Framework for Data Analysis

Template Analysis (King, 2004) is open to use as a data analysis process that recognises the researcher is part of the social world they are investigating. Researchers carry perceptions and preconceived ideas within, even when every effort is made to consciously ‘bracket’ these (Creswell, 2013; Miller & Crabtree, 1992). Both Adaptive Theory and Template Analysis approaches acknowledge that researchers carry their ontological and epistemological influences into the process, along with some expectations around what might be found. What is then encouraged is an opening up to the potential for new phenomena to be uncovered through the research. Template Analysis may be applied from a range of epistemological positions and is “a technique

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which feels eminently suited to this study.

The data analysis Chapters have been structured following themes which emerged from the data - this includes some of the tentative a priori themes which were then emphasised as important in the participants own narrative, represented strongly in the transcribed texts. Following the conventions of Template Analysis provided a method for producing an initial template (Appendix 3) which captured themes identified as important, both from the data set itself and some a priori codes which acknowledges that realistically, some of what I may expect to find, and the nature of the research questions, can provide a few tentative prior themes for the template. However, these can and were adjusted and indeed relegated when the data itself brought in new dimensions or suggested less relevance once coding began. This is different to the Grounded Theory (Glaser & Strauss, 1967) approach to analysis which is viewed as a completely ‘bottom up’ methodology because all the themes are identified in the data set only.

The approach does not involve analysing textual data line-by-line, such as that found in conversational analysis: instead, it enables a more free-flowing process: “It encourages

the analyst to develop themes more extensively where the richest data - in relation to the research questions - are found”. (Brooks & King, 2012, p.4). Also, because this

study was not concerned with conducting conversational analysis, examples used from the raw data in the Chapters analysing and discussing findings, have had filler words such as ‘umm’ and ‘aaah’ - which have no impact on the content (David & Sutton, 2011, p.335), edited out to assist the flow of reading. Having first defined some a priori themes, I thoroughly read through the transcribed interviews to immerse myself once again in their content and direction. It was then possible to begin the initial coding of data - which used the original research focus and questions of this study as a reference point. Themes from the data were then allocated against a priori themes or listed as new ones. This process produced the initial template, illustrating higher order codes (broad themes in the data) and I was able to do this once all the transcripts from the first set of interviews had been reviewed. Once the second data set was produced and read through, the initial template was developed and revised further as each transcript was compared against others, enabling me to continue coding common themes and, most

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importantly identify deeper sub-themes, until a ‘final template’ was arrived at (Appendix 5). As Cassell (2012) observes, Template Analysis offers:

A structured technique for analysing qualitative data that enables researchers to place some order on their data from the start of the analytic process … and a comparatively structured pathway for critically interpreting and presenting empirical findings (Casell, 2008, p.103).

Although acknowledging some prior themes is a recognised characteristic of Template Analysis, the identification of themes in advance needs to be handled with care. One danger King (2012) cautions against is having an overly defined set of a priori themes on the initial template, as this can restrict and ‘blinker’ the analysis process. The researcher needs to consciously check against distortion and ‘convenient positivistic answers’ throughout the iterative routes involved. So, these themes were always viewed as tentative; a helpful way to hasten the first phase of coding. Some further discussion of the data analysis process is outlined in chapter five.

Only a small number of qualitative studies exploring notions of professional identity (Puusa, Kuittinen & Kuusela 2013; Kenny & Briner, 2010; Ross, 2005) have utilised Template Analysis as a flexible approach to data analysis. Yet, Creswell (2005) believes the approach is particularly appropriate for in-depth interviews as it is easy to reconcile to the purpose of particular research compared to more prescriptive analytical approaches. Indeed he is keen to emphasise that traditions of enquiry need not be pure and one might mix procedures from several. This can include an analytical process that moves between theory and data influenced by the research question.

Waring and Wainwright (2008) suggests one criticism of Template Analysis is that it offers little different to what can be generated by analysis software packages such as Nvivo (p.92). However, they take the position – also adopted in this study, that IT applications can act as a barrier to the essential interpretative process that needs to take place; where researchers immerse themselves in the data to identify rich insights about the frequency, nature and relationships of themes, while also contributing new perspectives to inform theory-building. This fits elegantly with the application of the under-used Adaptive Theory methodology (Jacobsen, & Kristiansen, 2012) in this study, with its emphasis on both theory-testing and theory-constructing.

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4.9 Chapter Summary and Conclusion

The purpose of a methodology chapter in its broadest sense is to explore, examine and explain “the systems, principles, theories and values that underpin the approach to

research” (Somekh & Lewin, 2011, p. 326) and of course within this, to deal with some

of the practical, conceptual and ethical concerns of the research project such as sample, method, research schedule, confidentiality, bias and the data analysis process. In this chapter I have aimed to do that: reiterating my research purpose and aims and the underpinning epistemology which led to the choice of Adaptive Theory (Layder, 1998) as methodology. I discussed the selection of a group of DCSs from a Northern region of England as my sample, and some of the very particular concerns related to anonymity and confidentiality which needed to be considered at each stage of the research process. Some organisational context about the participants’ role and operating environment was also provided before I justified my choice of extended in- depth interviews as method to support a narrative research approach. It was important to build a picture, to get a sense of the Psychobiography of my participants as I explored their experiences and identity work - both early career and critical life incidents to help inform how they enact identity in their current role as DCS. Finally, I discussed and qualified my use of Template Analysis (King, 2004) as the most appropriate framework for my data analysis.

The next chapter considers the application of the data analysis framework and an introduction to how the findings are presented and analysed in forthcoming Chapters.

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5. INTRODUCING THE FINDINGS, ANALYSIS AND DISCUSSION