Thematic Analysis and Grounded Theory

Thematic analysis is widely used analytic method in qualitative research, valued for its flexibility and the potential it presents to produce a “rich and detailed, yet

complex, account of data” (Braun & Clarke, 2006, p. 78). Thematic analysis searches for repeated patterns throughout a set of data. Boyatzis (1998) identifies thematic analysis as a process ideally suited for use with the mass quantities of data generated in qualitative studies and involving three stages: deciding on sampling and design; developing themes and a code; validating and using the code. This has been expanded by Braun and Clarke (2006) to six phases as followed in this study:

 familiarizing yourself with the data;

 generating initial codes;

 searching for themes;

 reviewing themes;

 defining and naming themes; and

 producing the report.

Boyatzis (1998) observes that a code that is useful in every stage of the analysis and interpretive processes “is one that captures the qualitative richness of the

phenomenon” (p. 31). Attaching a code begins the organization of data by enabling identification of themes emerging in a process of interpretation and involves the recognition of important moments in the text under consideration. Encoding can be

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theory driven, prior data or research driven, or data driven. Theory driven code development proceeds from the researcher‟s theory established prior to undertaking the study and for which support is sought from the data. Prior data or research driven coding employs the codes developed by other researchers while data driven codes remain close to the data without attempting to impose a pre-existing coding

framework. For this study, data driven coding was utilised with the aim of reflecting the raw data as closely as possible (Boyatzis, 1998; Braun & Clarke, 2006).

Having identified and drawn together data that are related into patterns or themes, both further organization and analysis or interpretation of data are facilitated. Themes identified are those that are of importance to the phenomenon being studied and these can be identified at two different categories or levels of analysis: the explicit or semantic level identifies themes at a surface, visible or apparent level while latent themes identified are underlying “ideas, assumptions and

conceptualizations - and ideologies” (Braun & Clarke, 2006, p. 84) of the data and are necessarily more interpretive.

It is acknowledged in thematic analysis that the search for and discovery of themes arising from the data cannot be finished completely (Boyatzis, 1998). Hatch (2002) concurs, commenting that no qualitative analysis can ever be complete as “there are always more data than can be adequately processed, more levels or understanding than can be explored, and more stories than can be told” (p. 149). This reflects the comment by van Manen (1997), as related previously in section 5.1, that the possibilities for further interpretation will never be exhausted.

It is notable that the necessity for researchers to be “open to all information”

(Boyatzis, 1998, p. 9), to become immersed in the data, and the constant reading and re-reading of the data employed in thematic analysis reflect a foundational principle of hermeneutic phenomenology (Fereday & Muir-Cochrane, 2006; Hatch, 2002). The hermeneutic spiral or circle, the constant return from the part to the whole, ensures that the themes developed remain connected strongly to the original data and provides a sense of the whole in context, regarded as essential in hermeneutic

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Just as thematic analysis ensures a strong connection to data collected,grounded theory is explicitly a strategy to develop or generate theory inductively from data (Punch, 2009). The data becomes reduced as connections between concepts

emerging are integrated to construct theory (Punch, 1998), establishing relationships between concepts regarded as essential. To Strauss and Corbin (1998) theory is “a set of well-developed concepts related through statements of relationship, which together constitute an integrated framework that can be used to explain phenomena” (p. 15). These relationships are established through coding in a systematic process. Grounded theory was originally formalised by Strauss and Corbin in 1967, providing researchers with a framework with which to approach qualitative data and to

legitimize qualitative inquiry, however the approach has continued to develop from the original into four manifestations; those of dimensional analysis, situational analysis, constructivist grounded theory and Glaserian grounded theory (Charmaz, 2006; Morse et al., 2009). This study adopts a constructivist grounded theory approach to data analysis to take the study towards the development of theory through the identification of related concepts which describe the experiences of the participants in this study.

In the grounded theory approach, theory is seen as a set of propositions which show the connections between concepts at a higher level of abstraction than the data themselves. Coding is central to grounded theory, as it is to thematic analysis, enabling the researcher to build rather than test theory (Strauss & Corbin, 1998). Using grounded theory procedures, four levels of coding may be undertaken: open coding, focused coding, axial coding, and theoretical coding. Open coding is the initial level of analysis, where the data are opened up, “broken down into discrete parts, closely examined and compared for similarities and differences” (Strauss & Corbin, 1998, p. 102). Data are used to generate broad or narrow categories that are “grounded abstract concepts” (Punch, 1998, p. 211), where categories identify significant phenomenon arising from the data. Identifying concepts that are relevant involves interaction with the data, asking questions of the data to establish what is happening or what is being expressed (Corbin & Holt, 2005).

