridi, W.A., Yusuf, A., Akgül, A., Tawfiq, F.M.O., Tchier, F., Al-deiakeh, R., Sulaiman, T.A., Hassan, A.M., Ma, W.-X.: The computation of Lie point symmetry generators, modulational instability, classification of conserved quantities, and explicit power series solutions of the coupled system. Results Phys. 54 , 107126 (2023)

Sadaf, M., Arshed, S., Akram, G., Ali, M.R., Bano, I.: Analytical investigation and graphical simulations for the solitary wave behavior of Chaffee–Infante equation. Results Phys. 54 , 107097 (2023)

Günhan Ay, N., Yaşar, E.: The residual symmetry, Bäcklund transformations, CRE integrability and interaction solutions: (2+1)-dimensional Chaffee–Infante equation. Commun. Theor. Phys. 75 (11), 115004 (2023)

Sebogodi, M.C., Muatjetjeja, B., Adem, A.R.: Traveling wave solutions and conservation laws of a generalized Chaffee–Infante equation in (1+3) dimensions. Universe 9 (5), 224 (2023)

Mahmood, A., Abbas, M., Akram, G., Sadaf, M., Riaz, M.B., Abdeljawad, T.: Solitary wave solution of (2+1)-dimensional Chaffee–Infante equation using the modified Khater method. Results Phys. 48 , 106416 (2023)

Khater, M.M.A., Alfalqi, S.H., Alzaidi, J.F., Attia, R.A.M.: Plenty of accurate novel solitary wave solutions of the fractional Chaffee–Infante equation. Results Phys. 48 , 106400 (2023)

Khater, M.M.A., Attia, R.A.M.: Simulating the behavior of the population dynamics using the non-local fractional Chaffee–Infante equation. Fractals 31 (10), 2340200–18 (2023)

Şengül, T., Tiryakioglu, B.: Dynamic transitions and bifurcations of 1D reaction–diffusion equations: the self-adjoint case. Math. Methods Appl. Sci. 45 (5), 2871–2892 (2022)

Article   MathSciNet   Google Scholar  

Kumar, S., Almusawa, H., Hamid, I., Akbar, M.A., Abdou, M.A.: Abundant analytical soliton solutions and Evolutionary behaviors of various wave profiles to the Chaffee–Infante equation with gas diffusion in a homogeneous medium. Results Phys. 30 , 104866 (2021)

Sulaiman, T.A., Yusuf, A., Alquran, M.: Dynamics of lump solutions to the variable coefficients (2+1)-dimensional Burger’s and Chaffee–Infante equations. J. Geom. Phys. 168 , 104315 (2021)

Riaz, M.B., Atangana, A., Jhangeer, A., Junaid-U-Rehman, M.: Some exact explicit solutions and conservation laws of Chaffee–Infante equation by Lie symmetry analysis. Phys. Scr. 96 (8), 084008 (2021)

Khater, M.M.A., Ghanbari, B.: On the solitary wave solutions and physical characterization of gas diffusion in a homogeneous medium via some efficient techniques. Eur. Phys. J. Plus 136 (4), 447 (2021)

Younas, U., Sulaiman, T., Ismael, H.F., Shah, N.A., Eldin, S.M.: On the lump interaction phenomena to the conformable fractional (2+ 1)-dimensional KdV equation. Results Phys. 52 , 106863 (2023)

Younas, U., Seadawy, A.R., Younis, M., Rizvi, S.T., Althobaiti, S.: Diverse wave propagation in shallow water waves with the Kadomtsev–Petviashvili–Benjamin–Bona–Mahony and Benney–Luke integrable models. Open Phys. 19 (1), 808–818 (2021)

Nasreen, N., Younas, U., Lu, D., Zhang, Z., Rezazadeh, H., Hosseinzadeh, M.: Propagation of solitary and periodic waves to conformable ion sound and Langmuir waves dynamical system. Opt. Quant. Electron. 55 (10), 868 (2023)

Nasreen, N., Younas, U., Sulaiman, T.A., Zhang, Z., Lu, D.: A variety of M-truncated optical solitons to a nonlinear extended classical dynamical model. Results Phys. 51 , 106722 (2023)

Ismael, H.F., Younas, U., Sulaiman, T.A., Nasreen, N., Shah, N.A., Ali, M.R.: Non classical interaction aspects to a nonlinear physical model. Results Phys. 49 , 106520 (2023)

Nasreen, N., Lu, D., Zhang, Z., Akgül, A., Younas, U., Nasreen, S., Al-Ahmadi, A.N.: Propagation of optical pulses in fiber optics modelled by coupled space-time fractional dynamical system. Alex. Eng. J. 73 , 173–187 (2023)

