qualitative research is interpretive which involves

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31 Interpretation In Qualitative Research: What, Why, How

Allen Trent, College of Education, University of Wyoming

Jeasik Cho, Department of Educational Studies, University of Wyoming

• Published: 02 September 2020
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This chapter addresses a wide range of concepts related to interpretation in qualitative research, examines the meaning and importance of interpretation in qualitative inquiry, and explores the ways methodology, data, and the self/researcher as instrument interact and impact interpretive processes. Additionally, the chapter presents a series of strategies for qualitative researchers engaged in the process of interpretation and closes by presenting a framework for qualitative researchers designed to inform their interpretations. The framework includes attention to the key qualitative research concepts transparency, reflexivity, analysis, validity, evidence, and literature. Four questions frame the chapter: What is interpretation, and why are interpretive strategies important in qualitative research? How do methodology, data, and the researcher/self impact interpretation in qualitative research? How do qualitative researchers engage in the process of interpretation? And, in what ways can a framework for interpretation strategies support qualitative researchers across multiple methodologies and paradigms?

“ All human knowledge takes the form of interpretation.” In this seemingly simple statement, the late German philosopher Walter Benjamin asserted that all knowledge is mediated and constructed. In doing so, he situates himself as an interpretivist, one who believes that human subjectivity, individuals’ characteristics, feelings, opinions, and experiential backgrounds impact observations, analysis of these observations, and resultant knowledge/truth constructions. Hammersley ( 2013 ) noted,

People—unlike atoms … actively interpret or make sense of their environment and of themselves; the ways in which they do this are shaped by the particular cultures in which they live; and these distinctive cultural orientations will strongly influence not only what they believe but also what they do. (p. 26)

Contrast this perspective with positivist claims that knowledge is based exclusively on external facts, objectively observed and recorded. Interpretivists, then, acknowledge that if positivistic notions of knowledge and truth are inadequate to explain social phenomena, then positivist, hard science approaches to research (i.e., the scientific method and its variants) are also inadequate and can even have a detrimental impact. According to Polyani (1967), “The ideal of exact science would turn out to be fundamentally misleading and possibly a source of devastating fallacies” (as cited in Packer, 2018 , p. 71). So, although the literature often contrasts quantitative and qualitative research as largely a difference in kinds of data employed (numerical vs. linguistic), instead, the primary differentiation is in the foundational, paradigmatic assumptions about truth, knowledge, and objectivity.

This chapter is about interpretation and the strategies that qualitative researchers use to interpret a wide variety of “texts.” Knowledge, we assert, is constructed, both individually (constructivism) and socially (constructionism). We accept this as our starting point. Our aim here is to share our perspective on a broad set of concepts associated with the interpretive, or meaning-making, process. Although it may happen at different times and in different ways, interpretation is part of almost all qualitative research.

Qualitative research is an umbrella term that encompasses a wide array of paradigmatic views, goals, and methods. Still, there are key unifying elements that include a generally constructionist epistemological standpoint, attention to primarily linguistic data, and generally accepted protocols or syntax for conducting research. Typically, qualitative researchers begin with a starting point—a curiosity, a problem in need of solutions, a research question, and/or a desire to better understand a situation from the “native” perspectives of the individuals who inhabit that context. This is what anthropologists call the emic , or insider’s, perspective. Olivier de Sardan ( 2015 ) wrote, “It evokes the meaning that social facts have for the actors concerned. It is opposed to the term etic , which, at times, designates more external or ‘objective’ data, and, at others, the researcher’s interpretive analysis” (p. 65).

From this starting point, researchers determine the appropriate kinds of data to collect, engage in fieldwork as participant observers to gather these data, organize the data, look for patterns, and attempt to understand the emic perspectives while integrating their own emergent interpretations. Researchers construct meaning from data by synthesizing research “findings,” “assertions,” or “theories” that can be shared so that others may also gain insights from the conducted inquiry. This interpretive process has a long history; hermeneutics, the theory of interpretation, blossomed in the 17th century in the form of biblical exegesis (Packer, 2018 ).

Although there are commonalities that cut across most forms of qualitative research, this is not to say that there is an accepted, linear, standardized approach. To be sure, there are an infinite number of variations and nuances in the qualitative research process. For example, some forms of inquiry begin with a firm research question; others start without even a clear focus for study. Grounded theorists begin data analysis and interpretation very early in the research process, whereas some case study researchers, for example, may collect data in the field for a period of time before seriously considering the data and its implications. Some ethnographers may be a part of the context (e.g., observing in classrooms), but they may assume more observer-like roles, as opposed to actively participating in the context. Alternatively, action researchers, in studying issues related to their own practice, are necessarily situated toward the participant end of the participant–observer continuum.

Our focus here is on one integrated part of the qualitative research process, interpretation, the hermeneutic process of collective and individual “meaning making.” Like Willig ( 2017 ), we believe “interpretation is at the heart of qualitative research because qualitative research is concerned with meaning and the process of meaning-making … qualitative data … needs to be given meaning by the researcher” (p. 276). As we discuss throughout this chapter, researchers take a variety of approaches to interpretation in qualitative work. Four general questions guide our explorations:

What is interpretation, and why are interpretive strategies important in qualitative research?

How do methodology, data, and the researcher/self impact interpretation in qualitative research?

How do qualitative researchers engage in the process of interpretation?

In what ways can a framework for interpretation strategies support qualitative researchers across multiple methodological and paradigmatic views?

We address each of these guiding questions in our attempt to explicate our interpretation of “interpretation” and, as educational researchers, we include examples from our own work to illustrate some key concepts.

What Is Interpretation, and Why Are Interpretive Strategies Important in Qualitative Research?

Qualitative researchers and those writing about qualitative methods often intertwine the terms analysis and interpretation . For example, Hubbard and Power ( 2003 ) described data analysis as “bringing order, structure, and meaning to the data” (p. 88). To us, this description combines analysis with interpretation. Although there is nothing wrong with this construction, our understanding aligns more closely with Mills’s ( 2018 ) claim that, “put simply, analysis involves summarizing what’s in the data, whereas interpretation involves making sense of—finding meaning in—that data” (p. 176). Hesse-Biber ( 2017 ) also separated out the essential process of interpretation. She described the steps in qualitative analysis and interpretation as data preparation, data exploration, and data reduction (all part of Mills’s “analysis” processes), followed by interpretation (pp. 307–328). Willig ( 2017 ) elaborated: analysis, she claims, is “sober and systematic,” whereas interpretation is associated with “creativity and the imagination … interpretation is seen as stimulating, it is interesting and it can be illuminating” (p. 276). For the purpose of this chapter, we will adhere to Mills’s distinction, understanding analysis as summarizing and organizing and interpretation as meaning making. Unavoidably, these closely related processes overlap and interact, but our focus will be primarily on the more complex of these endeavors, interpretation. Interpretation, in this sense, is in part translation, but translation is not an objective act. Instead, translation necessarily involves selectivity and the ascribing of meaning. Qualitative researchers “aim beneath manifest behavior to the meaning events have for those who experience them” (Eisner, 1991 , p. 35). The presentation of these insider/emic perspectives, coupled with researchers’ own interpretations, is a hallmark of qualitative research.

Qualitative researchers have long borrowed from extant models for fieldwork and interpretation. Approaches from anthropology and the arts have become especially prominent. For example, Eisner’s ( 1991 ) form of qualitative inquiry, educational criticism , draws heavily on accepted models of art criticism. T. Barrett ( 2011 ), an authority on art criticism, described interpretation as a complex set of processes based on a set of principles. We believe many of these principles apply as readily to qualitative research as they do to critique. The following principles, adapted from T. Barrett’s principles of interpretation (2011), inform our examination:

Qualitative phenomena have “aboutness” : All social phenomena have meaning, but meanings in this context can be multiple, even contradictory.

Interpretations are persuasive arguments : All interpretations are arguments, and qualitative researchers, like critics, strive to build strong arguments grounded in the information, or data, available.

  Some interpretations are better than others : Barrett noted that “some interpretations are better argued, better grounded with evidence, and therefore more reasonable, more certain, and more acceptable than others.” This contradicts the argument that “all interpretations are equal,” heard in the common refrain, “Well, that’s just your interpretation.”

There can be different, competing, and contradictory interpretations of the same phenomena : As noted at the beginning of this chapter, we acknowledge that subjectivity matters, and, unavoidably, it impacts one’s interpretations. As Barrett noted, “Interpretations are often based on a worldview.”

Interpretations are not (and cannot be) “right,” but instead, they can be more or less reasonable, convincing, and informative : There is never one “true” interpretation, but some interpretations are more compelling than others.

Interpretations can be judged by coherence, correspondence, and inclusiveness : Does the argument/interpretation make sense (coherence)? Does the interpretation fit the data (correspondence)? Have all data been attended to, including outlier data that do not necessarily support identified themes (inclusiveness)?

Interpretation is ultimately a communal endeavor : Initial interpretations may be incomplete, nearsighted, and/or narrow, but eventually these interpretations become richer, broader, and more inclusive. Feminist revisionist history projects are an exemplary case. Over time, the writing, art, and cultural contributions of countless women, previously ignored, diminished, or distorted, have come to be accepted as prominent contributions given serious consideration.

So, meaning is conferred; interpretations are socially constructed arguments; multiple interpretations are to be expected; and some interpretations are better than others. As we discuss later in this chapter, what makes an interpretation “better” often hinges on the purpose/goals of the research in question. Interpretations designed to generate theory, or generalizable rules, will be better for responding to research questions aligned with the aims of more traditional quantitative/positivist research, whereas interpretations designed to construct meanings through social interaction, to generate multiple perspectives, and to represent the context-specific perspectives of the research participants are better for researchers constructing thick, contextually rich descriptions, stories, or narratives. The former relies on more atomistic interpretive strategies, whereas the latter adheres to a more holistic approach (Willis, 2007 ). Both approaches to analysis/interpretation are addressed in more detail later in this chapter.

At this point, readers might ask, Why does interpretation matter, anyway? Our response to this question involves the distinctive nature of interpretation and the ability of the interpretive process to put unique fingerprints on an otherwise relatively static set of data. Once interview data are collected and transcribed (and we realize that even the process of transcription is, in part, interpretive), documents are collected, and observations are recorded, qualitative researchers could just, in good faith and with fidelity, represent the data in as straightforward ways as possible, allowing readers to “see for themselves” by sharing as much actual data (e.g., the transcribed words of the research participants) as possible. This approach, however, includes analysis, what we have defined as summarizing and organizing data for presentation, but it falls short of what we reference and define as interpretation—attempting to explain the meaning of others’ words and actions. According to Lichtman ( 2013 ),

While early efforts at qualitative research might have stopped at description, it is now more generally accepted that a qualitative researcher goes beyond pure description.… Many believe that it is the role of the researcher to bring understanding, interpretation, and meaning. (p. 17)

Because we are fond of the arts and arts-based approaches to qualitative research, an example from the late jazz drummer, Buddy Rich, seems fitting. Rich explains the importance of having the flexibility to interpret: “I don’t think any arranger should ever write a drum part for a drummer, because if a drummer can’t create his own interpretation of the chart, and he plays everything that’s written, he becomes mechanical; he has no freedom.” The same is true for qualitative researchers: without the freedom to interpret, the researcher merely regurgitates, attempting to share with readers/reviewers exactly what the research subjects shared with him or her. It is only through interpretation that the researcher, as collaborator with unavoidable subjectivities, is able to construct unique, contextualized meaning. Interpretation, then, in this sense, is knowledge construction.

In closing this section, we will illustrate the analysis-versus-interpretation distinction with the following transcript excerpt. In this study, the authors (Trent & Zorko, 2006 ) were studying student teaching from the perspective of K–12 students. This quote comes from a high school student in a focus group interview. She is describing a student teacher she had:

The right-hand column contains codes or labels applied to parts of the transcript text. Coding will be discussed in more depth later in this chapter, but for now, note that the codes are mostly summarizing the main ideas of the text, sometimes using the exact words of the research participant. This type of coding is a part of what we have called analysis—organizing and summarizing the data. It is a way of beginning to say “what is” there. As noted, though, most qualitative researchers go deeper. They want to know more than what is; they also ask, What does it mean? This is a question of interpretation.

Specific to the transcript excerpt, researchers might next begin to cluster the early codes into like groups. For example, the teacher “felt targeted,” “assumed kids were going to behave inappropriately,” and appeared to be “overwhelmed.” A researcher might cluster this group of codes in a category called “teacher feelings and perceptions” and may then cluster the codes “could not control class” and “students off task” into a category called “classroom management.” The researcher then, in taking a fresh look at these categories and the included codes, may begin to conclude that what is going on in this situation is that the student teacher does not have sufficient training in classroom management models and strategies and may also be lacking the skills she needs to build relationships with her students. These then would be interpretations, persuasive arguments connected to the study’s data. In this specific example, the researchers might proceed to write a memo about these emerging interpretations. In this memo, they might more clearly define their early categories and may also look through other data to see if there are other codes or categories that align with or overlap this initial analysis. They may write further about their emergent interpretations and, in doing so, may inform future data collection in ways that will allow them to either support or refute their early interpretations. These researchers will also likely find that the processes of analysis and interpretation are inextricably intertwined. Good interpretations very often depend on thorough and thoughtful analyses.

How Do Methodology, Data, and the Researcher/Self Impact Interpretation in Qualitative Research?

Methodological conventions guide interpretation and the use of interpretive strategies. For example, in grounded theory and in similar methodological traditions, “formal analysis begins early in the study and is nearly completed by the end of data collection” (Bogdan & Biklen, 2007 , p. 73). Alternatively, for researchers from other traditions, for example, case study researchers, “formal analysis and theory development [interpretation] do not occur until after the data collection is near complete” (p. 73).

Researchers subscribing to methodologies that prescribe early data analysis and interpretation may employ methods like analytic induction or the constant comparison method. In using analytic induction, researchers develop a rough definition of the phenomena under study; collect data to compare to this rough definition; modify the definition as needed, based on cases that both fit and do not fit the definition; and, finally, establish a clear, universal definition (theory) of the phenomena (Robinson, 1951, cited in Bogdan & Biklen, 2007 , p. 73). Generally, those using a constant comparison approach begin data collection immediately; identify key issues, events, and activities related to the study that then become categories of focus; collect data that provide incidents of these categories; write about and describe the categories, accounting for specific incidents and seeking others; discover basic processes and relationships; and, finally, code and write about the categories as theory, “grounded” in the data (Glaser, 1965 ). Although processes like analytic induction and constant comparison can be listed as steps to follow, in actuality, these are more typically recursive processes in which the researcher repeatedly goes back and forth between the data and emerging analyses and interpretations.

In addition to methodological conventions that prescribe data analysis early (e.g., grounded theory) or later (e.g., case study) in the inquiry process, methodological approaches also impact the general approach to analysis and interpretation. Ellingson ( 2011 ) situated qualitative research methodologies on a continuum spanning “science”-like approaches on one end juxtaposed with “art”-like approaches on the other.

Researchers pursuing a more science-oriented approach seek valid, reliable, generalizable knowledge; believe in neutral, objective researchers; and ultimately claim single, authoritative interpretations. Researchers adhering to these science-focused, postpositivistic approaches may count frequencies, emphasize the validity of the employed coding system, and point to intercoder reliability and random sampling as criteria that bolster the research credibility. Researchers at or near the science end of the continuum might employ analysis and interpretation strategies that include “paired comparisons,” “pile sorts,” “word counts,” identifying “key words in context,” and “triad tests” (Bernard, Wutich, & Ryan, 2017 , pp. 112, 381, 113, 170). These researchers may ultimately seek to develop taxonomies or other authoritative final products that organize and explain the collected data.

For example, in a study we conducted about preservice teachers’ experiences learning to teach second-language learners, the researchers collected larger data sets and used a statistical analysis package to analyze survey data, and the resultant findings included descriptive statistics. These survey results were supported with open-ended, qualitative data. For example, one of the study’s findings was that “a strong majority of candidates (96%) agreed that an immersion approach alone will not guarantee academic or linguistic success for second language learners.” In narrative explanations, one preservice teacher, representative of many others, remarked, “There has to be extra instructional efforts to help their students learn English … they won’t learn English by merely sitting in the classrooms” (Cho, Rios, Trent, & Mayfield, 2012 , p. 75).

Methodologies on the art side of Ellingson’s ( 2011 ) continuum, alternatively, “value humanistic, openly subjective knowledge, such as that embodied in stories, poetry, photography, and painting” (p. 599). Analysis and interpretation in these (often more contemporary) methodological approaches do not strive for “social scientific truth,” but instead are formulated to “enable us to learn about ourselves, each other, and the world through encountering the unique lens of a person’s (or a group’s) passionate rendering of a reality into a moving, aesthetic expression of meaning” (p. 599). For these “artistic/interpretivists, truths are multiple, fluctuating and ambiguous” (p. 599). Methodologies taking more subjective approaches to analysis and interpretation include autoethnography, testimonio, performance studies, feminist theorists/researchers, and others from related critical methodological forms of qualitative practice. More specifically arts-based approaches include poetic inquiry, fiction-based research, music as method, and dance and movement as inquiry (Leavy, 2017 ). Interpretation in these approaches is inherent. For example, “ interpretive poetry is understood as a method of merging the participant’s words with the researcher’s perspective” (Leavy, 2017 , p. 82).

As an example, one of us engaged in an artistic inquiry with a group of students in an art class for elementary teachers. We called it “Dreams as Data” and, among the project aims, we wanted to gather participants’ “dreams for education in the future” and display these dreams in an accessible, interactive, artistic display (see Trent, 2002 ). The intent was not to statistically analyze the dreams/data; instead, it was more universal. We wanted, as Ellingson ( 2011 , p. 599) noted, to use participant responses in ways that “enable us to learn about ourselves, each other, and the world.” The decision was made to leave responses intact and to share the whole/raw data set in the artistic display in ways that allowed the viewers to holistically analyze and interpret for themselves. Additionally, the researcher (Trent, 2002 ) collaborated with his students to construct their own contextually situated interpretations of the data. The following text is an excerpt from one participant’s response:

Almost a century ago, John Dewey eloquently wrote about the need to imagine and create the education that ALL children deserve, not just the richest, the Whitest, or the easiest to teach. At the dawn of this new century, on some mornings, I wake up fearful that we are further away from this ideal than ever.… Collective action, in a critical, hopeful, joyful, anti-racist and pro-justice spirit, is foremost in my mind as I reflect on and act in my daily work.… Although I realize the constraints on teachers and schools in the current political arena, I do believe in the power of teachers to stand next to, encourage, and believe in the students they teach—in short, to change lives. (Trent, 2002 , p. 49)

In sum, researchers whom Ellingson ( 2011 ) characterized as being on the science end of the continuum typically use more detailed or atomistic strategies to analyze and interpret qualitative data, whereas those toward the artistic end most often employ more holistic strategies. Both general approaches to qualitative data analysis and interpretation, atomistic and holistic, will be addressed later in this chapter.

As noted, qualitative researchers attend to data in a wide variety of ways depending on paradigmatic and epistemological beliefs, methodological conventions, and the purpose/aims of the research. These factors impact the kinds of data collected and the ways these data are ultimately analyzed and interpreted. For example, life history or testimonio researchers conduct extensive individual interviews, ethnographers record detailed observational notes, critical theorists may examine documents from pop culture, and ethnomethodologists may collect videotapes of interaction for analysis and interpretation.

In addition to the wide range of data types that are collected by qualitative researchers (and most qualitative researchers collect multiple forms of data), qualitative researchers, again influenced by the factors noted earlier, employ a variety of approaches to analyzing and interpreting data. As mentioned earlier in this chapter, some advocate for a detailed/atomistic, fine-grained approach to data (see, e.g., Bernard et al., 2017 ); others prefer a more broad-based, holistic, “eyeballing” of the data. According to Willis ( 2007 ), “Eyeballers reject the more structured approaches to analysis that break down the data into small units and, from the perspective of the eyeballers, destroy the wholeness and some of the meaningfulness of the data” (p. 298).

Regardless, we assert, as illustrated in Figure 31.1 , that as the process evolves, data collection becomes less prominent later in the process, as interpretation and making sense/meaning of the data becomes more prominent. It is through this emphasis on interpretation that qualitative researchers put their individual imprints on the data, allowing for the emergence of multiple, rich perspectives. This space for interpretation allows researchers the freedom Buddy Rich alluded to in his quote about interpreting musical charts. Without this freedom, Rich noted that the process would simply be “mechanical.” Furthermore, allowing space for multiple interpretations nourishes the perspectives of many others in the community. Writer and theorist Meg Wheatley explained, “Everyone in a complex system has a slightly different interpretation. The more interpretations we gather, the easier it becomes to gain a sense of the whole.” In qualitative research, “there is no ‘getting it right’ because there could be many ‘rights’ ” (as cited in Lichtman, 2013 ).

Increasing Role of Interpretation in Data Analysis

In addition to the roles methodology and data play in the interpretive process, perhaps the most important is the role of the self/the researcher in the interpretive process. According to Lichtman ( 2013 ), “Data are collected, information is gathered, settings are viewed, and realities are constructed through his or her eyes and ears … the qualitative researcher interprets and makes sense of the data” (p. 21). Eisner ( 1991 ) supported the notion of the researcher “self as instrument,” noting that expert researchers know not simply what to attend to, but also what to neglect. He describes the researcher’s role in the interpretive process as combining sensibility , the ability to observe and ascertain nuances, with schema , a deep understanding or cognitive framework of the phenomena under study.

J. Barrett ( 2007 ) described self/researcher roles as “transformations” (p. 418) at multiple points throughout the inquiry process: early in the process, researchers create representations through data generation, conducting observations and interviews and collecting documents and artifacts. Then,

transformation occurs when the “raw” data generated in the field are shaped into data records by the researcher. These data records are produced through organizing and reconstructing the researcher’s notes and transcribing audio and video recordings in the form of permanent records that serve as the “evidentiary warrants” of the generated data. The researcher strives to capture aspects of the phenomenal world with fidelity by selecting salient aspects to incorporate into the data record. (J. Barrett, 2007 , p. 418)

Transformation continues when the researcher codes, categorizes, and explores patterns in the data (the process we call analysis).

Transformations also involve interpreting what the data mean and relating these interpretations to other sources of insight about the phenomena, including findings from related research, conceptual literature, and common experience.… Data analysis and interpretation are often intertwined and rely upon the researcher’s logic, artistry, imagination, clarity, and knowledge of the field under study. (J. Barrett, 2007 , p. 418)

We mentioned the often-blended roles of participation and observation earlier in this chapter. The role(s) of the self/researcher are often described as points along a participant–observer continuum (see, e.g., Bogdan & Biklen, 2007 ). On the far observer end of this continuum, the researcher situates as detached, tries to be inconspicuous (so as not to impact/disrupt the phenomena under study), and approaches the studied context as if viewing it from behind a one-way mirror. On the opposite, participant end, the researcher is completely immersed and involved in the context. It would be difficult for an outsider to distinguish between researcher and subjects. For example, “some feminist researchers and postmodernists take a political stance and have an agenda that places the researcher in an activist posture. These researchers often become quite involved with the individuals they study and try to improve their human condition” (Lichtman, 2013 , p. 17).

