qualitative research definition and meaning

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on September 5, 2024.

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

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

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalizability

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

• Labor-intensive

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

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

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

Research bias

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Qualitative Research : Definition

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

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Home » Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research – Methods, Analysis Types and Guide

Table of Contents

Qualitative Research

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

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

Qualitative Research Methods

Qualitative Research Methods are as follows:

One-to-One Interview

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

Focus Groups

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

Ethnographic Studies

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

Text Analysis

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

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

Process of Observation

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

Record Keeping

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

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

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

Qualitative Research Analysis Methods

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

Thematic Analysis

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

Content Analysis

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

Discourse Analysis

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

Grounded Theory Analysis

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

Narrative Analysis

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

Phenomenological Analysis

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

Comparative Analysis

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

Applications of Qualitative Research

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

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

How to Conduct Qualitative Research

Here are some general steps for conducting qualitative research:

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

Examples of Qualitative Research

Here are some real-time examples of qualitative research:

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

Purpose of Qualitative Research

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

Qualitative research can serve multiple purposes, including:

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

When to use Qualitative Research

Here are some situations where qualitative research may be appropriate:

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

Characteristics of Qualitative Research

Qualitative research is characterized by several key features, including:

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

Advantages of Qualitative Research

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

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

Limitations of Qualitative Research

Qualitative research also has some limitations, including:

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

Also see Research Methods

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• Knowledge Base
• Methodology
• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

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

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

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

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

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

Table of contents

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

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

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

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 analysing the data.

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

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

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

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

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

• Flexibility

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

• Natural settings

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

• Meaningful insights

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

• Generation of new ideas

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

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

• Unreliability

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

• Subjectivity

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

• Limited generalisability

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

• Labour-intensive

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

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

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

There are five common approaches to qualitative research :

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

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

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

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

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

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Bhandari, P. (2023, January 30). What Is Qualitative Research? | Methods & Examples. Scribbr. Retrieved 16 September 2024, from https://www.scribbr.co.uk/research-methods/introduction-to-qualitative-research/

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• Introduction

Qualitative research is a type of research that explores and provides deeper insights into real-world problems. [1] Instead of collecting numerical data points or intervening or introducing treatments just like in quantitative research, qualitative research helps generate hypothenar to further investigate and understand quantitative data. Qualitative research gathers participants' experiences, perceptions, and behavior. It answers the hows and whys instead of how many or how much. It could be structured as a standalone study, purely relying on qualitative data, or part of mixed-methods research that combines qualitative and quantitative data. This review introduces the readers to some basic concepts, definitions, terminology, and applications of qualitative research.

Qualitative research, at its core, asks open-ended questions whose answers are not easily put into numbers, such as "how" and "why." [2] Due to the open-ended nature of the research questions, qualitative research design is often not linear like quantitative design. [2] One of the strengths of qualitative research is its ability to explain processes and patterns of human behavior that can be difficult to quantify. [3] Phenomena such as experiences, attitudes, and behaviors can be complex to capture accurately and quantitatively. In contrast, a qualitative approach allows participants themselves to explain how, why, or what they were thinking, feeling, and experiencing at a particular time or during an event of interest. Quantifying qualitative data certainly is possible, but at its core, qualitative data is looking for themes and patterns that can be difficult to quantify, and it is essential to ensure that the context and narrative of qualitative work are not lost by trying to quantify something that is not meant to be quantified.

However, while qualitative research is sometimes placed in opposition to quantitative research, where they are necessarily opposites and therefore "compete" against each other and the philosophical paradigms associated with each other, qualitative and quantitative work are neither necessarily opposites, nor are they incompatible. [4] While qualitative and quantitative approaches are different, they are not necessarily opposites and certainly not mutually exclusive. For instance, qualitative research can help expand and deepen understanding of data or results obtained from quantitative analysis. For example, say a quantitative analysis has determined a correlation between length of stay and level of patient satisfaction, but why does this correlation exist? This dual-focus scenario shows one way in which qualitative and quantitative research could be integrated.

Qualitative Research Approaches

Ethnography

Ethnography as a research design originates in social and cultural anthropology and involves the researcher being directly immersed in the participant’s environment. [2] Through this immersion, the ethnographer can use a variety of data collection techniques to produce a comprehensive account of the social phenomena that occurred during the research period. [2] That is to say, the researcher’s aim with ethnography is to immerse themselves into the research population and come out of it with accounts of actions, behaviors, events, etc, through the eyes of someone involved in the population. Direct involvement of the researcher with the target population is one benefit of ethnographic research because it can then be possible to find data that is otherwise very difficult to extract and record.

Grounded theory

Grounded Theory is the "generation of a theoretical model through the experience of observing a study population and developing a comparative analysis of their speech and behavior." [5] Unlike quantitative research, which is deductive and tests or verifies an existing theory, grounded theory research is inductive and, therefore, lends itself to research aimed at social interactions or experiences. [3] [2] In essence, Grounded Theory’s goal is to explain how and why an event occurs or how and why people might behave a certain way. Through observing the population, a researcher using the Grounded Theory approach can then develop a theory to explain the phenomena of interest.

Phenomenology

Phenomenology is the "study of the meaning of phenomena or the study of the particular.” [5] At first glance, it might seem that Grounded Theory and Phenomenology are pretty similar, but the differences can be seen upon careful examination. At its core, phenomenology looks to investigate experiences from the individual's perspective. [2] Phenomenology is essentially looking into the "lived experiences" of the participants and aims to examine how and why participants behaved a certain way from their perspective. Herein lies one of the main differences between Grounded Theory and Phenomenology. Grounded Theory aims to develop a theory for social phenomena through an examination of various data sources. In contrast, Phenomenology focuses on describing and explaining an event or phenomenon from the perspective of those who have experienced it.

Narrative research

One of qualitative research’s strengths lies in its ability to tell a story, often from the perspective of those directly involved in it. Reporting on qualitative research involves including details and descriptions of the setting involved and quotes from participants. This detail is called a "thick" or "rich" description and is a strength of qualitative research. Narrative research is rife with the possibilities of "thick" description as this approach weaves together a sequence of events, usually from just one or two individuals, hoping to create a cohesive story or narrative. [2] While it might seem like a waste of time to focus on such a specific, individual level, understanding one or two people’s narratives for an event or phenomenon can help to inform researchers about the influences that helped shape that narrative. The tension or conflict of differing narratives can be "opportunities for innovation." [2]

Research Paradigm

Research paradigms are the assumptions, norms, and standards underpinning different research approaches. Essentially, research paradigms are the "worldviews" that inform research. [4] It is valuable for qualitative and quantitative researchers to understand what paradigm they are working within because understanding the theoretical basis of research paradigms allows researchers to understand the strengths and weaknesses of the approach being used and adjust accordingly. Different paradigms have different ontologies and epistemologies. Ontology is defined as the "assumptions about the nature of reality,” whereas epistemology is defined as the "assumptions about the nature of knowledge" that inform researchers' work. [2] It is essential to understand the ontological and epistemological foundations of the research paradigm researchers are working within to allow for a complete understanding of the approach being used and the assumptions that underpin the approach as a whole. Further, researchers must understand their own ontological and epistemological assumptions about the world in general because their assumptions about the world will necessarily impact how they interact with research. A discussion of the research paradigm is not complete without describing positivist, postpositivist, and constructivist philosophies.

Positivist versus postpositivist

To further understand qualitative research, we must discuss positivist and postpositivist frameworks. Positivism is a philosophy that the scientific method can and should be applied to social and natural sciences. [4] Essentially, positivist thinking insists that the social sciences should use natural science methods in their research. It stems from positivist ontology, that there is an objective reality that exists that is wholly independent of our perception of the world as individuals. Quantitative research is rooted in positivist philosophy, which can be seen in the value it places on concepts such as causality, generalizability, and replicability.

Conversely, postpositivists argue that social reality can never be one hundred percent explained, but could be approximated. [4] Indeed, qualitative researchers have been insisting that there are “fundamental limits to the extent to which the methods and procedures of the natural sciences could be applied to the social world,” and therefore, postpositivist philosophy is often associated with qualitative research. [4] An example of positivist versus postpositivist values in research might be that positivist philosophies value hypothesis-testing, whereas postpositivist philosophies value the ability to formulate a substantive theory.

Constructivist

Constructivism is a subcategory of postpositivism. Most researchers invested in postpositivist research are also constructivist, meaning they think there is no objective external reality that exists but instead that reality is constructed. Constructivism is a theoretical lens that emphasizes the dynamic nature of our world. "Constructivism contends that individuals' views are directly influenced by their experiences, and it is these individual experiences and views that shape their perspective of reality.” [6]  constructivist thought focuses on how "reality" is not a fixed certainty and how experiences, interactions, and backgrounds give people a unique view of the world. Constructivism contends, unlike positivist views, that there is not necessarily an "objective"reality we all experience. This is the ‘relativist’ ontological view that reality and our world are dynamic and socially constructed. Therefore, qualitative scientific knowledge can be inductive as well as deductive.” [4]

So why is it important to understand the differences in assumptions that different philosophies and approaches to research have? Fundamentally, the assumptions underpinning the research tools a researcher selects provide an overall base for the assumptions the rest of the research will have. It can even change the role of the researchers. [2] For example, is the researcher an "objective" observer, such as in positivist quantitative work? Or is the researcher an active participant in the research, as in postpositivist qualitative work? Understanding the philosophical base of the study undertaken allows researchers to fully understand the implications of their work and their role within the research and reflect on their positionality and bias as it pertains to the research they are conducting.

Data Sampling 

The better the sample represents the intended study population, the more likely the researcher is to encompass the varying factors. The following are examples of participant sampling and selection: [7]

• Purposive sampling- selection based on the researcher’s rationale for being the most informative.
• Criterion sampling selection based on pre-identified factors.
• Convenience sampling- selection based on availability.
• Snowball sampling- the selection is by referral from other participants or people who know potential participants.
• Extreme case sampling- targeted selection of rare cases.
• Typical case sampling selection based on regular or average participants. 

Data Collection and Analysis

Qualitative research uses several techniques, including interviews, focus groups, and observation. [1] [2] [3] Interviews may be unstructured, with open-ended questions on a topic, and the interviewer adapts to the responses. Structured interviews have a predetermined number of questions that every participant is asked. It is usually one-on-one and appropriate for sensitive topics or topics needing an in-depth exploration. Focus groups are often held with 8-12 target participants and are used when group dynamics and collective views on a topic are desired. Researchers can be participant-observers to share the experiences of the subject or non-participants or detached observers.

While quantitative research design prescribes a controlled environment for data collection, qualitative data collection may be in a central location or the participants' environment, depending on the study goals and design. Qualitative research could amount to a large amount of data. Data is transcribed, which may then be coded manually or using computer-assisted qualitative data analysis software or CAQDAS such as ATLAS.ti or NVivo. [8] [9] [10]

After the coding process, qualitative research results could be in various formats. It could be a synthesis and interpretation presented with excerpts from the data. [11] Results could also be in the form of themes and theory or model development.

Dissemination

The healthcare team can use two reporting standards to standardize and facilitate the dissemination of qualitative research outcomes. The Consolidated Criteria for Reporting Qualitative Research or COREQ is a 32-item checklist for interviews and focus groups. [12] The Standards for Reporting Qualitative Research (SRQR) is a checklist covering a more comprehensive range of qualitative research. [13]

Applications

Many times, a research question will start with qualitative research. The qualitative research will help generate the research hypothesis, which can be tested with quantitative methods. After the data is collected and analyzed with quantitative methods, a set of qualitative methods can be used to dive deeper into the data to better understand what the numbers truly mean and their implications. The qualitative techniques can then help clarify the quantitative data and also help refine the hypothesis for future research. Furthermore, with qualitative research, researchers can explore poorly studied subjects with quantitative methods. These include opinions, individual actions, and social science research.

