importance of qualitative research in various fields

The Ultimate Guide to Qualitative Research - Part 1: The Basics

Introduction and overview

Basics of qualitative research

Types, aspects, examples, benefits and challenges, how qualitative research complements quantitative research, how is qualitative research reported.

What is qualitative data?
Examples of qualitative data
Qualitative vs. quantitative research
Mixed methods
Qualitative research preparation
Theoretical perspective
Theoretical framework
Literature reviews
Research question
Conceptual framework
Conceptual vs. theoretical framework
Data collection
Qualitative research methods
Focus groups
Observational research
Case studies
Ethnographical research

Ethical considerations

Confidentiality and privacy
Power dynamics
Reflexivity

What is qualitative research?

Qualitative research is an essential approach in various academic disciplines and professional fields, as it seeks to understand and interpret the meanings, experiences, and social realities of people in their natural settings. This type of research employs an array of qualitative methods to gather and analyze non-numerical data, such as words, images, and behaviors, and aims to generate in-depth and contextualized insights into the phenomena under study.

Qualitative research is designed to address research questions that focus on understanding the "why" and "how" of human behavior, experiences, and interactions, rather than just the "what" or "how many" that quantitative methods typically seek to answer. The main purpose of qualitative research is to gain a rich and nuanced understanding of people's perspectives, emotions, beliefs, and motivations in relation to specific issues, situations, or phenomena.

Characteristics of qualitative research

Several key characteristics distinguish qualitative research from other types of research, such as quantitative research:

Naturalistic settings : Qualitative researchers collect data in the real-world settings where the phenomena of interest occur, rather than in controlled laboratory environments. This allows researchers to observe and understand the participants' behavior, experiences, and social interactions in their natural context.

Inductive approach : Unlike quantitative research, which often follows a deductive approach , qualitative research begins with the collection of data and then seeks to develop theories, concepts, or themes that emerge from the data. This inductive approach enables researchers to stay open to new insights and unexpected findings.

Holistic perspective : Qualitative research aims to provide a comprehensive understanding of the phenomena under study by considering multiple dimensions, such as the social, cultural, historical, and psychological aspects that shape people's experiences and behavior.

Subjectivity and interpretation : Epistemology plays a crucial role in qualitative research. Researchers are encouraged to reflect on their biases, assumptions, and values , and to consider how these may influence their data collection, analysis, and interpretation.

Flexibility : Qualitative research methods are often flexible and adaptable, allowing researchers to refine their research questions , sampling strategies, or data collection techniques as new insights and perspectives emerge during the research process.

Key principles of qualitative research

Qualitative research is guided by several fundamental principles that shape its approach, methods, and analysis:

Empathy and reflexivity : Qualitative researchers strive to empathize with the participants and to understand their perspectives, experiences, and emotions from their viewpoint. This requires researchers to be attentive, open-minded, and sensitive to the participants' verbal and non-verbal cues. At the same, qualitative researchers critically reflect on their participants’ perspectives, experiences, and emotions to develop their findings and conclusions, instead of taking these at face value. In addition, it is important for the researcher to reflect on how their own role and viewpoint may be shaping the research.

Trustworthiness : Establishing trustworthiness in qualitative research involves demonstrating credibility, transferability, dependability, and confirmability. Researchers can enhance trustworthiness by using various strategies, such as triangulation, member checking , peer debriefing , and reflexivity .

Iterative analysis : Qualitative data analysis is an ongoing and iterative process, in which researchers continually review, compare, and revise their interpretations as they collect and analyze more data. This iterative process allows researchers to refine their understanding of the phenomena and to develop more robust and nuanced theories, concepts, or themes.

Rich description : Providing detailed, vivid, and context-sensitive descriptions of the data is essential in qualitative research. Rich descriptions help convey the complexity and nuances of the phenomena under study, and enable readers to assess the relevance and transferability of the findings to other settings or populations.

What are the common types of qualitative research?

Qualitative research is an umbrella term for various methodologies that focus on understanding and interpreting human experiences, behaviors, and social phenomena within their context. These approaches seek to gather in-depth, rich data through the analysis of language, actions, and expressions. Five common types of qualitative research are narrative research , phenomenology , grounded theory , ethnography , and case study .

Narrative research : This approach focuses on the stories and experiences of individuals, aiming to understand their lives and personal perspectives. Researchers can collect data through interviews, letters, diaries, or autobiographies, and analyze these narratives to identify recurring themes, patterns, and meanings . Narrative research can be valuable for exploring individual identities, cultural beliefs, and historical events.

Phenomenology : Phenomenology seeks to understand the essence of a particular phenomenon by analyzing the experiences and perceptions of individuals who have gone through that phenomenon . Researchers can explore participants' thoughts, feelings, and experiences through in-depth interviews, observations, or written materials. The goal is to describe the commonalities and variations in these experiences, ultimately revealing the underlying structures and meaning of the phenomenon under study.

Grounded theory : This inductive research method aims to generate new theories by systematically collecting and analyzing data. Researchers begin with an open-ended research question and gather data through observations, interviews, and document analysis . They then use a process of coding and constant comparison to identify patterns, categories, and relationships in the data. This iterative process continues until a comprehensive, grounded theory emerges that is based in the recollected data and explains the topic of interest.

Ethnography : Ethnographic research involves the in-depth study of a specific cultural or social group, focusing on understanding its members' behaviors, beliefs, and interactions. Researchers immerse themselves in the group's environment, often for extended periods, to observe and participate in daily activities. They can collect data through field notes, interviews, and document analysis, aiming to provide a holistic and nuanced understanding of the group's cultural practices and social dynamics.

Case study : A case study is an in-depth examination of a specific instance, event, organization, or individual within its real-life context. Researchers use multiple sources of data, such as interviews, observations, documents, and artifacts to build a rich, detailed understanding of the case. Case study research can be used to explore complex phenomena, generate new hypotheses , or evaluate the effectiveness of interventions or policies.

What are the purposes of qualitative research?

Qualitative research presents outcomes that emerge from the process of collecting and analyzing qualitative data. These outcomes often involve generating new theories, developing or challenging existing theories, and proposing practical implications based on actionable insights. The products of qualitative research contribute to a deeper understanding of human experiences, social phenomena, and cultural contexts. Qualitative research can also be a powerful complement to quantitative research.

Generating new theory : One of the primary goals of qualitative research is to develop new theories or conceptual frameworks that help explain previously unexplored or poorly understood phenomena. By conducting in-depth investigations and analyzing rich data, researchers can identify patterns, relationships, and underlying structures that form the basis of novel theoretical insights.

Developing or challenging existing theory : Qualitative research can also contribute to the refinement or expansion of existing theories by providing new perspectives, revealing previously unnoticed complexities, or highlighting areas where current theories may be insufficient or inaccurate. By examining the nuances and context-specific details of a phenomenon, researchers can generate evidence that supports, contradicts, or modifies existing theoretical frameworks .

Proposing practical implications : Qualitative research often yields actionable insights that can inform policy, practice, and intervention strategies. By delving into the lived experiences of individuals and communities, researchers can identify factors that contribute to or hinder the effectiveness of certain approaches, uncovering opportunities for improvement or innovation. The insights gained from qualitative research can be used to design targeted interventions, develop context-sensitive policies, or inform the professional practices of practitioners in various fields.

Enhancing understanding and empathy : Qualitative research promotes a deeper understanding of human experiences, emotions, and perspectives, fostering empathy and cultural sensitivity. By engaging with diverse voices and experiences, researchers can develop a more nuanced appreciation of the complexities of human behavior and social dynamics, ultimately contributing to more compassionate and inclusive societies.

Informing mixed-methods research : The products of qualitative research can also be used in conjunction with quantitative research, as part of a mixed-methods approach . Qualitative findings can help generate hypotheses for further testing, inform the development of survey instruments , or provide context and explanation for quantitative results. Combining the strengths of both approaches can lead to more robust and comprehensive understanding of complex research questions .

What are some examples of qualitative research?

Qualitative research can be conducted across various scientific fields, exploring diverse topics and phenomena. Here are six brief descriptions of qualitative studies that can provide researchers with ideas for their own projects:

Exploring the lived experiences of refugees : A phenomenological study could be conducted to investigate the lived experiences and coping strategies of refugees in a specific host country. By conducting in-depth interviews with refugees and analyzing their narratives , researchers can gain insights into the challenges they face, their resilience, and the factors that contribute to successful integration into their new communities.

