Thematic Analysis

My analysis was based heavily on the work of Braun and Clarke (2006) and their step-by- step guide to thematic analysis. I chose this approach as it is more prescriptive than others while remaining flexible, is in line with my theoretical stance and addresses the research aims. Thematic analysis is a method for identifying, analysing and reporting patterns (or themes) within data. At its most basic level it organises and describes the data, with more sophisticated analysis interpreting aspects of the phenomenon under scrutiny (Boyatzis, 1998).

A common discourse within thematic analysis and qualitative analysis in general, is that of ‘themes emerging’ from the data during analysis. Taylor and Ussher (2001) argue that: “Discursive themes do not just lay about waiting to be discovered, they do not simply emerge, but must be actively sought out” (p.310). Braun and Clarke (2006) develop this idea further by highlighting that describing themes as ‘emerging’ presents analysis as a passive process and does not take into account the active role the researcher plays in identifying, selecting and reporting themes. This implies that the themes exist in the data independent of the researchers’ interpretations, a position that is not consistent with a phenomenological stance. Braun and Clarke stress the point that thematic analysis is about making decisions regarding the data and recognising them as decisions.

Thematic analysis can be either deductive or inductive. Deductive analysis works from a pre-existing coding frame generated from theory or building on prior research. Inductive analysis generates themes from the data with no prior assumptions or framework (Boyatzis, 1998; Patton, 2002). As the purpose of this research was to explore the PPI process from the perspective of those involved, with the belief that currently little is ‘known’ in the literature, my analysis was an inductive one. All codes and themes originated from my interpretations of the data during the analysis process, with the research objectives as a guide. Figure 8 describes Braun and Clarke’s (2006) six phases of thematic analysis which I used as the basis of my analysis. In addition, in keeping with the ethnographic approach, I viewed my fieldnotes as part of phase one (Hammersley & Atkinson, 2003) and viewed the process of writing as an ‘analytical tool’ to further data analysis and integration of related empirical literature (Hammersley & Atkinson, 2007). This placed greater importance on phase six than implied by Braun and Clarke.

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Figure 8: Phases of thematic analysis, from Braun and Clarke (2006, p.87)

As each interview was completed it was transcribed verbatim by a professional scribe. The decision not to transcribe the interviews myself – useful to facilitate the familiarisation process – was based on two factors. Firstly the number of interviews meant that transcription would be very time consuming and I might not be able to finish one set before the next round of interviews, affecting the iterative nature of the ethnography. Secondly the use of correct spelling, grammar and punctuation is extremely important during transcription as it can affect the meaning of and in turn the interpretation of a sentence. Achieving the required level of accuracy is outside of my abilities given my dyslexia. Once I received a completed transcript I checked it against the audio recording to ensure accuracy and anonymity.

As detailed in Section 2.6.1 alongside the formal, semi-structured interviews I also collected data in the form of fieldnotes from my observations and relevant documents. As I collected data they were combined in one NVivo database, making up my data corpus. Each piece of data was cross-referenced by site, type of data, type of participant (professional or representative) and pseudonym. This was necessary to manage the quantity of data collected and reduce the likelihood of information getting lost or missed. NVivo’s ‘query’ function allows for cross-referencing and pulls out information based on code and category. For example, it can pull out all data coded as ‘challenges’ within the representatives’ data, or data coded as ‘process’ in a given site. This made it easier to analyse the data as a whole and by sub-group, which was required for reasons that will become apparent later in this section.

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Each type of data was treated in the same exact same manner. As it was imported into NVivo I read it through carefully (at least twice), recording any thoughts or ideas for further exploration using the ‘memo’ function (phase 1). During this time I also started to generate initial codes (phase 2). These early codes were very broad sweeping and loosely based on the interview questions, for example: benefits, challenges, motivations and understanding of PPI. Rather than adopting a grounded-theory, line-by-line coding method (Glaser & Strauss, 1974), I used a broader point-by-point approach to help keep the parts of the data linked to the whole (Riessman, 2008).The time frame of the data collection (see Figure 6) meant that I was able to do preliminary coding of the data from the comparator epilepsy network prior to conducting interviews at other sites. After reviewing these initial codes and reading over the ‘memos’ I started to identify possible areas of interest (phase 3), to explore further during subsequent observations and interviews (phase 4). Throughout my data collection period I cycled through phases 1-4 as new data was collected. I went through preliminary coding and I identified potential areas of interest that were then explored. Alongside regular reflective discussions with my supervisors (one of whom, as noted, was also a primary informant), I had many opportunities to explore and test my developing theories with different participants across different sites, both formally as part of interviews and informally during unstructured conversations, providing a consistent form of member checking. I prioritised analysing data from participants who were interviewed at multiple time points and keeping track of potential themes or things to ‘follow-up on’ in my fieldnotes to ensure that later interviews were grounded in, and developed from, pre- existing data. One of the main advantages of conducting multiple interviews was that it gave me an opportunity to clarify any ambiguity arising from preceding interviews in subsequent ones. This iterative method of analysis meant that both my fieldnotes and interview data became enmeshed as information from the fieldnotes helped to determine interview questions, and participants responses in interviews affected what I focused on during my observations.