We assert that most researchers fall somewhere between these poles. We believe that complete detachment is both impossible and misguided. In doing so, we, along with many others, acknowledge (and honor) the role of subjectivity, the researcher’s beliefs, opinions, biases, and predispositions. Positivist researchers seeking objective data and accounts either ignore the impact of subjectivity or attempt to drastically diminish/eliminate its impact. Even qualitative researchers have developed methods to avoid researcher subjectivity affecting research data collection, analysis, and interpretation. For example, foundational phenomenologist Husserl ( 1913/1962 ) developed the concept of bracketing , what Lichtman describes as “trying to identify your views on the topic and then putting them aside” (2013, p. 22). Like Slotnick and Janesick ( 2011 ), we ultimately claim “it is impossible to bracket yourself” (p. 1358). Instead, we take a balanced approach, like Eisner, understanding that subjectivity allows researchers to produce the rich, idiosyncratic, insightful, and yet data-based interpretations and accounts of lived experience that accomplish the primary purposes of qualitative inquiry. Eisner ( 1991 ) wrote, “Rather than regarding uniformity and standardization as the summum bonum, educational criticism [Eisner’s form of qualitative research] views unique insight as the higher good” (p. 35). That said, we also claim that, just because we acknowledge and value the role of researcher subjectivity, researchers are still obligated to ground their findings in reasonable interpretations of the data. Eisner ( 1991 ) explained:

This appreciation for personal insight as a source of meaning does not provide a license for freedom. Educational critics must provide evidence and reasons. But they reject the assumption that unique interpretation is a conceptual liability in understanding, and they see the insights secured from multiple views as more attractive than the comforts provided by a single right one. (p. 35)

Connected to this participant–observer continuum is the way the researcher positions him- or herself in relation to the “subjects” of the study. Traditionally, researchers, including early qualitative researchers, anthropologists, and ethnographers, referenced those studied as subjects . More recently, qualitative researchers better understand that research should be a reciprocal process in which both researcher and the foci of the research should derive meaningful benefit. Researchers aligned with this thinking frequently use the term participants to describe those groups and individuals included in a study. Going a step further, some researchers view research participants as experts on the studied topic and as equal collaborators in the meaning-making process. In these instances, researchers often use the terms co-researchers or co-investigators .

The qualitative researcher, then, plays significant roles throughout the inquiry process. These roles include transforming data, collaborating with research participants or co-researchers, determining appropriate points to situate along the participant–observer continuum, and ascribing personal insights, meanings, and interpretations that are both unique and justified with data exemplars. Performing these roles unavoidably impacts and changes the researcher. Slotnick and Janesick ( 2011 ) noted, “Since, in qualitative research the individual is the research instrument through which all data are passed, interpreted, and reported, the scholar’s role is constantly evolving as self evolves” (p. 1358).

As we note later, key in all this is for researchers to be transparent about the topics discussed in the preceding section: What methodological conventions have been employed and why? How have data been treated throughout the inquiry to arrive at assertions and findings that may or may not be transferable to other idiosyncratic contexts? And, finally, in what ways has the researcher/self been situated in and impacted the inquiry? Unavoidably, we assert, the self lies at the critical intersection of data and theory, and, as such, two legs of this stool, data and researcher, interact to create the third, theory.

How Do Qualitative Researchers Engage in the Process of Interpretation?

Theorists seem to have a propensity to dichotomize concepts, pulling them apart and placing binary opposites on the far ends of conceptual continuums. Qualitative research theorists are no different, and we have already mentioned some of these continua in this chapter. For example, in the previous section, we discussed the participant–observer continuum. Earlier, we referenced both Willis’s ( 2007 ) conceptualization of atomistic versus holistic approaches to qualitative analysis and interpretation and Ellingson’s ( 2011 ) science–art continuum. Each of these latter two conceptualizations inform how qualitative researchers engage in the process of interpretation.

Willis ( 2007 ) shared that the purpose of a qualitative project might be explained as “what we expect to gain from research” (p. 288). The purpose, or what we expect to gain, then guides and informs the approaches researchers might take to interpretation. Some researchers, typically positivist/postpositivist, conduct studies that aim to test theories about how the world works and/or how people behave. These researchers attempt to discover general laws, truths, or relationships that can be generalized. Others, less confident in the ability of research to attain a single, generalizable law or truth, might seek “local theory.” These researchers still seek truths, but “instead of generalizable laws or rules, they search for truths about the local context … to understand what is really happening and then to communicate the essence of this to others” (Willis, 2007 , p. 291). In both these purposes, researchers employ atomistic strategies in an inductive process in which researchers “break the data down into small units and then build broader and broader generalizations as the data analysis proceeds” (p. 317). The earlier mentioned processes of analytic induction, constant comparison, and grounded theory fit within this conceptualization of atomistic approaches to interpretation. For example, a line-by-line coding of a transcript might begin an atomistic approach to data analysis.

Alternatively, other researchers pursue distinctly different aims. Researchers with an objective description purpose focus on accurately describing the people and context under study. These researchers adhere to standards and practices designed to achieve objectivity, and their approach to interpretation falls within the binary atomistic/holistic distinction.

The purpose of hermeneutic approaches to research is to “understand the perspectives of humans. And because understanding is situational, hermeneutic research tends to look at the details of the context in which the study occurred. The result is generally rich data reports that include multiple perspectives” (Willis, 2007 , p. 293).

Still other researchers see their purpose as the creation of stories or narratives that utilize “a social process that constructs meaning through interaction … it is an effort to represent in detail the perspectives of participants … whereas description produces one truth about the topic of study, storytelling may generate multiple perspectives, interpretations, and analyses by the researcher and participants” (Willis, 2007 , p. 295).

In these latter purposes (hermeneutic, storytelling, narrative production), researchers typically employ more holistic strategies. According to Willis ( 2007 ), “Holistic approaches tend to leave the data intact and to emphasize that meaning must be derived for a contextual reading of the data rather than the extraction of data segments for detailed analysis” (p. 297). This was the case with the Dreams as Data project mentioned earlier.

We understand the propensity to dichotomize, situate concepts as binary opposites, and create neat continua between these polar descriptors. These sorts of reduction and deconstruction support our understandings and, hopefully, enable us to eventually reconstruct these ideas in meaningful ways. Still, in reality, we realize most of us will, and should, work in the middle of these conceptualizations in fluid ways that allow us to pursue strategies, processes, and theories most appropriate for the research task at hand. As noted, Ellingson ( 2011 ) set up another conceptual continuum, but, like ours, her advice was to “straddle multiple points across the field of qualitative methods” (p. 595). She explained, “I make the case for qualitative methods to be conceptualized as a continuum anchored by art and science, with vast middle spaces that embody infinite possibilities for blending artistic, expository, and social scientific ways of analysis and representation” (p. 595).

We explained at the beginning of this chapter that we view analysis as organizing and summarizing qualitative data and interpretation as constructing meaning. In this sense, analysis allows us to describe the phenomena under study. It enables us to succinctly answer what and how questions and ensures that our descriptions are grounded in the data collected. Descriptions, however, rarely respond to questions of why . Why questions are the domain of interpretation, and, as noted throughout this text, interpretation is complex. Gubrium and Holstein ( 2000 ) noted, “Traditionally, qualitative inquiry has concerned itself with what and how questions … qualitative researchers typically approach why questions cautiously, explanation is tricky business” (p. 502). Eisner ( 1991 ) described this distinctive nature of interpretation: “It means that inquirers try to account for [interpretation] what they have given account of ” (p. 35).

Our focus here is on interpretation, but interpretation requires analysis, because without clear understandings of the data and its characteristics, derived through systematic examination and organization (e.g., coding, memoing, categorizing), “interpretations” resulting from inquiry will likely be incomplete, uninformed, and inconsistent with the constructed perspectives of the study participants. Fortunately for qualitative researchers, we have many sources that lead us through analytic processes. We earlier mentioned the accepted processes of analytic induction and the constant comparison method. These detailed processes (see, e.g., Bogdan & Biklen, 2007 ) combine the inextricably linked activities of analysis and interpretation, with analysis more typically appearing as earlier steps in the process and meaning construction—interpretation—happening later.

A wide variety of resources support researchers engaged in the processes of analysis and interpretation. Saldaña ( 2011 ), for example, provided a detailed description of coding types and processes. He showed researchers how to use process coding (uses gerunds, “-ing” words to capture action), in vivo coding (uses the actual words of the research participants/ subjects), descriptive coding (uses nouns to summarize the data topics), versus coding (uses “vs” to identify conflicts and power issues), and values coding (identifies participants’ values, attitudes, and/or beliefs). To exemplify some of these coding strategies, we include an excerpt from a transcript of a meeting of a school improvement committee. In this study, the collaborators were focused on building “school community.” This excerpt illustrates the application of a variety of codes described by Saldaña to this text:

To connect and elaborate the ideas developed in coding, Saldaña ( 2011 ) suggested researchers categorize the applied codes, write memos to deepen understandings and illuminate additional questions, and identify emergent themes. To begin the categorization process, Saldaña recommended all codes be “classified into similar clusters … once the codes have been classified, a category label is applied to them” (p. 97). So, in continuing with the study of school community example coded here, the researcher might create a cluster/category called “Value of Collaboration” and in this category might include the codes “relationships,” “building community,” and “effective strategies.”

Having coded and categorized a study’s various data forms, a typical next step for researchers is to write memos or analytic memos . Writing analytic memos allows the researcher(s) to

set in words your interpretation of the data … an analytic memo further articulates your … thinking processes on what things may mean … as the study proceeds, however, initial and substantive analytic memos can be revisited and revised for eventual integration into the report itself. (Saldaña, 2011 , p. 98)

In the study of student teaching from K–12 students’ perspectives (Trent & Zorko, 2006 ), we noticed throughout our analysis a series of focus group interview quotes coded “names.” The following quote from a high school student is representative of many others:

I think that, ah, they [student teachers] should like know your face and your name because, uh, I don’t like it if they don’t and they’ll just like … cause they’ll blow you off a lot easier if they don’t know, like our new principal is here … he is, like, he always, like, tries to make sure to say hi even to the, like, not popular people if you can call it that, you know, and I mean, yah, and the people that don’t usually socialize a lot, I mean he makes an effort to know them and know their name like so they will cooperate better with him.

Although we did not ask the focus groups a specific question about whether student teachers knew the K–12 students’ names, the topic came up in every focus group interview. We coded the above excerpt and the others “knowing names,” and these data were grouped with others under the category “relationships.” In an initial analytic memo about this, the researchers wrote,

STUDENT TEACHING STUDY—MEMO #3 “Knowing Names as Relationship Building” Most groups made unsolicited mentions of student teachers knowing, or not knowing, their names. We haven’t asked students about this, but it must be important to them because it always seems to come up. Students expected student teachers to know their names. When they did, students noticed and seemed pleased. When they didn’t, students seemed disappointed, even annoyed. An elementary student told us that early in the semester, “she knew our names … cause when we rose [sic] our hands, she didn’t have to come and look at our name tags … it made me feel very happy.” A high schooler, expressing displeasure that his student teacher didn’t know students’ names, told us, “They should like know your name because it shows they care about you as a person. I mean, we know their names, so they should take the time to learn ours too.” Another high school student said that even after 3 months, she wasn’t sure the student teacher knew her name. Another student echoed, “Same here.” Each of these students asserted that this (knowing students’ names) had impacted their relationship with the student teacher. This high school student focus group stressed that a good relationship, built early, directly impacts classroom interaction and student learning. A student explained it like this: “If you get to know each other, you can have fun with them … they seem to understand you more, you’re more relaxed, and learning seems easier.”

As noted in these brief examples, coding, categorizing, and writing memos about a study’s data are all accepted processes for data analysis and allow researchers to begin constructing new understandings and forming interpretations of the studied phenomena. We find the qualitative research literature to be particularly strong in offering support and guidance for researchers engaged in these analytic practices. In addition to those already noted in this chapter, we have found the following resources provide practical, yet theoretically grounded approaches to qualitative data analysis. For more detailed, procedural, or atomistic approaches to data analysis, we direct researchers to Miles and Huberman’s classic 1994 text, Qualitative Data Analysis , and Bernard et al.’s 2017 book Analyzing Qualitative Data: Systematic Approaches. For analysis and interpretation strategies falling somewhere between the atomistic and holistic poles, we suggest Hesse-Biber and Leavy’s ( 2011 ) chapter, “Analysis and Interpretation of Qualitative Data,” in their book, The Practice of Qualitative Research (second edition); Lichtman’s chapter, “Making Meaning From Your Data,” in her 2013 book Qualitative Research in Education: A User’s Guide (third edition); and “Processing Fieldnotes: Coding and Memoing,” a chapter in Emerson, Fretz, and Shaw’s ( 1995 ) book, Writing Ethnographic Fieldwork . Each of these sources succinctly describes the processes of data preparation, data reduction, coding and categorizing data, and writing memos about emergent ideas and findings. For more holistic approaches, we have found Denzin and Lincoln’s ( 2007 ) Collecting and Interpreting Qualitative Materials and Ellis and Bochner’s ( 2000 ) chapter “Autoethnography, Personal Narrative, Reflexivity” to both be very informative. Finally, Leavy’s 2017 book, Method Meets Art: Arts-Based Research Practice , provides support and guidance to researchers engaged in arts-based research.

Even after reviewing the multiple resources for treating data included here, qualitative researchers might still be wondering, But exactly how do we interpret? In the remainder of this section and in the concluding section of this chapter, we more concretely provide responses to this question and, in closing, we propose a framework for researchers to utilize as they engage in the complex, ambiguous, and yet exciting process of constructing meanings and new understandings from qualitative sources.

These meanings and understandings are often presented as theory, but theories in this sense should be viewed more as “guides to perception” as opposed to “devices that lead to the tight control or precise prediction of events” (Eisner, 1991 , p. 95). Perhaps Erickson’s ( 1986 ) concept of assertions is a more appropriate aim for qualitative researchers. He claimed that assertions are declarative statements; they include a summary of the new understandings, and they are supported by evidence/data. These assertions are open to revision and are revised when disconfirming evidence requires modification. Assertions, theories, or other explanations resulting from interpretation in research are typically presented as “findings” in written research reports. Belgrave and Smith ( 2002 ) emphasized the importance of these interpretations (as opposed to descriptions): “The core of the report is not the events reported by the respondent, but rather the subjective meaning of the reported events for the respondent” (p. 248).

Mills ( 2018 ) viewed interpretation as responding to the question, So what? He provided researchers a series of concrete strategies for both analysis and interpretation. Specific to interpretation, Mills (pp. 204–207) suggested a variety of techniques, including the following:

“ Extend the analysis ”: In doing so, researchers ask additional questions about the research. The data appear to say X , but could it be otherwise? In what ways do the data support emergent finding X ? And, in what ways do they not?

“ Connect findings with personal experience ”: Using this technique, researchers share interpretations based on their intimate knowledge of the context, the observed actions of the individuals in the studied context, and the data points that support emerging interpretations, as well as their awareness of discrepant events or outlier data. In a sense, the researcher is saying, “Based on my experiences in conducting this study, this is what I make of it all.”

“ Seek the advice of ‘critical’ friends ”: In doing so, researchers utilize trusted colleagues, fellow researchers, experts in the field of study, and others to offer insights, alternative interpretations, and the application of their own unique lenses to a researcher’s initial findings. We especially like this strategy because we acknowledge that, too often, qualitative interpretation is a “solo” affair.

“ Contextualize findings in the literature ”: This allows researchers to compare their interpretations to those of others writing about and studying the same/similar phenomena. The results of this contextualization may be that the current study’s findings correspond with the findings of other researchers. The results might, alternatively, differ from the findings of other researchers. In either instance, the researcher can highlight his or her unique contributions to our understanding of the topic under study.

“ Turn to theory ”: Mills defined theory as “an analytical and interpretive framework that helps the researcher make sense of ‘what is going on’ in the social setting being studied.” In turning to theory, researchers search for increasing levels of abstraction and move beyond purely descriptive accounts. Connecting to extant or generating new theory enables researchers to link their work to the broader contemporary issues in the field.

Other theorists offer additional advice for researchers engaged in the act of interpretation. Richardson ( 1995 ) reminded us to account for the power dynamics in the researcher–researched relationship and notes that, in doing so, we can allow for oppressed and marginalized voices to be heard in context. Bogdan and Biklen ( 2007 ) suggested that researchers engaged in interpretation revisit foundational writing about qualitative research, read studies related to the current research, ask evaluative questions (e.g., Is what I’m seeing here good or bad?), ask about implications of particular findings/interpretations, think about the audience for interpretations, look for stories and incidents that illustrate a specific finding/interpretation, and attempt to summarize key interpretations in a succinct paragraph. All these suggestions can be pertinent in certain situations and with particular methodological approaches. In the next and closing section of this chapter, we present a framework for interpretive strategies we believe will support, guide, and be applicable to qualitative researchers across multiple methodologies and paradigms.

In What Ways Can a Framework for Interpretation Strategies Support Qualitative Researchers across Multiple Methodological and Paradigmatic Views?

The process of qualitative research is often compared to a journey, one without a detailed itinerary and ending, but with general direction and aims and yet an open-endedness that adds excitement and thrives on curiosity. Qualitative researchers are travelers. They travel physically to field sites; they travel mentally through various epistemological, theoretical, and methodological grounds; they travel through a series of problem-finding, access, data collection, and data analysis processes; and, finally—the topic of this chapter—they travel through the process of making meaning of all this physical and cognitive travel via interpretation.

Although travel is an appropriate metaphor to describe the journey of qualitative researchers, we will also use “travel” to symbolize a framework for qualitative research interpretation strategies. By design, this framework applies across multiple paradigmatic, epistemological, and methodological traditions. The application of this framework is not formulaic or highly prescriptive; it is also not an anything-goes approach. It falls, and is applicable, between these poles, giving concrete (suggested) direction to qualitative researchers wanting to make the most of the interpretations that result from their research and yet allowing the necessary flexibility for researchers to employ the methods, theories, and approaches they deem most appropriate to the research problem(s) under study.

TRAVEL, a Comprehensive Approach to Qualitative Interpretation

In using the word TRAVEL as a mnemonic device, our aim is to highlight six essential concepts we argue all qualitative researchers should attend to in the interpretive process: transparency, reflexivity, analysis, validity, evidence, and literature. The importance of each is addressed here.

Transparency , as a research concept seems, well, transparent. But, too often, we read qualitative research reports and are left with many questions: How were research participants and the topic of study selected/excluded? How were the data collected, when, and for how long? Who analyzed and interpreted these data? A single researcher? Multiple? What interpretive strategies were employed? Are there data points that substantiate these interpretations/findings? What analytic procedures were used to organize the data prior to making the presented interpretations? In being transparent about data collection, analysis, and interpretation processes, researchers allow reviewers/readers insight into the research endeavor, and this transparency leads to credibility for both researcher and researcher’s claims. Altheide and Johnson ( 2011 ) explained,

There is great diversity of qualitative research.… While these approaches differ, they also share an ethical obligation to make public their claims, to show the reader, audience, or consumer why they should be trusted as faithful accounts of some phenomenon. (p. 584)

This includes, they noted, articulating

what the different sources of data were, how they were interwoven, and … how subsequent interpretations and conclusions are more or less closely tied to the various data … the main concern is that the connection be apparent, and to the extent possible, transparent. (p. 590)

In the Dreams as Data art and research project noted earlier, transparency was addressed in multiple ways. Readers of the project write-up were informed that interpretations resulting from the study, framed as themes , were a result of collaborative analysis that included insights from both students and instructor. Viewers of the art installation/data display had the rare opportunity to see all participant responses. In other words, viewers had access to the entire raw data set (see Trent, 2002 ). More frequently, we encounter only research “findings” already distilled, analyzed, and interpreted in research accounts, often by a single researcher. Allowing research consumers access to the data to interpret for themselves in the Dreams project was an intentional attempt at transparency.

Reflexivity , the second of our concepts for interpretive researcher consideration, has garnered a great deal of attention in qualitative research literature. Some have called this increased attention the reflexive turn (see, e.g., Denzin & Lincoln, 2004 ).

Although you can find many meanings for the term reflexivity, it is usually associated with a critical reflection on the practice and process of research and the role of the researcher. It concerns itself with the impact of the researcher on the system and the system on the researcher. It acknowledges the mutual relationships between the researcher and who and what is studied … by acknowledging the role of the self in qualitative research, the researcher is able to sort through biases and think about how they affect various aspects of the research, especially interpretation of meanings. (Lichtman, 2013 , p. 165)

As with transparency, attending to reflexivity allows researchers to attach credibility to presented findings. Providing a reflexive account of researcher subjectivity and the interactions of this subjectivity within the research process is a way for researchers to communicate openly with their audience. Instead of trying to exhume inherent bias from the process, qualitative researchers share with readers the value of having a specific, idiosyncratic positionality. As a result, situated, contextualized interpretations are viewed as an asset, as opposed to a liability.

LaBanca ( 2011 ), acknowledging the often solitary nature of qualitative research, called for researchers to engage others in the reflexive process. Like many other researchers, LaBanca utilized a researcher journal to chronicle reflexive thoughts, explorations, and understandings, but he took it a step farther. Realizing the value of others’ input, LaBanca posts his reflexive journal entries on a blog (what he calls an online reflexivity blog ) and invites critical friends, other researchers, and interested members of the community to audit his reflexive moves, providing insights, questions, and critique that inform his research and study interpretations.

We agree this is a novel approach worth considering. We, too, understand that multiple interpreters will undoubtedly produce multiple interpretations, a richness of qualitative research. So, we suggest researchers consider bringing others in before the production of the report. This could be fruitful in multiple stages of the inquiry process, but especially in the complex, idiosyncratic processes of reflexivity and interpretation. We are both educators and educational researchers. Historically, each of these roles has tended to be constructed as an isolated endeavor, the solitary teacher, the solo researcher/fieldworker. As noted earlier and in the analysis section that follows, introducing collaborative processes to what has often been a solitary activity offers much promise for generating rich interpretations that benefit from multiple perspectives.

Being consciously reflexive throughout our practice as researchers has benefitted us in many ways. In a study of teacher education curricula designed to prepare preservice teachers to support second-language learners, we realized hard truths that caused us to reflect on and adapt our own practices as teacher educators. Reflexivity can inform a researcher at all parts of the inquiry, even in early stages. For example, one of us was beginning a study of instructional practices in an elementary school. The communicated methods of the study indicated that the researcher would be largely an observer. Early fieldwork revealed that the researcher became much more involved as a participant than anticipated. Deep reflection and writing about the classroom interactions allowed the researcher to realize that the initial purpose of the research was not being accomplished, and the researcher believed he was having a negative impact on the classroom culture. Reflexivity in this instance prompted the researcher to leave the field and abandon the project as it was just beginning. Researchers should plan to openly engage in reflexive activities, including writing about their ongoing reflections and subjectivities. Including excerpts of this writing in research account supports our earlier recommendation of transparency.

Early in this chapter, for the purposes of discussion and examination, we defined analysis as “summarizing and organizing” data in a qualitative study and interpretation as “meaning making.” Although our focus has been on interpretation as the primary topic, the importance of good analysis cannot be underestimated, because without it, resultant interpretations are likely incomplete and potentially uninformed. Comprehensive analysis puts researchers in a position to be deeply familiar with collected data and to organize these data into forms that lead to rich, unique interpretations, and yet interpretations that are clearly connected to data exemplars. Although we find it advantageous to examine analysis and interpretation as different but related practices, in reality, the lines blur as qualitative researchers engage in these recursive processes.