Understanding the dynamics of online communities : An ethnographic study could be designed to explore the culture and social dynamics of a particular online community or social media platform. By immersing themselves in the virtual environment, researchers can observe patterns of interaction, communication styles, and shared values among community members, providing a nuanced understanding of the factors that influence online behavior and group dynamics.

Examining the impact of gentrification on local communities : A case study could be conducted to explore the impact of gentrification on a specific neighborhood or community. Researchers can collect data through interviews with residents, local business owners, and policymakers, as well as analyzing relevant documents and media coverage. The study can shed light on the effects of gentrification on housing affordability, social cohesion, and cultural identity, informing policy and urban planning decisions.

Studying the career trajectories of women in STEM fields : A narrative research project can be designed to investigate the career experiences and pathways of women in science, technology, engineering, and mathematics (STEM) fields. By collecting and analyzing the stories of women at various career stages, researchers can identify factors that contribute to their success, as well as barriers and challenges they face in male-dominated fields.

Evaluating the effectiveness of a mental health intervention : A qualitative study can be conducted to evaluate the effectiveness of a specific mental health intervention, such as a mindfulness-based program for reducing stress and anxiety. Researchers can gather data through interviews and focus groups with program participants, exploring their experiences, perceived benefits, and suggestions for improvement. The findings can provide valuable insights for refining the intervention and informing future mental health initiatives.

Investigating the role of social media in political activism : A qualitative study using document analysis and visual methods could explore the role of social media in shaping political activism and public opinion during a specific social movement or election campaign. By analyzing user-generated content, such as tweets, posts, images, and videos, researchers can examine patterns of communication, mobilization, and discourse, shedding light on the ways in which social media influences political engagement and democratic processes.

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What are common qualitative research methods?

Qualitative research methods are techniques used to collect, analyze, and interpret data in qualitative studies. These methods prioritize the exploration of meaning, context, and individual experiences. Common qualitative research methods include interviews, focus groups, observations, document analysis, and visual methods.

Interviews : Interviews involve one-on-one conversations between the researcher and the participant. They can be structured, semi-structured, or unstructured, depending on the level of guidance provided by the researcher. Interviews allow for in-depth exploration of participants' experiences, thoughts, and feelings, providing rich and detailed data for analysis.

Focus groups : Focus groups are group discussions facilitated by a researcher, usually consisting of 6-12 participants. They enable researchers to explore participants' collective perspectives, opinions, and experiences in a social setting. Focus groups can generate insights into group dynamics, cultural norms, and shared understandings, as participants interact and respond to each other's viewpoints.

Observations : Observational research involves the systematic collection of data through watching and recording people, events, or behaviors in their natural settings. Researchers can take on different roles, such as participant-observer or non-participant observer, depending on their level of involvement. Observations provide valuable information about context, social interactions, and non-verbal communication, which can help researchers understand the nuances of a particular phenomenon.

Document analysis : Document analysis is the examination of written or visual materials, such as letters, diaries, reports, newspaper articles, photographs, or videos. This method can provide insights into historical or cultural contexts, individual perspectives, and organizational processes. Researchers may use content analysis, discourse analysis, or other analytic techniques to interpret the meaning and significance of these documents.

Visual methods : Visual methods involve the use of visual materials, such as photographs, drawings, or videos, to explore and represent participants' experiences and perspectives. Techniques like photo elicitation, where participants are asked to take or select photographs related to the research topic and discuss their meaning, can encourage reflection and stimulate discussion. Visual methods can be particularly useful in capturing non-verbal information, promoting cross-cultural understanding, and engaging with hard-to-reach populations.

Importance of qualitative research and qualitative data analysis

Qualitative research and qualitative data analysis play a vital role in advancing knowledge, informing policies, and improving practices in various fields, such as education, healthcare, business, and social work. The unique insights and in-depth understanding generated through qualitative research can accomplish a number of goals.

Inform decision-making

Qualitative research helps decision-makers better understand the needs, preferences, and concerns of different stakeholders, such as customers, employees, or community members. This can lead to more effective and tailored policies, programs, or interventions that address real-world challenges.

Enhance innovation

By exploring people's experiences, motivations, and aspirations, qualitative research can uncover new ideas, opportunities, and trends that can drive innovation in products, services, or processes.

Foster empathy and cultural competence

Qualitative research can increase our empathy and understanding of diverse populations, cultures, and contexts. This can enhance our ability to communicate, collaborate, and work effectively with people from different backgrounds.

Complement quantitative research

Qualitative research can complement quantitative research by providing rich contextual information and in-depth insights into the underlying mechanisms, processes, or factors that may explain the patterns or relationships observed in quantitative data.

Facilitate social change

Qualitative research can give voice to marginalized or underrepresented groups, highlight social injustices or inequalities, and inspire actions and reforms that promote social change and well-being.

Challenges of conducting qualitative research

While qualitative research offers valuable insights and understanding of human experiences, it also presents some challenges that researchers must navigate. Acknowledging and addressing these challenges can help ensure the rigor, credibility, and relevance of qualitative research. In this section, we will discuss some common challenges that researchers may encounter when conducting qualitative research and offer suggestions on how to overcome them.

Subjectivity and bias

One of the primary challenges in qualitative research is managing subjectivity and potential biases that may arise from the researcher's personal beliefs, values, and experiences. Since qualitative research relies on the researcher's interpretation of the data , there is a risk that the researcher's subjectivity may influence the findings.

Researchers can minimize the impact of subjectivity and bias by maintaining reflexivity , or ongoing self-awareness and critical reflection on their role, assumptions, and influences in the research process. This may involve keeping a reflexive journal, engaging in peer debriefing , and discussing potential biases with research participants during member checking .

Data collection and quality

Collecting high-quality data in qualitative research can be challenging, particularly when dealing with sensitive topics, hard-to-reach populations, or complex social phenomena. Ensuring the trustworthiness of qualitative data collection is essential to producing credible and meaningful findings.

Researchers can enhance data quality by employing various strategies, such as purposive or theoretical sampling, triangulation of data sources, methods or researchers, and establishing rapport and trust with research participants.

Data analysis and interpretation

The analysis and interpretation of qualitative data can be a complex, time-consuming, and sometimes overwhelming process. Researchers must make sense of large amounts of diverse and unstructured data, while also ensuring the rigor, transparency, and consistency of their analysis.

Researchers can facilitate data analysis and interpretation by adopting systematic and well-established approaches, such as thematic analysis , grounded theory , or content analysis . Utilizing qualitative data analysis software , like ATLAS.ti, can also help manage and analyze data more efficiently and rigorously.

Qualitative research often involves exploring sensitive issues or working with vulnerable populations, which raises various ethical considerations , such as privacy, confidentiality , informed consent , and potential harm to participants.

Researchers should be familiar with the ethical guidelines and requirements of their discipline, institution, or funding agency, and should obtain ethical approval from relevant review boards or committees before conducting the research. Researchers should also maintain open communication with participants, respect their autonomy and dignity, and protect their well-being throughout the research process.

Generalizability and transferability

Qualitative research typically focuses on in-depth exploration of specific cases or contexts, which may limit the generalizability or transferability of the findings to other settings or populations. However, the goal of qualitative research is not to produce statistically generalizable results but rather to provide a rich, contextualized, and nuanced understanding of the phenomena under study.

Researchers can enhance the transferability of their findings by providing rich descriptions of the research context, participants, and methods, and by discussing the potential applicability or relevance of the findings to other settings or populations. Readers can then assess the transferability of the findings based on the similarity of their own context to the one described in the research.

By addressing these challenges and adopting rigorous and transparent research practices, qualitative researchers can contribute valuable and meaningful insights that advance knowledge, inform policies, and improve practices in various fields and contexts.

Qualitative and quantitative research approaches are often seen as distinct and even opposing paradigms. However, these two approaches can be complementary, providing a more comprehensive understanding of complex social phenomena when combined. In this section, we will discuss how qualitative research can complement quantitative research and enhance the overall depth, breadth, and rigor of research findings.

Exploring and understanding context

Quantitative research excels at identifying patterns, trends, and relationships among variables using numerical data, while qualitative research provides rich and nuanced insights into the context, meaning, and underlying processes that shape these patterns or relationships. By integrating qualitative research with quantitative research, researchers can explore not only the "what" or "how many" but also the "why" and "how" of the phenomena under study.

For example, a quantitative study in health services research might reveal a correlation between social media usage and mental health outcomes, while a qualitative study could help explain the reasons behind this correlation by exploring users' experiences, motivations, and perceptions of social media. Qualitative and quantitative data in this case complement each other to contribute to a more robust theory and more informed policy implications.

