Volume 20, No. 3, Art. 32 – September 2019

Qualitative Content Analysis: A Novice's Perspective

Amir B. Marvasti

Abstract: In this article, I consider how qualitative content analysis (QCA) relates to other qualitative research methods and the field of qualitative research in general. I begin by reviewing the commonalities between QCA and more generic forms of content analysis and grounded theory methodology. I then suggest how QCA practitioners can reach a larger audience by more systematically 1. attending to the diversity of qualitative research paradigms, 2. better differentiating and theorizing the content under analysis and 3. more fully engaging in the emergent debate about mixed methods.

Key words: qualitative content analysis; qualitative research; grounded theory methodology; mixed methods; narrative analysis; interviews; international dialogue

Table of Contents

1. Introduction

2. Qualitative Content Analysis versus Content Analysis

3. Defining Qualitative Research

4. Importance of Content Type

4.1 Qualitative content and the interview

4.2 Qualitative content and narratives

5. Mixed Methods

6. Conclusion






1. Introduction

Although I am familiar with qualitative research (MARVASTI, 2003; SILVERMAN & MARVASTI, 2006) and forms of content analysis (CA), I am a novice in the subfield of qualitative content analysis (QCA). This is in part because outside of the Continent no special emphasis is placed on the qualitative aspect of CA. Instead, CA is mostly used as a generic phrase to describe the process of reducing textual data (written or visual) into smaller, often quantifiable segments following a set of specific codes. Therefore, it is fitting that I begin this article with a broad description of what CA is and how it relates to QCA (Section 2). I then consider three important dimensions of qualitative research: the diversity of the field (Section 3), the theoretical significance of qualitative content (Section 4) and the emergence of mixed methods (Section 5) that might be of interest to practitioners of QCA as they try to engage in a dialog with their counterparts, particularly in the United States. [1]

2. Qualitative Content Analysis versus Content Analysis

With the use of CA, large amounts of data become more manageable, or as Martin BAUER puts it, CA involves "systematic classification and counting of text units [to] distill a large amount of material into a short description of some of its features" (2000, pp.132-133). Another strength of CA is that the analysis is replicable by others:

"The objectivity of content analysis resides in the devising of precisely and clearly defined categories to apply to the material analyzed in accordance with explicitly formulated rules and procedures. In principle, different analysts using the same categories and rules would obtain identical results from their analysis of any given body of data" (BALL & SMITH, 1992, p.21). [2]

Adapting BALL and SMITH, the basic steps in CA include:

  • define the research problem or question;

  • decide what the source of the material will be;

  • identify the categories or features that will be the focus of research;

  • sample documents from the sources previously defined;

  • measure or count the occurrence of the pre-established categories. [3]

More broadly, CA can be approached as a continuum of analytic options with varying emphasis on the quantitative and qualitative dimensions of data and data collection (BORÉUS & BERGSTRÖM, 2017; SCHREIER, 2012). As SCHREIER notes, in the pedagogy of social science research published in English, QCA is rarely treated as a separate method, the most notable exception being her own book "Qualitative Content Analysis in Practice" (2012), which is referenced throughout this chapter. For example, in "Content Analysis: An Introduction to Its Methodology," under the heading "Qualitative Approaches" to CA, Klaus KRIPPENDORFF (2013) lists discourse analysis, constructivist analysis, rhetorical analysis, ethnographic content analysis, and conversation analysis. In fact, KRIPPENDORFF casts doubt on the necessity of the qualitative-quantitative divide when he states: "I question the validity and usefulness of the distinction between quantitative and qualitative analyses. Ultimately, all reading of texts is qualitative, even when certain characteristics of text are later converted into numbers" (p.22). The scant coverage of QCA is evident in other texts, such as the brief discussion of SCHREIER's approach to QCA in Kristina BORÉUS and Göran BERGSTRÖM's "Analyzing Text and Discourse" (2017). [4]

In the United States, in particular, the possibility that CA can be conducted in a manner that is purely qualitative and inductive (working from observations to discern specific thematic patterns) is subsumed under "grounded theory methodology" (GTM), originally developed by Barney GLASER and Anselm STRAUSS in "The Discovery of Grounded Theory" (1967). In their words:

"A grounded theory that is faithful to everyday realities of a substantive area is one that has been carefully induced from diverse data, as we have described them. Only in this way will the theory be closely related to the daily realities (what is actually going on) of substantive areas, and so be highly applicable to dealing with them" (p.239). [5]

