Interviews were recoded and transcribed anonymously. In order to become familiarized with the content, identify key topics and ensure an in-depth overall understanding of the content, all transcribed interviews were reviewed by RC and SD in an interactive process. Then, RC and SD analyzed texts independently using the conventional content analysis approach. This analysis is a systematic method of generating new knowledge about perceptions and feelings.42 This step requires going back and forth between every interview across the different codes and themes and their relationships. A data-driven thematic analysis was conducted using the verbatim transcriptions of the interviews, ie, an inductive approach without a theoretical framework to guide the analysis.43 According to the methodology previously published by Dahlgren et al, researchers sought to identify the underlying meaning of the transcribed texts, and then regrouped the parts of the text with similar meaning into paragraphs.44 Then, the paragraphs were divided into units, which were further categorized into sub-themes based on comparable content. The sub-themes were then combined into meaningful themes. After researchers had independently carried out this thematic encoding of the data, they compared notes and discussed disparities until consensus was reached. The two researchers shared their emerging themes and improved their comprehension through discussions with the research project team. All researchers checked the accuracy and clarity of themes and concepts. The research team then collaborated to create Table 3, which shows the final codes names, the sub-themes and themes to provide clear information on the content of the analysis.

Codes, Sub-Themes and Themes

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