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In order to analyse data from the simulations and interviews, the interview audio records were first transcribed, checked for accuracy and anonymised. Then, the data was entered into qualitative analysis software Nvivo version 83. Similarly, the discharge summary letters produced from the simulation were scanned and

entered into the software; the software supports coding for textual and visual elements. The data was initially analysed or coded thematically (Ryan and Bernard, 2003; Braun and Clarke, 2006).

The thematic coding was the first stage of the data analysis. Data analysis is essentially composed of analytic coding and data interpretation. Coding supports data analysis in a number ways. Firstly, coding helps the researcher to organise and retrieve research data. During a coding process, data is broken into chunks and segments and assigned with meaningful labels. These labels or codes may serve as indexes for retrieving, grouping and reviewing the data (Miles and Huberman, 1994). Quantitative methods such as content analysis use coding in this way; the coding assigns the same code to words of similar meaning to allow counting of their frequency of occurrence in the text for a descriptive analysis. Secondly, coding is essentially used as an analytical procedure in qualitative research (Strauss, 1987). Coffey and Atkinson described the coding as a heuristic tool to analyse data:

“Coding should be thought of as essentially heuristic, providing ways of interacting with and thinking about the data. Those processes of reflection are more important ultimately than the precise procedures and representations that are employed.”

(Coffey and Atkinson, 1996, p. 30)

This statement implies that analytic coding is not a mechanical procedure but a creative process. The researcher’s analytical frame influences the coding process. Coding is an heuristic tool for discovery from the data (Seidel and Kelle, 1995).

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65 Analytic coding is used to re-orientate (Strauss, 1987), re-contextualise (Tesch, 1990) and re-conceptualise (Coffey and Atkinson, 1996) empirical data. Each code represents a concept. A segment of data is associated with a concept and the linkage between concepts is established based on the relationship and pattern in the data. Coffey and Atkinson (1996) argued that the coding process essentially de-composes the empirical data and re-composes them within the new conceptual context. The contextualisation opens up further questions and analytical

possibilities for the data. The concepts used to re-orientate or re-contextualise the data can be derived from the interactions with data, literature, research questions or the researcher’s ideas. From the experience in this study, the conceptualisation process was dynamic and tended to change throughout the course of the research; and the conceptualisation contributed to the researcher’s interpretation when undertaking the coding and data analysis.

The characteristics of a coding process are sometimes associated exclusively with a particular research method or data analysis. For example, Grounded Theory Method (Glaser and Strauss, 1967; Strauss, 1987; Strauss and Corbin, 1990) is characterised by a coding process that starts without a preconceived coding frame. The coded structure is constructed through the interaction with the data.

Alternatively, a researcher may start with some code structure or frame which is gradually refined throughout the coding process; this coding style is referred to as template analysis (King, 1998). Data analysis whose coding process focuses on identifying general concepts, patterns or themes from the data is often called thematic analysis (Ryan and Bernard, 2003; Braun and Clarke, 2006). This study used a thematic analysis approach.

Initially, the coding process used a free coding technique. In this stage, no preconceived coding structure was imposed. After coding three interview transcripts, hundreds of codes emerged. These codes were then organised into a structure based on the research questions, the major themes and the conceptual frames (pragmatic, semantic, syntactic aspects) adopted for this study. The coding

66 structure was continuously revised as the remaining interview transcripts were coded. The revision included reorganising the code structure, moving codes around the structures, collapsing multiple codes into single codes, and dividing a code into multiple codes. In order to maintain simplicity of the code structure, the coding was limited to three levels of depth and the number of the top headings was limited to fifteen. From the experience of doing the coding, a long list of headings tended to slow down the coding process significantly. A fragment of the coding structure for this study is shown in Figure 3.2.

Figure 3.2 Fragment of the coding structure

The analytic coding was the first element of the data analysis. The second element was the reinterpretation of data based on the analytic coding. As the conceptual space was developed during the coding process, the data was continuously reinterpreted in the new conceptual context. This process involved inductive analysis (Johnson, 1998; Katz, 2001; Lathlean, 2006) in order to establish the

67 causative links across the identified themes or concepts so as to construct an explanation in relation to the research questions and objectives. Analytic induction was defined as:

“a process of analysing data where the researcher tries to find explanations by carrying on with the data collection until no cases are found that are

inconsistent with a hypothetical explanation of a phenomenon”

(Lathlean, 2006, p. 421)

The focus of the interpretation is to create an analytic narrative that was based on the data and to develop arguments in relation to the research questions or

objectives (Braun and Clarke, 2006), this goes beyond the descriptive account of the data in its original context.

This process continued into the writing-up stage. In the writing-up stage, the causative or explanatory links across different themes were presented in a sequential fashion. However, the writing-up process itself was not void from analytic induction. Consequently, during the writing-up process, the findings and data were still continuously reinterpreted. This process continued until the interpretation was stable, valid and coherent with the data according to the author’s perspective. Additionally, segments of data can be used to support the argument or for illustration in this thesis. Direct quotations from informants were used extensively in Chapters Four and Five. If the data were taken from the general interviews, they were indicated as “General Interview” in the quotation source. Similarly, the data taken from the discharge summaries created by the research participants were indicated as “Simulated Discharge Letter”, and the quotations taken from the simulation’s follow up interviews were indicated as

“Simulation Interview”.

The same coding software was used to organise quotations that are potentially to be incorporated in this thesis. These quotations can be organised according to the writing-up structure, as is the case with this thesis, as shown Figure 3.3.

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Figure 3.3 Coding structure to support the writing-up in this thesis