An excellent qualitative study design starts with a goal or objective. This should be clearly defined or stated. The target population needs to be specified. A method for obtaining information from the study population must be carefully detailed to ensure no omissions of part of the target population. A proper collection method should be selected that will help obtain the desired information without overly limiting the collected data because, often, the information sought is not well categorized or obtained. Finally, the design should ensure adequate methods for analyzing the data. An example may help better clarify some of the various aspects of qualitative research.

A researcher wants to decrease the number of teenagers who smoke in their community. The researcher could begin by asking current teen smokers why they started smoking through structured or unstructured interviews (qualitative research). The researcher can also get together a group of current teenage smokers and conduct a focus group to help brainstorm factors that may have prevented them from starting to smoke (qualitative research).

In this example, the researcher has used qualitative research methods (interviews and focus groups) to generate a list of ideas of why teens start to smoke and factors that may have prevented them from starting to smoke. Next, the researcher compiles this data. The research found that, hypothetically, peer pressure, health issues, cost, being considered "cool," and rebellious behavior all might increase or decrease the likelihood of teens starting to smoke.

The researcher creates a survey asking teen participants to rank how important each of the above factors is in either starting smoking (for current smokers) or not smoking (for current nonsmokers). This survey provides specific numbers (ranked importance of each factor) and is thus a quantitative research tool.

The researcher can use the survey results to focus efforts on the one or two highest-ranked factors. Let us say the researcher found that health was the primary factor that keeps teens from starting to smoke, and peer pressure was the primary factor that contributed to teens starting smoking. The researcher can go back to qualitative research methods to dive deeper into these for more information. The researcher wants to focus on keeping teens from starting to smoke, so they focus on the peer pressure aspect.

The researcher can conduct interviews and focus groups (qualitative research) about what types and forms of peer pressure are commonly encountered, where the peer pressure comes from, and where smoking starts. The researcher hypothetically finds that peer pressure often occurs after school at the local teen hangouts, mostly in the local park. The researcher also hypothetically finds that peer pressure comes from older, current smokers who provide the cigarettes.

The researcher could further explore this observation made at the local teen hangouts (qualitative research) and take notes regarding who is smoking, who is not, and what observable factors are at play for peer pressure to smoke. The researcher finds a local park where many local teenagers hang out and sees that the smokers tend to hang out in a shady, overgrown area of the park. The researcher notes that smoking teenagers buy their cigarettes from a local convenience store adjacent to the park, where the clerk does not check identification before selling cigarettes. These observations fall under qualitative research.

If the researcher returns to the park and counts how many individuals smoke in each region, this numerical data would be quantitative research. Based on the researcher's efforts thus far, they conclude that local teen smoking and teenagers who start to smoke may decrease if there are fewer overgrown areas of the park and the local convenience store does not sell cigarettes to underage individuals.

The researcher could try to have the parks department reassess the shady areas to make them less conducive to smokers or identify how to limit the sales of cigarettes to underage individuals by the convenience store. The researcher would then cycle back to qualitative methods of asking at-risk populations their perceptions of the changes and what factors are still at play, and quantitative research that includes teen smoking rates in the community and the incidence of new teen smokers, among others. [14] [15]

Qualitative research functions as a standalone research design or combined with quantitative research to enhance our understanding of the world. Qualitative research uses techniques including structured and unstructured interviews, focus groups, and participant observation not only to help generate hypotheses that can be more rigorously tested with quantitative research but also to help researchers delve deeper into the quantitative research numbers, understand what they mean, and understand what the implications are. Qualitative research allows researchers to understand what is going on, especially when things are not easily categorized. [16]

• Issues of Concern

As discussed in the sections above, quantitative and qualitative work differ in many ways, including the evaluation criteria. There are four well-established criteria for evaluating quantitative data: internal validity, external validity, reliability, and objectivity. Credibility, transferability, dependability, and confirmability are the correlating concepts in qualitative research. [4] [11] The corresponding quantitative and qualitative concepts can be seen below, with the quantitative concept on the left and the qualitative concept on the right:

• Internal validity: Credibility
• External validity: Transferability
• Reliability: Dependability
• Objectivity: Confirmability

In conducting qualitative research, ensuring these concepts are satisfied and well thought out can mitigate potential issues from arising. For example, just as a researcher will ensure that their quantitative study is internally valid, qualitative researchers should ensure that their work has credibility. 

Indicators such as triangulation and peer examination can help evaluate the credibility of qualitative work.

• Triangulation: Triangulation involves using multiple data collection methods to increase the likelihood of getting a reliable and accurate result. In our above magic example, the result would be more reliable if we interviewed the magician, backstage hand, and the person who "vanished." In qualitative research, triangulation can include telephone surveys, in-person surveys, focus groups, and interviews and surveying an adequate cross-section of the target demographic.
• Peer examination: A peer can review results to ensure the data is consistent with the findings.

A "thick" or "rich" description can be used to evaluate the transferability of qualitative research, whereas an indicator such as an audit trail might help evaluate the dependability and confirmability.

• Thick or rich description:  This is a detailed and thorough description of details, the setting, and quotes from participants in the research. [5] Thick descriptions will include a detailed explanation of how the study was conducted. Thick descriptions are detailed enough to allow readers to draw conclusions and interpret the data, which can help with transferability and replicability.
• Audit trail: An audit trail provides a documented set of steps of how the participants were selected and the data was collected. The original information records should also be kept (eg, surveys, notes, recordings).

One issue of concern that qualitative researchers should consider is observation bias. Here are a few examples:

• Hawthorne effect: The effect is the change in participant behavior when they know they are being observed. Suppose a researcher wanted to identify factors that contribute to employee theft and tell the employees they will watch them to see what factors affect employee theft. In that case, one would suspect employee behavior would change when they know they are being protected.
• Observer-expectancy effect: Some participants change their behavior or responses to satisfy the researcher's desired effect. This happens unconsciously for the participant, so it is essential to eliminate or limit the transmission of the researcher's views.
• Artificial scenario effect: Some qualitative research occurs in contrived scenarios with preset goals. In such situations, the information may not be accurate because of the artificial nature of the scenario. The preset goals may limit the qualitative information obtained.
• Clinical Significance

Qualitative or quantitative research helps healthcare providers understand patients and the impact and challenges of the care they deliver. Qualitative research provides an opportunity to generate and refine hypotheses and delve deeper into the data generated by quantitative research. Qualitative research is not an island apart from quantitative research but an integral part of research methods to understand the world around us. [17]

• Enhancing Healthcare Team Outcomes

Qualitative research is essential for all healthcare team members as all are affected by qualitative research. Qualitative research may help develop a theory or a model for health research that can be further explored by quantitative research. Much of the qualitative research data acquisition is completed by numerous team members, including social workers, scientists, nurses, etc. Within each area of the medical field, there is copious ongoing qualitative research, including physician-patient interactions, nursing-patient interactions, patient-environment interactions, healthcare team function, patient information delivery, etc. 

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Disclosure: Steven Tenny declares no relevant financial relationships with ineligible companies.

Disclosure: Janelle Brannan declares no relevant financial relationships with ineligible companies.

Disclosure: Grace Brannan declares no relevant financial relationships with ineligible companies.

This book is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ), which permits others to distribute the work, provided that the article is not altered or used commercially. You are not required to obtain permission to distribute this article, provided that you credit the author and journal.

• Cite this Page Tenny S, Brannan JM, Brannan GD. Qualitative Study. [Updated 2022 Sep 18]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-.

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What is qualitative research?

The most fundamental characteristic of qualitative research is its express commitment to viewing events, action, norms, values, etc. from the perspective of the people who experience them in everyday life. (Bryman, 2004: p. 61)

The term “qualitative research” refers to an umbrella concept that encompasses many different forms of inquiry and methodological practices. It engages a variety of theoretical lenses, strategies, and techniques. Different from quantitative research, which is based on probability and measurement ( quantity ), qualitative research is based on the quality of the data generated to explain a phenomenon (e.g., why older adults would resist using some kinds of mobility devices) (Gardner, 2014). Traditionally, in the health sciences, qualitative research has been defined in opposition to quantitative research. A stereotypical view of qualitative research is that it is defined by its data generation methods, such as interviews and observations. These techniques are in fact shared with quantitative research; for example in psychological studies, observation is a commonly used strategy for quantification of behaviours (Green & Thorogood, 2004).  We caution against these simplistic generalizations. As illustrated in this chapter, all qualitative health methodologies and methods are centred around the notion of knowledge production grounded in the quality (the explanatory potential) of the information generated about a phenomenon.

Qualitative research is best defined by its aims: it asks different questions and has a different focus than quantitative research. It is concerned with questions of how, why, and what (Green & Thorogood, 2004).  Qualitative research is rooted in the social sciences and is concerned with people and their social realities (Bryman, 2004), with how the social world is understood, experienced, interpreted, and constituted; with individual and collective meanings, interpretations, practices/behaviours, and social processes. Its perspective is emic; it focuses on the subjectivity of human experiences (de la Cuesta, 2015). In the health sciences, qualitative research is the ideal approach for studying the meanings people give to their experiences and how they make sense of their social worlds (e.g., patients’ perceptions of self-care education or reasons for adherence, or not, to prescribed medication). Health care and health promotion are largely shaped by people’s perceptions, social norms, and organizational standards and practices; all these issues are social in nature and hence can be studied qualitatively.

Qualitative research is also based on a naturalistic approach to data generation. This means that people, situations, and events are studied where they happen, in their “natural settings,” and thus all qualitative data are contextual, connected to the people, places, times, events, and the everyday social interactions – or “social and cultural contexts” –  in which the data are generated. Context is also essential for understanding social behaviours and for making sense of or analyzing data produced. Context includes considerations such as who, when, where, why, class, race/ethnicity/gender, age, and circumstances (Holstein & Gubrium, 2004; Korstjens & Moser, 2017).

Qualitative research has also been described in terms of its broad purposes or goals: exploratory, where researchers investigate phenomena about which little is known; explanatory, where relationships, events, behaviours, or beliefs related to a group are explained; descriptive, where experiences or events are documented; and emancipatory, where the goal is to create opportunities for people to engage in social action (Agee, 2009). While these objectives can be helpful in situating a study, they are artificial distinctions because qualitative researchers often combine more than one goal in their study design. For example, answering a question such as “what are the processes that shape the ability of patients with diabetes to follow a prescribed diet?” requires both description and explanation.

Additionally, qualitative research traditions vary according to the uses researchers in distinct disciplines make of them. Within health sciences, for example, there is a particular way to think about “types” of qualitative research. Eakin (2016) refers to the dominance of post-positivist qualitative research (PPQR) in the health sciences, where qualitative data is viewed through a positivist lens: for instance, data are “real” and speak for themselves; findings “emerge” from the data independently of the researcher, who assumes a veneer of neutrality; and “findings” are reported mainly in implicitly quantitative terms (“some,” “most”). In PPQR, qualitative research is conceived of as purely a “method or technique, a ‘toolbox’ of procedures divorced from their philosophical undercarriage” (Eakin, 2016: p.111). Eakin concludes that this type of qualitative research has “limited value either as positivist or interpretive enterprise [because] it cannot satisfy the criteria for adequate positivist design (objective standardized procedure, statistical generalizability) or for adequate interpretive design (researcher as instrument, conceptual generalizability)” (p. 111).

As we are interested in doing the most we can when we use qualitative research to improve health care delivery and to challenge the ways we think about health issues broadly (e.g., social discourses, policies, programs), we engage with an interpretive, rather than a post-positivist, form of qualitative research. This is also called “interpretive research” (Schwartz-Shea & Yanow, 2012). Interpretive qualitative research is rooted in the assumption that meaning is discerned by the researcher. Through language use, human interaction, and meaning-making, the researcher and participant create the conditions for an in-depth understanding of a phenomenon (e.g., the stigma associated with TB treatment).