We earlier noted our affinity for a variety of approaches to analysis (see, e.g., Hesse-Biber & Leavy, 2011 ; Lichtman, 2013 ; or Saldaña, 2011 ). Emerson et al. ( 1995 ) presented a grounded approach to qualitative data analysis: In early stages, researchers engage in a close, line-by-line reading of data/collected text and accompany this reading with open coding , a process of categorizing and labeling the inquiry data. Next, researchers write initial memos to describe and organize the data under analysis. These analytic phases allow the researcher(s) to prepare, organize, summarize, and understand the data, in preparation for the more interpretive processes of focused coding and the writing up of interpretations and themes in the form of integrative memos .

Similarly, Mills ( 2018 ) provided guidance on the process of analysis for qualitative action researchers. His suggestions for organizing and summarizing data include coding (labeling data and looking for patterns); identifying themes by considering the big picture while looking for recurrent phrases, descriptions, or topics; asking key questions about the study data (who, what, where, when, why, and how); developing concept maps (graphic organizers that show initial organization and relationships in the data); and stating what’s missing by articulating what data are not present (pp. 179–189).

Many theorists, like Emerson et al. ( 1995 ) and Mills ( 2018 ) noted here, provide guidance for individual researchers engaged in individual data collection, analysis, and interpretation; others, however, invite us to consider the benefits of collaboratively engaging in these processes through the use of collaborative research and analysis teams. Paulus, Woodside, and Ziegler ( 2008 ) wrote about their experiences in collaborative qualitative research: “Collaborative research often refers to collaboration among the researcher and the participants. Few studies investigate the collaborative process among researchers themselves” (p. 226).

Paulus et al. ( 2008 ) claimed that the collaborative process “challenged and transformed our assumptions about qualitative research” (p. 226). Engaging in reflexivity, analysis, and interpretation as a collaborative enabled these researchers to reframe their views about the research process, finding that the process was much more recursive, as opposed to following a linear progression. They also found that cooperatively analyzing and interpreting data yielded “collaboratively constructed meanings” as opposed to “individual discoveries.” And finally, instead of the traditional “individual products” resulting from solo research, collaborative interpretation allowed researchers to participate in an “ongoing conversation” (p. 226).

These researchers explained that engaging in collaborative analysis and interpretation of qualitative data challenged their previously held assumptions. They noted,

through collaboration, procedures are likely to be transparent to the group and can, therefore, be made public. Data analysis benefits from an iterative, dialogic, and collaborative process because thinking is made explicit in a way that is difficult to replicate as a single researcher. (Paulus et al., 2008 , p. 236)

They shared that, during the collaborative process, “we constantly checked our interpretation against the text, the context, prior interpretations, and each other’s interpretations” (p. 234).

We, too, have engaged in analysis similar to these described processes, including working on research teams. We encourage other researchers to find processes that fit with the methodology and data of a particular study, use the techniques and strategies most appropriate, and then cite the utilized authority to justify the selected path. We urge traditionally solo researchers to consider trying a collaborative approach. Generally, we suggest researchers be familiar with a wide repertoire of practices. In doing so, they will be in better positions to select and use strategies most appropriate for their studies and data. Succinctly preparing, organizing, categorizing, and summarizing data sets the researcher(s) up to construct meaningful interpretations in the forms of assertions, findings, themes, and theories.

Researchers want their findings to be sound, backed by evidence, and justifiable and to accurately represent the phenomena under study. In short, researchers seek validity for their work. We assert that qualitative researchers should attend to validity concepts as a part of their interpretive practices. We have previously written and theorized about validity, and, in doing so, we have highlighted and labeled what we consider two distinctly different approaches, transactional and transformational (Cho & Trent, 2006 ). We define transactional validity in qualitative research as an interactive process occurring among the researcher, the researched, and the collected data, one that is aimed at achieving a relatively higher level of accuracy. Techniques, methods, and/or strategies are employed during the conduct of the inquiry. These techniques, such as member checking and triangulation, are seen as a medium with which to ensure an accurate reflection of reality (or, at least, participants’ constructions of reality). Lincoln and Guba’s ( 1985 ) widely known notion of trustworthiness in “naturalistic inquiry” is grounded in this approach. In seeking trustworthiness, researchers attend to research credibility, transferability, dependability, and confirmability. Validity approaches described by Maxwell ( 1992 ) as “descriptive” and “interpretive” also proceed in the usage of transactional processes.

For example, in the write-up of a study on the facilitation of teacher research, one of us (Trent, 2012 ) wrote about the use of transactional processes:

“Member checking is asking the members of the population being studied for their reaction to the findings” (Sagor, 2000 , p. 136). Interpretations and findings of this research, in draft form, were shared with teachers (for member checking) on multiple occasions throughout the study. Additionally, teachers reviewed and provided feedback on the final draft of this article. (p. 44)

This member checking led to changes in some resultant interpretations (called findings in this particular study) and to adaptations of others that shaped these findings in ways that made them both richer and more contextualized.

Alternatively, in transformational approaches, validity is not so much something that can be achieved solely by employing certain techniques. Transformationalists assert that because traditional or positivist inquiry is no longer seen as an absolute means to truth in the realm of human science, alternative notions of validity should be considered to achieve social justice, deeper understandings, broader visions, and other legitimate aims of qualitative research. In this sense, it is the ameliorative aspects of the research that achieve (or do not achieve) its validity. Validity is determined by the resultant actions prompted by the research endeavor.

Lather ( 1993 ), Richardson ( 1997 ), and others (e.g., Lenzo, 1995 ; Scheurich, 1996 ) proposed a transgressive approach to validity that emphasized a higher degree of self-reflexivity. For example, Lather proposed a “catalytic validity” described as “the degree to which the research empowers and emancipates the research subjects” (Scheurich, 1996 , p. 4). Beverley ( 2000 , p. 556) proposed testimonio as a qualitative research strategy. These first-person narratives find their validity in their ability to raise consciousness and thus provoke political action to remedy problems of oppressed peoples (e.g., poverty, marginality, exploitation).

We, too, have pursued research with transformational aims. In the earlier mentioned study of preservice teachers’ experiences learning to teach second-language learners (Cho et al., 2012 ), our aims were to empower faculty members, evolve the curriculum, and, ultimately, better serve preservice teachers so that they might better serve English-language learners in their classrooms. As program curricula and activities have changed as a result, we claim a degree of transformational validity for this research.

Important, then, for qualitative researchers throughout the inquiry, but especially when engaged in the process of interpretation, is to determine the type(s) of validity applicable to the study. What are the aims of the study? Providing an “accurate” account of studied phenomena? Empowering participants to take action for themselves and others? The determination of this purpose will, in turn, inform researchers’ analysis and interpretation of data. Understanding and attending to the appropriate validity criteria will bolster researcher claims to meaningful findings and assertions.

Regardless of purpose or chosen validity considerations, qualitative research depends on evidence . Researchers in different qualitative methodologies rely on different types of evidence to support their claims. Qualitative researchers typically utilize a variety of forms of evidence including texts (written notes, transcripts, images, etc.), audio and video recordings, cultural artifacts, documents related to the inquiry, journal entries, and field notes taken during observations of social contexts and interactions. Schwandt ( 2001 ) wrote,

Evidence is essential to justification, and justification takes the form of an argument about the merit(s) of a given claim. It is generally accepted that no evidence is conclusive or unassailable (and hence, no argument is foolproof). Thus, evidence must often be judged for its credibility, and that typically means examining its source and the procedures by which it was produced [thus the need for transparency discussed earlier]. (p. 82)

Altheide and Johnson ( 2011 ) drew a distinction between evidence and facts:

Qualitative researchers distinguish evidence from facts. Evidence and facts are similar but not identical. We can often agree on facts, e.g., there is a rock, it is harder than cotton candy. Evidence involves an assertion that some facts are relevant to an argument or claim about a relationship. Since a position in an argument is likely tied to an ideological or even epistemological position, evidence is not completely bound by facts, but it is more problematic and subject to disagreement. (p. 586)

Inquirers should make every attempt to link evidence to claims (or findings, interpretations, assertions, conclusions, etc.). There are many strategies for making these connections. Induction involves accumulating multiple data points to infer a general conclusion. Confirmation entails directly linking evidence to resultant interpretations. Testability/falsifiability means illustrating that evidence does not necessarily contradict the claim/interpretation and so increases the credibility of the claim (Schwandt, 2001 ). In the study about learning to teach second-language learners, for example, a study finding (Cho et al., 2012 ) was that “as a moral claim , candidates increasingly [in higher levels of the teacher education program] feel more responsible and committed to … [English language learners]” (p. 77). We supported this finding with a series of data points that included the following preservice teacher response: “It is as much the responsibility of the teacher to help teach second-language learners the English language as it is our responsibility to teach traditional English speakers to read or correctly perform math functions.” Claims supported by evidence allow readers to see for themselves and to both examine researcher assertions in tandem with evidence and form further interpretations of their own.

Some postmodernists reject the notion that qualitative interpretations are arguments based on evidence. Instead, they argue that qualitative accounts are not intended to faithfully represent that experience, but instead are designed to evoke some feelings or reactions in the reader of the account (Schwandt, 2001 ). We argue that, even in these instances where transformational validity concerns take priority over transactional processes, evidence still matters. Did the assertions accomplish the evocative aims? What evidence/arguments were used to evoke these reactions? Does the presented claim correspond with the study’s evidence? Is the account inclusive? In other words, does it attend to all evidence or selectively compartmentalize some data while capitalizing on other evidentiary forms?

Researchers, we argue, should be both transparent and reflexive about these questions and, regardless of research methodology or purpose, should share with readers of the account their evidentiary moves and aims. Altheide and Johnson ( 2011 ) called this an evidentiary narrative and explain:

Ultimately, evidence is bound up with our identity in a situation.… An “evidentiary narrative” emerges from a reconsideration of how knowledge and belief systems in everyday life are tied to epistemic communities that provide perspectives, scenarios, and scripts that reflect symbolic and social moral orders. An “evidentiary narrative” symbolically joins an actor, an audience, a point of view (definition of a situation), assumptions, and a claim about a relationship between two or more phenomena. If any of these factors are not part of the context of meaning for a claim, it will not be honored, and thus, not seen as evidence. (p. 686)

In sum, readers/consumers of a research account deserve to know how evidence was treated and viewed in an inquiry. They want and should be aware of accounts that aim to evoke versus represent, and then they can apply their own criteria (including the potential transferability to their situated context). Renowned ethnographer and qualitative research theorist Harry Wolcott ( 1990 ) urged researchers to “let readers ‘see’ for themselves” by providing more detail rather than less and by sharing primary data/evidence to support interpretations. In the end, readers do not expect perfection. Writer Eric Liu ( 2010 ) explained, “We don’t expect flawless interpretation. We expect good faith. We demand honesty.”

Last, in this journey through concepts we assert are pertinent to researchers engaged in interpretive processes, we include attention to the literature . In discussing literature, qualitative researchers typically mean publications about the prior research conducted on topics aligned with or related to a study. Most often, this research/literature is reviewed and compiled by researchers in a section of the research report titled “Literature Review.” It is here we find others’ studies, methods, and theories related to our topics of study, and it is here we hope the assertions and theories that result from our studies will someday reside.

We acknowledge the value of being familiar with research related to topics of study. This familiarity can inform multiple phases of the inquiry process. Understanding the extant knowledge base can inform research questions and topic selection, data collection and analysis plans, and the interpretive process. In what ways do the interpretations from this study correspond with other research conducted on this topic? Do findings/interpretations corroborate, expand, or contradict other researchers’ interpretations of similar phenomena? In any of these scenarios (correspondence, expansion, contradiction), new findings and interpretations from a study add to and deepen the knowledge base, or literature, on a topic of investigation.

For example, in our literature review for the study of student teaching, we quickly determined that the knowledge base and extant theories related to the student teaching experience were immense, but also quickly realized that few, if any, studies had examined student teaching from the perspective of the K–12 students who had the student teachers. This focus on the literature related to our topic of student teaching prompted us to embark on a study that would fill a gap in this literature: Most of the knowledge base focused on the experiences and learning of the student teachers themselves. Our study, then, by focusing on the K–12 students’ perspectives, added literature/theories/assertions to a previously untapped area. The “literature” in this area (at least we would like to think) is now more robust as a result.

In another example, a research team (Trent et al., 2003 ) focused on institutional diversity efforts, mined the literature, found an appropriate existing (a priori) set of theories/assertions, and then used the existing theoretical framework from the literature as a framework to analyze data, in this case, a variety of institutional activities related to diversity.

Conducting a literature review to explore extant theories on a topic of study can serve a variety of purposes. As evidenced in these examples, consulting the literature/extant theory can reveal gaps in the literature. A literature review might also lead researchers to existing theoretical frameworks that support analysis and interpretation of their data (as in the use of the a priori framework example). Finally, a review of current theories related to a topic of inquiry might confirm that much theory already exists, but that further study may add to, bolster, and/or elaborate on the current knowledge base.

Guidance for researchers conducting literature reviews is plentiful. Lichtman ( 2013 ) suggested researchers conduct a brief literature review, begin research, and then update and modify the literature review as the inquiry unfolds. She suggested reviewing a wide range of related materials (not just scholarly journals) and additionally suggested that researchers attend to literature on methodology, not just the topic of study. She also encouraged researchers to bracket and write down thoughts on the research topic as they review the literature, and, important for this chapter, that researchers “integrate your literature review throughout your writing rather than using a traditional approach of placing it in a separate chapter” (p. 173).

We agree that the power of a literature review to provide context for a study can be maximized when this information is not compartmentalized apart from a study’s findings. Integrating (or at least revisiting) reviewed literature juxtaposed alongside findings can illustrate how new interpretations add to an evolving story. Eisenhart ( 1998 ) expanded the traditional conception of the literature review and discussed the concept of an interpretive review . By taking this interpretive approach, Eisenhart claimed that reviews, alongside related interpretations/findings on a specific topic, have the potential to allow readers to see the studied phenomena in entirely new ways, through new lenses, revealing heretofore unconsidered perspectives. Reviews that offer surprising and enriching perspectives on meanings and circumstances “shake things up, break down boundaries, and cause things (or thinking) to expand” (p. 394). Coupling reviews of this sort with current interpretations will “give us stories that startle us with what we have failed to notice” (p. 395).

In reviews of research studies, it can certainly be important to evaluate the findings in light of established theories and methods [the sorts of things typically included in literature reviews]. However, it also seems important to ask how well the studies disrupt conventional assumptions and help us to reconfigure new, more inclusive, and more promising perspectives on human views and actions. From an interpretivist perspective, it would be most important to review how well methods and findings permit readers to grasp the sense of unfamiliar perspectives and actions. (Eisenhart, 1998 , p. 397)

Though our interpretation-related journey in this chapter nears an end, we are hopeful it is just the beginning of multiple new conversations among ourselves and in concert with other qualitative researchers. Our aims have been to circumscribe interpretation in qualitative research; emphasize the importance of interpretation in achieving the aims of the qualitative project; discuss the interactions of methodology, data, and the researcher/self as these concepts and theories intertwine with interpretive processes; describe some concrete ways that qualitative inquirers engage the process of interpretation; and, finally, provide a framework of interpretive strategies that may serve as a guide for ourselves and other researchers.

In closing, we note that the TRAVEL framework, construed as a journey to be undertaken by researchers engaged in interpretive processes, is not designed to be rigid or prescriptive, but instead is designed to be a flexible set of concepts that will inform researchers across multiple epistemological, methodological, and theoretical paradigms. We chose the concepts of transparency, reflexivity, analysis, validity, evidence, and literature (TRAVEL) because they are applicable to the infinite journeys undertaken by qualitative researchers who have come before and to those who will come after us. As we journeyed through our interpretations of interpretation, we have discovered new things about ourselves and our work. We hope readers also garner insights that enrich their interpretive excursions. Happy travels!

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12 Interpretive research

Chapter 11 introduced interpretive research—or more specifically, interpretive case research. This chapter will explore other kinds of interpretive research. Recall that positivist or deductive methods—such as laboratory experiments and survey research—are those that are specifically intended for theory (or hypotheses) testing. Interpretive or inductive methods—such as action research and ethnography—one the other hand, are intended for theory building. Unlike a positivist method, where the researcher tests existing theoretical postulates using empirical data, in interpretive methods, the researcher tries to derive a theory about the phenomenon of interest from the existing observed data.

The term ‘interpretive research’ is often used loosely and synonymously with ‘qualitative research’, although the two concepts are quite different. Interpretive research is a research paradigm (see Chapter 3) that is based on the assumption that social reality is not singular or objective. Rather, it is shaped by human experiences and social contexts (ontology), and is therefore best studied within its sociohistoric context by reconciling the subjective interpretations of its various participants (epistemology). Because interpretive researchers view social reality as being embedded within—and therefore impossible to abstract from—their social settings, they ‘interpret’ the reality though a ‘sense-making’ process rather than a hypothesis testing process. This is in contrast to the positivist or functionalist paradigm that assumes that the reality is relatively independent of the context, can be abstracted from their contexts, and studied in a decomposable functional manner using objective techniques such as standardised measures. Whether a researcher should pursue interpretive or positivist research depends on paradigmatic considerations about the nature of the phenomenon under consideration and the best way to study it.

However, qualitative versus quantitative research refers to empirical or data-oriented considerations about the type of data to collect and how to analyse it. Qualitative research relies mostly on non-numeric data, such as interviews and observations, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures such as regression analysis, but is coded using techniques like content analysis. Sometimes, coded qualitative data is tabulated quantitatively as frequencies of codes, but this data is not statistically analysed. Many puritan interpretive researchers reject this coding approach as a futile effort to seek consensus or objectivity in a social phenomenon which is essentially subjective.

Although interpretive research tends to rely heavily on qualitative data, quantitative data may add more precision and clearer understanding of the phenomenon of interest than qualitative data. For example, Eisenhardt (1989), [1] in her interpretive study of decision-making in high-velocity firms (discussed in the previous chapter on case research), collected numeric data on how long it took each firm to make certain strategic decisions—which ranged from approximately six weeks to 18 months—how many decision alternatives were considered for each decision, and surveyed her respondents to capture their perceptions of organisational conflict. Such numeric data helped her clearly distinguish the high-speed decision-making firms from the low-speed decision-makers without relying on respondents’ subjective perceptions, which then allowed her to examine the number of decision alternatives considered by and the extent of conflict in high-speed versus low-speed firms. Interpretive research should attempt to collect both qualitative and quantitative data pertaining to the phenomenon of interest, and so should positivist research as well. Joint use of qualitative and quantitative data—often called ‘mixed-mode design’—may lead to unique insights, and is therefore highly prized in the scientific community.

Interpretive research came into existence in the early nineteenth century—long before positivist techniques were developed—and has its roots in anthropology, sociology, psychology, linguistics, and semiotics. Many positivist researchers view interpretive research as erroneous and biased, given the subjective nature of the qualitative data collection and interpretation process employed in such research. However, since the 1970s, many positivist techniques’ failure to generate interesting insights or new knowledge has resulted in a resurgence of interest in interpretive research—albeit with exacting methods and stringent criteria to ensure the reliability and validity of interpretive inferences.

Distinctions from positivist research

In addition to the fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organisations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling —or a variation of this technique—in which cases are chosen randomly from a population for the purpose of generalisability. Hence, convenience samples and small samples are considered acceptable in interpretive research—as long as they fit the nature and purpose of the study—but not in positivist research.

Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and their specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a ’neutral’ or unbiased stance during the data collection and analysis processes, and ensure that their personal biases or preconceptions do not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context, and is not presumed to bias the data collection and analytic procedures.

Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches to data collection and analysis, rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change their original research question if they realise that their original research questions are unlikely to generate new or useful insights. This is a valuable—but often understated—benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and challenges of interpretive research

Interpretive research has several unique advantages. First, it is well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes—such as inter-firm relationships or inter-office politics—where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, it is often helpful for theory construction in areas with no or insufficient a priori theory. Third, it is also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, interpretive research can also help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, interpretive research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than positivist research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, interpretive research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants, and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas which may lead to misleading or false impressions. Inadequate trust between the researcher and participants may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the interpretive researcher to ‘see through the smoke’ (i.e., hidden or biased agendas) and understand the true nature of the problem. Fourth, given the heavily contextualised nature of inferences drawn from interpretive research, such inferences do not lend themselves well to replicability or generalisability. Finally, interpretive research may sometimes fail to answer the research questions of interest or predict future behaviours.

Characteristics of interpretive research

All interpretive research must adhere to a common set of principles, as described below.

Naturalistic inquiry: Social phenomena must be studied within their natural setting.

Because interpretive research assumes that social phenomena are situated within—and cannot be isolated from—their social context, interpretations of such phenomena must be grounded within their sociohistorical context. This implies that contextual variables should be observed and considered in seeking explanations of a phenomenon of interest, even though context sensitivity may limit the generalisability of inferences.

Researcher as instrument: Researchers are often embedded within the social context that they are studying, and are considered part of the data collection instrument in that they must use their observational skills, their trust with the participants, and their ability to extract the correct information. Further, their personal insights, knowledge, and experiences of the social context are critical to accurately interpreting the phenomenon of interest. At the same time, researchers must be fully aware of their personal biases and preconceptions, and not let such biases interfere with their ability to present a fair and accurate portrayal of the phenomenon.

Interpretive analysis: Observations must be interpreted through the eyes of the participants embedded in the social context. Interpretation must occur at two levels. The first level involves viewing or experiencing the phenomenon from the subjective perspectives of the social participants. The second level is to understand the meaning of the participants’ experiences in order to provide a ‘thick description’ or a rich narrative story of the phenomenon of interest that can communicate why participants acted the way they did.

Use of expressive language: Documenting the verbal and non-verbal language of participants and the analysis of such language are integral components of interpretive analysis. The study must ensure that the story is viewed through the eyes of a person, and not a machine, and must depict the emotions and experiences of that person, so that readers can understand and relate to that person. Use of imageries, metaphors, sarcasm, and other figures of speech are very common in interpretive analysis.

Temporal nature: Interpretive research is often not concerned with searching for specific answers, but with understanding or ‘making sense of’ a dynamic social process as it unfolds over time. Hence, such research requires the researcher to immerse themself in the study site for an extended period of time in order to capture the entire evolution of the phenomenon of interest.

Hermeneutic circle: Interpretive interpretation is an iterative process of moving back and forth from pieces of observations (text), to the entirety of the social phenomenon (context), to reconcile their apparent discord, and to construct a theory that is consistent with the diverse subjective viewpoints and experiences of the embedded participants. Such iterations between the understanding/meaning of a phenomenon and observations must continue until ‘theoretical saturation’ is reached, whereby any additional iteration does not yield any more insight into the phenomenon of interest.

Interpretive data collection

Data is collected in interpretive research using a variety of techniques. The most frequently used technique is interviews (face-to-face, telephone, or focus groups). Interview types and strategies are discussed in detail in Chapter 9. A second technique is observation . Observational techniques include direct observation , where the researcher is a neutral and passive external observer, and is not involved in the phenomenon of interest (as in case research), and participant observation , where the researcher is an active participant in the phenomenon, and their input or mere presence influence the phenomenon being studied (as in action research). A third technique is documentation , where external and internal documents—such as memos, emails, annual reports, financial statements, newspaper articles, or websites—may be used to cast further insight into the phenomenon of interest or to corroborate other forms of evidence.

