Qualitative data analysis

The semi structured interviews and the focus group discussion were transcribed, then analysed to identify common or recurring themes. The aim of the analysis was to explore how the participants perceived, understood, and explained the first phase data. The sequential mixed analyses involved the sequential examination of one data type from another (Tashakkori & Teddlie, 2010). The process involved the conversion of the quantitative data into narrative data that could be analysed qualitatively (Padgett, 2012). The transcribed data were subjected to thematic analysis, a technique that is a widely used qualitative analytical method; it offers a flexible approach to analysing qualitative data. This approach was deemed as the most appropriate method to analyse the qualitative data collected in the current study (Onwuegbuzie & Combs, 2011; Padgett, 2012; Teddlie & Tashakkori, 2009).

Trustworthiness was considered in this research. Hence, the researcher’s triangulation was used to establish credibility of the analysis steps and results; another investigator checked and participated in the analysis and theorising themes of the qualitative findings (Thurmond, 2001).

Thematic analysis is a method of identifying, analysing and discovering the themes (Boyatzis, 1998). This method helped the researcher to identify the research themes and the important data related to the research questions, as well as to clarify the quantitative data (Braun & Clarke, 2006). Six steps were followed (Braun & Clarke, (2006); they involved the researcher’s familiarisation with the data by reading and re-reading the data, with the initial noting of ideas. Next, the theme was identified. The researcher arranged the data into each relevant code, across the entire data set; these codes were arranged into potential themes. The themes were revised and reviewed in relation to the coded extracts and in the generation of

the thematic map of the analysis. Then, the themes were defined and named. Lastly, the results were described.

The first step of the analysis involved the researcher checking the accuracy of the transcript against the audio recording. Some changes were made to the transcript (for example, punctuation), as well as corrections to verify the accuracy and quality of the data, ensuring both validation and trustworthiness. The second step of the analysis involved the researcher reading and rereading through the transcript to become immersed in, and familiarised with, the data. During the rereading, the researcher searched for, and identified, potential patterns.

The initial coding (or open coding) in the second step occurred as the transcript was read, line-by-line, and the code manually applied. Ideas were linked together when information was expressed using similar terminology. The named codes were highlighted to ensure the retention of the data’s context.

The first step of coding was performed manually, and then the MAXQDA computer software program was used to manage and facilitate the process of sorting, structuring, and analysing the data. While there are arguments against using computer programs in analysing qualitative data (Patton, 2002), qualitative software programs can be useful, for managing large volumes of data. However, to avoid any potential omissions, the current research used both coding approaches: the manual coding to enhance the trustworthiness of the result, followed by the qualitative software programs to assist the researcher in the categorisation of the data. This comprehensive approach enabled the researcher to interpret the data and help with the theorising.

The third step involved searching for themes by sorting the different codes into themes. The first step of the current phase involved organising and analysing the different codes; they were then combined into the relevant codes. The overarching theme was noted on a separate

sheet to the transcript. During this phase some combined codes formed themes and sub-themes. The relationships between the codes were re-arranged into defined significant themes. However, those themes were not final and required further examination. The data were extracted and sorted during the next phase: “reviewing themes”.

The fourth step involved reviewing the themes named as themes in the previous step. Those themes holding insufficient supporting data were discarded. Some themes were included into a larger theme; for example, the knowledge and skills of managers were subsumed under PHCC managers’ competencies. This approach sought to form tight and rational patterns that influenced the satisfaction of primary health care professionals. Furthermore, the analyses substantiated other evidence from the interviews and the focus group discussions.

The fifth step of the analysis involved defining and naming the themes. The overall relevance of the themes to the research question was confirmed. Also, the relationship of the themes to the other themes was reviewed to ensure that there was no overlap. A careful examination of the themes, with the focus on the core meaning and the labelling of each them, was performed. Finally, the report of the thematic analysis was produced (the sixth step, and the core focus of the next chapter).

When extracting themes from the qualitative data, the researcher refrained from using personal value judgments, that is, he did not qualify the evidence. Hence, the participants were not corrupted by the opinions of the researcher (Lincoln & Guba, 1985). Thus, preference was not given to either the voices of the participants who agreed with the researcher's opinions or the responses directly opposed to the researcher's opinions. The verbatim quotations of the participants were tabulated, so that the qualitative research provided the raw evidence, uncontaminated by the researcher’s viewpoint (Lincoln & Guba,

reflect the descriptions given by the participants in the discussion of an issue and their own inferences or conclusions.