This type of interpretive qualitative research strives for what Eakin (2016)  calls “value-added” analysis. It is an approach that refuses a mere cataloguing of pre-conceived or common-sense ideas, maximizes the “creative presence” of the researcher, and deploys theoretical abstraction as a key methodological strategy for reconceptualizing phenomena and creating generalizable knowledge, through the process of theorization (Eakin, 2016). Here the researcher goes beyond mere description of an experience or a phenomenon to question, for instance, commonly held notions and assumptions, or the everyday experiences that are taken for granted. The researcher does not take data as given but works hard to interpret it, considers the story behind the story, questions common-sense and received understandings, and asks questions about the nature of the phenomenon under study (Eakin, 2016). (see also Ward, Hoare & Gott, 2015).

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4.2 Definitions and Characteristics of Qualitative Research

Qualitative research aims to uncover the meaning and understanding of phenomena that cannot be broken down into measurable elements. It is based on naturalistic, interpretative and humanistic notions. 5 This research method seeks to discover, explore, identify or describe subjective human experiences using non-statistical methods and develops themes from the study participants’ stories. 5 Figure 4.1 depicts major features/ characteristics of qualitative research. It utilises exploratory open-ended questions and observations to search for patterns of meaning in collected data (e.g. observation, verbal/written narrative data, photographs, etc.) and uses inductive thinking (from specific observations to more general rules) to interpret meaning. 6 Participants’ voice is evident through quotations and description of the work. 6 The context/ setting of the study and the researcher’s reflexivity (i.e. “reflection on and awareness of their bias”, the effect of the researcher’s experience on the data and interpretations) are very important and described as part of data collection. 6 Analysis of collected data is complex, often involves inductive data analysis (exploration, contrasts, specific to general) and requires multiple coding and development of themes from participant stories. 6

Reflexivity- avoiding bias/Role of the qualitative researcher

Qualitative researchers generally begin their work with the recognition that their position (or worldview) has a significant impact on the overall research process. 7 Researcher worldview shapes the way the research is conducted, i.e., how the questions are formulated, methods are chosen, data are collected and analysed, and results are reported. Therefore, it is essential for qualitative researchers to acknowledge, articulate, reflect on and clarify their own underlying biases and assumptions before embarking on any research project. 7 Reflexivity helps to ensure that the researcher’s own experiences, values, and beliefs do not unintentionally bias the data collection, analysis, and interpretation. 7 It is the gold standard for establishing trustworthiness and has been established as one of the ways qualitative researchers should ensure rigour and quality in their work. 8 The following questions in Table 4.1 may help you begin the reflective process. 9

Table 4.1: Questions to aid the reflection process

Philosophical underpinnings to qualitative research

Qualitative research uses an inductive approach and stems from interpretivism or constructivism and assumes that realities are multiple, socially constructed, and holistic. 10 According to this philosophical viewpoint, humans build reality through their interactions with the world around them. 10 As a result, qualitative research aims to comprehend how individuals make sense of their experiences and build meaning in their lives. 10 Because reality is complex/nuanced and context-bound, participants constantly construct it depending on their understanding. Thus, the interactions between the researcher and the participants are considered necessary to offer a rich description of the concept and provide an in-depth understanding of the phenomenon under investigation. 11

An Introduction to Research Methods for Undergraduate Health Profession Students Copyright © 2023 by Faith Alele and Bunmi Malau-Aduli is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

Qualitative Research

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"Qualitative method is used to understand people's beliefs, experiences, attitudes, behavior, and interactions. It generates non-numerical data" (Pathak, Jena, & Kalra, 2013, p. 1). Qualitative research is not looking for cause and effect. Instead it looks at meaning, perspectives and motivations. It is looking for the WHY. It typically has a small sample and uses focus groups, interviews, observation, historical documents, etc. The data it collects are "words" while Quantitative research collects "numbers". Several methodologies have been developed for qualitative research. For more information on Qualitative Research, see  Synthesis of Qualitative Research  or  Qualitative Research Methods Overview  for more information.

Pathak, V., Jena, B., & Kalra, S. (2013). Qualitative research. Perspectives in Clinical Research, 4 (3), 192-194.  https://doi.org/10.4103/2229-3485.115389 .

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An Overview of Qualitative Research Methods

Direct Observation, Interviews, Participation, Immersion, Focus Groups

• Research, Samples, and Statistics
• Key Concepts
• Major Sociologists
• News & Issues
• Recommended Reading
• Archaeology

Qualitative research is a type of social science research that collects and works with non-numerical data and that seeks to interpret meaning from these data that help understand social life through the study of targeted populations or places.

People often frame it in opposition to quantitative research , which uses numerical data to identify large-scale trends and employs statistical operations to determine causal and correlative relationships between variables.

Within sociology, qualitative research is typically focused on the micro-level of social interaction that composes everyday life, whereas quantitative research typically focuses on macro-level trends and phenomena.

Key Takeaways

Methods of qualitative research include:

• observation and immersion
• open-ended surveys
• focus groups
• content analysis of visual and textual materials
• oral history

Qualitative research has a long history in sociology and has been used within it for as long as the field has existed.

This type of research has long appealed to social scientists because it allows the researchers to investigate the meanings people attribute to their behavior, actions, and interactions with others.

While quantitative research is useful for identifying relationships between variables, like, for example, the connection between poverty and racial hate, it is qualitative research that can illuminate why this connection exists by going directly to the source—the people themselves.

Qualitative research is designed to reveal the meaning that informs the action or outcomes that are typically measured by quantitative research. So qualitative researchers investigate meanings, interpretations, symbols, and the processes and relations of social life.

What this type of research produces is descriptive data that the researcher must then interpret using rigorous and systematic methods of transcribing, coding, and analysis of trends and themes.

Because its focus is everyday life and people's experiences, qualitative research lends itself well to creating new theories using the inductive method , which can then be tested with further research.

Qualitative researchers use their own eyes, ears, and intelligence to collect in-depth perceptions and descriptions of targeted populations, places, and events.

Their findings are collected through a variety of methods, and often a researcher will use at least two or several of the following while conducting a qualitative study:

• Direct observation : With direct observation, a researcher studies people as they go about their daily lives without participating or interfering. This type of research is often unknown to those under study, and as such, must be conducted in public settings where people do not have a reasonable expectation of privacy. For example, a researcher might observe the ways in which strangers interact in public as they gather to watch a street performer.
• Open-ended surveys : While many surveys are designed to generate quantitative data, many are also designed with open-ended questions that allow for the generation and analysis of qualitative data. For example, a survey might be used to investigate not just which political candidates voters chose, but why they chose them, in their own words.
• Focus group : In a focus group, a researcher engages a small group of participants in a conversation designed to generate data relevant to the research question. Focus groups can contain anywhere from 5 to 15 participants. Social scientists often use them in studies that examine an event or trend that occurs within a specific community. They are common in market research, too.
• In-depth interviews : Researchers conduct in-depth interviews by speaking with participants in a one-on-one setting. Sometimes a researcher approaches the interview with a predetermined list of questions or topics for discussion but allows the conversation to evolve based on how the participant responds. Other times, the researcher has identified certain topics of interest but does not have a formal guide for the conversation, but allows the participant to guide it.
• Oral history : The oral history method is used to create a historical account of an event, group, or community, and typically involves a series of in-depth interviews conducted with one or multiple participants over an extended period.
• Participant observation : This method is similar to observation, however with this one, the researcher also participates in the action or events to not only observe others but to gain the first-hand experience in the setting.
• Ethnographic observation : Ethnographic observation is the most intensive and in-depth observational method. Originating in anthropology, with this method, a researcher fully immerses themselves into the research setting and lives among the participants as one of them for anywhere from months to years. By doing this, the researcher attempts to experience day-to-day existence from the viewpoints of those studied to develop in-depth and long-term accounts of the community, events, or trends under observation.
• Content analysis : This method is used by sociologists to analyze social life by interpreting words and images from documents, film, art, music, and other cultural products and media. The researchers look at how the words and images are used, and the context in which they are used to draw inferences about the underlying culture. Content analysis of digital material, especially that generated by social media users, has become a popular technique within the social sciences.

While much of the data generated by qualitative research is coded and analyzed using just the researcher's eyes and brain, the use of computer software to do these processes is increasingly popular within the social sciences.

Such software analysis works well when the data is too large for humans to handle, though the lack of a human interpreter is a common criticism of the use of computer software.

Pros and Cons

Qualitative research has both benefits and drawbacks.

On the plus side, it creates an in-depth understanding of the attitudes, behaviors, interactions, events, and social processes that comprise everyday life. In doing so, it helps social scientists understand how everyday life is influenced by society-wide things like social structure , social order , and all kinds of social forces.

This set of methods also has the benefit of being flexible and easily adaptable to changes in the research environment and can be conducted with minimal cost in many cases.

Among the downsides of qualitative research is that its scope is fairly limited so its findings are not always widely able to be generalized.

Researchers also have to use caution with these methods to ensure that they do not influence the data in ways that significantly change it and that they do not bring undue personal bias to their interpretation of the findings.

Fortunately, qualitative researchers receive rigorous training designed to eliminate or reduce these types of research bias.

• How to Conduct a Sociology Research Interview
• What Is Participant Observation Research?
• Immersion Definition: Cultural, Language, and Virtual
• Definition and Overview of Grounded Theory
• The Differences Between Indexes and Scales
• Pros and Cons of Secondary Data Analysis
• Social Surveys: Questionnaires, Interviews, and Telephone Polls
• The Different Types of Sampling Designs in Sociology
• Principal Components and Factor Analysis
• Sociology Explains Why Some People Cheat on Their Spouses
• Deductive Versus Inductive Reasoning
• How to Construct an Index for Research
• Data Sources For Sociological Research
• A Review of Software Tools for Quantitative Data Analysis
• Constructing a Deductive Theory
• Scales Used in Social Science Research

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Qualitative Research Methods: Types, Analysis + Examples

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

What is qualitative research?

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

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

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

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

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Types of qualitative research methods with examples

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

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

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

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

1. One-on-one interview

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

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

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

2. Focus groups

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

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

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

3. Ethnographic research

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

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

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

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

4. Case study research

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

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

5. Record keeping

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

6. Process of observation

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

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

Explore Insightfully Contextual Inquiry in Qualitative Research

Qualitative research: data collection and analysis

A. qualitative data collection.

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

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

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

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

B. Qualitative data analysis

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

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

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

Choosing the right software can be tough. Whether you’re a researcher, business leader, or marketer, check out the top 10  qualitative data analysis software  for analyzing qualitative data.

Characteristics of qualitative research methods

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

Qualitative research method case study

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

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

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

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

When to use qualitative research

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

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

LEARN ABOUT: Steps in Qualitative Research

Qualitative research methods vs quantitative research methods

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

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

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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.

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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

Qualitative Research Definition

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

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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.”

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Who Uses Qualitative Research?

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

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

Other careers that may involve qualitative research include: 

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

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

Grounded Theory

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

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

Action Research

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

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

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

Phenomenological Research

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

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

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Ethnography

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

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

Case Studies

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

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

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

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

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

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

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

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

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

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

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

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What is Qualitative in Qualitative Research

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• Published: 27 February 2019
• Volume 42 , pages 139–160, ( 2019 )

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• Patrik Aspers 1 , 2 &
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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.

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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.

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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.

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29 Conceptualization in qualitative research

Chapter outline

• 15.1 Alternative paradigms: Interpretivism, critical paradigm, and pragmatism

15.2 Multiparadigmatic research: An example

15.3 idiographic causal relationships, 15.4 qualitative research questions.

