Table 3.

Data analysis process.

Stage	Analysis process
Familiarisation with the data	The authors immersed themselves into the data by reading through the transcripts while simultaneously listening to the audio to ensure the accuracy of the transcriptions. This enabled the authors to recall the interview atmosphere and note any reflections or observations that emerged—each new reading and listening to the audio allowed for further insights.
Generating initial codes	Thorough notes were produced that reflected the transcripts and audio recordings. This created initial codes to organize the data into meaningful clusters based on the detail provided by the participant. Due to the copious amount of data generated, qualitative data analysis software – ATLAS.ti – was used to facilitate this step and assist with the subsequent thematic process.
Generating initial themes	Using ATLAS.ti, the connections between the identified codes were categorized into themes based on shared conceptualizations. Each category was assigned a descriptive label, and the meanings of and relationships between codes were deciphered.
Reviewing potential themes	Patterns across coded data were identified, and the entire data set was reviewed. Overlapping themes were collapsed and refined.
Defining and naming themes	A list of major themes and subthemes were categorised, and the narrative of the themes was identified and conceptualised within the broader story of the data set in response to the research questions.
Producing the report	A narrative account of participant data was presented using short excerpts from the transcripts to convey our salient findings in response to our research questions.