As this quote indicates, following GTM, researchers are encouraged to theorize in direct and close connection with their empirical data, moving from observations to concepts and theoretical statements (compared with a deductive approach, where the research begins with a specific hypothesis that is subsequently tested using empirical data). In a more contemporary conceptualization of GTM, Kathy CHARMAZ describes the following as the key features of the method:

"[A] simultaneous data collection and analysis, (b) pursuit of emergent themes through early data analysis, (c) discovery of basic social processes within the data, (d) inductive construction of abstract categories that explain and synthesize these processes, (e) sampling to refine the categories through comparative processes, and (f) integration of categories into a theoretical framework that specifies causes, conditions, and consequences of the studied processes" (2002, p.677). [6]

As a novice, I began learning about QCA with this background in mind. My understanding of the method thus far suggests that QCA has much in common with GTM. Of course, such similarities are not lost on the practitioners of QCA. For example, in her discussion of a "data-driven strategy," SCHREIER suggests researchers can "adapt the steps of data analysis in grounded theory to generating inductive categories" (2012, p.88). Additionally, as is true with many other methods, it is apparent that there is not a single unifying approach that defines QCA. Philipp MAYRING, a leading scholar in the field, offers this definition: "Qualitative content analysis defines itself within this framework as an approach of empirical, methodological controlled analysis of texts within their context of communication, following content analytical rules and step by step models, without rash quantification" (2000, §5). In another source, the approach is described as "a research method for the subjective interpretation of the content of text data through the systematic classification process of coding and identifying themes or patterns" (HSIEH & SHANNON, 2005, p.1278). A similar definition is provided by SCHREIER: "QCA is a method for systematically describing the meaning of qualitative material. It is done by classifying material as instances of the categories of a coding frame" (2012, p.1). With these definitions, it seems that analytically QCA is positioned between the qualitative and the quantitative, or between positivistic and constructionist views of qualitative research, thus SCHREIER's assertion that "we construct meaning" but "meanings can be more or less standardized" (p.2), or HSIEH and SHANNON's suggestion that QCA can be at once "subjective" and "systematic" (2005, p.1278). On the one hand, the systematic view of data analysis in QCA echoes the positivistic tendencies of its quantitative progenitor (numerical CA), while its emphasis on "subjective interpretation" (ibid.) is consistent with the more qualitative end of the research continuum. [7]

When it comes to the actual conduct of research, or the basic steps involved in analyzing data, QCA does not vary considerably from the more traditional forms of CA. For example, the steps offered in SCHREIER's textbook for conducting QCA (2012) are similar to the procedures of CA described earlier in this article. Specifically, both involve a process that begins with a research question, proceeds to data collection, and ends with systematic coding and analysis. [8]

Despite these procedural similarities, proponents of QCA do offer a unique take on CA that can advance qualitative research in new directions. Specifically, the potential of QCA for aligning the subjective and the systematic should be of interest to all qualitative researchers, regardless of their particular methodological preferences. In my view, to reach this potential fully, QCA researchers should continue their dialog with the broader field of qualitative research. This interest in explicating the substantive and theoretical focus of QCA is indeed shared by its practitioners and is part of the discourse within the field (JANSSEN, STAMANN, KRUG & NEGELE, 2017). In the remainder of this article, I consider how QCA researchers can especially benefit from systematic consideration of the following topics: 1. definition of qualitative research, 2. theorizing the content of qualitative research and 3. mixed methods. [9]

3. Defining Qualitative Research

Adding the word "qualitative" to a type of analysis, in and of itself, reveals little about the approach. This point is astutely acknowledged in SCHREIER's textbook, where she considers the question "What is qualitative about qualitative content analysis?" (2012, p.20) and devotes an entire chapter to reviewing the key features of qualitative research (interpretive, naturalistic, reflexive, and inductive) and their overlap with QCA. This is a crucial step for defining the terrain of QCA as a subset of qualitative research. Here I would like to further SCHREIER's discussion by pointing out that qualitative research is a constellation of practices and methodologies (MARVASTI & TREVINO, 2019). As Carolyn ELLIS and Laura ELLINGSON put it:

"Qualitative researchers may be placed along a broad continuum ranging from an orientation akin to positivist science to one more akin to art and literature. In between is a vast middle ground where elements of both orientations are present. Across the continuum, the focus changes from studying others who are assumed to be uniquely separate from the researcher, to examining interactions between the researcher and others, to including the positionality, politics, and story of the researcher who interacts with others" (2001, p.2287). [10]