Now let’s change things up! In the previous chapters, we explored steps to create and carry out a quantitative research study. Quantitative studies are great when we want to summarize or test relationships between ideas using numbers and the power of statistics. However, qualitative research offers us a different and equally important tool. Sometimes the aim of research projects is to explore meaning and lived experience. Instead of trying to arrive at generalizable conclusions for all people, some research projects establish a deep, authentic description of a specific time, place, and group of people.

Qualitative research relies on the power of human expression through words, pictures, movies, performance and other artifacts that represent these things. All of these tell stories about the human experience and we want to learn from them and have them be represented in our research. Generally speaking, qualitative research is about the gathering up of these stories, breaking them into pieces so we can examine the ideas that make them up, and putting them back together in a way that allows us to tell a common or shared story that responds to our research question. To do that, we need to discuss the assumptions underlying social science.

17.1 Alternative paradigms: Interpretivism, critical, and pragmatism

Learning objectives.

Students will be able to…

• Distinguish between the assumptions of positivism, interpretivism, critical, and pragmatist research paradigms.
• Use paradigm to describe how scientific thought changes over time.

In Chapter 10, we reviewed the assumptions that underly post-positivism (abbreviated hereafter as positivism for brevity). Quantitative methods are most often the choice for positivist research questions because they conform to these assumptions. Qualitative methods  can conform to these assumptions; however, they are limited in their generalizability.

Kivunja & Kuyini (2017) [1] describe the essential features of positivism as:

• A belief that theory is universal and law-like generalizations can be made across contexts
• The assumption that context is not important
• The belief that truth or knowledge is ‘out there to be discovered’ by research
• The belief that cause and effect are distinguishable and analytically separable
• The belief that results of inquiry can be quantified
• The belief that theory can be used to predict and to control outcomes
• The belief that research should follow the scientific method of investigation
• Rests on formulation and testing of hypotheses
• Employs empirical or analytical approaches
• Pursues an objective search for facts
• Believes in ability to observe knowledge
• The researcher’s ultimate aim is to establish a comprehensive universal theory, to account for human and social behavior
• Application of the scientific method

Because positivism is the dominant social science research paradigm, it can be easy to ignore or be confused by research that does not use these assumptions. We covered in Chapter 10 the table reprinted below when discussing the assumptions underlying positivistic social science.

As you consider your research project, keep these philosophical assumptions in mind. They are useful shortcuts to understanding the deeper ideas and assumptions behind the construction of knowledge. The purpose of exploring these philosophical assumptions isn’t to find out which is true and which is false. Instead, the goal is to identify the assumptions that fit with how you think about your research question. Choosing a paradigm helps you make those assumptions explicit.

Before we explore alternative paradigms, it’s important for us to review what paradigms are.

How do scientific ideas change over time?

Much like your ideas develop over time as you learn more, so does the body of scientific knowledge. Kuhn’s (1962) [2] The Structure of Scientific Revolutions is one of the most influential works on the philosophy of science, and is credited with introducing the idea of competing paradigms (or “disciplinary matrices”) in research. Kuhn investigated the way that scientific practices evolve over time, arguing that we don’t have a simple progression from “less knowledge” to “more knowledge” because the way that we approach inquiry is changing over time. This can happen gradually, but the process results in moments of change where our understanding of a phenomenon changes more radically (such as in the transition from Newtonian to Einsteinian physics; or from Lamarckian to Darwinian theories of evolution). For a social work practice example, Fleuridas & Krafcik (2019) [3] trace the development of the “four forces” of psychotherapy , from psychodynamics to behaviorism to humanism as well as the competition among emerging perspectives to establish itself as the fourth force to guide psychotherapeutic practice. But how did the problems in one paradigm inspire new paradigms? Kuhn presents us with a way of understanding the history of scientific development across all topics and disciplines.

As you can see in this video from Matthew J. Brown (CC-BY), there are four stages in the cycle of science in Kuhn’s approach. Firstly, a pre-paradigmatic state where competing approaches share no consensus. Secondly, the “normal” state where there is wide acceptance of a particular set of methods and assumptions. Thirdly, a state of crisis where anomalies that cannot be solved within the existing paradigm emerge and competing theories to address them follow. Fourthly, a revolutionary phase where some new paradigmatic approach becomes dominant and supplants the old. Shnieder (2009) [4] suggests that the Kuhnian phases are characterized by different kinds of scientific activity.

Newer approaches often build upon rather than replace older ones, but they also overlap and can exist within a state of competition. Scientists working within a particular paradigm often share methods, assumptions and values. In addition to supporting specific methods, research paradigms also influence things like the ambition and nature of research, the researcher-participant relationship and how the role of the researcher is understood.

Paradigm vs. theory

The terms ‘ paradigm ‘ and ‘ theory ‘ are often used interchangeably in social science. There is not a consensus among social scientists as to whether these are identical or distinct concepts. With that said, in this text, we will make a clear distinction between the two ideas because thinking about each concept separately is more useful for our purposes.

We define paradigm a set of common philosophical (ontological, epistemological, and axiological) assumptions that inform research. The four paradigms we describe in this section refer to patterns in how groups of researchers resolve philosophical questions. Some assumptions naturally make sense together, and paradigms grow out of researchers with shared assumptions about what is important and how to study it. Paradigms are like “analytic lenses” and a provide framework on top of which we can build theoretical and empirical knowledge (Kuhn, 1962). [5] Consider this video of an interview with world-famous physicist Richard Feynman in which he explains why “when you explain a ‘why,’ you have to be in some framework that you allow something to be true. Otherwise, you are perpetually asking why.” In order to answer basic physics question like “what is happening when two magnets attract?” or a social work research question like “what is the impact of this therapeutic intervention on depression,” you must understand the assumptions you are making about social science and the social world. Paradigmatic assumptions about objective and subjective truth support methodological choices like whether to conduct interviews or send out surveys, for example.

While paradigms are broad philosophical assumptions, theory is more specific, and refers to a set of concepts and relationships scientists use to explain the social world. Theories are more concrete, while paradigms are more abstract. Look back to Figure 7.1 at the beginning of this chapter. Theory helps you identify the concepts and relationships that align with your paradigmatic understanding of the problem. Moreover, theory informs how you will measure the concepts in your research question and the design of your project.

For both theories and paradigms, Kuhn’s observation of scientific paradigms, crises, and revolutions is instructive for understanding the history of science. Researchers inherit institutions, norms, and ideas that are marked by the battlegrounds of theoretical and paradigmatic debates that stretch back hundreds of years. We have necessarily simplified this history into four paradigms: positivism, interpretivism, critical, and pragmatism. Our framework and explanation are inspired by the framework of Guba and Lincoln (1990) [6] and Burrell and Morgan (1979). [7] while also incorporating pragmatism as a way of resolving paradigmatic questions. Most of social work research and theory can be classified as belonging to one of these four paradigms, though this classification system represents only one of many useful approaches to analyzing social science research paradigms.

Building on our discussion in section 7.1 on objective vs. subjective epistemologies and ontologies, we will start with the difference between positivism and interpretivism. Afterward, we will link our discussion of axiology in section 7.2 with the critical paradigm. Finally, we will situate pragmatism as a way to resolve paradigmatic questions strategically. The difference between positivism and interpretivism is a good place to start, since the critical paradigm and pragmatism build on their philosophical insights.

It’s important to think of paradigms less as distinct categories and more as a spectrum along which projects might fall. For example, some projects may be somewhat positivist, somewhat interpretivist, and a little critical. No project fits perfectly into one paradigm. Additionally, there is no paradigm that is more correct than the other. Each paradigm uses assumptions that are logically consistent, and when combined, are a useful approach to understanding the social world using science. The purpose of this section is to acquaint you with what research projects in each paradigm look like and how they are grounded in philosophical assumptions about social science.

You should read this section to situate yourself in terms of what paradigm feels most “at home” to both you as a person and to your project. You may find, as I have, that your research projects are more conventional and less radical than what feels most like home to you, personally. In a research project, however, students should start with their working question rather than their heart. Use the paradigm that fits with your question the best, rather than which paradigm you think fits you the best.

Interpretivism: Researcher as “empathizer”

Positivism is focused on generalizable truth. Interpretivism , by contrast, develops from the idea that we want to understand the truths of individuals, how they interpret and experience the world, their thought processes, and the social structures that emerge from sharing those interpretations through language and behavior. The process of interpretation (or social construction) is guided by the empathy of the researcher to understand the meaning behind what other people say.

Historically, interpretivism grew out of a specific critique of positivism: that knowledge in the human and social sciences cannot conform to the model of natural science because there are features of human experience that cannot objectively be “known”. The tools we use to understand objects that have no self-awareness may not be well-attuned to subjective experiences like emotions, understandings, values, feelings, socio-cultural factors, historical influences, and other meaningful aspects of social life. Instead of finding a single generalizable “truth,” the interpretivist researcher aims to generate understanding and often adopts a relativist position.

While positivists seek “the truth,” the social constructionist framework argues that “truth” varies. Truth differs based on who you ask, and people change what they believe is true based on social interactions. These subjective truths also exist within social and historical contexts, and our understanding of truth varies across communities and time periods. This is because we, according to this paradigm, create reality ourselves through our social interactions and our interpretations of those interactions. Key to the interpretivist perspective is the idea that social context and interaction frame our realities.

Researchers operating within this framework take keen interest in how people come to socially agree, or disagree, about what is real and true. Consider how people, depending on their social and geographical context, ascribe different meanings to certain hand gestures. When a person raises their middle finger, those of us in Western cultures will probably think that this person isn’t very happy (not to mention the person at whom the middle finger is being directed!). In other societies around the world, a thumbs-up gesture, rather than a middle finger, signifies discontent (Wong, 2007). [8] The fact that these hand gestures have different meanings across cultures aptly demonstrates that those meanings are socially and collectively constructed. What, then, is the “truth” of the middle finger or thumbs up? As we’ve seen in this section, the truth depends on the intention of the person making the gesture, the interpretation of the person receiving it, and the social context in which the action occurred.

Qualitative methods are preferred as ways to investigate these phenomena. Data collected might be unstructured (or “messy”) and correspondingly a range of techniques for approaching data collection have been developed. Interpretivism acknowledges that it is impossible to remove cultural and individual influence from research, often instead making a virtue of the positionality of the researcher and the socio-cultural context of a study.

One common objection positivists levy against interpretivists is that interpretivism tends to emphasize the subjective over the objective. If the starting point for an investigation is that we can’t fully and objectively know the world, how can we do research into this without everything being a matter of opinion? For the positivist, this risk for confirmation bias as well as invalid and unreliable measures makes interpretivist research unscientific. Clearly, we disagree with this assessment, and you should, too. Positivism and interpretivism have different ontologies and epistemologies with contrasting notions of rigor and validity (for more information on assumptions about measurement, see Chapter 11 for quantitative validity and reliability and Chapter 20 for qualitative rigor). Nevertheless, both paradigms apply the values and concepts of the scientific method through systematic investigation of the social world, even if their assumptions lead them to do so in different ways. Interpretivist research often embraces a relativist epistemology, bringing together different perspectives in search of a trustworthy and authentic understanding or narrative.