Generating and refining hypotheses

Qualitative research can inform the development and refinement of hypotheses for quantitative research by identifying new concepts, variables, or relationships that emerge from the data. This can lead to more focused, relevant, and innovative quantitative research questions and hypotheses. For instance, a qualitative study on employee motivation might uncover the importance of meaningful work and supportive relationships with supervisors as key factors influencing motivation. These findings could then be incorporated into a quantitative study to test the relationships between these factors and employee motivation.

Validating and triangulating findings

Combining qualitative and quantitative research methods can enhance the credibility and trustworthiness of research findings through validation and triangulation. Validation involves comparing the findings from different methods to assess their consistency and convergence, while triangulation involves using multiple methods, data sources, or researchers to gain a more comprehensive understanding of the phenomena under study.

For example, a researcher might use both quantitative surveys and qualitative interviews in a mixed methods research design to assess the effectiveness of a health intervention. If both methods yield similar findings, this can increase confidence in the results. If the findings differ, the researcher can further investigate the reasons for these discrepancies and refine their understanding of the intervention's effectiveness.

Enhancing communication and dissemination

Qualitative research can enhance the communication and dissemination of quantitative research findings by providing vivid narratives, case studies, or examples that bring the data to life and make it more accessible and engaging for diverse audiences, such as policymakers, practitioners, or the public.

For example, a quantitative study on the impact of a community-based program might report the percentage of participants who experienced improvements in various outcomes. By adding qualitative data, such as quotes or stories from participants, the researcher can illustrate the human impact of the program and make the findings more compelling and relatable.

In conclusion, qualitative research can complement and enrich quantitative research in various ways, leading to a more comprehensive, contextualized, and rigorous understanding of complex social phenomena. By integrating qualitative and quantitative research methods, researchers can harness the strengths of both approaches to produce more robust, relevant, and impactful findings that inform theory, policy, and practice.

Qualitative research findings are typically reported in various formats, depending on the audience, purpose, and context of the research. Common ways to report qualitative research include dissertations, journal articles, market research reports, and needs assessment reports. Each format has its own structure and emphasis, tailored to meet the expectations and requirements of its target audience.

Dissertations and theses : Doctoral,master's, or bachelor students often conduct qualitative research as part of their dissertation or thesis projects. In this format, researchers provide a comprehensive account of their research questions , methodology, data collection , data analysis , and findings. Dissertations are expected to make a significant contribution to the existing body of knowledge and demonstrate the researcher's mastery of the subject matter.

Journal articles : Researchers frequently disseminate their qualitative research findings through articles published in academic journals . These articles are typically structured in a way that includes an introduction, literature review, methodology, results, and discussion sections. In addition, articles often undergo a peer-review process before being published in the academic journal. Journal articles focus on communicating the study's purpose, methods, and findings in a concise and coherent manner, providing enough detail for other researchers to evaluate the rigor and validity of the research so that they can cite the article and build on it in their own studies.

Market research reports : Market research often employs qualitative methods to gather insights into consumer behavior, preferences, and attitudes. Market research reports present the findings of these studies to clients, typically businesses or organizations interested in understanding their target audience or market trends. These reports focus on providing actionable insights and recommendations based on the qualitative data, helping clients make informed decisions and develop effective marketing strategies.

Needs assessment reports : Needs assessment is a process used to identify gaps or areas of improvement in a specific context, such as healthcare, education, or social services. Qualitative research methods can be used to collect data on the needs, challenges, and experiences of the target population. Needs assessment reports present the findings of this research, highlighting the identified needs and providing recommendations for addressing them. These reports are used by organizations and policymakers to inform the development and implementation of targeted interventions and policies.

Other formats : In addition to the aforementioned formats, qualitative research findings can also be reported in conference presentations, white papers, policy briefs, blog posts, or multimedia presentations. The choice of format depends on the target audience and the intended purpose of the research, as well as the researcher's preferences and resources. Regardless of the format, it is important for researchers to present their findings in a clear, accurate, and engaging manner, ensuring that their work is accessible and relevant to their audience.

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Chapter 1. Introduction

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

Why an Open Access Textbook on Qualitative Research Methods?

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

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

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

What is Research?

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

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

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

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

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

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

What is Qualitative Research?

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

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

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

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

Examples of Qualitative Research

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

Example 1 : The End Game (ethnography + interviews)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

How Is This Book Organized?

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

Chapter Descriptions

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Patton’s Ten Suggestions for Doing Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Qualitative Research: An Overview

First Online: 24 April 2019

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Yanto Chandra 3 &
Liang Shang 4

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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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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Akira Minoura 1 ,
Yuhei Shimada 2 , 3 ,
Keisuke Kuwahara 4 , 5 , 6 ,
Makoto Kondo 7 ,
Hiroko Fukushima 8 , 9 ,
http://orcid.org/0000-0001-5391-682X Takehiro Sugiyama 3 , 10
1 Department of Hygiene, Public Health and Preventive Medicine, Showa University School of Medicine , Shinagawa-ku , Japan
2 Department of Law and Politics , The University of Tokyo , Bunkyo-ku , Japan
3 Diabetes and Metabolism Information Center, Research Institute , National Center for Global Health and Medicine , Shinjuku-ku , Japan
4 Department of Epidemiology and Prevention, Center for Clinical Sciences , National Center for Global Health and Medicine , Shinjuku-ku , Japan
5 Department of Public Health , Yokohama City University School of Medicine , Yokohama , Japan
6 Department of Health Data Science, Graduate School of Data Science , Yokohama City University , Yokohama , Japan
7 Department of Anatomy and Neuroscience, Graduate School of Medicine , Osaka Metropolitan University , Osaka , Japan
8 Department of Pediatrics , University of Tsukuba Hospital , Tsukuba , Japan
9 Department of Child Health, Institute of Medicine , University of Tsukuba , Tsukuba , Japan
10 Department of Health Services Research, Institute of Medicine , University of Tsukuba , Tsukuba , Japan
Correspondence to Dr Takehiro Sugiyama; tsugiyama{at}hosp.ncgm.go.jp

Objectives Japanese medical academia continues to depend on quantitative indicators, contrary to the general trend in research evaluation. To understand this situation better and facilitate discussion, this study aimed to examine how Japanese medical researchers perceive quantitative indicators and qualitative factors of research evaluation and their differences by the researchers’ characteristics.

Design We employed a web-based cross-sectional survey and distributed the self-administered questionnaire to academic society members via the Japanese Association of Medical Sciences.

Participants We received 3139 valid responses representing Japanese medical researchers in any medical research field (basic, clinical and social medicine).

Outcomes The subjective importance of quantitative indicators and qualitative factors in evaluating researchers (eg, the journal impact factor (IF) or the originality of the research topic) was assessed on a four-point scale, with 1 indicating ‘especially important’ and 4 indicating ‘not important’. The attitude towards various opinions in quantitative and qualitative research evaluation (eg, the possibility of research misconduct or susceptibility to unconscious bias) was also evaluated on a four-point scale, ranging from 1, ‘strongly agree’, to 4, ‘completely disagree’.

Results Notably, 67.4% of the medical researchers, particularly men, younger and basic medicine researchers, responded that the journal IF was important in researcher evaluation. Most researchers (88.8%) agreed that some important studies do not get properly evaluated in research evaluation using quantitative indicators. The respondents perceived quantitative indicators as possibly leading to misconduct, especially in basic medicine (strongly agree—basic, 22.7%; clinical, 11.7%; and social, 16.1%). According to the research fields, researchers consider different qualitative factors, such as the originality of the research topic (especially important—basic, 46.2%; social, 39.1%; and clinical, 32.0%) and the contribution to solving clinical and social problems (especially important—basic, 30.4%; clinical, 41.0%; and social, 52.0%), as important. Older researchers tended to believe that qualitative research evaluation was unaffected by unconscious bias.

Conclusion Despite recommendations from the Declaration on Research Assessment and the Leiden Manifesto to de-emphasise quantitative indicators, this study found that Japanese medical researchers have actually tended to prioritise the journal IF and other quantitative indicators based on English-language publications in their research evaluation. Therefore, constantly reviewing the research evaluation methods while respecting the viewpoints of researchers from different research fields, generations and genders is crucial.

MEDICAL EDUCATION & TRAINING
Health policy
GENERAL MEDICINE (see Internal Medicine)

Data availability statement

Data are available upon reasonable request. Data used in the analysis will be made available to researchers upon request, in compliance with ethical guidelines and with the ethics committee’s approval.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2023-079269

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STRENGTHS AND LIMITATIONS OF THIS STUDY

A web-based survey was conducted for Japanese medical researchers in research fields by various medical societies and the Japan Association of Medical Sciences.

