Data analysis.
The first step in coding the data collected from the interviews was to transcribe the interviews into a written format. This was done manually. After this, we read through the transcripts several times to become familiar with the data and identify potential codes. We identified relevant themes by using a combination of underpinning issues in the interview guides that formed the basis of the research questions and issues that emerged during the interviews. Subsequently, we developed a codebook that outlined the codes and categories that we used to analyze the data. Two members of our team (Am. D. and Ad. D.) coded the data and used NVivo software version 12.0 (QSR International, Burlington, MA), to manage the data and apply the codes. The two researchers who coded the data met regularly to discuss their coding decisions and resolve any discrepancies. Unresolved disagreements by the two researchers were resolved after discussions with a third independent researcher (N. M. S.). As the coding process progressed, the two researchers refined the codebook and added new codes or categories, based on the emerging themes in the data. The coded data were analyzed by using the emerging themes and patterns in the data. This involved creating visualizations such as word clouds to identify similarities between common themes. We triangulated common themes arising from the interviews and included verbatim quotes of the study participants to buttress certain views expressed in the course of the interviews.