Interpretive research designs

Case research . As discussed in the previous chapter, case research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualised inferences, and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories, or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting, rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Action research . Action research is a qualitative but positivist research design aimed at theory testing rather than theory building. This is an interactive design that assumes that complex social phenomena are best understood by introducing changes, interventions, or ‘actions’ into those phenomena, and observing the outcomes of such actions on the phenomena of interest. In this method, the researcher is usually a consultant or an organisational member embedded into a social context —such as an organisation—who initiates an action in response to a social problem, and examines how their action influences the phenomenon, while also learning and generating insights about the relationship between the action and the phenomenon. Examples of actions may include organisational change programs—such as the introduction of new organisational processes, procedures, people, or technology or the replacement of old ones—initiated with the goal of improving an organisation’s performance or profitability. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may bring forth the desired social change. The theory is validated by the extent to which the chosen action is successful in remedying the targeted problem. Simultaneous problem-solving and insight generation are the central feature that distinguishes action research from other research methods (which may not involve problem solving), and from consulting (which may not involve insight generation). Hence, action research is an excellent method for bridging research and practice.

There are several variations of the action research method. The most popular of these methods is participatory action research , designed by Susman and Evered (1978). [2] This method follows an action research cycle consisting of five phases: diagnosing, action-planning, action-taking, evaluating, and learning (see Figure 12.1). Diagnosing involves identifying and defining a problem in its social context. Action-planning involves identifying and evaluating alternative solutions to the problem, and deciding on a future course of action based on theoretical rationale. Action-taking is the implementation of the planned course of action. The evaluation stage examines the extent to which the initiated action is successful in resolving the original problem—i.e., whether theorised effects are indeed realised in practice. In the learning phase, the experiences and feedback from action evaluation are used to generate insights about the problem and suggest future modifications or improvements to the action. Based on action evaluation and learning, the action may be modified or adjusted to address the problem better, and the action research cycle is repeated with the modified action sequence. It is suggested that the entire action research cycle be traversed at least twice so that learning from the first cycle can be implemented in the second cycle. The primary mode of data collection is participant observation, although other techniques such as interviews and documentary evidence may be used to corroborate the researcher’s observations.

Ethnography . The ethnographic research method—derived largely from the field of anthropology—emphasises studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time—usually eight months to two years—and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a ‘sense-making’ approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the transsituational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviours. While living with chimpanzees in their natural habitat at Gombe National Park in Tanzania, she observed their behaviours, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialise with each other, their communication patterns, their mating behaviours, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996) [3] study of decision-making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and healthcare providers to document their lived experience.

Phenomenology. Phenomenology is a research method that emphasises the study of conscious experiences as a way of understanding the reality around us. It is based on the ideas of early twentieth century German philosopher, Edmund Husserl, who believed that human experience is the source of all knowledge. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences such as human judgment, perceptions, and actions. Its goal is (appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and understanding the symbolic meanings (‘deep structure’) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathise with the participant’s situation, and tune into existential dimensions of that situation so that they can fully understand the deep structures that drive the conscious thinking, feeling, and behaviour of the studied participants.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) [4] developed an existential phenomenological research method to guide studies in this area. This method, illustrated in Figure 12.2, can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation. Examples of questions that may be asked include ‘Can you describe a typical day?’ or ‘Can you describe that particular incident in more detail?’. These interviews are recorded and transcribed for further analysis. During data analysis , the researcher reads the transcripts to: get a sense of the whole, and establish ‘units of significance’ that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as ‘felt-space’ and ‘felt-time’, which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (‘felt-space’)? Did they feel that their experience was pressured, slow, or discontinuous (‘felt-time’)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose his/herself in an imaginary sense into the participant’s situation (i.e., temporarily live the participant’s life). The participants’ lived experience is described in the form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Rigor in interpretive research

While positivist research employs a ‘reductionist’ approach by simplifying social reality into parsimonious theories and laws, interpretive research attempts to interpret social reality through the subjective viewpoints of the embedded participants within the context where the reality is situated. These interpretations are heavily contextualised, and are naturally less generalisable to other contexts. However, because interpretive analysis is subjective and sensitive to the experiences and insight of the embedded researcher, it is often considered less rigorous by many positivist (functionalist) researchers. Because interpretive research is based on a different set of ontological and epistemological assumptions about social phenomena than positivist research, the positivist notions of rigor—such as reliability, internal validity, and generalisability—do not apply in a similar manner. However, Lincoln and Guba (1985) [5] provide an alternative set of criteria that can be used to judge the rigor of interpretive research.

Dependability. Interpretive research can be viewed as dependable or authentic if two researchers assessing the same phenomenon, using the same set of evidence, independently arrive at the same conclusions, or the same researcher, observing the same or a similar phenomenon at different times arrives at similar conclusions. This concept is similar to that of reliability in positivist research, with agreement between two independent researchers being similar to the notion of inter-rater reliability, and agreement between two observations of the same phenomenon by the same researcher akin to test-retest reliability. To ensure dependability, interpretive researchers must provide adequate details about their phenomenon of interest and the social context in which it is embedded, so as to allow readers to independently authenticate their interpretive inferences.

Credibility. Interpretive research can be considered credible if readers find its inferences to be believable. This concept is akin to that of internal validity in functionalistic research. The credibility of interpretive research can be improved by providing evidence of the researcher’s extended engagement in the field, by demonstrating data triangulation across subjects or data collection techniques, and by maintaining meticulous data management and analytic procedures—such as verbatim transcription of interviews, accurate records of contacts and interviews—and clear notes on theoretical and methodological decisions, that can allow an independent audit of data collection and analysis if needed.

Confirmability. Confirmability refers to the extent to which the findings reported in interpretive research can be independently confirmed by others—typically, participants. This is similar to the notion of objectivity in functionalistic research. Since interpretive research rejects the notion of an objective reality, confirmability is demonstrated in terms of ‘intersubjectivity’—i.e., if the study’s participants agree with the inferences derived by the researcher. For instance, if a study’s participants generally agree with the inferences drawn by a researcher about a phenomenon of interest—based on a review of the research paper or report—then the findings can be viewed as confirmable.

Transferability. Transferability in interpretive research refers to the extent to which the findings can be generalised to other settings. This idea is similar to that of external validity in functionalistic research. The researcher must provide rich, detailed descriptions of the research context (‘thick description’) and thoroughly describe the structures, assumptions, and processes revealed from the data so that readers can independently assess whether and to what extent the reported findings are transferable to other settings.

• Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal , 32(3), 543–576. ↵
• Susman, G. I. and Evered, R. D. (1978) An assessment of the scientific merits of action research. Administrative Science Quarterly , 23, 582–603. ↵
• Bluebond-Langer, M. (1996). In the shadow of illness: Parents and siblings of the chronically ill child . Princeton, NJ: Princeton University Press. ↵
• Giorgi, A., & Giorgi, B. (2003). Phenomenology. In J. A. Smith (ed.), Qualitative psychology: A practical guide to research methods (pp. 25–50). London: Sage Publications ↵
• Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry . Beverly Hills: Sage Publications. ↵

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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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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Chandra, Y., Shang, L. (2019). Qualitative Research: An Overview. In: Qualitative Research Using R: A Systematic Approach. Springer, Singapore. https://doi.org/10.1007/978-981-13-3170-1_1

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1.12: Chapter 12 Interpretive Research

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The last chapter introduced interpretive research, or more specifically, interpretive case research. This chapter will explore other kinds of interpretive research. Recall that positivist or deductive methods, such as laboratory experiments and survey research, are those that are specifically intended for theory (or hypotheses) testing, while interpretive or inductive methods, such as action research and ethnography, are intended for theory building. Unlike a positivist method, where the researcher starts with a theory and tests theoretical postulates using empirical data, in interpretive methods, the researcher starts with data and tries to derive a theory about the phenomenon of interest from the observed data.

The term “interpretive research” is often used loosely and synonymously with “qualitative research”, although the two concepts are quite different. Interpretive research is a research paradigm (see Chapter 3) that is based on the assumption that social reality is not singular or objective, but is rather shaped by human experiences and social contexts (ontology), and is therefore best studied within its socio-historic context by reconciling the subjective interpretations of its various participants (epistemology). Because interpretive researchers view social reality as being embedded within and impossible to abstract from their social settings, they “interpret” the reality though a “sense-making” process rather than a hypothesis testing process. This is in contrast to the positivist or functionalist paradigm that assumes that the reality is relatively independent of the context, can be abstracted from their contexts, and studied in a decomposable functional manner using objective techniques such as standardized measures. Whether a researcher should pursue interpretive or positivist research depends on paradigmatic considerations about the nature of the phenomenon under consideration and the best way to study it.

However, qualitative versus quantitative research refers to empirical or data -oriented considerations about the type of data to collect and how to analyze them. Qualitative research relies mostly on non-numeric data, such as interviews and observations, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures such as regression analysis, but is coded using techniques like content analysis. Sometimes, coded qualitative data is tabulated quantitatively as frequencies of codes, but this data is not statistically analyzed. Many puritan interpretive researchers reject this coding approach as a futile effort to seek consensus or objectivity in a social phenomenon which is essentially subjective.

Although interpretive research tends to rely heavily on qualitative data, quantitative data may add more precision and clearer understanding of the phenomenon of interest than qualitative data. For example, Eisenhardt (1989), in her interpretive study of decision making n high-velocity firms (discussed in the previous chapter on case research), collected numeric data on how long it took each firm to make certain strategic decisions (which ranged from 1.5 months to 18 months), how many decision alternatives were considered for each decision, and surveyed her respondents to capture their perceptions of organizational conflict. Such numeric data helped her clearly distinguish the high-speed decision making firms from the low-speed decision makers, without relying on respondents’ subjective perceptions, which then allowed her to examine the number of decision alternatives considered by and the extent of conflict in high-speed versus low-speed firms. Interpretive research should attempt to collect both qualitative and quantitative data pertaining to their phenomenon of interest, and so should positivist research as well. Joint use of qualitative and quantitative data, often called “mixed-mode designs”, may lead to unique insights and are highly prized in the scientific community.

Interpretive research has its roots in anthropology, sociology, psychology, linguistics, and semiotics, and has been available since the early 19 th century, long before positivist techniques were developed. Many positivist researchers view interpretive research as erroneous and biased, given the subjective nature of the qualitative data collection and interpretation process employed in such research. However, the failure of many positivist techniques to generate interesting insights or new knowledge have resulted in a resurgence of interest in interpretive research since the 1970’s, albeit with exacting methods and stringent criteria to ensure the reliability and validity of interpretive inferences.

Distinctions from Positivist Research

In addition to fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organizations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling (or a variation of this technique), where cases are chosen randomly from a population, for purposes of generalizability. Hence, convenience samples and small samples are considered acceptable in interpretive research as long as they fit the nature and purpose of the study, but not in positivist research.

Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and her specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a “neutral” or unbiased stance during the data collection and analysis processes, and ensure that her personal biases or preconceptions does not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context and is not presumed to bias the data collection and analytic procedures.

Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches for data collection and analysis rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change her original research question if she realizes that her original research questions are unlikely to generate new or useful insights. This is a valuable but often understated benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and Challenges of Interpretive Research

Interpretive research has several unique advantages. First, they are well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes, such as inter-firm relationships or inter-office politics, where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, they are often helpful for theory construction in areas with no or insufficient a priori theory. Third, they are also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, interpretive research can also help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, interpretive research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than positivist research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, interpretive research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas, which may lead to misleading or false impressions. Inadequate trust between participants and researcher may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the interpretive researcher to

“see through the smoke” (hidden or biased agendas) and understand the true nature of the problem. Fourth, given the heavily contextualized nature of inferences drawn from interpretive research, such inferences do not lend themselves well to replicability or generalizability. Finally, interpretive research may sometimes fail to answer the research questions of interest or predict future behaviors.

Characteristics of Interpretive Research

All interpretive research must adhere to a common set of principles, as described below.

Naturalistic inquiry : Social phenomena must be studied within their natural setting. Because interpretive research assumes that social phenomena are situated within and cannot be isolated from their social context, interpretations of such phenomena must be grounded within their socio-historical context. This implies that contextual variables should be observed and considered in seeking explanations of a phenomenon of interest, even though context sensitivity may limit the generalizability of inferences.

Researcher as instrument : Researchers are often embedded within the social context that they are studying, and are considered part of the data collection instrument in that they must use their observational skills, their trust with the participants, and their ability to extract the correct information. Further, their personal insights, knowledge, and experiences of the social context is critical to accurately interpreting the phenomenon of interest. At the same time, researchers must be fully aware of their personal biases and preconceptions, and not let such biases interfere with their ability to present a fair and accurate portrayal of the phenomenon.

Interpretive analysis : Observations must be interpreted through the eyes of the participants embedded in the social context. Interpretation must occur at two levels. The first level involves viewing or experiencing the phenomenon from the subjective perspectives of the social participants. The second level is to understand the meaning of the participants’ experiences in order to provide a “thick description” or a rich narrative story of the phenomenon of interest that can communicate why participants acted the way they did.

Use of expressive language : Documenting the verbal and non-verbal language of participants and the analysis of such language are integral components of interpretive analysis. The study must ensure that the story is viewed through the eyes of a person, and not a machine, and must depict the emotions and experiences of that person, so that readers can understand and relate to that person. Use of imageries, metaphors, sarcasm, and other figures of speech is very common in interpretive analysis.

Temporal nature : Interpretive research is often not concerned with searching for specific answers, but with understanding or “making sense of” a dynamic social process as it unfolds over time. Hence, such research requires an immersive involvement of the researcher at the study site for an extended period of time in order to capture the entire evolution of the phenomenon of interest.

Hermeneutic circle : Interpretive interpretation is an iterative process of moving back and forth from pieces of observations (text) to the entirety of the social phenomenon (context) to reconcile their apparent discord and to construct a theory that is consistent with the diverse subjective viewpoints and experiences of the embedded participants. Such iterations between the understanding/meaning of a phenomenon and observations must continue until “theoretical saturation” is reached, whereby any additional iteration does not yield any more insight into the phenomenon of interest.

Interpretive Data Collection

Data is collected in interpretive research using a variety of techniques. The most frequently used technique is interviews (face-to-face, telephone, or focus groups). Interview types and strategies are discussed in detail in a previous chapter on survey research. A second technique is observation. Observational techniques include direct observation, where the researcher is a neutral and passive external observer and is not involved in the phenomenon of interest (as in case research), and participant observation, where the researcher is an active participant in the phenomenon and her inputs or mere presence influence the phenomenon being studied (as in action research). A third technique is documentation, where external and internal documents, such as memos, electronic mails, annual reports, financial statements, newspaper articles, websites, may be used to cast further insight into the phenomenon of interest or to corroborate other forms of evidence.

Interpretive Research Designs

Case research . As discussed in the previous chapter, case research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualized inferences and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Action research . Action research is a qualitative but positivist research design aimed at theory testing rather than theory building (discussed in this chapter due to lack of a proper space). This is an interactive design that assumes that complex social phenomena are best understood by introducing changes, interventions, or “actions” into those phenomena and observing the outcomes of such actions on the phenomena of interest. In this method, the researcher is usually a consultant or an organizational member embedded into a social context (such as an organization), who initiates an action in response to a social problem, and examines how her action influences the phenomenon while also learning and generating insights about the relationship between the action and the phenomenon. Examples of actions may include organizational change programs, such as the introduction of new organizational processes, procedures, people, or technology or replacement of old ones, initiated with the goal of improving an organization’s performance or profitability in its business environment. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may bring forth the desired social change. The theory is validated by the extent to which the chosen action is successful in remedying the targeted problem. Simultaneous problem solving and insight generation is the central feature that distinguishes action research from other research methods (which may not involve problem solving) and from consulting (which may not involve insight generation). Hence, action research is an excellent method for bridging research and practice.

There are several variations of the action research method. The most popular of these method is the participatory action research, designed by Susman and Evered (1978) [13] . This method follows an action research cycle consisting of five phases: (1) diagnosing, (2) action planning, (3) action taking, (4) evaluating, and (5) learning (see Figure 10.1). Diagnosing involves identifying and defining a problem in its social context. Action planning involves identifying and evaluating alternative solutions to the problem, and deciding on a future course of action (based on theoretical rationale). Action taking is the implementation of the planned course of action. The evaluation stage examines the extent to which the initiated action is successful in resolving the original problem, i.e., whether theorized effects are indeed realized in practice. In the learning phase, the experiences and feedback from action evaluation are used to generate insights about the problem and suggest future modifications or improvements to the action. Based on action evaluation and learning, the action may be modified or adjusted to address the problem better, and the action research cycle is repeated with the modified action sequence. It is suggested that the entire action research cycle be traversed at least twice so that learning from the first cycle can be implemented in the second cycle. The primary mode of data collection is participant observation, although other techniques such as interviews and documentary evidence may be used to corroborate the researcher’s observations.

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Qualitative Research Methods

Research methodology discloses the ways in which we approach problems and look for answers. Our assumptions, interests, and purposes influence our selection of methodology and the mode of application. Debates over methodology, therefore, are debates over assumptions and intent, ideology and perspective. No where is this more apparent than in the debates surrounding the use of quantitative versus qualitative methodologies (Harding, 1986; Keller & Longino, 1996; Kerlinger, 1992).

The debate has been largely played out in the academic arena (Taylor & Bogdan, 1998). Academic resistance to qualitative research illustrates the politics and vested interests embedded in the social sciences and academic institutions. Detractors call qualitative researchers soft scientists whose work is full of bias, entirely personal, and unscientific. Proponents of qualitative methods decry quantitative research as upholding the political status quo and proclaim that the premise of qualitative research challenges the very foundations of the scientific achievements of Western civilization. They hail qualitative research as an answer in the search for knowledge that transcends opinion and personal bias, recognizes individual voices and experience, and promotes the interests of marginalized members of society (Keller & Longino, 1996). In many cases, the conflict has been greater than the need to preserve scholarship or further knowledge (Creswell, 1994; Taylor & Bogdan, 1998).

This paper will review qualitative research methodology with an emphasis on the variations among the traditions of qualitative inquiry and the consequent impact on research design.

What is Qualitative Research?

Qualitative research is a growing field of inquiry that cuts across disciplines and subject matter. It is an elaborate, and often perplexing, grouping of terms, concepts, and assumptions that include the traditions associated with positivism, post-structuralism, and many cultural, critical, and interpretive qualitative research perspectives and methods (Banister, Burman, Parker, Taylor, & Tindall, 1994). Qualitative research, by definition, does not rely on numerical measurements, and depends instead on research that produces descriptive data. It subsumes a range of perspectives, paradigms and methods and within each epistemological theory, qualitative research can mean different things (Creswell, 1998).

Because qualitative research does subsume so many traditions of inquiry, there are possibly as many misconceptions about qualitative research methodology as there are definitions (Denzin & Lincoln, 1994a). There are, however, some consistencies among the varieties of qualitative research.

Parker (1994) calls qualitative research “part of a debate, not a fixed truth” (p. 3).   This highlights the nature of qualitative research as an interactive and ongoing process between the researcher and the researched. Banister et al.(1994) define qualitative research as: “an interpretive study of a specified issue or problem in which the researcher is central to the sense that is made (p. 2).”

Denzin & Lincoln (1994b) contribute this more inclusive definition:

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their actual 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. Accordingly, qualitative researchers deploy a wide range of interconnected methods, hoping always to get a better fix on the subject matter at hand (p. 2)

Qualitative versus Quantitative

King (1994) argues that the difference between qualitative and quantitative research is stylistic rather than substantive. The quality of the research, to King, lies in the underlying logic of inference, the quality of the procedure, theoretical basis, goals, and execution. As we know, there is good research that uses both approaches, just as there is bad research.

Both qualitative research and quantitative research seek to understand natural phenomena, provide new knowledge, and permit experience to be replicated in systematic ways. The major difference lies in the goals of each approach. Unlike quantitative research, qualitative research seeks to understand action and experience as a whole and in context. Qualitative research perceives the role of the investigator as integral to the data, not in the traditional view of an objective scientist looking through a telescope.

While quantitative research concentrates on measurements that operationalize constructs, qualitative research uses narrative descriptions, where the words are data and cannot be reduced to numbers. The lack of quantification eliminates the use of statistical analyses for patterns, averages, significance, and probabilities. Instead, the qualitative researcher must use literary and verbal data to reconstruct and understand experience and to identify themes in hopes that a new theory, hypothesis, or relation will be brought to light in ways that extend our understanding. The qualitative investigator is an integrator of the information, giving the data meaning and substance. As such, elimination of investigator bias may not be possible or even desirable.

Qualitative research is in a position to make a unique contribution by elaborating the nature of experience and meaning. Qualitative research has the ability to bring phenomena to life using the explanation of context, multiplicity of voices, and consideration of detail. By bringing experiences to sharp focus, qualitative research can move others to action. Qualitative research projects have triggered policy changes that support more research and better care for AIDS patients (Kazdin, 1998, p. 260), and the advancement of treatment interventions that come from a fuller understanding of lasting distress experienced by victims of childhood abuse (Morrow & Smith, 1995).

Qualitative research does not compete with or replace the value of quantitative research and analysis. Instead, qualitative research can add dimension when reductionist quantitative approaches eliminate the richness, texture, and context. The in-depth study of individuals has made major contributions to clinical psychology (Noblit & Hare, 1988) and the examination of phenomenon in depth permits the generation of hypotheses for further research in both qualitative and quantitative styles (Kazdin, 1998).

Quantitative and qualitative methodologies are framed by different traditions but can be combined to advantage (Denzin & Lincoln, 1994b; Glaser & Strauss, 1967). For example, researchers Campbell and Fisk applied both quantitative and qualitative methods to measure psychological traits. Their aim was to ensure that the variance belonged to the traits being measured, and was not due to methodology (Brewer & Hunter, 1989; cited in Creswell, 1994). Denzin (1978; cited in Janesick, 1994) uses the term triangulation, borrowed from navigation and military strategy, to argue for a combination of data sources and methodologies in the study of the same phenomenon. The concept is based on the assumption that any bias inherent in particular data sources, investigators, and methods would be exposed or neutralized when used in conjunction with other data sources, investigators, and methods (Creswell, 1994). Glaser and Strauss (1967) observe:

There is no fundamental clash between the purposes and capacities of qualitative and quantitative methods or data. What clash there is concerns the primacy of emphasis on verification or generation of theory—to which heated discussion on qualitative versus quantitative data have been linked historically. We believe that each form of data is useful for both verification and generation of theory, whatever the primacy of emphasis…   [author’s italics]

In many instances, both forms of data are necessary—not quantitative used to test qualitative, but both used as supplements, as mutual verification, and most important for us, as different forms of data on the same subject, which, when compared, will each generate theory…   (p.17-18)

History and Intellectual Heritage

Qualitative research has existed in various forms within fields of social science for almost a century (Tesch, 1990). From the inception, there has been tension between the scholars who advocated objective results that were consistent with the techniques of the natural sciences and those who felt that the phenomenon of human consciousness was too complex to be captured without a different approach (Tierney & Lincoln, 1994). Two philosophical perspectives embodying these distinctions, positivism and phenomenology, have dominated in the social sciences (Taylor & Bogdan, 1998).

