44 more on the proceedings of the interview rather than being worried if they were able to note down every important point that the participant had shared (De Vos et al., 2002).
45 researcher/s immerse themselves and engage from the initial encounter with the dataset up to the final stages of thematic analysis (Braun, & Clarke, 2006).
Prior to the transcription and analysing proceedings that led to the second phase analysis, the researcher uploaded life stories on a qualitative software package called NVivo. The computer software allowed the researcher to skilfully arrange and categorise each life story into specific codes and groupings according to areas that the researcher was interested in exploring for further analysis using thematic analysis. The NVivo software served as a tool that assists in analysing the data. NVivo was initially designed for qualitative researchers working with very rich text based on multimedia information, where deep level of analysis on small or large volumes of data sets (Anderson, 2010). This analytic approach allows for dominant themes and sub-themes of related information to be identified from the content of the interview and life stories data.
3.7.1 Thematic analysis process
Patton (as cited in Braun and Clarke 2006) provide a six-phase analysis guideline. The authors have highlighted the necessity to acknowledge that qualitative research does not adhere to rules but is important for the researcher to follow the basic precepts that are appropriate for the research questions. Braun and Clarke (2006) stress that the analysis is not a linear process and does not move from one phase to the next, however, it follows a recursive process, moving back and forth as required throughout the phases. The researcher then adapted the six phases of analysis guideline into the study to complete the analysis process.
Phase 1: Getting familiar with the data
The study comprised two sets of data, the life stories which were alrea dy narratively written and were obtained from the module coordinator which were the study’s raw dataset. The researcher then later conducted individual interviews where the audio recordings of the interviews were transcribed into text. However, the researcher did not transcribe the inter views in a verbatim manner. Reasons for the interview recordings to not be transcribed verbatim was because they followed after the information obtained from the life stories, hence the significance of the individual interviews in this instance was to clarify, follow up and probe further on aspects that the participants had previously presented on their life stories. By so doing, the researcher reduced cases of redundancy. Transcription was done on aspects that were on the study objectives and rich in valuable data.
46 The researcher first familiarised herself with the data whilst analysing life stories, during the development of the interview schedules. The process of engaging with the data set was of great importance, and particularly an excellent start point for the researcher to be acquainted with their data (Riessman, 1993). The researcher noted down initial thoughts and ideas that she later brought forward into the interview, and when she was transcribing the interview. The researcher had prior knowledge about some participants as she was also part of the module. Therefore, the development of the data and initial notes had to follow a rigour guideline of thematising. Braun and Clarke (2006) argue that although the researcher might be familiar with the data if they had collected themselves, it is crucial that they immerse themselves in the data and acquaint themselves with the depth and breadth of the content. Moreover, Bird (2005, p. 227) argued that this step ought to be recognised as “a key phase of data analysis within interpretative methodology”. The interpretative act expands towards creating meaning rather than simply a systematic act of translating spoken words into paper (Lapadat, & Lindsay, 1999).
Phase 2: Generating initial codes
The analysis proceeded to the researcher generating initial ideas regrading what she found within the data, which then progressed to producing initial codes from the data set (Braun & Clarke, 2006). Codes seek to identify features from the data set that emerge to be of interest to the researcher. The ecological systems theoretical framework guided the coding process. Boyatzis (1998) posits that raw data that is in its most basic segment or element has capability to be assessed in a meaningful manner regarding the phenomenon the study is exploring. This process was conducted manually as the researcher organised the data into meaningful groups (Tuckett, 2005).
The researcher also approached the data with specific inquisitions tha t she was keen to code around.
Phase 3: Searching for themes
Potential themes were generated once all the data was initially coded and collated. The researcher created a list of different codes that she was able to identify throughout the data set (Braun, &
Clarke, 2006). Furthermore, this phase provided the researcher with an opportunity to re-focus the analysis on a much broader scale of themes which was different from the coding process (Braun, & Clarke, 2006). The codes were later sorted into potential themes. From this step, the researcher was able to analyse the codes in detail and differentiate one from the other to combine
47 and create overall themes found in the data (Braun, & Clarke, 2006). During this phase, the researcher also assessed the relationship between the codes as well as between themes. This analysis extended to looking at the overarching themes and their relationship with the sub-themes, an essential step that the researcher had to consider when ensuring that the final themes that emerge from the data are of relevance to the research questions.
Phase 4: Reviewing themes
The reviewing and refinement of themes helped the researcher filter candidate themes that did not surface due to insufficient data to support them or the content being too diverse. The phase consists of two levels of reviewing and refinement of themes. The first level was conducted on the coded data extracts, where the researcher read and reviewed the collated extracts to assess whether these formed a coherent pattern. The second level was to consider the validity of individual themes and their linkage to the data set, to ascertain whether the themes were a true reflection of it. Any new themes that were possibly missed during the initial coding stages were assimilated in this phase (Braun, & Clarke, 2006). The process of reviewing themes was informed by the ecological framework, as translated from the life stories to the interview schedule.
Phase 5: Defining and naming themes
According to Braun and Clarke (2006), this current phase was a continuation of the analysis that refined the particulars of each theme. Through the defining and refining process, the researcher was able to identify the essence of each theme and determine certain aspects of each theme captured in line with the ecological systems framework in place.
Phase 6: Producing the report
Once all the themes and sub-themes had been fully established, the final step was for the researcher to draw up the report. It is of great importance that the analysis report presents data extracts on the final write up. According to Braun and Clarke (2006, p. 93), it “provides a concise, coherent, logical, non-repetitive and interesting account of the story the data tell”. By providing enough data extracts, they serve as evidence of themes the data encloses and a demonstration of the prevalence and the authenticity of the theme. Moreover, it presents the value and how rigour the analysis process progressed (Braun, & Clarke, 2006).
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