The questionnaire was developed through focus group interviews with 22 medical researchers from various backgrounds.

The subjective importance of quantitative indicators and qualitative factors in evaluating researchers, stratified by the respondents’ characteristics, was demonstrated.

The number of responses was limited when compared with the total number of medical researchers in Japan.

The design of a web-based self-administered survey could possibly result in bias.

Introduction

Evaluating research is essential for the continuous advancement of scientific progress nationally and internationally. 1 Although there is no universal definition, research evaluation refers to the assessment of all research project processes, from the planning of a research project to the dissemination of its results and the development of subsequent research areas. 2 Regardless of whether the evaluation is quantitative or qualitative, the research evaluation assesses performance in relation to the research missions or objectives. 3 Although researcher evaluation is also an evaluation of researchers, depending on the evaluation objective, it may include their cumulative research activities and non-research activities such as education, professional practice and administration. 4

However, some quantitative metrics of scientific outputs, such as the number of English-language publications and the number of citations, are considered important in the allocation of funds and the recruitment of researchers at universities. 5 In particular, the journal impact factor (IF), which was originally a measure for journals, not for each paper, has occasionally been used to evaluate the quality of an article or the productivity of a researcher. Actions have been taken to promote responsible research assessment among researchers worldwide as a countermeasure to the trend, symbolised by numerous researchers and organisations signing the Declaration on Research Assessment (DORA), which mainly dissents IF uses for research evaluation. 6 Furthermore, the Leiden Manifesto for Research Metrics alarms the pervasive misapplication not only of IF but also of quantitative indicators in general to the evaluation of scientific performance. 3 Recently, the Science Council of Japan issued a recommendation regarding research evaluation, stating that quantitative assessment methods should not be overemphasised in research evaluation; they hoped to introduce international trends to help Japanese researchers develop appropriate ways to conduct research evaluations. 7

However, the current state of the research evaluation has not yet achieved the stated goal. Indeed, the fourth Medium-Term Plans of National University Corporations, which are required by law to establish Key Performance Indicators to achieve the ministry’s Medium-Term Goals, state that they will measure their performance with a focus on quantitative indicators, including the number of published articles. 8 This is true in the field of medicine; combined with the fierce competition for positions as medical researchers, publishing in journals with high IFs is encouraged regardless of differences in fields. 9 Consequently, this merit-based evaluation, combined with an overcompetitive environment, puts pressure on researchers to publish, potentially making them more susceptible to research misconduct. 10–12

It is important to understand how medical researchers internalise the evaluation axes of their research/researcher and how they interpret the evaluations they receive to address this contentious situation and find a solution. Internationally, in addition to studies aimed at the entire research community, 13–15 some studies investigated medical researchers’ perceptions. 16–19 Similarly, in Japan, researchers’ perspectives on the evaluation system are discussed. 20 21 The problems with current evaluation practices have also been highlighted among domestic medical researchers. 22 23 However, no previous research has measured medical researchers’ perceptions of the evaluation of the research/researcher using a large-scale questionnaire to our knowledge.

This study aims to clarify the perceptions of Japanese researchers in medicine regarding research evaluation and extract the problems they face. We conducted a questionnaire survey among medical researchers in the fields of basic, clinical and social medicine to examine the characteristics and issues in the current evaluation axis of medical researchers and identify the evaluation methods that can be considered in the future. Specifically, the study identifies the current state of how medical research and researchers should be evaluated.

Development of the questionnaire

Figure 1 presents an overview of the survey, and the Method Detail in the online supplemental material describes the details. A team of volunteer junior faculties of the Scientific Committee for the 31st General Assembly of the Japanese Association of Medical Sciences worked on this study. Because the measures on this topic have not been established, we developed a preliminary questionnaire and refined it through focus group interviews (FGIs) with researchers affiliated with member societies of the Japanese Association of Medical Sciences (eg, the Japanese Society of Internal Medicine, the Japan Surgical Society, the Japanese Association of Anatomists and the Japanese Society of Public Health), (non-medical) experts in research evaluation, senior researchers and early career researchers and students. 24 FGIs allowed us to extract opinions on research evaluation across disciplines and careers in the Japanese medical field.

Supplemental material

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Overview of the survey. This study was conducted in two phases: a survey to improve and finalise the questionnaire (based on focus group interviews and receiving comments) and the implementation of our web-based survey. The details are described in the Method Detail in the online supplemental material .

Survey design

After each interview, we reviewed and revised the questionnaire based on the participants’ opinions. Using the revised questionnaire, we conducted a web-based survey of medical researchers. This survey was requested to be announced and distributed to members of medical academic societies through these societies from the Japanese Association of Medical Sciences. However, the survey announcement was voluntary; the method of announcement varied between societies (eg, email newsletter and notification on the society’s website); some societies may not have sent the announcement to their members. The organisation represents the entire Japanese medical research community, ensuring the broadest possible reach to the medical researchers who are the focus of our research. In Japan, in anticipation of the increasing sophistication of medical care and the decrease in the number of medical personnel due to the declining birthrate, the way doctors work will undergo major legal changes in 2024, and medical researchers are becoming increasingly interested in research evaluation. On the survey website, after explaining the present survey, those who did not consent to the study or those whose daily work (ie, work before going on maternity leave and childcare leave) is not related to research were asked to leave the website and therefore excluded. The survey period was from December 14, 2022, to January 17, 2023.

Statistical analyses

The survey involved a self-administered questionnaire to obtain responses on the evaluation’s current status and issues regarding how medical research and researchers were evaluated. In addition to the descriptive statistics, to reveal the difference in local situations, cross-tabulation was calculated stratified by various factors such as age, gender, position and family situation. Other variables indicate the characteristics of the respondents. To efficiently analyse the results, we summarised the characteristics of respondents into fewer classifications. Questionnaires with the same answers to all questions were considered invalid and were excluded. To confirm the robustness of the results of cross-tabulation, we additionally examined the adjusted values. Ordered logistic regression was used to adjust for factors of gender, research field and age and to calculate the predicted percentage of each answer. We excluded the ‘I do not know’ responses in the adjusted analyses. The methods used have been detailed in the online supplemental material . Descriptive analyses were conducted using QuickCross (Macromill, Inc., Minato-ku, Tokyo, Japan), and statistical analyses were conducted using Stata 17.0 (Stata Corp., TX, USA).

Ethical considerations

The study protocol was approved by the Institutional Review Board of the National Centre for Global Health and Medicine (NCGM-S-0 04 530–01).

Patient and public involvement

A total of 3169 researchers answered the questionnaire during the survey period; 386 respondents either did not consent to participate or declined because research activity was not a part of their job. Among the responses, 30 were excluded because they had invalid answers; thus, the analysis included 3139 researchers (2244 men, 852 women and 43 others). The response rate could not be calculated because the number of potential respondents (ie, medical researchers who received the survey announcement) was unknown. Table 1 shows the characteristics of the participants, whereas online supplemental table S1 presents more comprehensive descriptive analyses of the survey answers. By academic rank, professor level (eg, professors, directors of clinical departments or directors of research laboratories) was predominant (n=1213, 38.6%), and by employment status, full-time (tenured) employees were the most common (n=2009, 64.0%). Regarding effort for research, 33.3% (n=1048) of researchers answered that research work accounted for half or more of their work time.

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Characteristics of survey participants

For quantitative indicators in evaluating researchers ( figure 2 for stratified results, online supplemental table S1 Q3-1 for overall results and online supplemental table S3 Q3-1-1, Q3-1-2 and Q3-1-4 for details of stratified results), 67.4% answered that the journal IF was considered important (especially important, n=616, 19.6%; important, n=1501, 47.8%), notably more in basic medicine than in clinical and social medicine, among younger researchers than older researchers and among men than women. Compared with respondents with no medical license, physicians and other healthcare professionals were more likely to respond that IFs are important. The number of papers published in English-language journals was considered more important (especially important, n=1045, 33.3%; important, n=1625, 51.8%) than those published in Japanese-language journals (especially important, n=106, 3.4%; important, n=947, 30.2%). The preference for English-language journals over Japanese-language journals was more pronounced in basic medicine than in clinical and social medicine, in younger researchers (39 years old or lower) than older researchers (60 years old or older) and in men than in women. Online supplemental table S4 shows the results of cross-tabulations stratified by license and education to observe how the effect of education differed by the medical profession. Physicians and dentists with only an MD or doctor of dental surgery and those with a PhD placed more importance on the IF in research evaluation ( online supplemental table S4 Q3-1-4). Quantitative indicators were observed to be valued higher in the order of doctor, master and undergraduate scales for respondents with other medical licenses.

