Data analysis

A graphical presentation of the data collection methods and the analysis process is given in Fig. 1.

Overview data collection methods and the analysis process. Ovals represent primarily qualitative parts, rectangles primarily quantitative parts and hexagons meta-inferences

Thematic analysis will be used for qualitative data, following the method described by Braun and Clarke [27, 28]. The analysis will be inductive (i.e. the identified themes will derive from the data) and on a latent/interpretative level. The latter indicates that ideas, assumptions, conceptualisations and ideologies will be determined that are theorized as underlying to the semantic content of the data. The first phase of the thematic analysis involves familiarization with the data. Verbatim transcripts will be created, the data will be read repeatedly and initial ideas will be noted. Phase 2 comprises systematic generation of initial codes. During phase 3 themes will be searched for by arranging codes into potential themes. Next, applicability of these themes to the coded extracts as well as the entire data set will be reviewed in phase 4. Phase 5 involves creating clear definitions and names for the themes, in order to refine their specifics. Phase 6 will offer the final opportunity for analysis. After selecting decent extract examples, final analysis and comparison of the analysis to the research aim and literature, the report will be produced [27, 28]. The qualitative data analysis software NVivo will be used throughout the data analysis.

Descriptive statistics include mean (standard deviation) or median (range) and number (%) for continuous and categorical data, respectively.

Initially the qualitative and quantitative data will be analysed concurrently. Thereafter, a side-by-side comparison will be performed using a summary table in which the qualitative and quantitative findings are merged. This meta-inference will be followed by interpretation of the combined results.