THE DATA ANALYSIS PROCESS 1. Theoretical background

According to Ritchie, Spencer and O'Connor (2003) qualitative analysis requires a mix of creativity and methodology. They argue that there is no single correct analysis method and that considerations of the research objectives and data set are important.

I made the decision to use thematic analysis across the data set. There were several reasons for this choice. Firstly, because the study was exploratory it was essential that the analysis method allowed for revisiting, reworking and refining throughout the process (Braun & Clarke, 2006). Secondly, and for the same reason, I required an analysis approach which would allow for the identification of common sense data characteristics – like participant perceptions of phenomena they encountered in

practice (Ritchie et al., 2003). Thirdly, my project made use of numerous data sources - transplant professionals, transplant coordinators, cadaver donor families and living donors. Given that my main aim was to explore transplant communication in Gauteng it was important that the analysis framework allowed the integration of data into a logical set of findings (Ritchie et al., 2003). For instance, Fereday and Muir-Cochrane (2008) made use of thematic analysis to integrate a set of raw data from research interviews and focus groups with a set of institutional documents. Whilst I did not integrate the data set with institutional documents, I did integrate the data produced from the four different sources in terms of a pragmatic approach.

7.14.2. Data analysis - Braun and Clarke’s (2006) thematic analysis

Analysis for my project involved a continuous process of engagement with the data from the time the fieldwork first commenced. Considering the data regularly during the entire research process assisted in developing methods, concepts and testing findings (Silverman, 2010). Braun and Clarke (2006, pp. 16 - 23) advocated six phases of data analysis which were used in my study. The process which was followed is depicted in Figure F7.6:

a. Familiarising myself with the data b. Generating initial codes

c. Searching for themes d. Reviewing themes

e. Defining and naming themes f. Producing a research report

7.14.2.1. Familiarising myself with the data

This initial analysis period involved me familiarising myself with all the data. This was done through the data collection and transcription process, all of which I undertook

myself. I then engaged regularly with the data, primarily by reading and re-reading it over a period of time.

7.14.2.2. Generating initial codes

Interviews were coded in batches. The first ten interviews were coded simultaneously, and possible definitions for these codes were devised. The remainder of the data set was subsequently coded either according to the initial code definitions or into new codes which emerged.

Figure F7.6 – The analysis process

At the point when I started generating codes, I realised that differing perspectives on similar issues were emerging, based on the context of the participant. For instance, the notion of follow-up post-transplant emerged as a code; however this was viewed

•Familiarised myself with the data through transcription and re-reading

•I generated initial codes through colour-coding

•I re-coded my data, sometimes collapsing codes together

•I categorised my codes into eight general relationships

•I identified three themes

•I reviewed these themes according to their pertinent codes and in relation to the literature. Through this review I identified eight sub-themes which fitted wihtin the three main themes.

•I named my themes according to the most prominent commonalities between codes and themes were defined based on these commonalities and the characteristics of the sub-themes.

differently by transplant professionals and by donor families. In order to account for this difference in perspective and viewpoints, the donor family interviews and the living donor focus group were coded separately. This form of non-cross-sectional analysis (Ritchie et al., 2003) allowed me to generate a new set of codes, specific to the views of the donors. Subsequently, I sought to identify corresponding codes across the two data sets. In most cases correspondence was found. However, in the case of donor family follow-up, correspondence was not in evidence, because while donor families spent a long time discussing follow-up in their interviews, transplant professionals and coordinators did not mention it at all. Because of this large

disjunction in the data set I argue that cross-sectional analysis has produced some of the most surprising research results.

I then recoded and refined the coding of the entire data set. Here, some articles from the earlier coding session were recoded or were coded into more than one category.

Ultimately, thirty-seven codes were identified. I continuously questioned my

relationship with the data (Silverman, 2010). Questions and generalisations started to emerge, as well as some conflicting viewpoints and a number of outlying views and opinions.

7.14.2.3. Searching for themes

The initial search for themes involved examining the relationships between different codes (Braun & Clarke, 2006). I identified eight main relationships amongst the thirty-seven codes which reflected the characteristics of the data. These relationships are depicted at the beginning of each results chapter. The relationships were based on which aspect of the transplant process the code was pertinent to, on the kind of communication and its participants, and on the role of contextual factors which emerged in the data.

Numerous smaller links between codes were identified through sorting codes according to the eight relationships and it soon became evident that codes linked together and that these began to suggest the larger sub-themes of my research. A

consideration of these sub-themes led to the emergence of three themes in the data – context, transplant professional–patient communication and interprofessional

communication.

7.14.2.4. Reviewing themes

Once I had identified my three themes and the numerous sub-themes within them, I went back to the academic literature relevant to my study and examined the themes and sub-themes in relation to it. I started to identify aspects where my findings were different from those presented in the literature, and where findings converged or supported each other.

7.14.2.5. Defining and naming themes

The defining and naming of themes took place over time and with a great deal of input from supervisors and academic peers. Although the content of themes did not change after comparison to the literature, the naming of themes was revised to better

encompass all the sub-themes and codes which had been generated in the analysis process. The broad definition of themes was as follows:

• Context – Universal factors (Tronto, 1993) of the environment in which transplant takes place

• The decision – Communicating with patients (recipients, donors and their respective families) across the transplant process

• Interprofessional communication – Communication between transplant professionals and coordinators.