From a positivist perspective, a researcher seeks facts or causes of social phenomena independent from the subjective states of individuals. Positivism and the idea of scientific research was spawned by the works of Francis Bacon and Sir Isaac Newton and dates to the 17 th century. However, it was two centuries later when “science” emerged to challenge the authority of the Bible and organized religion as the sources of knowledge (Polkinghorne, 1983, p. 16). The burgeoning of the systematic study of human phenomena in history, languages and social institutions, along with the philosophical contributions of Thomas Hobbes, Auguste Comte, and John Stuart Mill, provided a firm philosophical and logical foundation for positivist empiricism as the basis of knowledge (Denzin & Lincoln, 1994a).

The anti-positivist response, a precursor of phenomenology, was inspired by the idealistic and Romantic legacy of philosophers such as Fichte and Schelling in Germany. Although not a unified response, there was general agreement among the anti-positivists that positivism neglected the “unique sphere of meaningful experience that was the defining characteristic of human phenomena and called attention to the sphere of reality that exists because of human beings”(Polkinghorne, 1983, p. 21). The philosophy of Wilhelm Dilthey, who had a prominent voice in the anti-positivist movement, was a harbinger of constructivist thought. He argued that individuals stand in a complex texture of relationships with others. Because individuals do not exist in isolation, he asserted, they cannot be studied outside of the context of their connections to cultural and social life. (Polkinghorne, 1983).

Phenomenology’s influence is great in both philosophy and sociology, where researchers were striving to understand social phenomena from the individual’s own perspective and experience. These philosophical lines of thought have nourished many themes central to qualitative research in postmodern thought, hermeneutics, and dialectics (Kvale, 1992).

Beginning in sociology, the philosophical evolution of qualitative research has been complex, intertwined with influences across disciplines and methods. Tesch (1990) articulated over twenty philosophical influences in this process, see the following flow chart. It is not surprising that there is so little agreement and clear definition in a field where individual experience is valued over reductionist uniformity.

Philosophical Heritage of Qualitative Research in Sociology and Psychology

(Source: Adapted from Tesch, 1990)

Guba & Lincoln (1994) summarize the field into four major ideological models vying for acceptance among researchers: positivism, postpositivism, critical theory (which includes related ideological positions such as feminist and Marxism), and constructivism. Postmodernism may best be viewed as a family of theories consistent with aspects of critical theory, constructivism and phenomenology (Creswell, 1998). As with the anti-positivists of the late 19 th century, postmodernists eschew the glorification of rationality and reason of the 19 th century Enlightenment. Critical of the 20 th century emphasis on technology, , universals, science, and the positivist, scientific method, postmodern thinking emerged in the humanities of the 1960s and by the 1990s has made a full scale invasion in the social sciences. Postmodern thought centers on the idea that knowledge must be defined within the context of the world today and in the multiples perspectives of race, gender, class, and other groups associations. Postmodernism is characterized by a number of interrelated characteristic and encourages the reading of qualitative narratives as rhetoric and a state of social being (Agger, 1991; in Creswell, 1998) Here is a summarized overview of Guba & Lincoln’s four models:

Overview of Qualitative Traditions

Qualitative research, though common in sociology and anthropology, had been applied in a nonsystematic and nonrigorous way and achieved little success at theory generation in the first half of the 20 th century (Glaser & Strauss, 1967). Quantitative researchers, however, were making considerable progress after World War II in advancing statistical measures, producing accurate evidence, and translating theoretical concepts into testable constructs. The enthusiasm to test unconfirmed theories, relegated qualitative work to preliminary, exploratory work for starting surveys. American sociology was soon awash in the emerging systematic canons and rules of evidence of quantitative analysis, including sampling, reliability, validity, frequency distributions, hypothesis construction, and the parsimonious presentation of data (Glaser & Strauss, 1967). Advocates of qualitative data tried to systematize the ways in which they collected, assembled and presented data, using the verification rhetoric of quantitative methodology (Glaser & Strauss, 1967, p. 15). Never the less, interest in qualitative methodology waned at the end of the 1940s (Taylor & Bogdan, 1998).

The end of the Cold War and the deconstruction of the Soviet Union revived nationalist and ethnic claims in almost every part of the world. In this newly decentralized world, cultural pluralism became the new shibboleth. The quandaries once posed by cultural relativism have been replaced by the questions arising out of the alleged certainties of primordial descent (Vidich & Lyman, 1994).

In spite of their history elsewhere, qualitative methods are relatively recent arrivals in psychology. They emerged initially as panoply of alternative approaches to those in the mainstream (Taylor & Bogdan, 1998). As interest in qualitative research increased, acceptance of these methods in applied fields, such as program evaluation, policy research, health research, education, social work, special education, treatment outcome, and organizational research, has grown.

Qualitative research is now emerging as a dominant paradigm, consistent with the heightened social and political sensitivity to cultural, contextual, and relational issues. The editorial boards of scholarly journals, always slow to accept change, are beginning to acknowledge the role that qualitative research plays and usage, once limited to management, education, and nursing applications, is increasingly widespread.

Assumptions in Qualitative Methodology

From its inception, qualitative research has sought to provide a vehicle for interpreting another’s experience. Early qualitative researchers made two assumptions. They believed that competent observers could objectively and clearly report on their observations in the social world and on the experiences of others. Researchers also assumed that an individual is able to report on his or her experiences. By combining their observations with the observations provided by subjects through interviews, life stories, personal experiences, and other documents, qualitative researchers sought to reveal the meaning their subjects brought to their life experiences (Denzin & Lincoln, 1994a).

The advent of the postmodernism and poststructuralism has challenged these assumptions, arguing that there is no “clear window to the inner life of the individual” (Denzin & Lincoln, 1994b, p. 12). They assert that there are no objective observations, only observations socially situated in the worlds of the observed and the observer; no single method can grasp the subtle variation in ongoing human experience. As a consequence, qualitative researchers increasingly use a wide range of interconnected, interpretive methods, always seeking improvements in the understanding of the worlds of experience they study (Guba & Lincoln, 1994).

There are some assumptions, however, that remain fundamental to all qualitative methods. a) The researcher’s framework about the nature of reality reflects his or her history, values, class, race, culture, and ethnic perspective. b) The researcher’s perspective inspires a set of questions that are examined in specific ways. c) The relationship between the researcher and the researched reflects the researcher’s epistemological perspective. d) The examination and interpretation of observations, interviews, and other artifacts enables an emerging process of constructed meaning. (Creswell, 1998; Denzin & Lincoln, 1994b).

Nearly all qualitative researchers now acknowledge that their research contains interpretive elements. Most accept the assumption that reality is mediated by many influences, such as the researcher’s bias, the context of the study, the audience for which the text is prepared, and the theoretical framework. Spindler emphasizes the need for researchers studying their own environments to accept the opposite, “making the familiar strange” to create a subjective distance (cited in Tierney & Lincoln, 1994, p. 111). Although we can never entirely step outside our selves, backing away from the data and phenomena enables us to see meanings we might miss in the context. This is well described by a quote from Margaret Mead, who said, “if a fish were to become an anthropologist, the last thing it would discover would be water” (cited in Tierney & Lincoln, 1994, p. 111).

Methodology

Contrary to what you may have heard, qualitative research designs do exist.” (Miles & Huberman, 1994, p. 16)

Qualitative research has evolved from the time where one went into the field and conducted fieldwork; anthropologists once believe that fieldwork was not something you could train people for, you had to do it (Tierney & Lincoln, 1994, p. 108). Now we recognize that methodological choices imply theoretical assumptions and that these assumptions influence virtually every part of the methodological undertaking. Mary Lee Smith (1987; cited in: Tierney & Lincoln, 1994) argues, for example, that different traditions also have different requirements for reliability and validity. Accordingly, in order to be an adequate judge of qualitative research, we must be aware of the questions of trustworthiness implied by each theoretical school.

Qualitative research is not a singular method, overall design strategy, or philosophical stance, even thought there are attempts to bring coherence to the differences among schools and postures. Tierny & Lincoln (1994) suggest that it is the nature of interpretation to be contradictory and have too many meanings. The process of interpretation connects us with the world, reaches into the gap between objects and our representation of them, and continues as our relationship with the world goes on.

The difference between objects and our representation of them is not unique to psychology; it appears in all sciences. Three aspects describe this disparity: a) indexicality occurs when an explanation is always tied to a particular circumstance and will change as the occasion changes; b) inconcludability occurs when supplementation to meaning causes continued mutation; and c) reflexivity describes the reciprocal influence of the way in which we model a phenomenon and our perception of the way it performs (Banister et al., 1994). These are deadly problems in quantitative research, but opportunities in qualitative inquiry. A qualitative researcher in psychology starts at the gap between the object of the study and the way we represent it; the interpretation generated closes the gap as the researcher connects and exchanges meaning with the participant.

As a set of interpretive practices, qualitative research advocates no single methodology over another. It is used in many separate disciplines and it does not belong to a single discipline (Denzin & Lincoln, 1994b). Qualitative research does not have a set of methods entirely its own. Creswell summarizes traditions into five different traditions or strategies of inquiry based upon their representation in the literature–biography, phenomenology, grounded theory, ethnography, and case studies (Creswell, 1998). Some authors (e.g. Denzin & Lincoln, 1994b; Guba & Lincoln, 1994) present similar summaries, while other authors do not distinguish beyond the theoretical bases, suggesting that theory provides the primary decision structure (Taylor & Bogdan, 1998). Still others do not acknowledge different qualitative models of inquiry at all (Bordens & Abbott, 1996; King et al., 1994).

Within the qualitative tradition, polarized debates arise from time to time demanding practitioners declare allegiance to one school or another (Taylor & Bogdan, 1998). Differences still exit among the various theoretical perspectives today. Taylor & Bogdan (1998) summarize these perspectives around three questions: 1) What is the relationship between the observer and the observed? 2) Whose side are we on? 3) Who cares about the research?

Qualitative researchers differ on the relationship between the researcher and the researched. At one extreme are researchers who share with the positivists a belief that realist exists and can be more or less objectively known by an unbiased researcher. Whyte holds firm to the belief that social and physical facts can be objectively discovered and reported on by a conscientious researcher (Denzin, 1992). At the other end of the spectrum are some postmodernists who believe that objective reality does not exist and that all knowledge is subjective and only subjective (Cole, 1994). For example, Denzin takes the position that there is no difference between fact and fiction; from this perspective ethnography becomes autobiography (Taylor & Bogdan, 1998). The views of most qualitative researchers fall somewhere between these two positions (Taylor & Bogdan, 1998). Within phenomenological, symbolic interactionist, and ethnomethodological perspectives, it is taken for granted that reality is socially constructed.

Kerlinger (1992), in writing the classic, Foundations of Behavior Research , clarified and distinguished between quantitative techniques, such as ex post facto, experimental, and survey designs. His work influenced later thinking about the types of quantitative designs (Creswell, 1994). Creswell (1998) suggests that clarity and comparison are needed in qualitative inquiry, too. Comparisons facilitate understanding and contribute to more rigorous and sophisticated designs (Glaser & Strauss, 1967; Strauss & Corbin, 1997).

Research Traditions

The definitions below are intended to provide an overview of variations in perspective and approach of differing qualitative traditions. They are not intended to be inclusive of the full range of diversity within qualitative research.

Grounded Theory

Grounded theory was conceived as a research methodology for generating theory rather than accepting a priori assumptions. Where quantitative researchers are trained to research and verify facts; qualitative researchers work to generate an explanation (Glaser & Strauss, 1967). Glaser & Strauss (1967) submit that this helps to eliminate opportunistic use of theories with dubious fit and working capacity.

Grounded theory is a comprehensive method of data collection, analysis and summarization in which an emergent theory is constructed from, and therefore grounded in, direct experience with the phenomena under study (Richie et al., 1997). Data collection, analysis, and theory construction occur concurrently in a reciprocal relationship (Strauss & Corbin, 1997). Grounded theory puts a high emphasis on “theory as process,” a continuously developing form that is not a perfect product (Glaser & Strauss, 1967, p. 32). There is no formal hypotheses developed for testing. Instead, a grounded theory approach attempts to generate an emergent theory reflective of the subjects’ experiences and voice, from their own phenomenological perspectives.

Grounded theory provides a systematic approach to qualitative subject matter. There are formal guidelines for collecting information, guarding against or minimizing bias, making interpretations, checking on interpretations, and ensuring internal consistency and confirmability of findings.

Richie, Fassinger, Linn, Johnson, Prosser & Robinson (1997) used grounded theory methodology to generate theory in “Persistence, Connection, and Passion: A Qualitative Study of the Career Development of Highly Achieving African American-Black and White Women.” The research team selected a sample of eighteen prominent, highly achieving African American-Black and White women in the United States across eight occupational fields. They collected data in semistructured interviews about the women’s experiences pursuing careers and professional success. Using a twelve member research team, Richie et al. focused numerous discussions on data analysis as well as the possible power differentials among team members. Effort was taken to make sure that each member, no matter when they joined the team, was ensured of an equal voice. This view was promoted due to the belief that multiple perspectives would aid in the ongoing articulation and management of subjectivity in data analysis, which Guba and Lincoln call “peer debriefing.”(1986; cited in Greene, 1994).

Using open coding, the data was coded into approximately 3,000 separate concepts, such as early lack of self-confidence . In open coding the research team creates initial categories of information about the phenomenon of interest. Within each category, the team finds properties or subcategories, and looks for data to show the possibilities of, or dimentionalize (Creswell, 1998), each property on a continuum.

The concepts were abstracted and grouped into 123 categories, such as work attitudes and peer career support . The team used axial coding to determine relationships among the categories that emerged from open coding. In axial coding, the research team assembles the data in new ways using a coding paradigm or logic diagram in which the researchers identify a central phenomenon, explore conditions that influence the phenomenon, specifies strategies or actions that result from the phenomenon, identifies the context and intervening conditions, and delineates the outcomes (Creswell, 1998).

The axial coding was the basis for the regrouping into higher order categories, resulting in fifteen distinguishable key categories, such as wanting to change the world, (Richie et al., 1997, p. 7).

As part of the procedure, Richie et al. (1997) used a number of strategies to increase the reliability and validity of the data. The team trained interviewers and both pretested and revised the interview protocol as suggested by Kerlinger (1992). Internal consistency was enhanced by using more than one judge or analyzer of the data. Citing the work of Marshall & Rossman (1989), Richie et al. (1997) encouraged all team members to offer challenges and alternate explanations to the prevailing assumptions.

Internal validity was proposed to be high since the conclusion of the research was grounded in and emerged directly from the data. The results of the study have face validity because the data generated the results directly and created results credible to both participants and consumers of the research. The work on “validity” of narratives emerging from interpretive studies suggests the importance of “verisimilitude” (Van Maanen, 1998; cited in Miles & Huberman, 1994) and authenticity. Kvale (1996) emphasizes validity as a process of checking, questioning and theorizing, not the establishment of rule-based equivalencies with the “real world.” Kvale (1996) observes:

The complexities of validating qualitative research need not be due to an inherent weakness in qualitative methods, but may on the contrary rest on their extraordinary power to picture and to question the complexity of the social reality investigated. (p. 244)

The authors discuss potential limitations that are factors for consideration in many grounded theory based studies. These include researcher bias in interview protocol and data interpretation, although efforts were taken to account for these possibilities by using a team approach and encouraging continued discussion and arbitration of disagreements and conclusions. Richie et al. (1997) also state that the use of grounded theory has potential for individual differences among participants to dissipate once analytic procedures are set into motion. In the grounded theory approach, discrete concepts are collapsed into increasingly general, abstract categories, which are constrained by the applicability to all participants. Consequently, variant responses and unique experiences may receive scant attention. Finally, sampling restrictions may be present in the study due to geographical considerations, the self-selection of the participants, and the time constraints on high achieving women. The standard for selecting these women may have been skewed by social factors, for example, toward women who enjoyed discussing their lives, or who believe in helping other women, among many possibilities. In addition, the study excluded women who were successful outside the workforce, such as homemakers or volunteers.

Richie et al. (1997) presented their results as a central or core story category consisting of beliefs the women held about them. They suggest that comparing their model with existing vocational literature is one method in which qualitative research can be used to increase the knowledge base of theory and empirical findings. Richie et al. felt their study illustrated many ways in which women’s career development differed from men’s and confirmed the inappropriateness of using career theories based upon sample of White men to White women and people of color.

A biographical study focuses on one individual and his or her experiences as told to a researcher or found in documents and archival material. From a postmodern or constructivist perspective, all methods are biographical in the sense that they are constructed from the personal histories of the investigator and the subject. Biographies cut across all social science disciplines and takes many different forms, including objective, historical, narrative, institutional, personal, or fictional (Smith, 1994). Denzin defines the biographical method as “studied use and collection of life documents that describe turning-point moments in an individual’s life” (1989; cited in Creswell, 1998, p. 47).

The investigator begins with an objective set of experiences in the subject’s life, noting life course stages and experiences. With a focus on gathering and organizing stories, the researcher explores the meanings of the stories looking for pivotal events and multiple meanings. At the same time, the researcher must be aware of the historical context and larger structures that may contribute to meanings, such as social interactions or cultural issues (Creswell, 1998).

The biography has not been a common form of research in psychology (Smith, 1994). An exception, however, is found in work by Henry Murray. Murray published several works, including the Use of Personal Documents in Psychological Science (1942) and Letters from Jenny (1965.) The Letters are a detailed account that provide a “vivid, troubling, introspective accounts of both her [Jenny’s] life as a working woman and mother and her accompanying mental states.” (Smith, 1994, p. 297).

Phenomenology

A phenomenological study is concerned with reality-constituting interpretive practices and describes the meaning of lived experiences for several individuals about a single phenomenon. Rooted in the philosophy of Husserl, Heidegger, Sartre, and Merle-Ponty (Creswell, 1998; Polkinghorne, 1983), it has been used in psychology, sociology, nursing and health sciences, and education (Tesch, 1990).

Many researchers use participant observation and interviewing as ways of investigating the interpretive practices of individuals (Holstein & Gubrium, 1994). Some investigators, more firmly grounded in the ethnomethodological tradition, argue against the use of any method as a tool that may only serve to produce verifiable findings for a given paradigm (Denzin & Lincoln, 1994b).

The phenomenological approach focuses on the interpretive procedures and practices that give structure and meaning to everyday life. These form the substance and the resources for the inquiry. From this framework, knowledge is local and embedded in the culture and organizational relations. Local culture contains stereotypes and ideologies, implications for gender, race and class, and the understandings about the rules of society that can also inspire critical, feminist, and Marxist theorists (Denzin & Lincoln, 1994b; Kitayama & Markus, 1995; Riger, 1995).

In a phenomenological study, researchers search for the essential or invariant structure that illuminates the underlying meaning of the experiences (Creswell, 1998). Phenomenology emphasizes the intentionality of consciousness that is expressed in both outward appearance and inward consciousness based on images, recollection, and interpretation. In phenomenology, reality is not divided into subjects and objects. Consciousness is always aimed toward an object; consequently the reality of an object is inextricably intertwined with our consciousness of it (Holstein & Gubrium, 1994). Reality only exists within the meaning of the individual’s experience.

Phenomenological data analysis employs the reduction of data, the analysis of specific passages, individual elements of discourse, and patterns, as well as a search for all possible meanings. The investigator attempts to set aside all personal judgments and expectations by bracketing his or her experiences. Bracketing is equivalent to Husserl’s notion of epoche , the suspension of “all judgments about what is real—the ‘natural attitude’—until they are founded on a more certain basis” (Creswell, 1998, p. 52).

In contrast to sociology, phenomenology in field of psychology places more importance on bracketing out prejudgments and developing universal structures. Moustakas (1994; cited in Creswell, 1998) observes that this approach focuses on the meaning of individual rather than group experiences with emphasis on:

…what an experience means for the persons who have had the experience and are able to provide a comprehensive description of it.   From the individual descriptions, general or universal meanings are derived, in other words, the essences of structures of the experience. (p. 54)

Worthen & McNeill (Worthen & McNeill, 1996) used a phenomenological approach in their investigation “A Phenomenological Investigation of ‘Good’ Supervision Events.” This study was conducted from the perspective doctoral level clinical supervisees regarding their experiences of supervision events. Worthen & McNeill established a general meaning structure for and identified the salient themes reflective of the experience of good supervision events. They interviewed eight trainees, four men and four women of European-American ethnicity. Although all interviews were conducted and taped by Worthen, a European-American, McNeill, who is of mixed Mexican-American and European-American descent, and an external auditor, participated in and reviewed the interpretive process and results. A research question was developed to guide the investigation: “Please describe for me as completely, clearly, and concretely as you can, an experience during this semester when you felt you received good psychotherapy supervision.” This was followed by prompts for clarification and elaboration as necessary with questions such as, “Can you describe what you felt like?” and “and how did he show that understanding?” (Worthen & McNeill, 1996, p. 28)

Worthen & McNeill went through the following steps, which they adapted from a pattern outlined by Giorgi (1985, 1989; cited in Worthen & McNeill, 1996).

The investigators obtained a sense of the whole from the transcript analysis by listening to the tapes and reading the transcripts several times.

They then identified meaning units by reviewing the transcripts for shifts in meaning. Meaning units represent small, more easily analyzable components. In a phenomenological study, the researcher lists the meaning units and then writes a description of the textures, or textural description, of the experience including literal examples (Creswell, 1998).

Worthen & McNeill then examined the meaning units for relevancy to the research question and discarded those deemed irrelevant.

Integration of the meaning units was achieved by creating a temporal sequence of events to more fully understand the contextual relationship.

The participants’ unanalyzed descriptions of their experiences were then translated into psychologically relevant meanings. Derived meanings were tested against raw interview data by moving back and forth from data to meanings to determine whether they were supported by the data. In the phenomenological process, the researcher reflects on his or her own description and uses “imaginative variation or structural description” to find all possible interpretations and conflicting perspectives by changing the contexts about the phenomenon and constructing a portrayal of how the phenomenon was experienced (Creswell, 1998, p. 150).

The articulated meaning units were then integrated and expressed into a meaningful description of a good supervision experience. These are termed situated meaning, which refers to meaning derived from the context of a specific situation.

From the situated meanings, the descriptions were distilled into a concise form that answered the question: “What is absolutely essential for this experience of good psychotherapy supervision, for which if it were missing this would not represent the experience of good supervision?” (Worthen & McNeill, 1996, p. 30).

The authors discussed the limitations on the generalizability of the results due to the small sample and potential cultural bias of the participants. Worthen and McNeill (1996) summarized the essence of the experience of good supervision through a series of themes–such as sensed inadequacy and sensed supervisor empathy –in the temporal order of appearance.

Ethnography

Denzin & Lincoln (1994) refer to ethnography as:

perhaps the most hotly contested site in qualitative research today. Traditionalists (positivists), postpositivists, and postmodernists compete over the definitions of this field, the criteria that are applied to its texts, and the reflexive place of the researcher in the interpretive process. (p. 203)

An ethnography is a description and interpretation of a cultural or social group or system (Creswell, 1998). The process of ethnographical research typically involves participant observation in which the researcher is immersed in the population of interest. From this vantage, he or she studies the meanings of behavior, language and the interactions of the culture-sharing group (Atkinson & Hammersley, 1994). Culture has been multiply defined, but it commonly refers to the beliefs, values and attitudes that structure the behavior patterns of a specific group of people (Merriam, 1998).