Hosseini, K., Alizadeh, F., Sadri, K., Hinçal, E., Akbulut, A., Alshehri, H., Osman, M.: Lie vector fields, conservation laws, bifurcation analysis, and Jacobi elliptic solutions to the Zakharov–Kuznetsov modified equal-width equation. Opt. Quant. Electron. 56 (4), 506 (2024)

Hosseini, K., Alizadeh, F., Hinçal, E., Baleanu, D., Akgül, A., Hassan, A.: Lie symmetries, bifurcation analysis, and Jacobi elliptic function solutions to the nonlinear Kodama equation. Results Phys. 54 , 107129 (2023)

Hosseini, K., Hinçal, E., Ilie, M.: Bifurcation analysis, chaotic behaviors, sensitivity analysis, and soliton solutions of a generalized Schrödinger equation. Nonlinear Dyn. 111 (18), 17455–17462 (2023)

Rafiq, M.H., Jannat, N., Rafiq, M.N.: Sensitivity analysis and analytical study of the three-component coupled NLS-type equations in fiber optics. Opt. Quant. Electron. 55 (7), 637 (2023)

Rafiq, M.H., Raza, N., Jhangeer, A.: Dynamic study of bifurcation, chaotic behavior and multi-soliton profiles for the system of shallow water wave equations with their stability. Chaos Solitons Fractals 171 , 113436 (2023)

Raza, N., Arshed, S., Butt, A.R., Inc, M., Yao, S.-W.: Investigation of new solitons in nematic liquid crystals with Kerr and non-Kerr law nonlinearities. J. Nonlinear Opt. Phys. Mater. 32 (02), 2350020 (2023)

Raza, N., Butt, A.R., Arshed, S., Kaplan, M.: A new exploration of some explicit soliton solutions of q-deformed Sinh–Gordon equation utilizing two novel techniques. Opt. Quant. Electron. 55 (3), 200 (2023)

Raza, N., Rani, B., Chahlaoui, Y., Shah, N.A.: A variety of new rogue wave patterns for three coupled nonlinear Maccari’s models in complex form. Nonlinear Dyn. 111 (19), 18419–18437 (2023)

Jaradat, M., Batool, A., Butt, A.R., Raza, N.: New solitary wave and computational solitons for Kundu–Eckhaus equation. Results Phys. 43 , 106084 (2022)

Rafiq, M.H., Raza, N., Jhangeer, A.: Nonlinear dynamics of the generalized unstable nonlinear Schrödinger equation: a graphical perspective. Opt. Quant. Electron. 55 (7), 628 (2023)

Arshad, M., Lu, D., Wang, J.: (n+ 1)-dimensional fractional reduced differential transform method for fractional order partial differential equations. Commun. Nonlinear Sci. Numer. Simul. 48 , 509–519 (2017)

Arshad, M., Seadawy, A.R., Mehmood, A., Shehzad, K.: Lump kink interactional and breather-type waves solutions of (3+ 1)-dimensional shallow water wave dynamical model and its stability with applications. Modern Phys. Lett. B (2024). https://doi.org/10.1142/S0217984924504025

Sarwar, A., Gang, T., Arshad, M., Ahmed, I., Ahmad, M.: Abundant solitary wave solutions for space-time fractional unstable nonlinear Schrödinger equations and their applications. Ain Shams Eng. J. 14 (2), 101839 (2023)

Batool, S., Arshad, M., Perveen, N., Sarwar, S.: Bright optical solution for fractional Lakshmanan–Porsezian–Daniel with spatio temporal dispersion by improved adomian decomposition method. Opt. Quant. Electron. 56 (7), 1137 (2024)

Seadawy, A.R., Arshad, M., Lu, D.: The weakly nonlinear wave propagation theory for the Kelvin–Helmholtz instability in magnetohydrodynamics flows. Chaos Solitons Fractals 139 , 110141 (2020)

Alquran, M., Al-deiakeh, R.: Lie–Backlund symmetry generators and a variety of novel periodic-soliton solutions to the complex-mode of modified Korteweg-de Vries equation. Qual. Theory Dyn. Syst. 23 (2), 95 (2024)

Alquran, M.: Necessary conditions for convex-periodic, elliptic-periodic, inclined-periodic, and rogue wave-solutions to exist for the multi-dispersions Schrodinger equation. Phys. Scr. 99 (2), 025248 (2024)

Alquran, M.: Dynamic behavior of explicit elliptic and quasi periodic-wave solutions to the generalized (2+ 1)-dimensional Kundu–Mukherjee–Naskar equation. Optik 301 , 171697 (2024)

Alquran, M.: The amazing fractional Maclaurin series for solving different types of fractional mathematical problems that arise in physics and engineering. Partial Differ. Equ. Appl. Math. 7 , 100506 (2023)