As indicated in this quote, the degree to which qualitative research is reflexive, interpretive or naturalistic (to borrow some of the key features of the approach outlined by SCHREIER) varies across "interpretive communities" (MILLER, 1997a, p.8). Autoethnography, for example, is far more reflexive than its more naturalistic predecessors. Furthermore, within autoethnography, there are multiple competing, if not conflicting, perspectives (ANDERSON, 2006; ELLIS, ADAMS & BOCHNER, 2011). [11]

Norman K. DENZIN and Yvonna S. LINCOLN suggest that there are multiple paradigms (such as positivism and post positivism) within the field of qualitative research and add that

"[q]ualitative research, as a set of interpretive activities, privileges no single methodological practice over another. As a site of discussion or discourse, qualitative research is difficult to define clearly. It has no theory or paradigm that is distinctly its own" (2018, p.12). [12]

Similarly, in "The New Language of Qualitative Method," Jaber GUBRIUM and James HOLSTEIN highlight distinct and at times conflicting "idioms" (1997, p.viii) within the field and note that

"[p]erhaps because it is typically counterposed with the contemporary monolith of quantitative sociology, qualitative method is often portrayed in broad strokes that blur differences. We believe it's important to recognize and appreciate these differences in order to evaluate their separate contributions as well as their overall direction" (p.5). [13]

Types of qualitative research and analysis also vary in terms of the emphasis placed on research practices themselves, or whether methodological rules are seen as fixed or emergent. For example, Clive SEALE, Giampietro GOBO, Jaber GUBRIUM and David SILVERMAN argue that methodological rules for conducting qualitative research are often modified and adapted in practice by researchers. In their words: "[W]e believe that debates and textbooks about qualitative research are best understood by foregrounding the practical activities of researchers" (2004, p.1). Another important debate among qualitative researchers in the US context, in particular, is about politics and social change (DENZIN & GIARDINA, 2011). The point is that qualitative research is not a static and unified point of reference that can be used easily as a marker for identifying QCA. Thus, it may be more fruitful for QCA researchers to define their endeavors relative to a particular methodological perspective within qualitative research rather than the field in general. This type of theoretical development within QCA is important because "the language of qualitative method shapes knowledge of social reality" (GUBRIUM & HOLSTEIN, 1997, p.5). Awareness of the ontological stance of QCA toward social reality and the practices and politics of qualitative research would expand readers' appreciation of why certain types of questions and data might be particularly suitable for QCA. [14]

4. Importance of Content Type

The content analyzed by qualitative researchers comes in many forms. Distinctions include verbal, written, and visual, as well as existing versus researcher-generated data. While some qualitative methods are exclusively utilized for one category of data, such as conversation analysis, QCA does not seem to be restricted to a particular type of data. For example, MAYRING states: "The object of (qualitative) content analysis can be all sort of recorded communication (transcripts of interviews, discourses, protocols of observations, video tapes, documents ...)" (2000, §4). Similarly, SCHREIER notes:

"QCA can be applied to a wide range of materials: interview transcripts, transcripts of focus groups, textbooks, company brochures, contracts, diaries, websites, entries on social network sites, television programs, newspaper articles, magazine advertisements, and many more" (2012, pp.2-3). [15]

However, SCHREIER acknowledges that some types of data, or at least some types of analyses, are not compatible with QCA. For example, she cautions that: "Narrative analysis, for example, is difficult to combine with QCA in general" (p.57). An important question here is whether the content represents mere facts or constructions and underlying constructive practices. In the next section, I expand on this analytic sensitivity about the type of material under consideration by theorizing qualitative content itself. I apply this consideration to two topics: the research interview and narrative content. [16]

4.1 Qualitative content and the interview

The interview is likely the most common type of data collection among qualitative researchers. HOLSTEIN and GUBRIUM (1995) suggest that one way to treat the interview is as a data extraction tool that brings to the surface inner truths about the respondent. In this sense, the interview is merely a tool for collecting content that will be subjected to analysis later in the research process. Likewise, the researcher takes on the role of simply administering the interview by asking carefully worded questions and following a rigid protocol. Under these conditions, it is assumed that the respondents will disclose "the unadulterated facts and details of experience under consideration" (p.8). Alternatively, according to HOLSTEIN and GUBRIUM (1995, 1997), the interview can be seen as a social occasion in which the respondent and the interviewer are engaged in the production of meaning (also DEPPERMANN, 2013; LAMPROPOULOU & MYERS, 2012). HOLSTEIN and GUBRIUM (1995, 1997) argue that the analysis of the interview requires attention to joint activities. To put this in the context of QCA, the analysis of the interview must attend to both what the content represents objectively as well as how it comes into existence through subjective interactions. [17]