Ethnography had its conception in anthropology and the studies of comparative cultures by scholars such as Mead, Malinowski, and Boas (Creswell, 1998). Atkinson & Hammersley (1994) summarize ethnographical approach based from a sociological vantage. a) There is a strong emphasis on exploring the nature of a social phenomenon. b) Ethnography has a strong tendency to work with unstructured or unanalyzed data. c) The inquiry is limited to a small number of cases or one detailed case. d) The data analysis in an ethnographic inquiry involves explicit interpretation of the meanings and function of behaviors. These can be presented as forms of verbal description and explanations.

Wilson (1997), in “Lost in the Fifties: A Study of Collected Memories,” uses an ethnographic approach to capture the culture and varied meanings of the 1950s through a series of unstructured interviews, artifacts, news media, and popular media. Creswell (1998) provides an example of an ethnographic study by Wolcott (1974; cited by Creswell, 1998) “The Elementary School Principal: Notes from a Field Study.”   This project was developed to provide an account of elementary school principalship through a series of interviews and documents.

Merriam (1998) observes that, “those with little or no preparation in qualitative research often designate the case study as a sort of catch-all for research that is not a survey or an experiment and is not statistical in nature” (p. 19).

A case study is discriminated from other types of qualitative research by the intensive focus on the description and analysis of a single unit, or bounded system (Creswell, 1998; Merriam, 1998). The object of the inquiry can be an individual, program, event, group, intervention or community, but the topic must deal with specificities not generalities. For example, a nurse may be a case, but his or her nursing lacks the specific boundaries to be called a case (Stake, 1994).

Case researchers seek out what is common and what is distinct about a case. The results, however, typically manifest something unique. Stake (1994) suggests that “uniqueness is likely to be pervasive” (p. 238) and will extend to the case’s nature, historical background, physical setting, economic, political, or aesthetic contexts, sources of information, and reference cases.

The researcher gathers information from all these areas, drawing on multiple sources such as observations, interviews, documents, audio-visual materials, and other media. The type of analysis can be either holistic, examining the entire case, or embedded analysis, which focuses on a single aspect (Yin, 1989; cited inCreswell, 1998). A detailed description is constructed and an interpretive analysis works toward emerging themes. The researcher tells the narrative using a chronology of major events followed by detailed examples, context, and interpretation. When multiple cases are presented, the researcher will typically provide a within-case analysis with a detailed description of each case, and a cross-case analysis tracing the themes throughout (Merriam, 1998).

McRae (McRae, 1994) uses a case study approach in “A Woman’s Story: E Pluribus Unum,” presenting the life of Louisa Rogers Alger. McRae traces the life of Ms. Alger through narratives, correspondence, documents, and interviews. She examines the forces, social and historical context, and experiences that shaped the identity and life of the then 93 year old Ms. Alger against a backdrop of feminist comparison and analysis (McRae, 1994)

Designing a Qualitative Project

Criteria for the selection of methodologies and traditions.

Creswell (1994) suggest several factors that need to be considered when selecting a research methodology. These include the researcher’s world view, training and experiences, psychological attributes, the nature of the problem, and the audience.

A researcher needs to be comfortable with the ontological, epistemological, axiological, rhetorical, and methodological assumptions of the qualitative traditions. Training and experiences should include literary writing skills, computer-text analysis skills, and library skills. The qualitative traditions do not provide a specific set of rules and procedures so the researcher must be willing and able to tolerate uncertainty and ambiguity as well as have patience for a potentially lengthy study.

While it is debatable whether certain issues are better for qualitative or quantitative studies (Creswell, 1994; Glaser & Strauss, 1967; King et al., 1994), the nature of the problem is a significant factor. In a qualitative study, the research question needs to be explored because little information exists and the variables are mostly unknown. The investigator focuses on the context that may shape the understanding of the phenomenon being studied, rather than relying on a theoretical base that may not even exist (Creswell, 1994).

Ethical Issues in Qualitative Inquiry

Laura will thoroughly address the topic of ethics in research. I want to mention, however, a couple of issues pertaining directly to qualitative research.

Deception of subjects is both a methodological and a moral issue; it is part of the question of treating people as subjects or as peers. Psychology, due to its reflexive quality, must take a morally and politically sensitive stand. Because the participant and the researcher work together, qualitative research eliminates most concerns of personal reactivity as a threat to procedural integrity, such as demand characteristics, volunteer characteristics, or experimenter effects.

Qualitative inquiry, however, has special characteristics that create ethical questions and dilemmas that do not often arise in experimental or survey research. It is important to be aware and consider each of these issues in the planning stage of the project: a) maintaining anonymity and confidentiality while using the direct works of the respondents to tell the story; b) recognizing the potential intensity and friendships that can be generated from a face to face relationship; c) writing with balance and fairness; and d) separating from the site in ways which preserve and enhance the dignity and respect of the participants and honor the new relationships that have developed (Glaser & Strauss, 1967; Josselson & Lieblich, 1996; Kazdin, 1998; Kvale, 1996).

The American Psychological Association (APA) Code of Ethics and the federal government regulations help protect human subjects’ privacy, confidentiality, anonymity and informed consent, but provide few guidelines for the dilemmas which might arise in the course of a qualitative research project (Keith-Spiegel & Koocher, 1995). Qualitative researchers may be subject to abuses or may subject research participants to types of vulnerability uncommon in quantitative research that require foresight and sensitivity.

Format for a Qualitative Research Design

Once the researcher establishes the framework and intent of qualitative research, the study can be designed (Miles & Huberman, 1994). The format of a qualitative study follows many of the traditional steps for presenting a research problem. However, qualitative designs have several unique features.

The researcher frames the study within the assumptions and characteristics of the qualitative approach, including an evolving design, the presentation of multiple realities, the researcher as an instrument of data collection and a focus on the participants’ views. This guides the researcher toward the identification of an appropriate tradition of inquiry and any attendant ethical issues.

The project should begin with a single, well-defined focus or issue that the researcher wants to understand with an overall strategy and rationale. The development of the statement of the problem should include examining the significance of the study. A literature review is used to develop interview questions and concepts, compare the constructs in the literature with those from emerging data, as well as to compare the final results with existing constructs. This facilitates refocusing and refining the research questions and aids in determining the significance and limitations of the study.

The research design includes a description of the specific setting, population or phenomenon and a detail plan of tasks, schedules, and deadlines. The project can be designed as emergent to respond to patterns and data as they occur, but it is critical to have plans and procedures in place (Creswell, 1998; Glaser & Strauss, 1967; Merriam, 1998; Miles & Huberman, 1994). Everything from the gathering and recording of fieldnotes, a plan for data management, data coding and retrieval systems, reflexive logs or journals, to a system of ongoing analysis needs to be thought through and clearly articulated. Computer software is now available for the process of data management, making connections, and interpreting data. There are several varieties of programs with different capabilities. These include word processors (Microsoft Word, WordPerfect), database managers (Access, FilemakerPro, Quattro), and text analysis and theory-building programs (QUALPRO, NUD*IST, AQUAD) (Tesch, 1990) as well as a new generation of  text analyzers with visual simulators (Leximancer, Dedoose, etc.). Software is very helpful and powerful; some programs display information in graphical hierarchies, as narratives, as selected word and meaning groups, and even highlight possible patterns (Tesch, 1990). Underlying assumptions shape each program, however, so it is important to be knowledgeable about your research problem and intentions in order to assure a useful software match.

The Quality of Data

Verification is an important issue in qualitative research. Tierney & Lincoln note that “the final report can not be better than the original data” (Tierney & Lincoln, 1994, p. 117). The goal of research is to provide information that has validity. In qualitative research, validity is determined by internal replicability; whether the analysis has some truth or confirmability. This includes coherence of interpretation, agreement among others including the participants, and the consensus that understanding is enhanced as a result of the analysis and that the analysis is salient (Kazdin, 1998, p. 253).

Reliability refers to the methods of studying the data, such as determining in what manner the themes and categories were developed. Reliability focuses on internal consistency. Qualitative research uses many other terms to describe the quality of the data. Trustworthiness refers primarily to credibility and to transferability (Guba & Lincoln, 1994). Credibility describes the appropriateness of the methods and subjects to the goals. Transferability indicates the contextual limitations of the data. Dependability pertains to the quality of the conclusions and data evaluations that framed them, Confirmability indicates the ability of an outside reviewer to audit the procedures and analysis and reach the same conclusions (Creswell, 1994; Kazdin, 1998)

Richie et al. (1997) discussed various measures taken to improve confirmability and transferability in the study on career development. For example, specific wording was chosen that would minimize response bias due to preconceptions of constructs already in psychological literature. The word handle was used instead of cope , believe internally replaced references to self-efficacy or attributions . (Richie et al., 1997, p. 5) .

Presentation

In the last few years, new attention has been paid to text creation. This follows logically from the idea that reality is socially constructed. If observed situations are cultural constructions, then so is the presentation of the text. The role of the researcher is defined by the theoretical orientation and that is reflected in the portrayal and interpretation of the data.

A qualitative research report can have many different forms or formats and the reader and writer may enter the narrative from many different perspectives and value points. Clandinin and Connelly (Tierney & Lincoln, 1994) discuss the potential interpretative differences and inconsistencies in the “text” in qualitative research. They note the difference in audience and potential author bias when compiling field text, which is all the materials from the context, compared with compiling research text, which is prepared to address the research community. There is considerably more literary freedom in the presentation of a case study where the researcher tells a narrative, formed and shaped by the story which the researcher is trying to represent. The narrative is enhanced and brought to life by findings, the authorial voice, voices of research respondents, and the original questions more than by reporting conventions.

Qualitative research is designed to describe, interpret and understand human experience. Though qualitative research is frequently defined by how it measures up to the quantitative methods that have played such a central role in psychological research, it has earned its acceptance in the social sciences the hard way—it earned it. At the same time, viewing qualitative research and quantitative research as diametrically opposed devalues them both. There are times when a qualitative researcher will choose to summarize data numerically just as there are times when a quantitative researcher will choose to include descriptive information to facilitate the presentation of statistical data. Qualitative research can open vistas of uncharted territory for further research; quantitative research can add powerful dimensions that come from an assessment of large populations.

A method is the way to a goal (Kvale, 1996), and not the goal itself. The selection of a methodology should not be determined by political or emotional preference, but by the thematic content and purpose of the investigation.

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Pamela Rutledge, PhD

Qualitative Data Coding

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

Coding is the process of analyzing qualitative data (usually text) by assigning labels (codes) to chunks of data that capture their essence or meaning. It allows you to condense, organize and interpret your data.

A code is a word or brief phrase that captures the essence of why you think a particular bit of data may be useful. A good analogy is that a code describes data like a hashtag describes a tweet.

Coding is an iterative process, with researchers refining and revising their codes as their understanding of the data evolves.

The ultimate goal is to develop a coherent and meaningful coding scheme that captures the richness and complexity of the participants’ experiences and helps answer the research questions.

Step 1: Familiarize yourself with the data

• Read through your data (interview transcripts, field notes, documents, etc.) several times. This process is called immersion.
• Think and reflect on what may be important in the data before making any firm decisions about ideas, or potential patterns.

Step 2: Decide on your coding approach

• Will you use predefined deductive codes (based on theory or prior research), or let codes emerge from the data (inductive coding)?
• Will a piece of data have one code or multiple?
• Will you code everything or selectively? Broader research questions may warrant coding more comprehensively.

If you decide not to code everything, it’s crucial to:

• Have clear criteria for what you will and won’t code
• Be transparent about your selection process in research reports
• Remain open to revisiting uncoded data later in analysis

Step 3: Do a first round of coding

• Go through the data and assign initial codes to chunks that stand out
• Create a code name (a word or short phrase) that captures the essence of each chunk
• Keep a codebook – a list of your codes with descriptions or definitions
• Be open to adding, revising or combining codes as you go

Descriptive codes

• In vivo coding / Semantic coding : This method uses words or short phrases directly from the participant’s own language as codes. It deals with the surface-level content, labeling what participants directly say or describe. It identifies keywords, phrases, or sentences that capture the literal content. Participant : “I was just so overwhelmed with everything.” Code : “overwhelmed”
• Process coding : Uses gerunds (“-ing” words) to connote observable or conceptual action in the data. Participant : “I started by brainstorming ideas, then I narrowed them down.” Codes : “brainstorming ideas,” “narrowing down”
• Open coding : A form of initial coding where the researcher remains open to any possible theoretical directions indicated by the data. Participant : “I found the class really challenging, but I learned a lot.” Codes : “challenging class,” “learning experience”
• Descriptive coding : Summarizes the primary topic of a passage in a word or short phrase. Participant : “I usually study in the library because it’s quiet.” Code : “study environment”

Step 4: Review and refine codes

• Look over your initial codes and see if any can be combined, split up, or revised
• Ensure your code names clearly convey the meaning of the data
• Check if your codes are applied consistently across the dataset
• Get a second opinion from a peer or advisor if possible

Interpretive codes

Interpretive codes go beyond simple description and reflect the researcher’s understanding of the underlying meanings, experiences, or processes captured in the data.

These codes require the researcher to interpret the participants’ words and actions in light of the research questions and theoretical framework.

For example, latent coding is a type of interpretive coding which goes beyond surface meaning in data. It digs for underlying emotions, motivations, or unspoken ideas the participant might not explicitly state

Latent coding looks for subtext, interprets the “why” behind what’s said, and considers the context (e.g. cultural influences, or unconscious biases).

• Example: A participant might say, “Whenever I see a spider, I feel like I’m going to pass out. It takes me back to a bad experience as a kid.” A latent code here could be “Feelings of Panic Triggered by Spiders” because it goes beyond the surface fear and explores the emotional response and potential cause.

It’s useful to ask yourself the following questions:

• What are the assumptions made by the participants? 
• What emotions or feelings are expressed or implied in the data?
• How do participants relate to or interact with others in the data?
• How do the participants’ experiences or perspectives change over time?
• What is surprising, unexpected, or contradictory in the data?
• What is not being said or shown in the data? What are the silences or absences?

Theoretical codes

Theoretical codes are the most abstract and conceptual type of codes. They are used to link the data to existing theories or to develop new theoretical insights.

Theoretical codes often emerge later in the analysis process, as researchers begin to identify patterns and connections across the descriptive and interpretive codes.

• Structural coding : Applies a content-based phrase to a segment of data that relates to a specific research question. Research question : What motivates students to succeed? Participant : “I want to make my parents proud and be the first in my family to graduate college.” Interpretive Code : “family motivation” Theoretical code : “Social identity theory”
• Value coding : This method codes data according to the participants’ values, attitudes, and beliefs, representing their perspectives or worldviews. Participant : “I believe everyone deserves access to quality healthcare.” Interpretive Code : “healthcare access” (value) Theoretical code : “Distributive justice”

Pattern codes

Pattern coding is often used in the later stages of data analysis, after the researcher has thoroughly familiarized themselves with the data and identified initial descriptive and interpretive codes.

By identifying patterns and relationships across the data, pattern codes help to develop a more coherent and meaningful understanding of the phenomenon and can contribute to theory development or refinement.

For Example

Let’s say a researcher is studying the experiences of new mothers returning to work after maternity leave. They conduct interviews with several participants and initially use descriptive and interpretive codes to analyze the data. Some of these codes might include:

• “Guilt about leaving baby”
• “Struggle to balance work and family”
• “Support from colleagues”
• “Flexible work arrangements”
• “Breastfeeding challenges”

As the researcher reviews the coded data, they may notice that several of these codes relate to the broader theme of “work-family conflict.”

They might create a pattern code called “Navigating work-family conflict” that pulls together the various experiences and challenges described by the participants.

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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.

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Contributor Information

Patrik Aspers, Email: [email protected] .

Ugo Corte, Email: [email protected] .

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Chapter 12 Interpretive Research

The last chapter introduced interpretive research, or more specifically, interpretive case research. This chapter will explore other kinds of interpretive research. Recall that positivist or deductive methods, such as laboratory experiments and survey research, are those that are specifically intended for theory (or hypotheses) testing, while interpretive or inductive methods, such as action research and ethnography, are intended for theory building. Unlike a positivist method, where the researcher starts with a theory and tests theoretical postulates using empirical data, in interpretive methods, the researcher starts with data and tries to derive a theory about the phenomenon of interest from the observed data.

The term “interpretive research” is often used loosely and synonymously with “qualitative research”, although the two concepts are quite different. Interpretive research is a research paradigm (see Chapter 3) that is based on the assumption that social reality is not singular or objective, but is rather shaped by human experiences and social contexts (ontology), and is therefore best studied within its socio-historic context by reconciling the subjective interpretations of its various participants (epistemology). Because interpretive researchers view social reality as being embedded within and impossible to abstract from their social settings, they “interpret” the reality though a “sense-making” process rather than a hypothesis testing process. This is in contrast to the positivist or functionalist paradigm that assumes that the reality is relatively independent of the context, can be abstracted from their contexts, and studied in a decomposable functional manner using objective techniques such as standardized measures. Whether a researcher should pursue interpretive or positivist research depends on paradigmatic considerations about the nature of the phenomenon under consideration and the best way to study it.

However, qualitative versus quantitative research refers to empirical or data -oriented considerations about the type of data to collect and how to analyze them. Qualitative research relies mostly on non-numeric data, such as interviews and observations, in contrast to quantitative research which employs numeric data such as scores and metrics. Hence, qualitative research is not amenable to statistical procedures such as regression analysis, but is coded using techniques like content analysis. Sometimes, coded qualitative data is tabulated quantitatively as frequencies of codes, but this data is not statistically analyzed. Many puritan interpretive researchers reject this coding approach as a futile effort to seek consensus or objectivity in a social phenomenon which is essentially subjective.

Although interpretive research tends to rely heavily on qualitative data, quantitative data may add more precision and clearer understanding of the phenomenon of interest than qualitative data. For example, Eisenhardt (1989), in her interpretive study of decision making n high-velocity firms (discussed in the previous chapter on case research), collected numeric data on how long it took each firm to make certain strategic decisions (which ranged from 1.5 months to 18 months), how many decision alternatives were considered for each decision, and surveyed her respondents to capture their perceptions of organizational conflict. Such numeric data helped her clearly distinguish the high-speed decision making firms from the low-speed decision makers, without relying on respondents’ subjective perceptions, which then allowed her to examine the number of decision alternatives considered by and the extent of conflict in high-speed versus low-speed firms. Interpretive research should attempt to collect both qualitative and quantitative data pertaining to their phenomenon of interest, and so should positivist research as well. Joint use of qualitative and quantitative data, often called “mixed-mode designs”, may lead to unique insights and are highly prized in the scientific community.

Interpretive research has its roots in anthropology, sociology, psychology, linguistics, and semiotics, and has been available since the early 19 th century, long before positivist techniques were developed. Many positivist researchers view interpretive research as erroneous and biased, given the subjective nature of the qualitative data collection and interpretation process employed in such research. However, the failure of many positivist techniques to generate interesting insights or new knowledge have resulted in a resurgence of interest in interpretive research since the 1970’s, albeit with exacting methods and stringent criteria to ensure the reliability and validity of interpretive inferences.

Distinctions from Positivist Research

In addition to fundamental paradigmatic differences in ontological and epistemological assumptions discussed above, interpretive and positivist research differ in several other ways. First, interpretive research employs a theoretical sampling strategy, where study sites, respondents, or cases are selected based on theoretical considerations such as whether they fit the phenomenon being studied (e.g., sustainable practices can only be studied in organizations that have implemented sustainable practices), whether they possess certain characteristics that make them uniquely suited for the study (e.g., a study of the drivers of firm innovations should include some firms that are high innovators and some that are low innovators, in order to draw contrast between these firms), and so forth. In contrast, positivist research employs random sampling (or a variation of this technique), where cases are chosen randomly from a population, for purposes of generalizability. Hence, convenience samples and small samples are considered acceptable in interpretive research as long as they fit the nature and purpose of the study, but not in positivist research.

Second, the role of the researcher receives critical attention in interpretive research. In some methods such as ethnography, action research, and participant observation, the researcher is considered part of the social phenomenon, and her specific role and involvement in the research process must be made clear during data analysis. In other methods, such as case research, the researcher must take a “neutral” or unbiased stance during the data collection and analysis processes, and ensure that her personal biases or preconceptions does not taint the nature of subjective inferences derived from interpretive research. In positivist research, however, the researcher is considered to be external to and independent of the research context and is not presumed to bias the data collection and analytic procedures.

Third, interpretive analysis is holistic and contextual, rather than being reductionist and isolationist. Interpretive interpretations tend to focus on language, signs, and meanings from the perspective of the participants involved in the social phenomenon, in contrast to statistical techniques that are employed heavily in positivist research. Rigor in interpretive research is viewed in terms of systematic and transparent approaches for data collection and analysis rather than statistical benchmarks for construct validity or significance testing.

Lastly, data collection and analysis can proceed simultaneously and iteratively in interpretive research. For instance, the researcher may conduct an interview and code it before proceeding to the next interview. Simultaneous analysis helps the researcher correct potential flaws in the interview protocol or adjust it to capture the phenomenon of interest better. The researcher may even change her original research question if she realizes that her original research questions are unlikely to generate new or useful insights. This is a valuable but often understated benefit of interpretive research, and is not available in positivist research, where the research project cannot be modified or changed once the data collection has started without redoing the entire project from the start.

Benefits and Challenges of Interpretive Research

Interpretive research has several unique advantages. First, they are well-suited for exploring hidden reasons behind complex, interrelated, or multifaceted social processes, such as inter-firm relationships or inter-office politics, where quantitative evidence may be biased, inaccurate, or otherwise difficult to obtain. Second, they are often helpful for theory construction in areas with no or insufficient a priori theory. Third, they are also appropriate for studying context-specific, unique, or idiosyncratic events or processes. Fourth, interpretive research can also help uncover interesting and relevant research questions and issues for follow-up research.

At the same time, interpretive research also has its own set of challenges. First, this type of research tends to be more time and resource intensive than positivist research in data collection and analytic efforts. Too little data can lead to false or premature assumptions, while too much data may not be effectively processed by the researcher. Second, interpretive research requires well-trained researchers who are capable of seeing and interpreting complex social phenomenon from the perspectives of the embedded participants and reconciling the diverse perspectives of these participants, without injecting their personal biases or preconceptions into their inferences. Third, all participants or data sources may not be equally credible, unbiased, or knowledgeable about the phenomenon of interest, or may have undisclosed political agendas, which may lead to misleading or false impressions. Inadequate trust between participants and researcher may hinder full and honest self-representation by participants, and such trust building takes time. It is the job of the interpretive researcher to

“see through the smoke” (hidden or biased agendas) and understand the true nature of the problem. Fourth, given the heavily contextualized nature of inferences drawn from interpretive research, such inferences do not lend themselves well to replicability or generalizability. Finally, interpretive research may sometimes fail to answer the research questions of interest or predict future behaviors.

Characteristics of Interpretive Research

All interpretive research must adhere to a common set of principles, as described below.

Naturalistic inquiry: Social phenomena must be studied within their natural setting. Because interpretive research assumes that social phenomena are situated within and cannot be isolated from their social context, interpretations of such phenomena must be grounded within their socio-historical context. This implies that contextual variables should be observed and considered in seeking explanations of a phenomenon of interest, even though context sensitivity may limit the generalizability of inferences.