Alquran, M.: Investigating the revisited generalized stochastic potential-KdV equation: fractional time-derivative against proportional time-delay. Rom. J. Phys. 68 , 106 (2023)

Google Scholar  

Raza, N., Rafiq, M.H., Kaplan, M., Kumar, S., Chu, Y.-M.: The unified method for abundant soliton solutions of local time fractional nonlinear evolution equations. Results Phys. 22 , 103979 (2021)

Tahir, M., Kumar, S., Rehman, H., Ramzan, M., Hasan, A., Osman, M.S.: Exact traveling wave solutions of Chaffee–Infante equation in (2 + 1)-dimensions and dimensionless Zakharov equation. Math. Methods Appl. Sci. 44 (2), 1500–1513 (2021)

Xu, H., Chang, H., Zhang, D.: DLGA-PDE: discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. J. Comput. Phys. 418 , 109584 (2020)

Mao, Y.: Exact solutions to (2+1) (2 + 1) -dimensional Chaffee–Infante equation. Pramana 91 (1), 9 (2018)

Li, J., Feng, Z.: Quadratic and cubic nonlinear oscillators with damping and their applications. Int. J. Bifurc. Chaos 26 (3), 1650050–350 (2016)

Rolland, J., Bouchet, F., Simonnet, E.: Rare transitions between metastable states in the stochastic Chaffee–Infante equation., In: EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, p. 14223 (2015)

Qiang, L., Yun, Z., Yuanzheng, W.: Qualitative Analysis and Travelling Wave Solutions for the Chaffee–Infante equation. Rep. Math. Phys. 71 (2), 177–193 (2013)

Sakthivel, R., Chun, C.: New soliton solutions of Chaffee–Infante equations using the exp-function method. Z. Naturforschung Teil A 65 (3), 197–202 (2010)

Xie, F.-D., Liu, X.-D., Sun, X.-P., Tang, D.: Application of computer algebra in solving Chaffee–Infante equation. Commun. Theor. Phys. 49 (4), 825–828 (2008)

Atangana, A., Alqahtani, R.T.: Modelling the spread of river blindness disease via the caputo fractional derivative and the beta-derivative. Entropy 18 (2), 40 (2016)

Atangana, A., Alkahtani, B.S.T.: Modeling the spread of R ubella disease using the concept of with local derivative with fractional parameter: beta-derivative. Complexity 21 (6), 442–451 (2016)

Download references

Acknowledgements

The authors extend their appreciation to Taif University, Saudi Arabia, for supporting this work through project number (TU-DSPP-2024-46).

Author information

Authors and affiliations.

School of Medicine and Health, Harbin Institute of Technology, Harbin, 150001, Heilongjiang, China

Department of Mathematics, College of Science, Taif University, P.O. Box 11099, 21944, Taif, Saudi Arabia

Taher A. Nofal

Institute of Information Technology, Chelyabinsk State University, Chelyabinsk, 454001, Russia

Aleksander Vokhmintsev

Institute of Digital Economy, Ugra State University, Khanty-Mansiysk, 628012, Russia

Aleksander Vokhmintsev & Mostafa M. A. Khater

School of Medical Informatics and Engineering, Xuzhou Medical University, 209 Tongshan Road, Xuzhou, 221004, Jiangsu Province, People’s Republic of China

Mostafa M. A. Khater

Department of Basic Science, The Higher Institute for Engineering & Technology, Al-Obour, Cairo, 10587, Egypt

You can also search for this author in PubMed   Google Scholar

Contributions

Xiao Zhang, and Mostafa M. A. Khater conceived and designed the experiments and performed them. Taher A. Nofal,  Aleksander Vokhmintsev and Mostafa M. A. Khater analyzed and interpreted the data, contributed to the provision of reagents, materials, analysis tools, or data, and wrote the paper.

Corresponding author

Correspondence to Mostafa M. A. Khater .

Ethics declarations

Conflict of interest.

The authors declare no conflict of interest.

Additional information

Publisher's note.

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Zhang, X., Nofal, T.A., Vokhmintsev, A. et al. Exploring Solitary Waves and Nonlinear Dynamics in the Fractional Chaffee–Infante Equation: A Study Beyond Conventional Diffusion Models. Qual. Theory Dyn. Syst. 23 (Suppl 1), 270 (2024). https://doi.org/10.1007/s12346-024-01121-w

Download citation

Received : 24 December 2023

Accepted : 07 August 2024

Published : 29 August 2024

DOI : https://doi.org/10.1007/s12346-024-01121-w

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

• Fractional Chaffee–Infante model
• Nonlinear evolution equation
• Analytical and numerical solutions
• Khater III method
• Improved Kudryashov method
• He’s variational iteration method

Mathematics Subject Classification

• Find a journal
• Publish with us
• Track your research