The reduction of data to codes or themes in QCA raises the question: To what degree can the contextualized practices and interactional dynamics of the interview be incorporated into the analysis? CHARMAZ and BELGRAVE explain how this question in essence divides grounded theory researchers into two camps: "Constructionist grounded theorists acknowledge that they define what is happening in the data. Objectivist grounded theorists assume that they discover what is happening in the data" (2012, pp.355-356). My admittedly tenuous grasp of QCA suggests that the approach leans toward the objectivist side of the debate. However, I suspect what constitutes data in QCA is more nuanced than that. For example, MAYRING describes four types of QCA: "summarizing content analysis," "inductive category formation," "explicating content analysis" and "structuring content analysis" (2004, p.269). He adds that within each approach content and context are treated differently. In particular, MAYRING notes that "explicating content analysis" involves "additional material beyond the text (information about the communicators, subject, socio-cultural background, target group)" (ibid.). My point is that a blanket statement that a certain type of analysis can be applied to all types of qualitative data runs the risk of overlooking the context of the data collection itself, thus contradicting the notion that QCA is qualitative because it attends to the context and subjective nature of content. A deeper analytical engagement with qualitative methods within QCA would consider how different types of qualitative analysis attend to different features of social reality and its production, as GUBRIUM and HOLSTEIN (1997) point out in their discussion of the different languages of qualitative research. As I discuss in the next section, analytic sensitivity to content type extends to working with narrative data as well. [18]

4.2 Qualitative content and narratives

The importance of content for the purpose of analysis is perhaps best illustrated using the case of narratives. In particular, the debates over what constitutes a narrative and what it represents demonstrate the significance of content type for qualitative researchers and its impact on how their analyses are conducted. Storied information, or narrative content, can come from respondents, existing scholarly and literary texts, or from researchers themselves. Scholars in this field take the position that narratives are ubiquitous:

"Narrative is present in myth, legend, fable, tale, novella, epic, history, tragedy, drama, comedy, mime, painting (think of Carpaccio's Saint Ursula), stained glass windows, cinema, comics, news item, conversation. Moreover, under this almost infinite diversity of forms, narrative is present in every age, in every place, in every society; it begins with the very history of mankind and there nowhere is nor has been a people without narrative" (BARTHES, 1977, p.79, cited in FRANZOSI, 2010, p.12). [19]

Furthermore, some researchers assert that there is something inherently authentic or natural about narrative content. For example, Laurel RICHARDSON states that:

"Narrative displays the goals and intentions of human actors; it makes individuals, cultures, societies, and historical epochs comprehensible as wholes; it humanizes time; and it allows us to contemplate the effects of our actions; and to alter the direction of our lives" (1990, p.117). [20]

Others take a more moderate stance, emphasizing that narratives should not be favored ontologically over other forms of communication or content. Paul ATKINSON, for example cautions: "[T]he ubiquity of narrative and its centrality to everyday work are not license simply to privilege those forms" (1997, p.341). There is also much scholarly debate about the very definition of "narrative." Catherine K. RIESSMAN (2008) discusses several approaches to defining narratives. For example, a formal definition would emphasize the presumably inherent features of a narrative: length, sequence, and the presence of an obstacle or disruption for the protagonist to overcome. RIESSMAN points out that the definition of "narrative" is ultimately decided by a researcher's discipline and ontological orientation toward the research content:

"The term narrative in the human sciences can refer to texts at several levels that overlap: stories told by research participants (which are themselves interpretive), interpretive accounts developed by an investigator based on interviews and fieldwork observation (a story about stories), and even the narrative a reader constructs after engaging with the participant's and investigator's narratives" (p.6). [21]

Types of narrative analysis vary depending on which feature of a story they capture. Martin CORTAZZI (2001) suggests that narratives can be analyzed based on their: 1. content (the substance of the story), 2. structure (how the story is told), 3. functions (the purposes the story serves) and 4. context (in what place or setting the story is told). Similarly, RIESSMAN (2008) explains that narratives can be analyzed in terms of their underlying themes or structures, how they are themselves constructed, as well as what they construct. Generally, narrative analysis hinges on the question: What does the narrative content represent? This in turn informs what features of a narrative are important for the purpose of analysis. Two possible answers are: 1. narrative content represents some objective truth (similar to the positivistic view of research interviews) or 2. narratives construct reality for a particular audience and in a particular place and time (similar to the idea of active interview discussed above). To put it another way:

"An objectivist approach to narratives seeks to give voice to a subject's presumably true experiences. By comparison, a constructionist approach to narrative analysis would envision a subject who is both constructed through narratives and constructing narratives for varying audiences and purposes" (MARVASTI, FOLEY & DELAMMERMORE, 2019, p.72). [22]

If one were to follow the first answer, the content of a story can be reduced to specific components and even subjected to quantitative narrative analysis (FRANZOSI, 2010). However, when narratives are approached as constructions and constructive of reality, the analysis must attend to how the stories are put together, under what conditions, for what purpose and what they achieve. Collectively, these concerns embody what GUBRIUM and HOLSTEIN call "narrative practice" (1998, p.163). As they explain:

"We use the term ‘narrative practice' to characterize simultaneously the activities of storytelling, the sources used to tell stories, and the auspices under which stories are told. Considering personal stories and their coherence as matters of practice centers attention on the relation between these ‘hows' and ‘whats' of narration, on storytellers engaged in the work of constructing coherence under the circumstances of storytelling. Orienting to practice allows us to see the storytelling process as both actively constructive and locally constrained" (p.164). [23]

Based on this model, in the analysis of narrative content, the researcher simultaneously attends to the substance of the story, its organization, as well as why it is being told in the first place. The implication of this for QCA is that narrative content is about more than its substance, or words that can be coded into a set of themes for the purpose of analysis. Rather, to fully appreciate the subjectivity and context of storytelling, it is essential to understand how words are used to create meaning for a specific purpose, time and place. What matters is not just the content but context and practice as well. For example, in my research on homelessness (MARVASTI, 2002), I studied how clients at an emergency shelter told stories of their plight for the purpose of receiving help. As such, their stories had a locally-specific content and structure. Typically, the stories were about falling victim to circumstances beyond one's control (such as a sudden financial or medical crisis) with the promise of a new beginning or redemption always on the horizon. The shelter staff sometimes helped clients by editing their stories in real time to bring the narratives in line with the shelter's official view of a "service worthy" client (SPENCER, 1994, p.39). Therefore, the substance or content of the stories, or the "whats" (GUBRIUM & HOLSTEIN, 1998, p.164), was intricately and reflexively linked to its "hows" (ibid.). As with the above discussion about interview data, content type matters because it explicitly or implicitly informs the analysis. A static view of content more logically fits to systematic coding of the data; whereas, viewing content as fluid, contextualized, and the product of ongoing practices requires a different analytic vocabulary. [24]

For the purpose of QCA, this means simultaneous attention to the content and how it is used in a specific context. The type of QCA that MAYRING (2004, p.268) labels "explicating content analysis" seems ideal for such a task. However, it is important not to freeze content and context in time and place, but to attend to how content and its context are infused with practice, or variations in what people do or say under different circumstances and for different purposes. My narrative analysis described above could be considered a type of QCA that involved coding interview stories, both in terms of their content and what was achieved with it under those particular conditions. In other words, my coding reflected the fluidity of the content in practice, as perceived through my own assumptions and background as a researcher. As Gale MILLER points out, organizations produce a wide range of content or "texts" and "qualitative researchers are uniquely positioned to study these texts by analyzing the practical social contexts of everyday life within which they are constructed and used" (1997b, p.77). This orientation toward content and context echoes CHARMAZ and BELGRAVE's description of constructionist GTM alluded to earlier. In their words: "We view data analyses as constructions that not only locate our data in time, place, culture and context but also reflect our social, epistemological, and research locations" (2012, p.349). [25]

5. Mixed Methods

The emphasis within QCA for developing a standardized approach to the construction of meaning (SCHREIER, 2012) echoes the central themes of the emergent field of mixed methods (CRESWELL, 2014; TEDDLIE & TASHAKKORI, 2010). The nexus between QCA and mixed methods is elucidated by MAYRING: "The main idea of the procedure of analysis is thereby, to preserve the advantages of quantitative content analysis as developed within communication science and to transfer and further develop them to qualitative-interpretative steps of analysis" (2000, §2, 2001). Mixed methods approaches to research design and analysis emphasize the same level of integration across quantitative and qualitative methods:

"Mixed methods research is the type of research in which a researcher or team of researchers combines elements of qualitative and quantitative research approaches (e.g., use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for the broad purposes of breadth and depth of understanding and corroboration" (JOHNSON, ONWUEGBUZIE & TURNER, 2007, p.123). [26]