Researcher as instrument: Researchers are often embedded within the social context that they are studying, and are considered part of the data collection instrument in that they must use their observational skills, their trust with the participants, and their ability to extract the correct information. Further, their personal insights, knowledge, and experiences of the social context is critical to accurately interpreting the phenomenon of interest. At the same time, researchers must be fully aware of their personal biases and preconceptions, and not let such biases interfere with their ability to present a fair and accurate portrayal of the phenomenon.

Interpretive analysis: Observations must be interpreted through the eyes of the participants embedded in the social context. Interpretation must occur at two levels. The first level involves viewing or experiencing the phenomenon from the subjective perspectives of the social participants. The second level is to understand the meaning of the participants’ experiences in order to provide a “thick description” or a rich narrative story of the phenomenon of interest that can communicate why participants acted the way they did.

Use of expressive language: Documenting the verbal and non-verbal language of participants and the analysis of such language are integral components of interpretive analysis. The study must ensure that the story is viewed through the eyes of a person, and not a machine, and must depict the emotions and experiences of that person, so that readers can understand and relate to that person. Use of imageries, metaphors, sarcasm, and other figures of speech is very common in interpretive analysis.

Temporal nature: Interpretive research is often not concerned with searching for specific answers, but with understanding or “making sense of” a dynamic social process as it unfolds over time. Hence, such research requires an immersive involvement of the researcher at the study site for an extended period of time in order to capture the entire evolution of the phenomenon of interest.

Hermeneutic circle: Interpretive interpretation is an iterative process of moving back and forth from pieces of observations (text) to the entirety of the social phenomenon (context) to reconcile their apparent discord and to construct a theory that is consistent with the diverse subjective viewpoints and experiences of the embedded participants. Such iterations between the understanding/meaning of a phenomenon and observations must continue until “theoretical saturation” is reached, whereby any additional iteration does not yield any more insight into the phenomenon of interest.

Interpretive Data Collection

Data is collected in interpretive research using a variety of techniques. The most frequently used technique is interviews (face-to-face, telephone, or focus groups). Interview types and strategies are discussed in detail in a previous chapter on survey research. A second technique is observation . Observational techniques include direct observation , where the researcher is a neutral and passive external observer and is not involved in the phenomenon of interest (as in case research), and participant observation , where the researcher is an active participant in the phenomenon and her inputs or mere presence influence the phenomenon being studied (as in action research). A third technique is documentation , where external and internal documents, such as memos, electronic mails, annual reports, financial statements, newspaper articles, websites, may be used to cast further insight into the phenomenon of interest or to corroborate other forms of evidence.

Interpretive Research Designs

Case research . As discussed in the previous chapter, case research is an intensive longitudinal study of a phenomenon at one or more research sites for the purpose of deriving detailed, contextualized inferences and understanding the dynamic process underlying a phenomenon of interest. Case research is a unique research design in that it can be used in an interpretive manner to build theories or in a positivist manner to test theories. The previous chapter on case research discusses both techniques in depth and provides illustrative exemplars. Furthermore, the case researcher is a neutral observer (direct observation) in the social setting rather than an active participant (participant observation). As with any other interpretive approach, drawing meaningful inferences from case research depends heavily on the observational skills and integrative abilities of the researcher.

Action research . Action research is a qualitative but positivist research design aimed at theory testing rather than theory building (discussed in this chapter due to lack of a proper space). This is an interactive design that assumes that complex social phenomena are best understood by introducing changes, interventions, or “actions” into those phenomena and observing the outcomes of such actions on the phenomena of interest. In this method, the researcher is usually a consultant or an organizational member embedded into a social context (such as an organization), who initiates an action in response to a social problem, and examines how her action influences the phenomenon while also learning and generating insights about the relationship between the action and the phenomenon. Examples of actions may include organizational change programs, such as the introduction of new organizational processes, procedures, people, or technology or replacement of old ones, initiated with the goal of improving an organization’s performance or profitability in its business environment. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may bring forth the desired social change. The theory is validated by the extent to which the chosen action is successful in remedying the targeted problem. Simultaneous problem solving and insight generation is the central feature that distinguishes action research from other research methods (which may not involve problem solving) and from consulting (which may not involve insight generation). Hence, action research is an excellent method for bridging research and practice.

There are several variations of the action research method. The most popular of these method is the participatory action research, designed by Susman and Evered (1978) [13] . This method follows an action research cycle consisting of five phases: (1) diagnosing, (2) action planning, (3) action taking, (4) evaluating, and (5) learning (see Figure 10.1). Diagnosing involves identifying and defining a problem in its social context. Action planning involves identifying and evaluating alternative solutions to the problem, and deciding on a future course of action (based on theoretical rationale). Action taking is the implementation of the planned course of action. The evaluation stage examines the extent to which the initiated action is successful in resolving the original problem, i.e., whether theorized effects are indeed realized in practice. In the learning phase, the experiences and feedback from action evaluation are used to generate insights about the problem and suggest future modifications or improvements to the action. Based on action evaluation and learning, the action may be modified or adjusted to address the problem better, and the action research cycle is repeated with the modified action sequence. It is suggested that the entire action research cycle be traversed at least twice so that learning from the first cycle can be implemented in the second cycle. The primary mode of data collection is participant observation, although other techniques such as interviews and documentary evidence may be used to corroborate the researcher’s observations.

Figure 10.1. Action research cycle.

Ethnography . The ethnographic research method, derived largely from the field of anthropology, emphasizes studying a phenomenon within the context of its culture. The researcher must be deeply immersed in the social culture over an extended period of time (usually 8 months to 2 years) and should engage, observe, and record the daily life of the studied culture and its social participants within their natural setting. The primary mode of data collection is participant observation, and data analysis involves a “sense-making” approach. In addition, the researcher must take extensive field notes, and narrate her experience in descriptive detail so that readers may experience the same culture as the researcher. In this method, the researcher has two roles: rely on her unique knowledge and engagement to generate insights (theory), and convince the scientific community of the trans-situational nature of the studied phenomenon.

The classic example of ethnographic research is Jane Goodall’s study of primate behaviors, where she lived with chimpanzees in their natural habitat at Gombe National Park in Tanzania, observed their behaviors, interacted with them, and shared their lives. During that process, she learnt and chronicled how chimpanzees seek food and shelter, how they socialize with each other, their communication patterns, their mating behaviors, and so forth. A more contemporary example of ethnographic research is Myra Bluebond-Langer’s (1996) [14] study of decision making in families with children suffering from life-threatening illnesses, and the physical, psychological, environmental, ethical, legal, and cultural issues that influence such decision-making. The researcher followed the experiences of approximately 80 children with incurable illnesses and their families for a period of over two years. Data collection involved participant observation and formal/informal conversations with children, their parents and relatives, and health care providers to document their lived experience.

Phenomenology. Phenomenology is a research method that emphasizes the study of conscious experiences as a way of understanding the reality around us. It is based on the ideas of German philosopher Edmund Husserl in the early 20 th century who believed that human experience is the source of all knowledge. Phenomenology is concerned with the systematic reflection and analysis of phenomena associated with conscious experiences, such as human judgment, perceptions, and actions, with the goal of (1) appreciating and describing social reality from the diverse subjective perspectives of the participants involved, and (2) understanding the symbolic meanings (“deep structure”) underlying these subjective experiences. Phenomenological inquiry requires that researchers eliminate any prior assumptions and personal biases, empathize with the participant’s situation, and tune into existential dimensions of that situation, so that they can fully understand the deep structures that drives the conscious thinking, feeling, and behavior of the studied participants.

Figure 10.2. The existential phenomenological research method.

Some researchers view phenomenology as a philosophy rather than as a research method. In response to this criticism, Giorgi and Giorgi (2003) [15] developed an existential phenomenological research method to guide studies in this area. This method, illustrated in Figure 10.2, can be grouped into data collection and data analysis phases. In the data collection phase, participants embedded in a social phenomenon are interviewed to capture their subjective experiences and perspectives regarding the phenomenon under investigation.

Examples of questions that may be asked include “can you describe a typical day” or “can you describe that particular incident in more detail?” These interviews are recorded and transcribed for further analysis. During data analysis , the researcher reads the transcripts to:

(1) get a sense of the whole, and (2) establish “units of significance” that can faithfully represent participants’ subjective experiences. Examples of such units of significance are concepts such as “felt space” and “felt time,” which are then used to document participants’ psychological experiences. For instance, did participants feel safe, free, trapped, or joyous when experiencing a phenomenon (“felt-space”)? Did they feel that their experience was pressured, slow, or discontinuous (“felt-time”)? Phenomenological analysis should take into account the participants’ temporal landscape (i.e., their sense of past, present, and future), and the researcher must transpose herself in an imaginary sense in the participant’s situati on (i.e., temporarily live the participant’s life). The participants’ lived experience is described in form of a narrative or using emergent themes. The analysis then delves into these themes to identify multiple layers of meaning while retaining the fragility and ambiguity of subjects’ lived experiences.

Rigor in Interpretive Research

While positivist research employs a “reductionist” approach by simplifying social reality into parsimonious theories and laws, interpretive research attempts to interpret social reality through the subjective viewpoints of the embedded participants within the context where the reality is situated. These interpretations are heavily contextualized, and are naturally less generalizable to other contexts. However, because interpretive analysis is subjective and sensitive to the experiences and insight of the embedded researcher, it is often considered less rigorous by many positivist (functionalist) researchers. Because interpretive research is based on different set of ontological and epistemological assumptions about social phenomenon than positivist research, the positivist notions of rigor, such as reliability, internal validity, and generalizability, do not apply in a similar manner. However, Lincoln and Guba (1985) [16] provide an alternative set of criteria that can be used to judge the rigor of interpretive research.

Dependability. Interpretive research can be viewed as dependable or authentic if two researchers assessing the same phenomenon using the same set of evidence independently arrive at the same conclusions or the same researcher observing the same or a similar phenomenon at different times arrives at similar conclusions. This concept is similar to that of reliability in positivist research, with agreement between two independent researchers being similar to the notion of inter-rater reliability, and agreement between two observations of the same phenomenon by the same researcher akin to test -retest reliability. To ensure dependability, interpretive researchers must provide adequate details about their phenomenon of interest and the social context in which it is embedded so as to allow readers to independently authenticate their interpretive inferences.

Credibility. Interpretive research can be considered credible if readers find its inferences to be believable. This concept is akin to that of internal validity in functionalistic research. The credibility of interpretive research can be improved by providing evidence of the researcher’s extended engagement in the field, by demonstrating data triangulation across subjects or data collection techniques, and by maintaining meticulous data management and analytic procedures, such as verbatim transcription of interviews, accurate records of contacts and interviews, and clear notes on theoretical and methodological decisions, that can allow an independent audit of data collection and analysis if needed.

Confirmability. Confirmability refers to the extent to which the findings reported in interpretive research can be independently confirmed by others (typically, participants). This is similar to the notion of objectivity in functionalistic research. Since interpretive research rejects the notion of an objective reality, confirmability is demonstrated in terms of “inter-subjectivity”, i.e., if the study’s participants agree with the inferences derived by the researcher. For instance, if a study’s participants generally agree with the inferences drawn by a researcher about a phenomenon of interest (based on a review of the research paper or report), then the findings can be viewed as confirmable.

Transferability. Transferability in interpretive research refers to the extent to which the findings can be generalized to other settings. This idea is similar to that of external validity in functionalistic research. The researcher must provide rich, detailed descriptions of the research context (“thick description”) and thoroughly describe the structures, assumptions, and processes revealed from the data so that readers can independently assess whether and to what extent are the reported findings transferable to other settings.

[13] Susman, G.I. and Evered, R.D. (1978). “An Assessment of the Scientific Merits of Action Research,”

Administrative Science Quarterly , (23), 582-603.

[14] Bluebond-Langer, M. (1996). In the Shadow of Illness: Parents and Siblings of the Chronically Ill Child . Princeton, NJ: Princeton University Press.

[15] Giorgi, A and Giorgi, B (2003) Phenomenology. In J A Smith (ed.) Qualitative Psychology: A Practical Guide to Research Methods . London: Sage Publications.

[16] Lincoln, Y. S., and Guba, E. G. (1985). Naturalistic Inquiry . Beverly Hills, CA: Sage Publications.

• Social Science Research: Principles, Methods, and Practices. Authored by : Anol Bhattacherjee. Provided by : University of South Florida. Located at : http://scholarcommons.usf.edu/oa_textbooks/3/ . License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike

• Open access
• Published: 15 May 2024

Sacred space: a qualitative interpretive meta-synthesis of women’s experiences of supportive birthing environments

• December Maxwell 1 ,
• Sarah R. Leat 2 ,
• Toni Gallegos 3 &
• Regina T. Praetorius 3  

BMC Pregnancy and Childbirth volume  24 , Article number:  372 ( 2024 ) Cite this article

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In the United States there are roughly three million births a year, ranging from cesarean to natural births. A major aspect of the birthing process is related to the healing environment, and how that helps or harms healing for the mother and child. Using the theoretical framework, Theory of Supportive Care Settings (TSCS), this study aimed to explore what is necessary to have a safe and sacred healing environment for mothers.

This study utilized an updated Qualitative Interpretive Meta-synthesis (QIMS) design called QIMS-DTT [deductive theory testing] to answer the research question, What are mother’s experiences of environmental factors contributing to a supportive birthing environment within healthcare settings?

Key terms were run through multiple databases, which resulted in 5,688 articles. After title and abstract screening, 43 were left for full-text, 12 were excluded, leaving 31 to be included in the final QIMS. Five main themes emerged from analysis: 1) Service in the environment, 2) Recognizing oneself within the birthing space, 3) Creating connections with support systems, 4) Being welcomed into the birthing space, and 5) Feeling safe within the birthing environment.

Conclusions

Providing a warm and welcoming birth space is crucial for people who give birth to have positive experiences. Providing spaces where the person can feel safe and supported allows them to find empowerment in the situation where they have limited control.

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Introduction

In 2021, there were 3,664,292 births in the United States. Of those birth, 98.3% took place in hospitals [ 1 ]. In hospital settings, medical interventions such as induction of labor, cesarean sections, and the use of instruments like forceps or vacuum extractors may be more common [ 2 ]. These interventions can carry risks such as increased likelihood of complications for both the birthing person and the baby [ 2 , 3 ]. Some women may feel stressed or anxious in a hospital setting, which could potentially slow down labor or lead to other complications. This stress can be due to various factors such as unfamiliar surroundings, medical procedures, or concerns about interventions [ 2 ]. In a hospital setting, decisions about the birth process may be influenced by hospital policies, medical protocols, and the preferences of healthcare providers, potentially leading to a loss of autonomy for the birthing person in decision-making about their own birth experience [ 4 ]. The experience of giving birth in a hospital, especially if it involves unexpected interventions or complications, can contribute to postpartum depression or anxiety in some women [ 5 ]. Hospital routines and policies may not always be conducive to establishing breastfeeding immediately after birth, which can lead to challenges in breastfeeding initiation and continuation [ 6 ].

Birthing requires healing and a supportive environment at every stage of the birthing process, consisting of holistic support and agency [ 7 ]. This involves “constant emotional, physical, spiritual, and psychosocial” support [ 8 ]. Experiencing birthing trauma has shown to result in postpartum post-traumatic stress disorder (P-PTSD) and postpartum depression (PPD) [ 9 , 10 , 11 ]. Likewise, disempowering births can have long term impacts of maternal self-esteem [ 12 , 13 ]. Maternal mental health issues have resulted in numerous public health concerns, specifically regarding the decreased safety and negative health outcomes that the infant faces [ 14 , 15 ]. Postpartum mental health disorders can also have lasting impacts on family outcomes [ 16 , 17 ]. As such, understanding how to improve the birth experience has the potential to reduce postpartum mental health issues, as well as reduce maternal morbidities, which can improve outcomes for both mother and child.

Of note is the influence of the built environment on healing. Given that thoughtfully designed healthcare facilities can influence the amount of privacy and control a patient perceives [ 18 ], the built environment plays an integral part in healing. Ample daylight, thermal comfort, color, and noise control all contribute to environmental healing within a hospital [ 19 ]. Furthermore, patient health outcomes have been linked to the built environment of hospitals in multiple studies [ 13 , 20 , 21 ]. More specific to birthing, women have indicated that perceived hominess and control in the environment relate to their birthing experience [ 20 , 22 , 23 ].

Control over the birthing environment, including comfort and perceived healing also have mental health impacts for birthing mothers, and the birth environment can have an impact on the mother’s perception of the birth which in turn can influence maternal mental health outcomes [ 24 , 25 ]. Given that approximately 1 in 7 mothers will experience postpartum depression (PPD) in the United States [ 26 , 27 ] and 0.05%-60% of mothers will experience PPD globally [ 28 , 29 ], understanding the impact of birthing environment on maternal morbidities and mental health can create holistic approaches to birthing environment design.

Given the impacts of the birthing environment on maternal mental health, learning what is necessary to have a safe and sacred healing environment for mothers is an important endeavor and the purpose of this qualitative interpretive meta-synthesis (QIMS). A QIMS is a method that is specific to the social work field. It was created to review and analyze qualitative data to identify and synthesize themes surrounding different phenomena found in existing qualitative research [ 30 ]. QIMS has previously been used to synthesize existing data regarding social justice concerns around minority police encounters [ 31 ] and children’s exposure to intimate partner violence [ 32 ]. Concerning the topic of birthing and motherhood, one QIMS explored marginalized women’s experiences of postpartum depression [ 33 ] and another explored the experience of suicidality postpartum [ 34 ]. To date, no QIMS has considered the experiences of the birth environment for birthing mothers and the impact on maternal mental health. A synthesis of the literature qualitatively evaluating women’s perspectives on what is necessary to have a safe and sacred healing environment for mothers could bolster understanding of how hospitals could better support birthing mothers. As such, this study uses QIMS to answer the following research question: what is necessary to have a safe and sacred healing environment for mothers?

Theoretical framework

This study sought to understand how birthing mothers experienced the birthing environment and which environmental factors contributed to a safe and sacred healing environment for mothers. As such, the Theory of Supportive Care Settings (TSCS) was used to frame this synthesis [ 35 ].

Theory of supportive care settings

Theory of Supportive Care Settings (TSCS) was created through research to have a theoretical understanding of which “processes supported a supportive care setting” [ 35 ]. TSCS was developed using three different care settings–a hospice, geriatric, and acute care ward, through qualitative interviews with patients, significant others, and care staff’s experiences. Although TSCS was not developed within the birthing environment, given the raise of childbirth induced P-PTSD, it is appropriate to apply the concepts to the birthing environment. One aspect of this synthesis is to assess the utility of the application of TSCS to the birthing environment using it as the main theoretical approach. There are five main processes the theory addresses as creating a supportive care environment: experiencing welcoming in the environment, recognizing oneself in the environment, creating and maintaining social relations in the environment, experiencing a willingness to serve in the environment, and experiencing safety in the environment. An applied theoretical framework was created (Fig.  1 ).

Framework of theory of supportive birth settings

Experiencing welcoming in the environment

Experiencing welcoming in the environment has three properties which are intensely experienced when the patient first enters the healthcare setting [ 35 ]. Being expected is the first property that involves the care setting knowing the patient is coming. This happens by having the patient’s name displayed and knowing pertinent information about the person before the beginning of care [ 35 ]. Being seen entails a warm welcome upon entering the care setting, having personal introductions, and care staff showing an interest [ 35 ]. Lastly, being invited consists of being shown around the care setting for the patient to become familiar with the environment and the people within [ 35 ].

Certainly, experiencing welcoming in a care setting, such as a hospital, heightens mood among patients and increases their satisfaction with their experience of the care setting [ 36 ]. Within a birthing environment, there is also evidence that being believed and welcomed upon arrival to the hospital increases the satisfaction of mothers as well as enhances their birthing experience [ 37 ].

Recognizing oneself in the environment

Within TSCS, recognizing oneself in the environment encapsulates the intensity of which patients recognize themselves within the care environment [ 35 ]. For example, environments that are perceived as too sterile do not allow the patient to recognize themselves in the environment. Being able to recognize oneself in the care setting includes being in a familiar and calm environment [ 35 ]. A familiar environment includes objects that are familiar to the patients, as well as beauty in the environment that includes windows and warm colors [ 35 ]. Further, a calm environment has minimal loud noises from machines, phones, and patients are allowed to move freely [ 35 ]. Features of familiarity in the birthing environment can reduce the length of labor and reduce pain intensity [ 38 ].

Creating and maintaining social relations in the environment

Creating and maintaining social relations in the environment within TSCS describes the social relations a patient develops that create ease within the environment [ 35 ]. Within this concept, there are two processes: staying in contact with social relations and creating new social relations. Staying in contact entails the patient’s ability to stay in contact with those in their social circles while undergoing care and can include environmental factors that facilitate this such as access to a personal phone and privacy to visit with social relations while in care. Creating new social relations explains the way patients can create new social relationships through positive interactions such as those that include laughter and support from care staff or others in the care setting. The process further includes the structural environment and facilitation of such connections, including openness of concept, support places, and comfortable furniture in private and common areas of the care setting [ 35 ].

This process of TSCS is again supported in literature regarding birthing environments. Availability of social support is integral to the birthing experience and increased access to social support creates better birthing outcomes and perceptions of birth [ 39 ]. Similarly, those supporting the birth need to feel welcomed and included in the birth environment, and there are specific aspects of the built environment that facilitate increased support during birth such as familial alcoves in birthing rooms and increased attempts at including the supporter by care setting providers [ 40 ].

Experiencing a willingness to serve in the environment

The willingness to serve in the environment from TCSC involves both care staff and patients. In TSCS doing a little extra and receiving a little extra are the processes that promote a willingness to serve. To the patients, seeing the care staff demonstrate thoughtful actions shows the staff’s willingness to serve. These actions can include things like remembering a patient’s preferences for their pillow or water temperature or arranging food in an appealing way. The willingness to serve can also come from patients though; some patients reaching out to other patients to give support or even just showing caring attitudes towards either nurses or other patients. For patients, an environment which demonstrates the willingness to serve is one when care staff do things without being asked, are intuitive in their approaches, and do not make the patient feel like a burden [ 35 ].

Within the birthing environment, willingness to serve can look like staff providing welcome distractions from the birthing process through music or aromatherapy, dimming lights, changing ambient temperature, and ensuring loud sounds are minimal. Further, care staff can exhibit willingness to serve by advocating for the birthing mother to have less people in the room, creating a familiar space, and providing comfort [ 38 ].

Experiencing safety in the environment

TSCA defines safety in the birthing environment as the safe feelings that arise from knowing what is happening, feeling informed, being comforted, and feeling trustful of care providers. Understanding what is happening includes, knowing what is happening, having information in an accessible language, and being aware of the course of events. For the patient, being is safe hands means having trust in the providers through honest conversations, knowing that their needs and requests are honored, and that the physical environment is clean, organized, and aesthetically pleasing rather than chaotic and messy [ 35 ].

The safety in the birthing environment often ties honest conversations and knowing needs and requests will be met to feel in control over the birth and the experience. Feeling in control of the birth environment can also include creating a familiar, homey space by being allowed to personalize the space with music, design elements like personal photos, pillows, or plants, and controlling the temperature and lighting [ 40 ]. In addition, knowing that healthcare providers are respecting the birth plan as much as possible and supporting freedom to move and move through the birth process in their own way [ 38 ]. Furthermore, machinery that ties the mother down, inhibiting freedom to move, can be distracting and reduce the time midwives or nurses spend in the birthing room, diminishing the birthing mother’s trust in care providers [ 41 ].