Kivunja & Kuyini (2017) [9] describe the essential features of interpretivism as:

• The belief that truths are multiple and socially constructed
• The acceptance that there is inevitable interaction between the researcher and his or her research participants
• The acceptance that context is vital for knowledge and knowing
• The belief that knowledge can be value laden and the researcher’s values need to be made explicit
• The need to understand specific cases and contexts rather deriving universal laws that apply to everyone, everywhere.
• The belief that causes and effects are mutually interdependent, and that causality may be circular or contradictory
• The belief that contextual factors need to be taken into consideration in any systematic pursuit of understanding

One important clarification: it’s important to think of the interpretivist perspective as not just about individual interpretations but the social life of interpretations. While individuals may construct their own realities, groups—from a small one such as a married couple to large ones such as nations—often agree on notions of what is true and what “is” and what “is not.” In other words, the meanings that we construct have power beyond the individuals who create them. Therefore, the ways that people and communities act based on such meanings is of as much interest to interpretivists as how they were created in the first place. Theories like social constructionism, phenomenology, and symbolic interactionism are often used in concert with interpretivism.

Is interpretivism right for your project?

An interpretivist orientation to research is appropriate when your working question asks about subjective truths. The cause-and-effect relationships that interpretivist studies produce are specific to the time and place in which the study happened, rather than a generalizable objective truth. More pragmatically, if you picture yourself having a conversation with participants like an interview or focus group, then interpretivism is likely going to be a major influence for your study.

Positivists critique the interpretivist paradigm as non-scientific. They view the interpretivist focus on subjectivity and values as sources of bias. Positivists and interpretivists differ on the degree to which social phenomena are like natural phenomena. Positivists believe that the assumptions of the social sciences and natural sciences are the same, while interpretivists strongly believe that social sciences differ from the natural sciences because their subjects are social creatures.

Similarly, the critical paradigm finds fault with the interpretivist focus on the status quo rather than social change. Although interpretivists often proceed from a feminist or other standpoint theory, the focus is less on liberation than on understanding the present from multiple perspectives. Other critical theorists may object to the consensus orientation of interpretivist research. By searching for commonalities between people’s stories, they may erase the uniqueness of each individual’s story. For example, while interpretivists may arrive at a consensus definition of what the experience of “coming out” is like for people who identify as lesbian, gay, bisexual, transgender, or queer, it cannot represent the diversity of each person’s unique “coming out” experience and what it meant to them. For example, see Rosario and colleagues’ (2009) [10] critique the literature on lesbians “coming out” because previous studies did not addressing how appearing, behaving, or identifying as a butch or femme impacted the experience of “coming out” for lesbians.

• From your literature search, identify an empirical article that uses qualitative methods to answer a research question similar to your working question or about your research topic.
• Review the assumptions of the interpretivist research paradigm.
• Discuss in a few sentences how the author’s conclusions are based on some of these paradigmatic assumptions. How might a researcher operating from a different paradigm (like positivism or the critical paradigm) critique the conclusions of this study?

Critical paradigm: Researcher as “activist”

As we’ve discussed a bit in the preceding sections, the critical paradigm focuses on power, inequality, and social change. Although some rather diverse perspectives are included here, the critical paradigm, in general, includes ideas developed by early social theorists, such as Max Horkheimer (Calhoun et al., 2007), [11] and later works developed by feminist scholars, such as Nancy Fraser (1989). [12] Unlike the positivist paradigm, the critical paradigm assumes that social science can never be truly objective or value-free. Furthermore, this paradigm operates from the perspective that scientific investigation should be conducted with the express goal of social change. Researchers in the critical paradigm foreground axiology, positionality and values . In contrast with the detached, “objective” observations associated with the positivist researcher, critical approaches make explicit the intention for research to act as a transformative or emancipatory force within and beyond the study.

Researchers in the critical paradigm might start with the knowledge that systems are biased against certain groups, such as women or ethnic minorities, building upon previous theory and empirical data. Moreover, their research projects are designed not only to collect data, but to impact the participants as well as the systems being studied. The critical paradigm applies its study of power and inequality to change those power imbalances as part of the research process itself. If this sounds familiar to you, you may remember hearing similar ideas when discussing social conflict theory in your human behavior in the social environment (HBSE) class. [13] Because of this focus on social change, the critical paradigm is a natural home for social work research. However, we fall far short of adopting this approach widely in our profession’s research efforts.

Is the critical paradigm right for your project?

Every social work research project impacts social justice in some way. What distinguishes critical research is how it integrates an analysis of power into the research process itself. Critical research is appropriate for projects that are activist in orientation. For example, critical research projects should have working questions that explicitly seek to raise the consciousness of an oppressed group or collaborate equitably with community members and clients to addresses issues of concern. Because of their transformative potential, critical research projects can be incredibly rewarding to complete. However, partnerships take a long time to develop and social change can evolve slowly on an issue, making critical research projects a more challenging fit for student research projects which must be completed under a tight deadline with few resources.

Positivists critique the critical paradigm on multiple fronts. First and foremost, the focus on oppression and values as part of the research process is seen as likely to bias the research process, most problematically, towards confirmation bias. If you start out with the assumption that oppression exists and must be dealt with, then you are likely to find that regardless of whether it is truly there or not. Similarly, positivists may fault critical researchers for focusing on how the world should be, rather than how it truly is . In this, they may focus too much on theoretical and abstract inquiry and less on traditional experimentation and empirical inquiry. Finally, the goal of social transformation is seen as inherently unscientific, as science is not a political practice.

Interpretivists often find common cause with critical researchers. Feminist studies, for example, may explore the perspectives of women while centering gender-based oppression as part of the research process. In interpretivist research, the focus is less on radical change as part of the research process and more on small, incremental changes based on the results and conclusions drawn from the research project. Additionally, some critical researchers’ focus on individuality of experience is in stark contrast to the consensus-orientation of interpretivists. Interpretivists seek to understand people’s true selves. Some critical theorists argue that people have multiple selves or no self at all.

• From your literature search, identify an article relevant to your working question or broad research topic that uses a critical perspective. You should look for articles where the authors are clear that they are applying a critical approach to research like feminism, anti-racism, Marxism and critical theory, decolonization, anti-oppressive practice, or other social justice-focused theoretical perspectives. To target your search further, include keywords in your queries to research methods commonly used in the critical paradigm like participatory action research and community-based participatory research. If you have trouble identifying an article for this exercise, consult your professor for some help. These articles may be more challenging to find, but reviewing one is necessary to get a feel for what research in this paradigm is like.
• Review the assumptions of the critical research paradigm.
• Discuss in a few sentences how the author’s conclusions are based on some of these paradigmatic assumptions. How might a researcher operating from different assumptions (like values-neutrality or researcher as neutral and unbiased) critique the conclusions of this study?

Pragmatism: Researcher as “strategist”

“Essentially, all models are wrong but some are useful.” (Box, 1976) [14]

Pragmatism is a research paradigm that suspends questions of philosophical ‘truth’ and focuses more on how different philosophies, theories, and methods can be used strategically to provide a multidimensional view of a topic. Researchers employing pragmatism will mix elements of positivist, interpretivist, and critical research depending on the purpose of a particular project and the practical constraints faced by the researcher and their research context. We favor this approach for student projects because it avoids getting bogged down in choosing the “right” paradigm and instead focuses on the assumptions that help you answer your question, given the limitations of your research context. Student research projects are completed quickly and moving in the direction of pragmatism can be a route to successfully completing a project. Your project is a representation of what you think is feasible, ethical, and important enough for you to study.

The crucial consideration for the pragmatist is whether the outcomes of research have any real-world application, rather than whether they are “true.” The methods, theories, and philosophies chosen by pragmatic researchers are guided by their working question. There are no distinctively pragmatic research methods since this approach is about making judicious use whichever methods fit best with the problem under investigation. Pragmatic approaches may be less likely to prioritize ontological, epistemological or axiological consistency when combining different research methods. Instead, the emphasis is on solving a pressing problem and adapting to the limitations and opportunities in the researchers’ context.

Adopt a multi-paradigmatic perspective

Believe it or not, there is a long literature of acrimonious conflict between scientists from positivist, interpretivist, and critical camps (see Heineman-Pieper et al., 2002 [15] for a longer discussion). Pragmatism is an old idea, but it is appealing precisely because it attempts to resolve the problem of multiple incompatible philosophical assumptions in social science. To a pragmatist, there is no “correct” paradigm. All paradigms rely on assumptions about the social world that are the subject of philosophical debate. Each paradigm is an incomplete understanding of the world, and it requires a scientific community using all of them to gain a comprehensive view of the social world. This multi-paradigmatic perspective is a unique gift of social work research, as our emphasis on empathy and social change makes us more critical of positivism, the dominant paradigm in social science.

We offered the metaphors of expert, empathizer, activist, and strategist for each paradigm. It’s important not to take these labels too seriously. For example, some may view that scientists should be experts or that activists are biased and unscientific. Nevertheless, we hope that these metaphors give you a sense of what it feels like to conduct research within each paradigm.

One of the unique aspects of paradigmatic thinking is that often where you think you are most at home may actually be the opposite of where your research project is. For example, in my graduate and doctoral education, I thought I was a critical researcher. In fact, I thought I was a radical researcher focused on social change and transformation. Yet, often times when I sit down to conceptualize and start a research project, I find myself squarely in the positivist paradigm, thinking through neat cause-and-effect relationships that can be mathematically measured. There is nothing wrong with that! Your task for your research project is to find the paradigm that best matches your research question. Think through what you really want to study and how you think about the topic, then use assumptions of that paradigm to guide your inquiry.

Another important lesson is that no research project fits perfectly in one paradigm or another. Instead, there is a spectrum along which studies are, to varying degrees, interpretivist, positivist, and critical. For example, all social work research is a bit activist in that our research projects are designed to inform action for change on behalf of clients and systems. However, some projects will focus on the conclusions and implications of projects informing social change (i.e., positivist and interpretivist projects) while others will partner with community members and design research projects collaboratively in a way that leads to social change (i.e. critical projects). In section 7.5, we will describe a pragmatic approach to research design guided by your paradigmatic and theoretical framework.

Key Takeaways

• Social work research falls, to some degree, in each of the four paradigms: positivism, interpretivism, critical, and pragmatist.
• Adopting a pragmatic, multi-paradigmatic approach to research makes sense for student researchers, as it directs students to use the philosophical assumptions and methodological approaches that best match their research question and research context.
• Research in all paradigms is necessary to come to a comprehensive understanding of a topic, and social workers must be able to understand and apply knowledge from each research paradigm.
• Describe which paradigm best fits your perspective on the world and which best fits with your project.
• Identify any similarities and differences in your personal assumptions and the assumption your research project relies upon. For example, are you a more critical and radical thinker but have chosen a more “expert” role for yourself in your research project?

Learners will be able to…

• Apply the assumptions of each paradigm to your project
• Summarize what aspects of your project stem from positivist, interpretivist, or critical assumptions

In the previous sections, we reviewed the major paradigms and theories in social work research. In this section, we will provide an example of how to apply theory and paradigm in research. This process is depicted in Figure 7.2 below with some quick summary questions for each stage. Some questions in the figure below have example answers like designs (i.e., experimental, survey) and data analysis approaches (i.e., discourse analysis). These examples are arbitrary. There are a lot of options that are not listed. So, don’t feel like you have to memorize them or use them in your study.

This diagram (taken from an archived Open University (UK) course entitled E89 ​- Educational Inquiry ) ​ shows one way to visualize the research design process. While research is far from linear, in general, this is how research projects progress sequentially. Researchers begin with a working question, and through engaging with the literature, develop and refine those questions into research questions (a process we will finalize in Chapter 9 ). But in order to get to the part where you gather your sample, measure your participants, and analyze your data, you need to start with paradigm. Based on your work in section 7.3, you should have a sense of which paradigm or paradigms are best suited to answering your question. The approach taken will often reflect the nature of the research question; the kind of data it is possible to collect; and work previously done in the area under consideration. When evaluating paradigm and theory, it is important to look at what other authors have done previously and the framework used by studies that are similar to the one you are thinking of conducting.