To illustrate the similarities between mixed methods and QCA, I consider a study in which Elizabeth G. CREAMER and Michelle GHOSTON used CA "to identify which of the educational outcomes officially endorsed by the engineering accrediting agency [in the US] have been most broadly incorporated into the culture and practices of colleges of engineering" (2012, p.111). During the inductive phase of the project, the researchers coded the mission statements in terms of their institutional objectives, such as promoting diversity. This was followed by the deductive phase where "[q]ualitative data about the values/objectives that were emphasized in each mission statement was converted to a nominal numeric value (1=no; 2=yes) and added to the institutional database" (p.115). The researchers were then able to correlate the presence or absence of certain institutional goals in the mission statements with known outcomes, such as the number of female graduates at a given institution. Among other things, CREAMER and GHOSTON showed that the presence of diversity-related objectives in the mission statement was "significantly correlated with all three measures of the representation of women (proportion of female graduates, r = .417, p .003; number of female graduates, r = .444, p .002; proportion of female faculty, r = .306, p .03)" (p.118). The design of this study closely parallels the type of QCA that MAYRING refers to as "inductive category development" (2000, §10), which he describes as follows:

"The main idea of the procedure is, to formulate a criterion of definition, derived from theoretical background and research question, which determines the aspects of the textual material taken into account. Following this criterion the material is worked through and categories are tentative and step by step deduced. Within a feedback loop those categories are revised, eventually reduced to main categories and checked in respect to their reliability. If the research question suggests quantitative aspects (e.g. frequencies of coded categories) can be analyzed" (2000, §12). [27]

The parallels across QCA and mixed methods research are evident. The innovative and practical research atmosphere created by researchers conducting mixed methods provides a fertile environment for QCA to expand and meld with other research approaches that share its methodological sensibilities. At the same time, there are lessons to be learned from the challenges facing mixed methods scholars in establishing their particular view of social science research. These include questions about "whether paradigms can be mixed (or integrated) in a mixed methods study, where this occurs in the process, and how it is done" (TASHAKKORI & CRESWELL, 2007, p.4). [28]

Another issue worth considering is the criticism that the potential and promise of mixed methods are exaggerated. As Uwe FLICK puts it:

"The fashion and attraction of mixed methods will come to an end once funders, researchers, publishers, and finally its protagonists realize that it is less a solution to all kinds of problems but just another methodological approach with limits and weaknesses" (2018, p.458). [29]

6. Conclusion

As practitioners of a distinct method for analyzing qualitative content, largely conceptualized and practiced on the Continent, QCA researchers have much to offer to the field of qualitative research in general, which, as Petri ALASUUTARI (2004) notes, tends to reflect developments in English-speaking countries. As they develop their analytical framework, QCA practitioners can facilitate dialog with other scholars in the field by engaging some of the issues discussed in this article. Specifically, they can expand their ontological orientation toward context, reflexivity, and practice and connect it with the relevant debates in the field of qualitative research. Overall, QCA researchers would benefit from 1) reflecting on the type or "idiom" of qualitative research (GUBRIUM & HOLSTEIN, 1997, p.3) with which they identify, 2) differentiating between the different contents they can analyze and 3) embracing or appraising their affinities with the emergent field of mixed methods. [30]


The author is grateful to Thomas DAHL, Markus JANSSEN, Margrit SCHREIER, Amanda WHITTAL and the anonymous reviewers for their comments on an earlier draft of this article.


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Amir MARVASTI is an associate professor of sociology at Penn State University, Altoona. His research focuses on the social construction of identity in everyday encounters and institutional settings. He also has an active publication record on the pedagogy of qualitative research. His books in this area include "Qualitative Research in Sociology" (Sage, 2004), "Doing Qualitative Research: A Comprehensive Guide" (Sage, 2008, with David SILVERMAN), "Researching Social Problems" (Routledge, 2019, with Javier TREVINO).


Amir B. Marvasti

Division of Education, Human Development and Social Sciences
Penn State Altoona
3000 Ivyside Park
United States

Tel.: +1 814 949-5448
Fax: +1 814 949-5449

E-mail: abm11@psu.edu
URL: https://altoona.psu.edu/person/amir-marvasti-phd


Marvasti, Amir B. (2019). Qualitative Content Analysis: A Novice's Perspective [30 paragraphs]. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research, 20(3), Art. 32, http://dx.doi.org/10.17169/fqs-20.3.3387.

Copyright (c) 2019 Amir Marvasti

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