Axial coding searches for subcategories to further define properties of the category so as to add coherence to the emerging analysis. According to Strauss and Corbin

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(1998, p. 125) “a subcategory answers questions about the category such as when, where, why, who, how, and with what consequences” while Charmaz (2006) comments that undertaking axial coding may “make grounded theory cumbersome” (p. 63). Corbin and Holt (2005) maintain however, that axial and open coding occur concurrently as “it is impossible for an analyst to pick out a concept from data without recognizing its possible connections to other bits of data and concepts” (p. 50). The final coding type utilised, theoretical coding, involves a process of

integrating and refining the categories into theory; a bringing together of the pieces. Theoretical coding also moves analysis to a conceptual level. It is of importance to acknowledge that there are different ways concepts can be integrated, rather than a single correct statement of relationships existing (Strauss & Corbin, 1998). This study adopted a constructivist approach to grounded theory as described in Morse et al., (2009) and Corbin and Holt (2005) where constructivist grounded theory makes a number of assumptions: that there are multiple realities and multiple perspectives on the realities; that data are constructed mutually through the

interaction of researcher and participant; and that analysis arises from this

interaction, and that therefore subjectivity is present and inheres the data analysis process. Data are regarded as situational as researcher and participant are situated in the context and analysis does not isolate the phenomenon from its location whether social or historical, but rather constructivist grounded theory “reshapes the

interaction between researcher and participant” (Mills, Bonner, & Francis, 2006, p. 31). In adopting a grounded theory approach to data analysis it is again

acknowledged that, for the constructivist, the theory that results is an interpretation, dependent on the researcher‟s approach and perspective (Charmaz, 2006).

Scholars acknowledge that grounded theory is not a prescribed method or formulaic techniquesbut rather a “way of thinking about data – processes of conceptualization- of theorizing from data” (Morse et al., 2009, p. 18). Charmaz (2006) presents the grounded theory process in a linear form with the qualification that, in reality, the process may not follow a linear pattern. In this study, grounded theory was used as a framework for approaching data, although the processes of grounded theory as developed originally or those suggested by Charmaz (2006) were not adhered to strictly. As pointed out in the current literature, grounded theory method involves

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“systematic, yet flexible guidelines” (Charmaz, 2006, p. 2), Morse et al. (2009) agreeing that techniques and procedures adopted are “to be used by the researcher as he or she sees fit to solve methodological problems... They are not a set of directives to be rigidly adhered to” (p. 40).

One aspect that continues to generate debate in the grounded theory discourse is the timing of the literature review in the analysis process, with Strauss and Corbin (1998) cautioning that if undertaken early in the process, there is a danger of becoming “so steeped in the literature” (p. 49) that it detracts from making discoveries. In this study the researcher conducted an initial review prior to

undertaking data analysis to gain insight and to establish the “bearings” for the study, as aspects from a number of discourses inform the study returning regularly to the literature for clarification as necessary.

The issue of whether meaning emerges from the data or is constructed or co- constructed by researcher and participant is an area of difference between the

traditional grounded theory, the emergent viewpoint, and the constructivist approach. Charmaz (2006) notes that at times scholars and researchers “talk about discovering theory as emerging from data separate from the scientific observer” (p. 10). In the emergent viewpoint a single theory or truth or reality is “inherently embedded” in the data (Corbin & Holt, 2005, p. 49). According to the constructivist viewpoint a set of data can be interpreted in many ways, there are “multiple realities” (Corbin & Holt, 2005, p. 49), while grounded theory is constructed “through our past and present involvements and interactions with people, perspectives, and research practices” (Charmaz, 2006, p. 10).

In this study, the term emerge has been adopted to describe the process through which concepts that of importance are located within the data and then coded, it would seem that the term best captures the strong links to the data that the process maintains and the sense of immersion in the data already co-constructed by researcher and participant. However, it is acknowledged that the researcher

constructs codes, themes or theories to make sense of what is observed and that the final rendering is a construction of the reality as interpreted by the researcher; the researcher is active in the process. Analytic tools are used by the researcher to

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“clarify thinking, provide alternate ways of thinking about data and facilitate the teasing out of relevant concepts from data” (Corbin & Holt, 2005, p. 50).