Quantitative indicators in evaluating the surrounding researchers. Each colour represents the percentage of answers. The left, middle and right columns are the cross-tabulation results by research field, age and gender. The exact values are shown in online supplemental table S3 (Q3-1-1, Q3-1-2 and Q3-1-4 for tables stratified research field, age and gender). Note: the terms ‘clinical’, ‘basic‘ and ‘social’ refer to clinical, basic and social medicine. ‘yo’ means ‘years old’

Regarding the qualitative factors in evaluating researchers ( figure 3 for stratified results, online supplemental table S1 Q3-2 for overall results and online supplemental table S3 Q3-2-2, Q3-2-3 and Q3-2-5 for details of stratified results), the originality of the research topic (especially important, n=1159, 37.0%; important, n=1614, 51.5%) and contribution to the advancement of science (especially important, n=1172, 37.4; important, n=1485, 47.4%) were considered more important than the exhaustiveness of analyses (ie, the degree that necessary analyses are thoroughly performed) (especially important, n=392, 12.6%; important, n=1612, 51.6%). The originality of the research topic was considered more important in basic medicine than in clinical and social medicine (especially important—basic, n=321, 46.2%; social, n=223, 39.1%; and clinical, n=541, 32.0%), whereas the contribution to solving clinical and social problems was considered more important in social medicine than in basic and clinical medicine (especially important—basic, n=211, 30.4%; clinical, n=692, 41.0%; and social, n=295, 52.0%).

Qualitative factors in evaluating the surrounding researchers. Each colour represents the percentages of answers. The left, middle and right columns are the cross-tabulation results by research field, age and gender, respectively. The exact values are shown in online supplemental table S3 (Q3-2-2, Q3-2-3 and Q3-2-5 for tables stratified research field, age and gender). Note: the terms ‘clinical’, ‘basic’ and ‘social’ refer to clinical, basic and social medicine. ‘yo’ means ‘years old’.

Figure 4 illustrates the researchers’ perceptions of quantitative indicators and qualitative factors for research evaluation. Most researchers (88.8%) agreed that some important studies do not get properly evaluated in research evaluation using quantitative indicators, especially in basic and social medicine, among the 40–49 age group and men. The use of quantitative indicators was perceived to possibly lead to misconduct for researchers in basic medicine compared with those in clinical and social medicine (strongly agree—basic: 22.7%, clinical: 11.7%, social: 16.1%). Older researchers tended to consider that qualitative research evaluation was not affected by unconscious bias compared with younger researchers. Furthermore, online supplemental table S3 stratified by academic rank (Q3-4-8, Q3-5-2) revealed that respondents at the professor level were less likely to believe that focusing on quantitative indicators would lead to underestimation of non-research activities (eg, education, clinical practice and social activities) and were unaware of susceptibility of qualitative evaluation to biases caused by interpersonal relationships or unconscious biases.

Researchers’ perceptions of quantitative indicators and qualitative factors for research evaluation. Each colour represents the percentages of answers. The left, middle and right columns are the cross-tabulation results by research field, age and gender, respectively. The exact values are shown in online supplemental table S3 (Q3-4-5Q-4-7and Q-5-2 for tables stratified research field, age and gender). Note: the terms ‘clinical’, ‘basic’ and ‘social’ refer to clinical, basic and social medicine. ‘yo’ means ‘years old’.

Online supplemental table S5 shows the proportion for each choice, adjusted for gender, research field and age category, using ordered logistic regression analysis. These tables suggest that the main results shown in figures 2–4 were not explained solely by confounding.

Regarding DORA recognition, only 10.1% of the respondents knew its contents, whereas 28.8% knew the name but not the contents ( online supplemental table S1 Q4-3). In other words, 61.1% were unfamiliar with the name DORA. Given that DORA recognition represents evaluation knowledge, this variable’s stratified results can be interpreted as the effect of evaluation literacy. Researchers who recognised the DORA tended to place slightly less emphasis on the importance of the IF ( online supplemental table S3 stratified by research evaluation literacy Q3-1-4). Among them, those who knew its contents were likely to value the qualitative factors such as the originality of the topic or methodology (Q3-2-1 and Q3-2-2), contribution to the advancement of science (Q3-2-3) and contribution to clinical and social problem-solving (Q3-2-4). Furthermore, they also agreed that some important studies do not get properly evaluated by quantitative indicators (Q3-4-5), quantitative indicators may lead to research misconduct (Q3-4-7), and the validity of the qualitative evaluator’s (ie, reviewer’s) assessments should be evaluated (Q3-5-4).

We obtained a total of 645 responses for open-ended inquiries. We classified these responses into seven categories. Out of the 232 survey responses, 37 recommended public reporting of results, 34 suggested incorporating results into policy, 77 highlighted survey problems and criticisms, and 91 expressed positive attitudes towards the survey. The responses that mentioned activities other than work research (n=84) included education, clinical practice, social activities, administrative work and peer review. We also received responses regarding institutional-environmental conditions for research evaluation (n=77), and problems were identified, such as differences in fields, evaluators’ abilities and the amount of available financial and human resources. Regarding the nature of the indicators (n=69), opinions were divided into two groups: 32 criticised and 26 supported the quantitative indicators. Online supplemental table S6 contains additional categories (activities outside of work (n=11), structural conflicts between valuable research and evaluation (n=11) and evaluation fatigue (n=7)), subcategories and examples.

Summary findings

The web-based survey yielded two major findings. First, it was discovered that the majority of medical researchers in Japan, particularly those in basic medicine, young researchers and men, believe that IF and other quantitative indicators based on English publications are appropriate for assessing researchers. Second, medical researchers’ perceptions of quantitative and qualitative indicators in evaluating medical research and researchers varied depending on the participants’ characteristics, such as research field, age and gender. When evaluating researchers, basic medicine researchers were more likely to consider the number of articles published in English-language journals, the journal’s IF and the originality of the research topic. Meanwhile, more social medicine researchers than other medical researchers believed that the number of articles published in Japanese-language journals and the contribution to the resolution of clinical and social problems were important. To our knowledge, this is the first study to clarify perceptions of research/researcher evaluation among medical researchers in Japan.

Reliance on quantitative indicators derived from English-language publications

The general tendency to emphasise IF across disciplines deviates significantly from the DORA, while it recommends against using IFs for research evaluation. Not only IF but also other quantitative indicators based on English-language publications were also regarded as significant factors for evaluation, which was the situation the Leiden Manifesto is concerned with. This result was widely observed among respondents, as 67.4% placed importance on the IF and 85.1% placed importance on the number of English-language journals ( online supplemental table S3 Q3-1). It demonstrates that metrics play an important role in the evaluation system among the Japanese medical research communities as a whole. To advance current evaluation practices, we must approach the entire medical community rather than a specific group. Although many researchers or research institutes in Japan use IF as a metric for study importance or for a researcher’s productivity (eg, by adding the IFs of the journals in which they published papers), it should be noted that the IF was originally designed to measure the influence of a scientific journal, rather than the quality of the research or the researchers. 5

In addition to the general over-reliance on these metrics, there are attribute-specific trends in the preference for quantitative measures. Younger researchers were likely to refer to IF and other quantitative indicators based on English-language publications, perhaps because many hold fiercely competitive positions; they tended to internalise the widely used evaluation metrics. This tendency to place importance on the evaluation axes in the form of published papers is possibly compatible with the study’s results; among the qualitative factors for evaluating researchers, the exhaustiveness of analyses was rated lower than the originality of the research topic and contribution to the advancement of science. This may be due in part to the requirement to present through the medium of a paper that demands conciseness rather than exhaustiveness. 25 The importance of IF in research evaluation was not significantly affected by knowledge of DORA. However, it was linked to higher rates in qualitative factors such as research topic originality. As only 10% of participants claimed to be familiar with DORA and its contents, advocating for and supporting these activities and statements may influence perceptions of research evaluation.