Consequently, by the end of my data collection period I was already very familiar with the data and had developed ideas about codes and themes for when I shifted to a period of more focused and intense analysis. Building on the preceding analysis the whole data corpus was re-read and coded. I felt that this was particularly important as some of the earlier data had not been looked at in light of later insights and codes. By this stage of the process the codes were less linked to the original topic guide and were more detailed. For

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example, rather than just coding data as a ‘challenge’, it was also coded by ‘type’ of challenge, which by this stage of the analysis consisted of 43 sub-codes that I had identified over the course of the data collection and analysis process. By the end of the data analysis process as a whole there were 109 codes and 169 sub codes, although it needs to be noted that many of the codes heavily overlapped.

Having established this overview of the data corpus I started to define and name themes within the data (Phase 5). It became apparent to me that there were four main areas of interest that I then pursued by conducting more focused analysis.

The first area of interest and analysis concentrated on data related to the PPI processes within each of the sites (this was largely based on the professionals’ data and fieldnotes). Drawing on the questions, what did they actually do? and why did they do it?, this helped to address research objective 1: ‘To describe how PPI was implemented within the specific context of the UKERN, and in the research linked to this network’, and to provide a context for the rest of the findings (see Chapter 3). The second area of interest and analysis drew exclusively on data from the professionals to explore their experiences and views of PPI. The findings of this analysis are presented in Chapter 4. The same process was then repeated with the focus on the representatives for the third analysis (see Chapter 5) thus addressing research objective 3: ‘to describe the experiences of the representatives and professionals involved in the PPI process, including their perceptions of the benefits and challenges of PPI’.

During the second and third focused analysis the professionals and representatives were initially treated as a cohesive group. The data was then further analysed to look at the experiences across and within sites, this was part of the fourth ‘synthesis’ analysis. As explained in section 2.3 the hermeneutic circle moves between interpretations of the parts of a phenomenon under study and the whole (Chadderton, 1994) so that by systematically exploring the whole, new insights and an increased depth of understanding of the phenomenon will be produced. This information is then used to examine the sub- components of the phenomenon, in turn resulting in new understandings that need to be re-explored in terms of the whole (Leonard, 1994). I drew on the premise of the hermeneutic circle during the fourth analysis in order to address objective 4: ‘to compare different approaches of implementing PPI, by contrasting the experiences of the professionals and representatives across the different research sites’. As insights were

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gained from the three sub- components or themes they were then used to examine my data as a whole. For example was there any consistency across all the groups about what were considered essential aspects of PPI? Was there any consistency in the decision making process about the approaches to PPI adopted by each of the sites? Where was there dissidence in opinion? Was there any anomalous information that provided insight into a majority view? As I developed my understanding of PPI in my sites as a whole this information was then evaluated and re-tested within the sub-components, which in turn fed into my understanding of the whole. This continued until I had reached the point that I considered ‘optimal understanding’ (see Chapter 6).

My ideas were developed through discussions of my findings with my supervisors, informal discussions with my colleagues and presenting at the PhD data analysis sessions in my department. These meetings provided me with space to step back from the data and to obtain the opinions of others not immersed in it. This was invaluable as it helped me evaluate and justify the decisions I was making with regard to my analysis.

As identified by Broun and Clarke (2006) the 6th phase of a thematic analysis is producing the report. In writing my results chapters I was continually refining themes, making decisions regarding which themes and codes were pertinent, linking them to each other, to the research question and relevant literature. It was also the point at which I had to choose which extracts in my substantial data set most supported my findings. During the concentrated data analysis process I found that the data from documents was not, on the whole, as pertinent as that from interviews and fieldnotes. While in some cases they gave insight into process, they gave little understanding of people’s experiences and perceptions. Consequently they are only sparsely represented in the following results chapters. As previously mentioned my fieldnotes were enmeshed with my interviews, many of the issues identified in my fieldnotes were discussed directly with participants in the formal interviews. In presenting my data in the following chapters, I have prioritised examples of findings from the interview data over that of fieldnotes as it allows for more of the results to be supported by participants’ own words.

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