Once you situate your project in a research paradigm, it becomes possible to start making concrete choices about methods. Depending on the project, this will involve choices about things like:

• What is my final research question?
• What are the key variables and concepts under investigation, and how will I measure them?
• How do I find a representative sample of people who experience the topic I’m studying?
• What design is most appropriate for my research question?
• How will I collect and analyze data?
• How do I determine whether my results describe real patterns in the world or are the result of bias or error?

The data collection phase can begin once these decisions are made. It can be very tempting to start collecting data as soon as possible in the research process as this gives a sense of progress. However, it is usually worth getting things exactly right before collecting data as an error found in your approach further down the line can be harder to correct or recalibrate around.

Designing a study using paradigm and theory: An example

Paradigm and theory have the potential to turn some people off since there is a lot of abstract terminology and thinking about real-world social work practice contexts. In this section, I’ll use an example from my own research, and I hope it will illustrate a few things. First, it will show that paradigms are really just philosophical statements about things you already understand and think about normally. It will also show that no project neatly sits in one paradigm and that a social work researcher should use whichever paradigm or combination of paradigms suit their question the best. Finally, I hope it is one example of how to be a pragmatist and strategically use the strengths of different theories and paradigms to answering a research question. We will pick up the discussion of mixed methods in the next chapter.

Thinking as an expert: Positivism

In my undergraduate research methods class, I used an open textbook much like this one and wanted to study whether it improved student learning. You can read a copy of the article we wrote on based on our study . We’ll learn more about the specifics of experiments and evaluation research in Chapter 13 , but you know enough to understand what evaluating an intervention might look like. My first thought was to conduct an experiment, which placed me firmly within the positivist or “expert” paradigm.

Experiments focus on isolating the relationship between cause and effect. For my study, this meant studying an open textbook (the cause, or intervention) and final grades (the effect, or outcome). Notice that my position as “expert” lets me assume many things in this process. First, it assumes that I can distill the many dimensions of student learning into one number—the final grade. Second, as the “expert,” I’ve determined what the intervention is: indeed, I created the book I was studying, and applied a theory from experts in the field that explains how and why it should impact student learning.

Theory is part of applying all paradigms, but I’ll discuss its impact within positivism first. Theories grounded in positivism help explain why one thing causes another. More specifically, these theories isolate a causal relationship between two (or more) concepts while holding constant the effects of other variables that might confound the relationship between the key variables. That is why experimental design is so common in positivist research. The researcher isolates the environment from anything that might impact or bias the cause and effect relationship they want to investigate.

But in order for one thing to lead to change in something else, there must be some logical, rational reason why it would do so. In open education, there are a few hypotheses (though no full-fledged theories) on why students might perform better using open textbooks. The most common is the access hypothesis , which states that students who cannot afford expensive textbooks or wouldn’t buy them anyway can access open textbooks because they are free, which will improve their grades. It’s important to note that I held this theory prior to starting the experiment, as in positivist research you spell out your hypotheses in advance and design an experiment to support or refute that hypothesis.

Notice that the hypothesis here applies not only to the people in my experiment, but to any student in higher education. Positivism seeks generalizable truth, or what is true for everyone. The results of my study should provide evidence that  anyone  who uses an open textbook would achieve similar outcomes. Of course, there were a number of limitations as it was difficult to tightly control the study. I could not randomly assign students or prevent them from sharing resources with one another, for example. So, while this study had many positivist elements, it was far from a perfect positivist study because I was forced to adapt to the pragmatic limitations of my research context (e.g., I cannot randomly assign students to classes) that made it difficult to establish an objective, generalizable truth.

Thinking like an empathizer: Interpretivism

One of the things that did not sit right with me about the study was the reliance on final grades to signify everything that was going on with students. I added another quantitative measure that measured research knowledge, but this was still too simplistic. I wanted to understand how students used the book and what they thought about it. I could create survey questions that ask about these things, but to get at the subjective truths here, I thought it best to use focus groups in which students would talk to one another with a researcher moderating the discussion and guiding it using predetermined questions. You will learn more about focus groups in Chapter 18 .

Researchers spoke with small groups of students during the last class of the semester. They prompted people to talk about aspects of the textbook they liked and didn’t like, compare it to textbooks from other classes, describe how they used it, and so forth. It was this focus on  understanding and subjective experience that brought us into the interpretivist paradigm. Alongside other researchers, I created the focus group questions but encouraged researchers who moderated the focus groups to allow the conversation to flow organically.

We originally started out with the assumption, for which there is support in the literature, that students would be angry with the high-cost textbook that we used prior to the free one, and this cost shock might play a role in students’ negative attitudes about research. But unlike the hypotheses in positivism, these are merely a place to start and are open to revision throughout the research process. This is because the researchers are not the experts, the participants are! Just like your clients are the experts on their lives, so were the students in my study. Our job as researchers was to create a group in which they would reveal their informed thoughts about the issue, coming to consensus around a few key themes.

When we initially analyzed the focus groups, we uncovered themes that seemed to fit the data. But the overall picture was murky. How were themes related to each other? And how could we distill these themes and relationships into something meaningful? We went back to the data again. We could do this because there isn’t one truth, as in positivism, but multiple truths and multiple ways of interpreting the data. When we looked again, we focused on some of the effects of having a textbook customized to the course. It was that customization process that helped make the language more approachable, engaging, and relevant to social work practice.

Ultimately, our data revealed differences in how students perceived a free textbook versus a free textbook that is customized to the class. When we went to interpret this finding, the remix  hypothesis of open textbook was helpful in understanding that relationship. It states that the more faculty incorporate editing and creating into the course, the better student learning will be. Our study helped flesh out that theory by discussing the customization process and how students made sense of a customized resource.

In this way, theoretical analysis operates differently in interpretivist research. While positivist research tests existing theories, interpretivist research creates theories based on the stories of research participants. However, it is difficult to say if this theory was totally emergent in the dataset or if my prior knowledge of the remix hypothesis influenced my thinking about the data. Interpretivist researchers are encouraged to put a box around their prior experiences and beliefs, acknowledging them, but trying to approach the data with fresh eyes. Interpretivists know that this is never perfectly possible, though, as we are always influenced by our previous experiences when interpreting data and conducting scientific research projects.

Thinking like an activist: Critical

Although adding focus groups helped ease my concern about reducing student learning down to just final grades by providing a more rich set of conversations to analyze. However, my role as researcher and “expert” was still an important part of the analysis. As someone who has been out of school for a while, and indeed has taught this course for years, I have lost touch with what it is like to be a student taking research methods for the first time. How could I accurately interpret or understand what students were saying? Perhaps I would overlook things that reflected poorly on my teaching or my book. I brought other faculty researchers on board to help me analyze the data, but this still didn’t feel like enough.

By luck, an undergraduate student approached me about wanting to work together on a research project. I asked her if she would like to collaborate on evaluating the textbook with me. Over the next year, she assisted me with conceptualizing the project, creating research questions, as well as conducting and analyzing the focus groups. Not only would she provide an “insider” perspective on coding the data, steeped in her lived experience as a student, but she would serve as a check on my power through the process.

Including people from the group you are measuring as part of your research team is a common component of critical research. Ultimately, critical theorists would find my study to be inadequate in many ways. I still developed the research question, created the intervention, and wrote up the results for publication, which privileges my voice and role as “expert.” Instead, critical theorists would emphasize the role of students (community members) in identifying research questions, choosing the best intervention to used, and so forth. But collaborating with students as part of a research team did address some of the power imbalances in the research process.

Critical research projects also aim to have an impact on the people and systems involved in research. No students or researchers had profound personal realizations as a result of my study, nor did it lessen the impact of oppressive structures in society. I can claim some small victory that my department switched to using my textbook after the study was complete (changing a system), though this was likely the result of factors other than the study (my advocacy for open textbooks).

Social work research is almost always designed to create change for people or systems. To that end, every social work project is at least somewhat critical. However, the additional steps of conducting research with people rather than on people reveal a depth to the critical paradigm. By bringing students on board the research team, study had student perspectives represented in conceptualization, data collection, and analysis. That said, there was much to critique about this study from a critical perspective. I retained a lot of the power in the research process, and students did not have the ability to determine the research question or purpose of the project. For example, students might likely have said that textbook costs and the quality of their research methods textbook were less important than student debt, racism, or other potential issues experienced by students in my class. Instead of a ground-up research process based in community engagement, my research included some important participation by students on project created and led by faculty.

Conceptualization is an iterative process

I hope this conversation was useful in applying paradigms to a research project. While my example discusses education research, the same would apply for social work research about social welfare programs, clinical interventions, or other topics. Paradigm and theory are covered at the beginning of the conceptualization of your project because these assumptions will structure the rest of your project. Each of the research steps that occur after this chapter (e.g., forming a question, choosing a design) rely upon philosophical and theoretical assumptions. As you continue conceptualizing your project over the next few weeks, you may find yourself shifting between paradigms. That is normal, as conceptualization is not a linear process. As you move through the next steps of conceptualizing and designing a project, you’ll find philosophies and theories that best match how you want to study your topic.

Viewing theoretical and empirical arguments through this lens is one of the true gifts of the social work approach to research. The multi-paradigmatic perspective is a hallmark of social work research and one that helps us contribute something unique on research teams and in practice.

• Multi-paradigmatic research is a distinguishing hallmark of social work research. Understanding the limitations and strengths of each paradigm will help you justify your research approach and strategically choose elements from one or more paradigms to answer your question.
• Paradigmatic assumptions help you understand the “blind spots” in your research project and how to adjust and address these areas. Keep in mind, it is not necessary to address all of your blind spots, as all projects have limitations.
• Sketch out which paradigm applies best to your project. Second, building on your answer to the exercise in section 7.3, identify how the theory you chose and the paradigm in which you find yourself are consistent or are in conflict with one another. For example, if you are using systems theory in a positivist framework, you might talk about how they both rely on a deterministic approach to human behavior with a focus on the status-quo and social order.
• Define and provide an example of an idiographic causal explanation
• Differentiate between idiographic and nomothetic causal relationships
• Link idiographic and nomothetic causal relationships with the process of theory building and theory testing
• Describe how idiographic and nomothetic causal explanations can be complementary

As we transition away from positivism, it is important to highlight the assumptions it makes about the scientific process–the hypothetico-deductive method, sometimes referred to as the research circle.

The hypothetico-deductive method

The primary way that researchers in the positivist paradigm use theories is sometimes called the hypothetico-deductive method (although this term is much more likely to be used by philosophers of science than by scientists themselves). Researchers choose an existing theory. Then, they make a prediction about some new phenomenon that should be observed if the theory is correct. Again, this prediction is called a hypothesis. The researchers then conduct an empirical study to test the hypothesis. Finally, they reevaluate the theory in light of the new results and revise it if necessary.

This process is usually conceptualized as a cycle because the researchers can then derive a new hypothesis from the revised theory, conduct a new empirical study to test the hypothesis, and so on. As Figure 8.8 shows, this approach meshes nicely with the process of conducting a research project—creating a more detailed model of “theoretically motivated” or “theory-driven” research. Together, they form a model of theoretically motivated research. 

Keep in mind the hypothetico-deductive method is only one way of using social theory to inform social science research. It starts with describing one or more existing theories, deriving a hypothesis from one of those theories, testing your hypothesis in a new study, and finally reevaluating the theory based on the results data analyses. This format works well when there is an existing theory that addresses the research question—especially if the resulting hypothesis is surprising or conflicts with a hypothesis derived from a different theory.

But what if your research question is more interpretive? What if it is less about theory-testing and more about theory-building? This is what our next chapter covers: the process of inductively deriving theory from people’s stories and experiences. This process looks different than that depicted in Figure 8.8. It still starts with your research question and answering that question by conducting a research study. But instead of testing a hypothesis you created based on a theory, you will create a theory of your own that explain the data you collected. This format works well for qualitative research questions and for research questions that existing theories do not address.