Variety of research evaluation axis by attributes

Remarkably, the evaluation axes differed among research fields, age groups, genders and other subcategories. Researchers of basic medicine tend to rate IFs and the number of papers published in English-language journals higher and the number of papers in Japanese-language journals lower. This may be because the research product in basic medicine is often applicable in any country; thus, it is reasonable to publish information in English. In addition, basic medicine is more susceptible to funding shortages due to maintenance cost for laboratory equipment so that researchers in this field may need to generate well-evaluated outputs. However, this may not be the case in clinical and social medicine; the main readers of their research products may also be clinicians or policymakers who may not be well versed in English. 26 Clinical and social medicine, in contrast to basic medicine, sometimes focus on the domestic context, which is separate from international journals. 23 Furthermore, researchers in clinical or social medicine are expected to engage in a variety of tasks in addition to writing papers in English (eg, clinical practice, guideline development and social practice). Therefore, it is not easy to establish a universal evaluation axis across research fields.

Furthermore, the difference in perception by age and academic rank may partly represent the contrast between evaluators and those who are evaluated. For example, while older and professor-level researchers placed less importance on quantitative indicators, they tended to be unaware of the risk of unconscious biases derived from qualitative evaluation. Although senior researchers frequently evaluate junior researchers and therefore have the authority to determine evaluation axes, discussions about research evaluation between age groups can foster mutual understanding and enhance young researchers’ capacity and responsibility to take on future research fields. 27 28

Mild differences were also observed by gender, such as women placing less emphasis on IF than men, which persisted after adjustment for covariates; thus, gender diversity should be considered when discussing research evaluation. Meanwhile, the low number of women in management positions 29 and difficulties in maintaining work-life balance, which is expected to improve in the near future, may have contributed to reducing the observed differences based on gender in these results. Regarding profession and education, respondents with medical license generally tended to respond IFs are important; it is interesting that the effect of graduate education was heterogeneous between physician/dentist and other medical professionals.

Implication of the study for further consensus

This study did not set out to find a new indicator for research evaluation. Although we found that the situation in Japan differs from what the DORA and the Leiden Manifesto aim for, many researchers may become unsure which evaluation axis to use and require alternative research evaluation axes to rely on.

One possible solution is to develop more reliable evaluation criteria. In fact, "field weighted citation impact (FWCI)" and "top 10% of highly cited papers" compensate for differences in disciplines better than the (unadjusted) journal IF. 30 31 This may help alleviate differences between disciplines, such as basic, clinical and social medicine. The H-index takes into account both the number and impact of articles written by a researcher. 32 Additionally, advanced metrics known as altmetrics, which measure social impact, are being developed. In the age of open-access journals and social networking services, efforts to establish metrics for medical research evaluation should continue. However, it is difficult to develop a definitive metric. For example, the FWCI or top 10% of highly cited papers cannot fully account for the differences between research fields; citations may not be the best indicator of impact in some fields. The H-index, which is influenced by the researcher’s academic age and research field, should be used with caution. Actually, its excessive use was questioned by scientometricians and resulted in the publication of the Leiden Manifesto. 3 33 Moreover, the development of a definitive metric does not imply that we can stop thinking about it, because once a metric is established, it becomes self-objective, undermining efforts towards overall optimisation.

Rather than looking for better metrics, we must accept the limitations of quantitative indicators and share the understanding that quantitative indicators should only be used in conjunction with qualitative evaluation. Even though it is difficult to evaluate research/researcher solely in qualitative manner as academic disciplines get specialised and subdivided, it is important to conduct the research/researcher evaluation based on a deeper qualitative assessment in a balanced manner. 3 6 One of the limitations of qualitative evaluation is its time-consuming nature. It is advantageous to reach an agreement on the importance of this time-consuming process and to shorten the time required for qualitative evaluation. Another limitation is the transparency of the assessment’s basis. It is desirable to reconsider which aspects of research/researcher should be valued, namely, the research/researcher’s mission, within each community or organisation, as well as to clarify the evaluation objective. 3 34

Strengths and limitations

This study conducted a nationwide survey with the assistance of the Japanese Association of Medical Sciences. It serves as the umbrella organisation for all medical academic societies in Japan. This design allowed us to reach our target population (ie, medical researchers in Japan) as much as possible. Finally, we received 3139 valid responses from medical researchers in Japan, which improved the analysis’s robustness.

The study’s limitations include the use of a self-administered web-based survey. Furthermore, although the present sample of over 3000 responses produced robust results, the survey was only completed by a subset of medical researchers. Those who are initially interested in research evaluation are more likely to complete the survey, which may lead to bias in the results. The respondents’ gender imbalance was obvious, and it appeared to reflect the basic gender gap that exists among Japanese doctors and medical researchers, 29 35 which we and others regard as a problem in and of itself. 36 37 Despite sampling limitations, this study is the first to examine how medical researchers perceive the evaluation of research and researchers nationwide in Japan. This study’s results are expected to improve researchers’ evaluation methods and, in turn, their research performance.

The primary analyses (shown in figures 2–4 ) focused on stratification by age groups, gender and research fields that were three characteristic variables out of eight listed in Table 1. Meanwhile, cross-tabulation results for all variables were described in online supplemental table S3 . Future studies should explore the relationships between these variables in greater depth. For example, the effect of academic rank and age cannot be completely separated.

Conclusions

Although most medical researchers in Japan refer to IF and other quantitative indicators based on English paper publications for evaluating researchers, the ideal evaluation axes differ across research fields, generations and genders. We believe it is important to assess research evaluations and constantly review whether there is room for improvement while respecting different ideas from every research field, generation and gender.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by the Institutional Review Board of the National Center for Global Health and Medicine (NCGM-S-004530-01), and the study protocol was approved on 9 December 2022. Participants gave informed consent to participate in the study before taking part.

Acknowledgments

The authors appreciate the interview and survey respondents’ time and effort. For their unwavering support of the research, the authors thank the members of the committee of junior faculties (U40 Committee) of the Scientific Committee and executive members of the 31st General Assembly of the Japanese Association of Medical Sciences. The authors appreciate the questionnaire’s review and distribution by committee members of the Japanese Association of Medical Sciences and the Japanese Association of Medical Sciences Coalitions. The authors are grateful to the members of the Young Academy of Japan and the Science Council of Japan for several productive discussions. The authors also thank Dr Kenjiro Imai, Dr Noriko Ihana-Sugiyama and Ms Akiko Kimura-Wakui for supporting project administration. The authors extend their gratitude to Dr Takahiro Higashi, Dr. Yoshiharu Fukuda and Dr Hideaki Shiroyama for their insightful advice. Finally, the authors appreciate the assistance provided by Dr Kenkichi Takase, Dr Amane Koizumi and Dr Kazuhiro Hayashi throughout the research.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Data supplement 1

Contributors Conceptualisation: AM, KK, MK, HF, TS. Methodology: AM, YS, KK, MK, HF, TS. Investigation: AM, YS, KK, MK, HF, TS. Visualisation: AM, YS, KK, MK, HF, TS. Funding acquisition: AM, KK, MK, HF, TS. Project administration: AM, TS. Supervision: TS. Writing – original draft: AM, YS, TS. Writing – review and editing: AM, YS, KK, MK, HF, TS. All authors have conducted the following: (1) substantial contributions to the conception or design of the work or the acquisition, analysis or interpretation of data for the work; (2) drafting the work or reviewing it critically for important intellectual content; (3) final approval of the version to be published; and (4) agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

TS is the guarantor of this work and, as such, has full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Funding This work was supported by the 53rd Kurata Grants (the Hitachi Global Foundation) in Humanities and Social Sciences 'Reconsideration of evaluation criteria for medical research and researchers aiming for better medical care from the standpoint of young medical researchers' (No. 1523).

Competing interests None declared.

Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Data Visulization Techniques for Qualitative Research

Data visualization techniques play a crucial role in qualitative research by helping researchers explore and communicate patterns, relationships, and insights within their data. Here are some effective techniques commonly used in qualitative research. Qualitative data, conveyed through narratives, descriptions, and quotations, differs significantly from quantitative numerical data, necessitating distinct display strategies. The richness of qualitative data lies in its contextual nuances, which must be preserved in visual representations to accurately reflect underlying meanings and relationships. However, this depth of information poses a challenge in maintaining clarity and insightfulness in visualizations. Unlike standardized quantitative data, qualitative data is unstructured and varied, making it challenging to produce consistent and informative visual representations. To fully comprehend complex events, qualitative research employs an exploratory and interpretive methodology.

In this post, we will look into some Data Visualization Techniques to present Qualitative data.

Table of Content

Different Types of Techniques for Visualizing Qualitative Data

1. word clouds, 2. text networks, 3. heatmaps, 4. chronology charts, 5. mind maps and concept maps, 6. flow charts, 7. narrative visualizations, importance of data visualization in qualitative research, best practices for visualizing qualitative data, data visualization techniques for qualitative research- faqs.