Despite the lack of use of TCSC in birthing environment literature, all five concepts from TCSC are found within the existing literature to be recommended for use in birthing environments. That said, there is not a synthesis to date utilizing the framework to evaluate qualitative perspectives of the birthing environment. This review aims to organize the existing qualitative literature within TCSC to provide a roadmap for birthing space design that aligns with a supportive care environment, with the hopes of creating more functional birthing spaces which may reduce the rates of maternal mental health challenges following the birth of a child.

Ethics, consent for publication, availability of data and materials

The data used in this study are derived from publicly available, published research articles and thus, in the public domain. Similarly, Institutional Review Board approval was not required since all data used were in the public domain in publicly available, published research articles. Informed consent was not required as no participants were recruited to participate in this study. There is no identifiable information of participants used in this method nor do we as consumers of previously published qualitative research have access to the original data.

QIMS is a method that lets researchers find a deeper understanding of a phenomenon or shared experience using qualitative journal articles as secondary data. QIMS is focused on researchers synthesizing previously published qualitative findings on a topic across the literature to reveal insights of participants’ experiences with a phenomenon [ 30 ]. This process includes creating a research question, conducting a systematic search of existing literature, and finally analyzing identified articles through theme extraction, synthesis, and triangulation [ 30 ].

QIMS has a set analysis process that involves reviewing the original authors’ published themes, as well as the participant's quotations in the manuscript. Themes and quotations are extracted and compiled into a new dataset to capture participants’ experiences of shared phenomenon across literature, providing a larger, more diverse sample size.

Sometimes, the analysis ends with a methodological reduction as well. Methodological reduction is an accepted method within phenomenological inquiry that permits researchers to understand the phenomena being observed through a new contextual lens allowing for further abstraction [ 42 ]. That said, due to the paucity of research evaluating what is necessary to have a safe and sacred healing environment for mothers, this study utilized a rare approach to QIMS wherein the theoretical framework was provided at the outset of the study to guide the entirety of the synthesis. This deviates from the more inductive approach of traditional QIMS, but this deductive approach allows for a more pointed answer to a specific research question that seeks to operationalize a construct within a distinctive context or population and has been used previously [ 30 ]. Essentially, this analysis approach used a combination of both QIMS and theory-testing deductive analysis methods. The theory guides each step of the QIMS process, and specific steps have been applied (see Fig.  2 ). This combined approach is formalized here and is called QIMS-DTT [deductive theory testing].

Associations of birthing environment to Theory of Supportive Care Settings 

First, in line with theory-testing deductive analysis [ 43 ], a qualitative question was posed with a specific theoretical lens in mind, in this case, Edvardsson’s Theory of Supportive Care Setting. Then, following QIMS, a systematic search of the literature was conducted using PRISMA guidelines [ 44 ]. The keywords for the initial search included “birth or childbirth or labour or labor or delivery or birthing” as subject terms. The key terms “experiences or experience” and “qualitative” were added to “in abstract” as well as “birthing experiences” and “birthing perceptions.” Key terms were searched within the following databases: ERIC, Academic Search Complete, APA PsycInfo, CINAHL Complete, Family Studies Abstracts, MedicLatina, MEDLINE, Psychology and Behavioral Sciences Collection, Alt HealthWatch. This initial search yielded 5,688 articles. After duplicates were removed 5,167 articles remained. The title and abstract screened for content relating to the desired topic, and inclusion and exclusion criteria were applied.

Inclusion criteria were that the studies were U.S. based only, included pregnant women’s experiences of hospital or birthing center birth, and were qualitative research with quotations presented in the article. Inclusion was limited to U.S. based studies given that birthing practices differ vastly across the world; focusing on the U.S. provides homogeneity of context for understanding the birthing environment impact. Furthermore, even though the U.S. is a high resource country, the perinatal care system is considered unique as requires private pay insurance and not every woman has access to Medicaid or Medicare federal and state funded health insurance programs [ 45 ]. Furthermore, among 11 high resourced countries, the U.S. has the highest maternal mortality rate, which some scholars attribute to how the U.S. has the lowest supply of obstetricians and heavily lacks midwives and insurance coverage for midwifery care [ 46 ]. Theory was incorporated here as well as an inclusion criterion, and the results were filtered through the operationalization of Edvardsson’s Theory of Supportive Care Setting used for this study. Using the five constructs of the theory that were operationalized for this study, the articles were included if authors discussed at least one construct from the theory (the constructs that articles discussed can be found in Table  1 ). Articles not discussing at least one of the five constructs of the theory were excluded. In addition, other exclusion criteria included articles discussing future births or expectations about future births, choice of location for birth, mode of delivery, labor pain, healthcare providers’ perspectives, existing reviews or syntheses, and articles discussing techniques of or towards birthing [e.g., acupuncture, Lamaze, education]. After title and abstract screening, 3,178 articles were excluded, leaving 43 articles to be screened full text. During the full-text screen, 12 articles were excluded, leaving 31 total articles to be included in the QIMS.

Following this approach (inclusive of both QIMS and theory-testing deductive analysis) we have formalized within this study, the original themes (Table  2 ) from the articles were organized by one researcher into appropriate theoretical assumptions that most aligned with the constructs of TSCS (See Table  1 –providing theoretical triangulation). Then, the quotations from each article were extracted and uploaded to qualitative software, atlas.ti (v.8.1). The quotations were coded deductively by the first two authors using the theoretical framework as a guide for thematic development. The themes were then aligned with each of the five theoretical constructs by unanimous rating. This process provided a layer of analyst triangulation additional to the triangulation inherent in QIMS design resulting from triangulation in the individual studies prior to the QIMS.

Instrumentation

In addition to the analysis process, it is also important for researchers to bracket, or disclose, their experiences with a phenomenon to increase the trustworthiness of the synthesis. The authors are the main instruments of this study, as is frequently the case in qualitative research. To further lend credibility and transparency to the QIMS process, brief descriptions of the authors can be found in Table  3 . The authors purposefully include two mothers–one who experienced Postpartum Mood and Anxiety Disorders (PMADs) and one who did not, and two women who were not mothers at the time of this writing. This intentionally focused toward balancing any biases the two mothers might have brought to the analyses given their experiences further explained in Table  3 .

The final sample included 30 qualitative studies giving ear to the voices of 1,802 postpartum mothers. These mothers ranged in age from 12 to 71 and represented a wide range of races and ethnicities. For more demographic information including data collection methods and settings, see Table  4 .

Using a theory-testing deductive analysis process in conjunction with QIMS, the analysis results in five themes with various subthemes. The supporting quotations can be found in Table  5 . In addition, thematic constructs of TSCS were found across the included articles and the theoretical deduction was sound. Evidence of theoretical constructs can be found in Table  1 .

Theme 1: service in the environment

The first theme consists of ways that participants experienced service within the birthing environment. This service can be either from the healthcare team or the woman themselves and can be expressed in ways more encompassing than just direct labor. Participants described providers who exhibited exceptional care as a memorable part of their birthing experience. This aspect of service within the environment contributed to warm feelings towards their providers and allowed them to feel important and cared for. Many described how taking time out of their busy schedules to focus on the woman one-on-one, accommodating disabilities or medical conditions without being asked, and going out of their way to encourage and empower women was how a provider demonstrated “above and beyond” care.

Theme 2: recognizing oneself within the birthing space

The second theme described how birthing persons saw themselves within the birthing space. This included their personhood being acknowledged and their maternal role being validated by providers.

Subtheme 2A: acknowledging personhood

Recognizing oneself within the environment should be facilitated by feeling acknowledged as persons with dignity. For participants in these studies, this was expressed in their experiences of not having their personhood acknowledged and valued during the birthing process. One participant was not allowed to walk to the bathroom and was also not clearly told why. Her dignity was wounded, and the situation introduced emotional trauma into her birth story. Other women had a similarly emotionally traumatic experience that compromised their dignity and devalued their personhood.

Subtheme 2B: validating maternal role

Validation in becoming a mother is an important step in a woman’s transition into motherhood. The birth is an experience that will forever impact how the person views their maternal role. Many participants felt that their role as mother was overlooked by providers or not validated in a way that made them feel unequipped to mother their children. Often, participants described how providers made decisions for their newborns for them without consulting or trusting them to make such decisions.

Theme 3: creating connections with support systems

The third theme describes the ability of participants to forge or maintain social connection while experiencing birth. This could be availability of social support through communication from providers or through inclusion of support persons. Furthermore, disrespect hampered the formation of social connections.

Subtheme 3A: communication is key

This subtheme revolved around the necessity of communication to forge a strong, trusting social connection between provider and women. This communication included informing the women of medically necessary interventions and allowing them to understand the necessity of them before consenting when medically possible. Communication also included introducing themselves and accepting a patient introduction genuinely through learning womens’ names and making eye contact and gathering consent before touching the client. When providers communicated in this fashion, the participants indicated that they felt a stronger social bond to the providers and their trust and satisfaction with them was increased.

Subtheme 3B: team effort among providers

Relationships required a team effort, which meant that multiple providers needed to be on the same page and operating in good communication with one another to support mothers. Participants in the included studies described how both providers and the birthing person, as well as their support people could work together to ensure the birthing process was a positive one. Others explained that when providers did not work together or communicate among each other the birthing process felt chaotic and disjointed, leaving them feeling unsatisfied and unsafe.

Subtheme 3C: respect forges social connection

This sub theme describes how care providers can forge social connection with their patients through respecting the wishes of the birthing person. Examples included respecting their birthing plan even when it was not medically necessary, allowing the birthing person to make choices about pain interventions, and not respecting the minimal birthing requests that were not related to medical interventions. Conversely, not hearing or respecting the birthing person created a negative experience which was detrimental to social connection in the birthing space.

Theme 4: being welcomed into the birthing space

The fourth theme that emerged encompassed participants’ desires to be welcomed into the birthing space. This involved experiences of being admitted into the maternity ward or birthing suite upon arrival at the hospital and being made to feel comfortable in the space.

Subtheme 4A: being believed and admitted

Participants within the included articles discussed the importance of being believe when they presented to the hospital in what they perceived as active labor. Participants described being unsure if the sensations they were feeling were in labor and expressed anxiety as to whether they would be admitted into the maternity ward. Participants worried that if they arrived at the hospital too early, they would be treated poorly for “over-reacting” and be sent home, even though they were in pain. Participants also described the feeling of being rejected as failure. Being admitted into the birthing space was crucial for participants in the included articles to feel supported and validated.

Subtheme 4B: comfortable birthing space

In addition to being admitted, having the birthing space be comfortable was also necessary for participants to feel welcomed. Participants described spaces that had enough room for all their family members, single-occupancy rooms that allowed the birthing mother to have the whole room to herself, and rooms that had calming items present to be the most comfortable. In addition, participants in the included articles described experiences of uncomfortable spaces. Several participants expressed discomfort at having to be moved to multiple locations within the hospital. Participants also found hospitals challenging to navigate which caused stress on the family and the laboring mothering. Some participants described how the temperature of the space affected them as well, with the ability to control the temperature helping them to feel comfortable, both themselves and their families.

Theme 5: feeling safe within the birthing environment

The fifth theme encompasses various ways birthing persons felt or did not feel safety in the birthing environment. Either through consent in procedures, being able to follow birth plans, having freedom to move, and having trust and confidence in the healthcare team, there were many ways participants expressed their perceptions of safety in the birthing environment.

Subtheme 5A: interpersonal safety

This theme described how interpersonal relationships contributed to feeling safety in the birthing environment. Participants in the original studies talked about how they took action to ensure they had interpersonal safety through choosing obstetricians that felt safe to them, either due to gender or validation tactics. Others described how having continuity of care when possible created safe feeling interpersonal relationships, such as having the same nurse throughout or when they did change shifts- the outgoing nurse took extra steps to introduce the new nurse and supported the forging of an interpersonal relationship between birthing person and new nurse. Having a familiar face consistently throughout the birthing process was comforting. In addition, many quotations described how a provider could focus on the woman in a way that was comforting and forged and interpersonal connection by ensuring they knew they were being heard and supported.

Subtheme 5B: Confidence in the healthcare team

Feeling safe in the birthing environment was also influenced by how much confidence the women had in their healthcare team. Some participants in the original study described how they trust doctors because they know better through education, while others felt like their care providers were not listening to their concerns, eroding their trust and making them feel unsafe. Others explained actions the healthcare team took to ruin the trust between them, either by not sharing the full truth of the current process or by giving false information. When the providers were not honest with their patients, the birthing person was less likely to feel safe and therefore it tainted their birthing experience with anxious feelings.

Subtheme 5C: Feeling in control of the birth

Participants also described feeling in control of the space allowed them to feel safe within the birthing space. Participants who were given the ability to make decisions about positions, movements, and even presented with a way to watch the birth felt in control and supported by staff. Conversely, participants who were restricted in their movement felt trapped.

The findings of this QIMS-DTT highlight what is necessary to have a safe and sacred healing environment for mothers. Filtered through the adapted Theory of Supportive Care Settings, the findings of this deductive theory-testing study found multiple overlaps with the theoretical approach and as such, propose the importance of utilizing a Theory of Supportive Birthing Environments when evaluating birthing care environments. The five main components of Edvardsson’s theory can be found across all included articles and in the findings of this QIMS-DTT, making the findings unique in the application of the theory as a framework to approach environmental birth design.

For instance, a novel finding was the participant-described need for a welcoming birthing environment, including their initial admission to the hospital, being believed, and validated about their labor process, and the birthing environment itself being welcoming to them and their support persons. The initial moments upon arrival at the birthing facility or the presence of the healthcare team can significantly impact the birthing person's emotional well-being, comfort, and sense of security. Indeed, research does indicate that a warm welcome can help alleviate these feelings by making the birthing person feel valued, respected, and cared for from the moment they arrive. A positive and supportive atmosphere can contribute to a more relaxed state of mind [ 47 ]. Although the findings illuminate that a warm welcome into the birthing environment is critically important as it sets the tone for the entire childbirth experience, there is scant literature on this phenomenon as an attribute of the birth environment experience. A warm welcome also fosters trust and rapport between the birthing person and the healthcare team [ 46 ] which is essential for effective communication and cooperation throughout labor and childbirth. When trust is established early on, it can lead to a more collaborative and positive birthing experience. Beyond alleviating stress, feeling welcomed and respected empowers the birthing person to actively engage in their care and decision-making [ 47 ]. When they are treated with kindness and dignity, they are more likely to voice their preferences, concerns, and questions, leading to informed decision-making [ 47 , 77 ]. As many participants shared, the birthing environment itself was responsible for the welcoming feeling and contributed to a positive and comfortable birthing environment. In this study, this included friendly greetings, a clean and inviting room, soft lighting, and soothing sounds. Such an environment can promote relaxation and facilitate a smoother labor and birth [ 77 ].

The findings also illuminate the importance of social connection within the birthing space, through feeling respected and heard, clear communication, and acknowledgment and validation. Social relationships, including those with partners, family members, friends, and healthcare providers, offer emotional support during a time that can be physically and emotionally challenging. Previous literature has supported these findings, indicating that when there are people who care about the birthing person's well-being and provide comfort and encouragement, it can reduce stress and anxiety for the birthing person [ 40 ]. Trust is a critical component of any healthcare relationship, especially during childbirth [ 52 ]. Unique within these findings, however, is the importance of social connection between the women and providers on the recounting of birth stories and satisfaction with the birth environment. Furthermore, although support by providers is well documented, the findings here offer a unique approach as establishing these relationships as a facet of the birth environment. Establishing trust with healthcare providers and support staff is essential for effective communication, which, in turn, leads to better decision-making and a more positive birthing experience.

Safety in the environment was a salient finding of this study, and with good reason. Participants expressed that having interpersonal safety, seeing a good team effort among healthcare providers, and confidence in that healthcare team all contributed to their perceptions of safety in the birthing environment. Creating feelings of safety in the birthing environment is of paramount importance for several reasons. A safe and supportive birthing environment not only ensures the physical well-being of the birthing person and baby but also has a profound impact on the overall childbirth experience. Feelings of safety help reduce stress and anxiety during labor and childbirth [ 78 ]. Perceived safety benefits medical providers as well- when the birthing environment is perceived as safe, it can facilitate the release of endorphins, the body's natural pain relief hormones, and contribute to a smoother labor and birth process without unnecessary medical interventions [ 79 ].

Another important, but already substantiated, finding within safety in the environment was the element of control and agency within the birthing environment that was necessary to have positive birth experiences. Participants engaged in self-advocacy and described the importance of feeling in control over the birthing process to their well-being. Agency and control in the birthing environment are documented crucial aspects of the childbirth experience, as they can significantly impact the physical and emotional well-being of the birthing person and their overall satisfaction with the process [ 45 ]. When birthing people have a sense of agency and control over their birth experience, they report higher levels of satisfaction with the process, regardless of whether their birth unfolds as planned or not [ 45 ]. Agency and control also empower the birthing person to make informed decisions about their birth plan and medical interventions and endorse their maternal role. Informed decision-making allows individuals to choose the options that align with their values, preferences, and health needs. Notably, the findings in this study indicate that when birthing persons do not feel in control of their birth, they had poor retrospective memories about their birth and sometimes felt shame or anger about it. Indeed, a lack of agency and control during childbirth can sometimes lead to feelings of trauma or dissatisfaction [ 80 ]. Although this phenomenon is well documented, the findings from this review contextualize the need for agency and control within the theoretical approach and creates a more comprehensive look at birth environment attributes.

Implications for providers and research

The findings of this study illuminate numerous implications for providers and researchers. For providers, the knowledge that a warm welcome extends beyond them to the entire birthing team, including nurses, midwives, doulas, and support persons. A cohesive and supportive team that welcomes the birthing person with open arms can enhance the overall birthing experience. Furthermore, welcoming includes initial contact and the way a birthing person is received and treated upon arrival can significantly influence their overall perception of their birth experience. A warm welcome contributes to positive birth memories and can have long-lasting emotional and psychological benefits [ 47 ].

Empowering birthing people to have control over their experience can help reduce the risk of trauma. Establishing trust and effective communication between the birthing person, their support team, and healthcare providers is essential for maintaining agency and control. When there is open dialogue and mutual respect, the birthing person is more likely to feel comfortable expressing their preferences and concerns. In some cases, having control over the birthing environment can lead to better physical outcomes. For example, a birthing person who can move freely, choose their birthing position, and have access to comfort measures may experience shorter labor and fewer complications [ 77 ]. In addition, providers should recognize that every birthing experience is unique and respecting cultural and individual differences is essential for promoting agency and control. What one person values or finds empowering in their birthing experience may differ from another, and healthcare providers should strive to accommodate these variations. More research may be needed to understand the prevalence of agency and control better quantitatively in the birthing environment and its relationship to maternal mental health outcomes using measurements surveying the birth environment that combine the attributes of the framework presented in the findings.

Building social relationships in the birthing environment can create a supportive and celebratory atmosphere. The birthing person, their partner, and their support network can share in the joy and excitement of welcoming a new life into the world, enhancing the overall experience.

Social relationships formed during childbirth can extend into the postpartum period, providing ongoing emotional support, advice, and assistance as the birthing person navigates the challenges of early parenthood. Social relationships in the birthing environment can also be a source of valuable information and education. Healthcare providers and support persons can share knowledge about the birthing process, available options, and potential interventions, empowering the birthing person to make informed decisions.

Another implication for providers is building a culture of safety within the environment. When the birthing environment feels unsafe or traumatic, it can have long-lasting negative effects on the birthing person's mental and emotional well-being. Feelings of trauma during childbirth can lead to post-traumatic stress disorder [PTSD] and have a significant impact on future pregnancies [ 80 , 81 ]. Safety also includes trust. Trust is a cornerstone of the birthing experience and when the birthing person trusts their healthcare providers and the birthing environment, they are more likely to follow recommendations, cooperate with care plans, and have a positive overall experience. More research is needed to better understand how women experience trust in the birthing environment specifically, including better understanding of the frequencies of agency, consent, and control over their environments. In addition, research surveying the use of interdisciplinary communication and communication mechanisms with women regarding birth plans might illuminate fragmented communication in the birth environment.

Limitations

Within this study there were some primary limitations related to sampling of studies. When identifying studies through databases and services such as GoogleScholar, embargoes and artificial intelligence interference [e.g., search algorithms] create challenges in replicating and updating searches. For this study, the search was initially conducted then redone to ensure all studies were identified since sufficient time had passed since the initial search. Although exact keywords and procedures were followed from search one to search two, algorithms and embargoes may have led to some key studies not emerging in the search. A second limitation is that given the breadth of birthing environments and cultural orientations to birthing, despite the number of studies analyzed, it is likely that some experiences are not represented in this study.

While the experiences of the participants appeared to range, the scope of the search did not include birthing person experiences outside of the US. Consequently, this leaves the results of this study to only be applicable to what is needed in the small context of the US. Problems that are faced by participants in this study may not be seen as harmful to others. Likewise, since QIMS-DTT is a social work focused method, it can limit how the researchers approached the material from the participants. This can be related to the complex nature of constraints that are often faced in the health-care field. Furthermore, there is a limitation related to the relevancy of applying the TSCS to the birthing space. A key difference between the concept of service in birthing space is that mothers only spend an average of 24 to 48 h in the birthing space, whereas those in nursing care, the environmental in which TSCS originated, could spend an extended period of time in the environment.

In conclusion, a new framework using the Theory of Supportive Care Settings can be applied to evaluate a sacred and healing birthing experience. This new framework includes a balance of already documented phenomenon such as agency and control during birth, as well as integrates new findings, such as the necessity of a warm welcome into the birthing environment to promote trust, comfort, and empowerment. Indeed, the importance of a welcoming environment cannot be overstated. It sets the initial tone for the birthing experience, influencing the individual's stress levels and emotional state, which, in turn, can affect the physiological aspects of childbirth. This study supports the hypothesis from applying TSCS to the birth environment that when individuals feel welcomed, they are more likely to experience a sense of calm and readiness for birth, which can lead to more positive outcomes.

Our study contributes to the growing body of literature that underscores the significance of the birth environment in shaping birth experiences. It calls for a reevaluation of current practices and environments in which childbirth takes place, advocating for a more holistic approach that encompasses emotional, psychological, and physical well-being. The implications of our findings extend beyond the individual, suggesting that by improving birth experiences, we can foster better early bonding experiences, potentially leading to long-term benefits for both the mother and child.

Authors’contributions

Authors DM and SL contributed to the initial design and concept. DM, SL, RT, and TG all performed data collection, data analysis, interpretation of results, and drafting of the article. All authors made substantial contributions to the initial and revised manuscript. All authors have read and approved the final version and are accountable for all aspects of the work.

Availability of data and materials

The data used in this study are from publicly available existing literature, therefore the data is available within this article from the data tables.

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Maxwell, D., Leat, S.R., Gallegos, T. et al. Sacred space: a qualitative interpretive meta-synthesis of women’s experiences of supportive birthing environments. BMC Pregnancy Childbirth 24 , 372 (2024). https://doi.org/10.1186/s12884-024-06544-6

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Received : 06 November 2023

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DOI : https://doi.org/10.1186/s12884-024-06544-6

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