Inductive reasoning is most commonly found in studies using qualitative methods, such as focus groups and interviews. Because inductive reasoning involves the creation of a new theory, researchers need very nuanced data on how the key concepts in their working question operate in the real world. Qualitative data is often drawn from lengthy interactions and observations with the individuals and phenomena under examination. For this reason, inductive reasoning is most often associated with qualitative methods, though it is used in both quantitative and qualitative research.

Whose truth does science establish?

Social work is concerned with the “isms” of oppression (ableism, ageism, cissexism, classism, heterosexism, racism, sexism, etc.), and so our approach to science must reconcile its history as both a tool of oppression and its exclusion of oppressed groups. Science grew out of the Enlightenment, a philosophical movement which applied reason and empirical analysis to understanding the world. While the Enlightenment brought forth tremendous achievements, the critiques of Marxian, feminist, and other critical theorists complicated the Enlightenment understanding of science. For this section, I will focus on feminist critiques of science, building upon an entry in the Stanford Encyclopedia of Philosophy (Crasnow, 2020). [16]

In its original formulation, science was an individualistic endeavor. As we learned in Chapter 1 , a basic statement of the scientific method is that a researcher studies existing theories on a topic, formulates a hypothesis about what might be true, and either confirms or disconfirms their hypothesis through experiment and rigorous observation. Over time, our theories become more accurate in their predictions and more comprehensive in their conclusions. Scientists put aside their preconceptions, look at the data, and build their theories based on objective rationality.

Yet, this cannot be perfectly true. Scientists are human, after all. As a profession historically dominated by white men, scientists have dismissed women and other minorities as being psychologically unfit for the scientific profession. While attitudes have improved, science, technology, engineering, mathematics (STEM) and related fields remain dominated by white men (Grogan, 2019). [17] Biases can persist in social work theory and research when social scientists do not have similar experiences to the populations they study.

Gender bias can influence the research questions scientists choose to answer. Feminist critiques of medical science drew attention to women’s health issues, spurring research and changing standards of care. The focus on domestic violence in the empirical literature can also be seen as a result of feminist critique. Thus, critical theory helps us critique what is on the agenda for science. If science is to answer important questions, it must speak to the concerns of all people. Through the democratization in access to scientific knowledge and the means to produce it, science becomes a sister process of social development and social justice.

The goal of a diverse and participatory scientific community lies in contrast to much of what we understand to be “proper” scientific knowledge. Many of the older, classic social science theories were developed based on research which observed males or from university students in the United States or other Western nations. How these observations were made, what questions were asked, and how the data were interpreted were shaped by the same oppressive forces that existed in broader society, a process that continues into the present. In psychology, the concept of hysteria or hysterical women was believed to be caused by a wandering womb (Tasca et al., 2012). [18] Even today, there are gender biases in diagnoses of histrionic personality disorder and racial biases in psychotic disorders (Klonsky et al., 2002) [19] because the theories underlying them were created in a sexist and racist culture. In these ways, science can reinforce the truth of the white Western male perspective.

Finally, it is important to note that social science research is often conducted on populations rather than with populations. Historically, this has often meant Western men traveling to other countries and seeking to understand other cultures through a Western lens. Lacking cultural humility and failing to engage stakeholders, ethnocentric research of this sort has led to the view of non-Western cultures as inferior. Moreover, the use of these populations as research subjects rather than co-equal participants in the research process privileges the researcher’s knowledge over that from other groups or cultures. Researchers working with indigenous cultures, in particular, had a destructive habit of conducting research for a short time and then leaving, without regard for the impact their study had on the population. These critiques of Western science aim to decolonize social science and dismantle the racist ideas the oppress indigenous and non-Western peoples through research (Smith, 2013). [20]

The central concept in feminist, anti-racist, and decolonization critiques (among other critical frames) is epistemic injustice. Epistemic injustice happens when someone is treated unfairly in their capacity to know something or describe their experience of the world. As described by Fricker (2011), [21] the injustice emerges from the dismissal of knowledge from oppressed groups, discrimination against oppressed groups in scientific communities, and the resulting gap between what scientists can make sense of from their experience and the experiences of people with less power who have lived experience of the topic. We recommend this video from Edinburgh Law School which applies epistemic injustice to studying public health emergencies, disabilities, and refugee services .

Positivism relies on nomothetic causality, or the idea that “one event, behavior, or belief will result in the occurrence of another, subsequent event, behavior, or belief.” Then, we described one kind of causality: a simple cause-and-effect relationship supported by existing theory and research on the topic, also known as a nomothetic causal relationship. But what if there is not a lot of literature on your topic? What if your question is more exploratory than explanatory? Then, you need a different kind of causal explanation, one that accounts for the complexity of human interactions.

How can we build causal relationships if we are just describing or exploring a topic? Recall the definitions of exploratory research , descriptive research , and explanatory research from Chapter 2. Wouldn’t we need to do explanatory research to build any kind of causal explanation? Explanatory research attempts to establish nomothetic causal relationships: an independent variable is demonstrated to cause change in a dependent variable. Exploratory and descriptive qualitative research contains some causal relationships, but they are actually descriptions of the causal relationships established by the study participants.

What do idiographic causal explanations look like?

An idiographic causal relationship   tries to identify the many, interrelated causes that account for the phenomenon the researcher is investigating. So, if idiographic causal explanations do not look like Figure 8.5, 8.6, or 8.7 what do they look like? Instead of saying “x causes y,” your participants will describe their experiences with “x,” which they will tell you was caused and influenced by a variety of other factors, as interpreted through their unique perspective, time, and environment. As we stated before, idiographic causal explanations are messy. Your job as a social science researcher is to accurately describe the patterns in what your participants tell you.

Let’s think about this using an example. If I asked you why you decided to become a social worker, what might you say? For me, I would say that I wanted to be a mental health clinician since I was in high school. I was interested in how people thought, and I was privileged enough to have psychology courses at my local high school. I thought I wanted to be a psychologist, but at my second internship in my undergraduate program, my supervisors advised me to become a social worker because the license provided greater authority for independent practice and flexibility for career change. Once I found out social workers were like psychologists who also raised trouble about social justice, I was hooked.

That’s not a simple explanation at all! But it’s definitely a causal explanation. It is my individual, subjective truth of a complex process. If we were to ask multiple social workers the same question, we might find out that many social workers begin their careers based on factors like personal experience with a disability or social injustice, positive experiences with social workers, or a desire to help others. No one factor is the “most important factor,” like with nomothetic causal relationships. Instead, a complex web of factors, contingent on context, emerge when you interpret what people tell you about their lives.

Understanding “why?”

In creating an idiographic explanation, you are still asking “why?” But the answer is going to be more complex. Those complexities are described in Table 8.1 as well as this short video comparing nomothetic and idiographic relationships .

Remember our question from the last section, “Are you trying to generalize or nah?” If you answered nah (or no, like a normal person), you are trying to establish an idiographic causal explanation. The purpose of that explanation isn’t to predict the future or generalize to larger populations, but to describe the here-and-now as it is experienced by individuals within small groups and communities. Idiographic explanations are focused less on what is generally experienced by all people but more on the particularities of what specific individuals in a unique time and place experience.

Researchers seeking idiographic causal relationships are not trying to generalize or predict, so they have no need to reduce phenomena to mathematics. In fact, only examining things that can be counted can rob a causal relationship of its meaning and context. Instead, the goal of idiographic causal relationships is understanding, rather than prediction. Idiographic causal relationships are formed by interpreting people’s stories and experiences. Usually, these are expressed through words. Not all qualitative studies use word data, as some can use interpretations of visual or performance art. However, the vast majority of qualitative studies do use word data, like the transcripts from interviews and focus groups or documents like journal entries or meeting notes. Your participants are the experts on their lives—much like in social work practice—and as in practice, people’s experiences are embedded in their cultural, historical, and environmental context.

Idiographic causal explanations are powerful because they can describe the complicated and interconnected nature of human life. Nomothetic causal explanations, by comparison, are simplistic. Think about if someone asked you why you wanted to be a social worker. Your story might include a couple of vignettes from your education and early employment. It might include personal experience with the social welfare system or family traditions. Maybe you decided on a whim to enroll in a social work course during your graduate program. The impact of each of these events on your career is unique to you.

Idiographic causal explanations are concerned with individual stories, their idiosyncrasies, and the patterns that emerge when you collect and analyze multiple people’s stories. This is the inductive reasoning we discussed at the beginning of this chapter. Often, idiographic causal explanations begin by collecting a lot of qualitative data, whether though interviews, focus groups, or looking at available documents or cultural artifacts. Next, the researcher looks for patterns in the data and arrives at a tentative theory for how the key ideas in people’s stories are causally related.

Unlike nomothetic causal relationships, there are no formal criteria (e.g., covariation) for establishing causality in idiographic causal relationships. In fact, some criteria like temporality and nonspuriousness may be violated. For example, if an adolescent client says, “It’s hard for me to tell whether my depression began before my drinking, but both got worse when I was expelled from my first high school,” they are recognizing that it may not so simple that one thing causes another. Sometimes, there is a reciprocal relationship where one variable (depression) impacts another (alcohol abuse), which then feeds back into the first variable (depression) and into other variables as well (school). Other criteria, such as covariation and plausibility, still make sense, as the relationships you highlight as part of your idiographic causal explanation should still be plausible and its elements should vary together.

Theory building and theory testing

As we learned in the previous section, nomothetic causal explanations are created by researchers applying deductive reasoning to their topic and creating hypotheses using social science theories. Much of what we think of as social science is based on this hypothetico-deductive method, but this leaves out the other half of the equation. Where do theories come from? Are they all just revisions of one another? How do any new ideas enter social science?

Through inductive reasoning and idiographic causal explanations!

Let’s consider a social work example. If you plan to study domestic and sexual violence, you will likely encounter the Power and Control Wheel, also known as the Duluth Model (Figure 8.9). The wheel is a model designed to depict the process of domestic violence. The wheel was developed based on qualitative focus groups conducted by sexual and domestic violence advocates in Duluth, MN. This video explains more about the Duluth Model of domestic abuse.

The Power and Control Wheel is an example of what an idiographic causal relationship looks like. By contrast, look back at the previous section’s Figure 8.5, 8.6, and 8.7 on nomothetic causal relationships between independent and dependent variables. See how much more complex idiographic causal explanations are?! They are complex, but not difficult to understand. At the center of domestic abuse is power and control, and while not every abuser would say that is what they were doing, that is the understanding of the survivors who informed this theoretical model. Their power and control is maintained through a variety of abusive tactics from social isolation to use of privilege to avoid consequences.

What about the role of hypotheses in idiographic causal explanations? In nomothetic causal explanations, researchers create hypotheses using existing theory and then test them for accuracy. Hypotheses in idiographic causality are much more tentative, and are probably best considered as “hunches” about what they think might be true. Importantly, they might indicate the researcher’s prior knowledge and biases before the project begins, but the goal of idiographic research is to let your participants guide you rather than existing social work knowledge. Continuing with our Duluth Model example, advocates likely had some tentative hypotheses about what was important in a relationship with domestic violence. After all, they worked with this population for years prior to the creation of the model. However, it was the stories of the participants in these focus groups that led the Power and Control Wheel explanation for domestic abuse.

As qualitative inquiry unfolds, hypotheses and hunches are likely to emerge and shift as researchers learn from what their participants share. Because the participants are the experts in idiographic causal relationships, a researcher should be open to emerging topics and shift their research questions and hypotheses accordingly. This is in contrast to hypotheses in quantitative research, which remain constant throughout the study and are shown to be true or false.