Qualitative data lends itself especially well to the following visualization techniques:

Word frequency determines the size and prominence of words in a word cloud, which is a visual representation of text data. They provide a brief synopsis of important ideas and terms and may be particularly helpful for huge datasets, such as social media analysis or open-ended survey replies.

Identifying key themes or topics in qualitative data.
Visualizing the frequency of words or concepts within a text corpus.
Highlighting prominent terms in interviews, surveys, or open-ended responses.

Revealing relationships between words or concepts in textual data.
They support the identification of connections, overarching themes, and conceptual co-occurrences in the data.
Text networks are useful for investigating semantic structures and may be used to the creation of theories or the comprehension of intricate connections.

Within a matrix, data values are represented by color changes in heatmaps. They are used in qualitative research to illustrate the prevalence of certain themes or codes among various variables or time periods. Heatmaps provide a concise visual synopsis that facilitates the identification of noteworthy regions or unforeseen outcomes.

Identifying patterns or clusters in qualitative data.
Visualizing the intensity or density of themes or concepts across multiple dimensions.
Highlighting areas of interest or divergence within a dataset.

Chronology charts are a great tool for showing how themes or ideas change over time, particularly in studies that follow a subject across time or when examining how an idea or phenomena develops.

Illustrating the chronological order of events, actions, or developments.
Visualizing temporal patterns, trends, or changes over time.
Analyzing the sequence of activities or decision-making processes.

Organizing and structuring complex qualitative data into hierarchical frameworks.
Visualizing relationships between concepts, ideas, or components of a system.
Brainstorming ideas, exploring connections, and generating new insights.

Flow charts are an effective tool in data visualization approaches for qualitative research. They provide a visual depiction of processes, workflows, and linkages, making complicated information more accessible and understandable. Flow charts assits in depicting phases of the research process, from data collection to analysis.

They are used to map narrative structures, demonstrating how tales or events are related within the data visualizing the sequence of steps or stages in a workflow.

Helpful in clarifying complex systems or pathways in a visual format.

Flowcharts-(especially-for-processes-or-decision-trees)-copy-2

Narrative visualizations are effective data visualization strategies for qualitative research. They blend narrative elements with visual data representation to communicate ideas and conclusions in an engaging and intelligible way. Narrative visualizations lead the audience through the data, offering context, emphasizing key results, and making difficult material more understandable. This strategy is especially useful in qualitative research, where data is often composed of textual material, interviews, and observational notes.

Narrative visualizations enhance understanding by presenting complicated qualitative by:

Combining text, visuals, and multimedia elements to engage audiences.
Exploring complex qualitative insights through interactive storytelling.
Narrative visualizations help to communicate qualitative results to a larger audience, including non-experts.

For several reasons, data visualization is essential in qualitative research:

Improved Communication : Compared to text alone, visualization is a more effective tool for explaining complicated concepts and connections. Graphs, charts, and diagrams may help make complex relationships easier to understand for a wider range of people, including those with different degrees of subject matter experience.
Promote Insights : Patterns and trends that would otherwise go undetected in raw qualitative data can be made visible via the use of visual representations of data. With the comprehensive perspective that visualizations provide, researchers may more easily spot relationships, anomalies, and patterns.
Engage Audiences : Stylish, well-thought-out images have the power to pique the attention of both the general audience and stakeholders. This interaction promotes further investigation and conversation as well as a better comprehension of the study results.
Memorability : People tend to remember images better than words. The possibility that important ideas will be remembered and maintained by the audience is increased when study results are presented graphically.
Assist in Decision-Making : By offering a concise summary of the study findings, visual data representations help in well-informed decision-making. For stakeholders and policymakers who must analyze and act upon study findings, this is very helpful.

In order to guarantee the efficient and accurate representation of qualitative data, consider below recommended practices:

Clarity and Simplicity: To make the message understandable and obvious, aim for simplicity in your visualizations. Refrain from overcomplication, since it might overshadow the main points.
Preserve Context: Make sure the original data’s richness and context are preserved in the display. Avoid simplifying things too much. Where needed, use more language or notes to help explain.
Effective Use of Color : While color may improve understanding, too much of it or the wrong kind of color can take away from the content. Use color deliberately and consistently to draw attention to connections or patterns.
Label and Annotate : To aid viewers in understanding, provide relevant labels, titles, and annotations. Make sure the main points can be understood even in the absence of more explanation and that the visuals are self-explanatory.
To achieve a unified and polished appearance, keep design components, typefaces, and color schemes consistent throughout visualizations. Maintaining consistency improves the overall visual appeal and facilitates comparisons.
Investigate Several Representations : Try out several visualization strategies to see which one best suits your data. Instead of depending on just pre-made chart types, think about creating custom visualizations that are suited to your particular dataset.

For qualitative researchers, data visualization is an invaluable tool that helps them make sense of complicated, rich data and detect patterns as well as explain results. Researchers are able to adequately portray and study the intricacies and complexity of human experiences, actions, and views by using suitable approaches, best practices, and developing technology. Data visualization will play a more and more important role in supporting comprehension, teamwork, and powerful narrative as qualitative research develops.

Which data visualization trends are we seeing emerge for qualitative research?

Immersion and interactive visualizations, automated visualization generation, multimodal and multimedia visualizations, collaborative and participatory visualizations, integration with mixed methods research, explainable AI and interpretable visualizations, and the democratization of visualization tools are some of the emerging trends in visualization.

How can academics make sure that data visualization techniques are morally and responsibly done?

Informed permission should be obtained, participant privacy and confidentiality should be given top priority, interpretive integrity should be maintained, biased or misleading visualizations should be avoided, cultural sensitivity should be taken into account, and accessible visualizations should be created.

What abilities are required for qualitative research data visualization that works?

Understanding qualitative research techniques, interpreting and analyzing data, visual communication and design concepts, developing narratives and stories, and being proficient with pertinent visualization tools and technologies are all crucial abilities.

How might intricate qualitative data be made simpler for efficient visualization?

In order to simplify complicated qualitative data, one must concentrate on the most important linkages and insights found in the data. Decide which quotations, themes, or patterns best capture the main idea of your study. Make use of visuals like word clouds, bar charts, or mind maps that provide a clear and succinct summary. To make sure your target audience can comprehend and use the visualization, think about adding further information or comments.

What typical mistakes should one avoid when putting qualitative data into a visual format?

Oversimplification, data distortion or misrepresentation, and context-free presentation are some common mistakes to avoid. Make sure the intricacy and subtleties of the original data are preserved in your representations. Keep ethical issues in mind, particularly those pertaining to participant privacy and informed permission. Furthermore, stay away from using improper or very complicated graphics that might mislead or confuse your viewers. Make your visual representations accurate, simple, and clear.

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Evaluating Local Government Policy Innovations

A case study of surabaya's efforts in combating stunting and enhancing public health services quality.

Deasy Arieffiani Public Administration Department, Hang Tuah University, Surabaya, Indonesia
Mas Roro Lilik Ekowanti Public Administration Department, Hang Tuah University, Surabaya, Indonesia

This research aims to evaluate regional innovations in implementing Surabaya City government policies to reduce stunting rates and improve the quality of public health services. A qualitative descriptive method was used with a case study approach involving field observations and structured interviews. The research results show the success of Posyandu Prima in reducing stunting rates significantly in the last two years. The Surabaya City Government has proven effective in managing this program's human resources and budget. The active involvement of Great Surabaya Cadres (KSH) and non-governmental organizations also contributed greatly to the program's success. Cross-sector collaboration plays an important role in supporting implementation. Institutional characteristics, such as commitment to public health and ability to collaborate, also matter. Theoretically, this research shows that synergy between the parties involved and government commitment can achieve significant results in handling the stunting problem. In conclusion, the Prima Posyandu Program has proven successful in reducing stunting rates and improving the quality of public health services in Surabaya. Additionally, the collaborative efforts between community stakeholders, healthcare providers, and governmental bodies underscore the crucial role of multi-sectoral partnerships in addressing complex public health issues like stunting. This synergy fosters comprehensive approaches that combine local knowledge, resources, and policy support to effectively combat stunting and enhance the well-being of communities. Thus, the Prima Posyandu Program's success is a compelling example of how concerted action and sustained commitment can yield tangible improvements in population health outcomes.

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Facility for Rare Isotope Beams

At michigan state university, international research team uses wavefunction matching to solve quantum many-body problems, new approach makes calculations with realistic interactions possible.

FRIB researchers are part of an international research team solving challenging computational problems in quantum physics using a new method called wavefunction matching. The new approach has applications to fields such as nuclear physics, where it is enabling theoretical calculations of atomic nuclei that were previously not possible. The details are published in Nature (“Wavefunction matching for solving quantum many-body problems”) .

Ab initio methods and their computational challenges

An ab initio method describes a complex system by starting from a description of its elementary components and their interactions. For the case of nuclear physics, the elementary components are protons and neutrons. Some key questions that ab initio calculations can help address are the binding energies and properties of atomic nuclei not yet observed and linking nuclear structure to the underlying interactions among protons and neutrons.

Yet, some ab initio methods struggle to produce reliable calculations for systems with complex interactions. One such method is quantum Monte Carlo simulations. In quantum Monte Carlo simulations, quantities are computed using random or stochastic processes. While quantum Monte Carlo simulations can be efficient and powerful, they have a significant weakness: the sign problem. The sign problem develops when positive and negative weight contributions cancel each other out. This cancellation results in inaccurate final predictions. It is often the case that quantum Monte Carlo simulations can be performed for an approximate or simplified interaction, but the corresponding simulations for realistic interactions produce severe sign problems and are therefore not possible.

Using ‘plastic surgery’ to make calculations possible

The new wavefunction-matching approach is designed to solve such computational problems. The research team—from Gaziantep Islam Science and Technology University in Turkey; University of Bonn, Ruhr University Bochum, and Forschungszentrum Jülich in Germany; Institute for Basic Science in South Korea; South China Normal University, Sun Yat-Sen University, and Graduate School of China Academy of Engineering Physics in China; Tbilisi State University in Georgia; CEA Paris-Saclay and Université Paris-Saclay in France; and Mississippi State University and the Facility for Rare Isotope Beams (FRIB) at Michigan State University (MSU)—includes Dean Lee , professor of physics at FRIB and in MSU’s Department of Physics and Astronomy and head of the Theoretical Nuclear Science department at FRIB, and Yuan-Zhuo Ma , postdoctoral research associate at FRIB.

“We are often faced with the situation that we can perform calculations using a simple approximate interaction, but realistic high-fidelity interactions cause severe computational problems,” said Lee. “Wavefunction matching solves this problem by doing plastic surgery. It removes the short-distance part of the high-fidelity interaction, and replaces it with the short-distance part of an easily computable interaction.”

This transformation is done in a way that preserves all of the important properties of the original realistic interaction. Since the new wavefunctions look similar to that of the easily computable interaction, researchers can now perform calculations using the easily computable interaction and apply a standard procedure for handling small corrections called perturbation theory. A team effort

The research team applied this new method to lattice quantum Monte Carlo simulations for light nuclei, medium-mass nuclei, neutron matter, and nuclear matter. Using precise ab initio calculations, the results closely matched real-world data on nuclear properties such as size, structure, and binding energies. Calculations that were once impossible due to the sign problem can now be performed using wavefunction matching.

“It is a fantastic project and an excellent opportunity to work with the brightest nuclear scientist s in FRIB and around the globe,” said Ma. “As a theorist , I'm also very excited about programming and conducting research on the world's most powerful exascale supercomputers, such as Frontier , which allows us to implement wavefunction matching to explore the mysteries of nuclear physics.”

While the research team focused solely on quantum Monte Carlo simulations, wavefunction matching should be useful for many different ab initio approaches, including both classical and quantum computing calculations. The researchers at FRIB worked with collaborators at institutions in China, France, Germany, South Korea, Turkey, and United States.

“The work is the culmination of effort over many years to handle the computational problems associated with realistic high-fidelity nuclear interactions,” said Lee. “It is very satisfying to see that the computational problems are cleanly resolved with this new approach. We are grateful to all of the collaboration members who contributed to this project, in particular, the lead author, Serdar Elhatisari.”

This material is based upon work supported by the U.S. Department of Energy, the U.S. National Science Foundation, the German Research Foundation, the National Natural Science Foundation of China, the Chinese Academy of Sciences President’s International Fellowship Initiative, Volkswagen Stiftung, the European Research Council, the Scientific and Technological Research Council of Turkey, the National Natural Science Foundation of China, the National Security Academic Fund, the Rare Isotope Science Project of the Institute for Basic Science, the National Research Foundation of Korea, the Institute for Basic Science, and the Espace de Structure et de réactions Nucléaires Théorique.

Michigan State University operates the Facility for Rare Isotope Beams (FRIB) as a user facility for the U.S. Department of Energy Office of Science (DOE-SC), supporting the mission of the DOE-SC Office of Nuclear Physics. Hosting what is designed to be the most powerful heavy-ion accelerator, FRIB enables scientists to make discoveries about the properties of rare isotopes in order to better understand the physics of nuclei, nuclear astrophysics, fundamental interactions, and applications for society, including in medicine, homeland security, and industry.

The U.S. Department of Energy Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of today’s most pressing challenges. For more information, visit energy.gov/science.

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What is Qualitative in Qualitative Research

Patrik aspers.

1 Department of Sociology, Uppsala University, Uppsala, Sweden

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

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

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

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

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

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

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

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

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

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

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

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

Towards a Definition of Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Analysis – What is Qualitative Research?

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

Qualitative and Quantitative

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

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

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

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

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

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

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

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

Qualitative Research

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

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

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

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

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

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

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

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

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

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

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

Grounded Theory

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

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

Defining Qualitative Research

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

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

Distinctions

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

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

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

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

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

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

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

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

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

Improved Understanding

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

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

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

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

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

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

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

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

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

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

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

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

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

Acknowledgements

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

Biographies

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

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

Publisher’s Note

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

Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Importance of Qualitative Research Across Different Fields
Importance of Qualitative Research Across Different Fields
Understanding Qualitative Research: An In-Depth Study Guide
The Importance of Qualitative Research Across Fields of Inquiry
Importance of Qualitative Research Across Different Fields
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The Importance of Quantitative Research Across Fields || Practical Research 2 || Quarter 1/3 Week 2
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LESSON: THE IMPORTANCE OF QUALITATIVE RESEARCH ACCROSS FIELDS OF INQUIRY
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Qualitative Research in Healthcare: Necessity and Characteristics
Quantitative and qualitative research explore various social phenomena using different methods. However, there has been a tendency to treat quantitative studies using complicated statistical techniques as more scientific and superior, whereas relatively few qualitative studies have been conducted in the medical and healthcare fields.
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While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
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The Ultimate Guide to Qualitative Research - Part 1: The Basics

Basics of qualitative research

Ethical considerations

What is qualitative research?

Characteristics of qualitative research

Key principles of qualitative research

What are the common types of qualitative research?

What are the purposes of qualitative research?

What are some examples of qualitative research?

Whatever your research topic may be, ATLAS.ti makes it happen

What are common qualitative research methods?

Importance of qualitative research and qualitative data analysis

Inform decision-making

Enhance innovation

Foster empathy and cultural competence

Complement quantitative research

Facilitate social change

Challenges of conducting qualitative research

Subjectivity and bias

Data collection and quality

Data analysis and interpretation

Generalizability and transferability

Exploring and understanding context

Generating and refining hypotheses

Validating and triangulating findings

Enhancing communication and dissemination

Analyze qualitative data with ATLAS.ti

Chapter 1. Introduction

Why an Open Access Textbook on Qualitative Research Methods?

What is Research?

What is Qualitative Research?

Examples of Qualitative Research

Example 1 : The End Game (ethnography + interviews)

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

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

How Is This Book Organized?

Chapter Descriptions

Recommended Reading: Other Qualitative Research Textbooks

Patton’s Ten Suggestions for Doing Qualitative Research

Qualitative Research: An Overview

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Qualitative Research – Methods, Analysis Types and Guide

Qualitative Research

Qualitative Research Methods

One-to-One Interview

Focus Groups

Ethnographic Studies

Text Analysis

Process of Observation

Record Keeping

Qualitative Research Analysis Methods

Thematic Analysis

Content Analysis

Discourse Analysis

Grounded Theory Analysis

Narrative Analysis

Phenomenological Analysis

Comparative Analysis

Applications of Qualitative Research

How to Conduct Qualitative Research

Examples of Qualitative Research

Purpose of Qualitative Research

When to use Qualitative Research

Characteristics of Qualitative Research

Advantages of Qualitative Research

Limitations of Qualitative Research

About the author

Muhammad Hassan

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