Over time, as more qualitative studies are done and patterns emerge across different studies and locations, more sophisticated theories emerge that explain phenomena across multiple contexts. Once a theory is developed from qualitative studies, a quantitative researcher can seek to test that theory. For example, a quantitative researcher may hypothesize that men who hold traditional gender roles are more likely to engage in domestic violence. That would make sense based on the Power and Control Wheel model, as the category of “using male privilege” speaks to this relationship. In this way, qualitatively-derived theory can inspire a hypothesis for a quantitative research project, as we will explore in the next section.

Complementary approaches

If idiographic and nomothetic still seem like obscure philosophy terms, let’s consider another example. Imagine you are working for a community-based non-profit agency serving people with disabilities. You are putting together a report to lobby the state government for additional funding for community support programs. As part of that lobbying, you are likely to rely on both nomothetic and idiographic causal relationships.

If you looked at nomothetic causal relationships, you might learn how previous studies have shown that, in general, community-based programs like yours are linked with better health and employment outcomes for people with disabilities. Nomothetic causal explanations seek to establish that community-based programs are better for everyone with disabilities, including people in your community.

If you looked at idiographic causal explanations, you would use stories and experiences of people in community-based programs. These individual stories are full of detail about the lived experience of being in a community-based program. You might use one story from a client in your lobbying campaign, so policymakers can understand the lived experience of what it’s like to be a person with a disability in this program. For example, a client who said “I feel at home when I’m at this agency because they treat me like a family member,” or “this is the agency that helped me get my first paycheck,” can communicate richer, more complex causal relationships.

Neither kind of causal explanation is better than the other. A decision to seek idiographic causal explanations means that you will attempt to explain or describe your phenomenon exhaustively, attending to cultural context and subjective interpretations. A decision to seek nomothetic causal explanations, on the other hand, means that you will try to explain what is true for everyone and predict what will be true in the future. In short, idiographic explanations have greater depth, and nomothetic explanations have greater breadth.

Most importantly, social workers understand the value of both approaches to understanding the social world. A social worker helping a client with substance abuse issues seeks idiographic explanations when they ask about that client’s life story, investigate their unique physical environment, or probe how their family relationships. At the same time, a social worker also uses nomothetic explanations to guide their interventions. Nomothetic explanations may help guide them to minimize risk factors and maximize protective factors or use an evidence-based therapy, relying on knowledge about what in general  helps people with substance abuse issues.

So, which approach speaks to you? Are you interested in learning about (a) a few people’s experiences in a great deal of depth, or (b) a lot of people’s experiences more superficially, while also hoping your findings can be generalized to a greater number of people? The answer to this question will drive your research question and project. These approaches provide different types of information and both types are valuable.

• Idiographic causal explanations focus on subjectivity, context, and meaning.
• Idiographic causal explanations are best suited to exploratory research questions and qualitative methods.
• Idiographic causal explanations are used to create new theories in social science.
• Explore the literature on the theory you identified in section 8.1.
• Read about the origins of your theory. Who developed it and from what data?
• See if you can find a figure like Figure 8.9 in an article or book chapter that depicts the key concepts in your theory and how those concepts are related to one another causally. Write out a short statement on the causal relationships contained in the figure.
• List the key terms associated with qualitative research questions
• Distinguish between qualitative and quantitative research questions

Qualitative research questions differ from quantitative research questions. Because qualitative research questions seek to explore or describe phenomena, not provide a neat nomothetic explanation, they are often more general and openly worded. They may include only one concept, though many include more than one. Instead of asking how one variable causes changes in another, we are instead trying to understand the experiences ,  understandings , and  meanings that people have about the concepts in our research question. These keywords often make an appearance in qualitative research questions.

Let’s work through an example from our last section. In Table 9.1, a student asked, “What is the relationship between sexual orientation or gender identity and homelessness for late adolescents in foster care?” In this question, it is pretty clear that the student believes that adolescents in foster care who identify as LGBTQ+ may be at greater risk for homelessness. This is a nomothetic causal relationship—LGBTQ+ status causes changes in homelessness.

However, what if the student were less interested in  predicting  homelessness based on LGBTQ+ status and more interested in  understanding  the stories of foster care youth who identify as LGBTQ+ and may be at risk for homelessness? In that case, the researcher would be building an idiographic causal explanation . The youths whom the researcher interviews may share stories of how their foster families, caseworkers, and others treated them. They may share stories about how they thought of their own sexuality or gender identity and how it changed over time. They may have different ideas about what it means to transition out of foster care.

Because qualitative questions usually center on idiographic causal relationships, they look different than quantitative questions. Table 9.3 below takes the final research questions from Table 9.1 and adapts them for qualitative research. The guidelines for research questions previously described in this chapter still apply, but there are some new elements to qualitative research questions that are not present in quantitative questions.

• Qualitative research questions often ask about lived experience, personal experience, understanding, meaning, and stories.
• Qualitative research questions may be more general and less specific.
• Qualitative research questions may also contain only one variable, rather than asking about relationships between multiple variables.

Qualitative research questions have one final feature that distinguishes them from quantitative research questions: they can change over the course of a study. Qualitative research is a reflexive process, one in which the researcher adapts their approach based on what participants say and do. The researcher must constantly evaluate whether their question is important and relevant to the participants. As the researcher gains information from participants, it is normal for the focus of the inquiry to shift.

For example, a qualitative researcher may want to study how a new truancy rule impacts youth at risk of expulsion. However, after interviewing some of the youth in their community, a researcher might find that the rule is actually irrelevant to their behavior and thoughts. Instead, their participants will direct the discussion to their frustration with the school administrators or the lack of job opportunities in the area. This is a natural part of qualitative research, and it is normal for research questions and hypothesis to evolve based on information gleaned from participants.

However, this reflexivity and openness unacceptable in quantitative research for good reasons. Researchers using quantitative methods are testing a hypothesis, and if they could revise that hypothesis to match what they found, they could never be wrong! Indeed, an important component of open science and reproducability is the preregistration of a researcher’s hypotheses and data analysis plan in a central repository that can be verified and replicated by reviewers and other researchers. This interactive graphic from 538 shows how an unscrupulous research could come up with a hypothesis and theoretical explanation  after collecting data by hunting for a combination of factors that results in a statistically significant relationship. This is an excellent example of how the positivist assumptions behind quantitative research and intepretivist assumptions behind qualitative research result in different approaches to social science.

• Qualitative research questions often contain words or phrases like “lived experience,” “personal experience,” “understanding,” “meaning,” and “stories.”
• Qualitative research questions can change and evolve over the course of the study.
• Using the guidance in this chapter, write a qualitative research question. You may want to use some of the keywords mentioned above.
• Kivuna, C. & Kuyini, A. B. (2017). Understanding and applying research paradigms in educational contexts. International Journal of Higher Education, 6 (5), 26-41. https://eric.ed.gov/?id=EJ1154775 ↵
• Kuhn, T. (1962). The structure of scientific revolutions . Chicago: University of Chicago Press. ↵
• Fleuridas, C., & Krafcik, D. (2019). Beyond four forces: The evolution of psychotherapy. Sage Open ,  9 (1), 2158244018824492. ↵
• Shneider, A. M. (2009). Four stages of a scientific discipline; four types of scientist. Trends in Biochemical Sciences 34 (5), 217-233. https://doi.org/10.1016/j.tibs.2009.02.00 ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organizational analysis . Routledge. Guba, E. (ed.) (1990). The paradigm dialog . SAGE. ↵
• Routledge. Guba, E. (ed.) (1990). The paradigm dialog . SAGE. ↵
• Burrell, G. & Morgan, G. (1979). Sociological paradigms and organizational analysis . Here is a summary of Burrell & Morgan from Babson College , and our classification collapses radical humanism and radical structuralism into the critical paradigm, following Guba and Lincoln's three-paradigm framework. We feel this approach is more parsimonious and easier for students to understand on an introductory level. ↵
• For more about how the meanings of hand gestures vary by region, you might read the following blog entry: Wong, W. (2007). The top 10 hand gestures you’d better get right . Retrieved from: http://www.languagetrainers.co.uk/blog/2007/09/24/top-10-hand-gestures ↵
• Rosario, M., Schrimshaw, E. W., Hunter, J., & Levy-Warren, A. (2009). The coming-out process of young lesbian and bisexual women: Are there butch/femme differences in sexual identity development?. Archives of sexual behavior ,  38 (1), 34-49. ↵
• Calhoun, C., Gerteis, J., Moody, J., Pfaff, S., & Virk, I. (Eds.). (2007). Classical sociological theory  (2nd ed.). Malden, MA: Blackwell. ↵
• Fraser, N. (1989).  Unruly practices: Power, discourse, and gender in contemporary social theory . Minneapolis, MN: University of Minnesota Press. ↵
• Here are links to two HBSE open textbooks, if you are unfamiliar with social work theories and would like more background. https://uark.pressbooks.pub/hbse1/ and https://uark.pressbooks.pub/humanbehaviorandthesocialenvironment2/ ↵
• Box, G. E. P.. (1976). Science and statistics. Journal of the American Statistical Association, 71 (356), 791. ↵
• Heineman-Pieper, J., Tyson, K., & Pieper, M. H. (2002). Doing good science without sacrificing good values: Why the heuristic paradigm is the best choice for social work.  Families in Society ,  83 (1), 15-28. ↵
• Crasnow, S. (2020). Feminist perspectives on science. In E. N. Zalta (ed.), The Stanford Encyclopedia of Philosophy (Winter 2020 Edition). Retrieved from: https://plato.stanford.edu/entries/feminist-science/ ↵
• Grogan, K.E. (2019) How the entire scientific community can confront gender bias in the workplace. Nature Ecology & Evolution, 3 ,  3–6. doi:10.1038/s41559-018-0747-4 ↵
• Tasca, C., Rapetti, M., Carta, M. G., & Fadda, B. (2012). Women and hysteria in the history of mental health. Clinical practice and epidemiology in mental health: Clinical practice & epidemiology in mental health ,  8 , 110-119. ↵
• Klonsky, E. D., Jane, J. S., Turkheimer, E., & Oltmanns, T. F. (2002). Gender role and personality disorders.  Journal of personality disorders ,  16 (5), 464-476. ↵
• Smith, L. T. (2013). Decolonizing methodologies: Research and indigenous peoples . Zed Books Ltd. ↵
• Fricker, M. (2011). Epistemic injustice: Power and the ethics of knowing . Oxford University Press. ↵

The highest level of measurement. Denoted by mutually exclusive categories, a hierarchy (order), values can be added, subtracted, multiplied, and divided, and the presence of an absolute zero.

a paradigm based on the idea that social context and interaction frame our realities

a paradigm in social science research focused on power, inequality, and social change

a research paradigm that suspends questions of philosophical ‘truth’ and focuses more on how different philosophies, theories, and methods can be used strategically to resolve a problem or question within the researcher's unique context

A cyclical process of theory development, starting with an observed phenomenon, then developing or using a theory to make a specific prediction of what should happen if that theory is correct, testing that prediction, refining the theory in light of the findings, and using that refined theory to develop new hypotheses, and so on.

when someone is treated unfairly in their capacity to know something or describe their experience of the world

conducted during the early stages of a project, usually when a researcher wants to test the feasibility of conducting a more extensive study or if the topic has not been studied in the past

research that describes or defines a particular phenomenon

explains why particular phenomena work in the way that they do; answers “why” questions

attempts to explain or describe your phenomenon exhaustively, based on the subjective understandings of your participants

"Assuming that the null hypothesis is true and the study is repeated an infinite number times by drawing random samples from the same populations(s), less than 5% of these results will be more extreme than the current result" (Cassidy et al., 2019, p. 233).

Scientific Inquiry in Social Work (2nd Edition) Copyright © 2020 by Matthew DeCarlo, Cory Cummings, and Kate Agnelli is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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