All interview audio-recordings were transcribed in the electronic software – OTTER and verified by KJ. NVivo version 12 software (QSR International, Melbourne, Australia) was used to assist with data management and analysis. All transcripts were de-identified and analysed by AS, KJ and BMA, with discrepancies resolved in a consensus meeting. Data analysis occurred at multiple levels, and it involved thematic inductive analysis whereby transcripts were coded using a line-by-line open coding process and constant comparison process as advocated by Corbin and Strauss [26 (link)], to develop emergent themes. Ritchie and Spencer’s [27 ] six-staged (reading, identifying, indexing, charting, mapping and interpreting generated themes) theoretical framework analysis was employed to identify and contextualise the transformative learning aspects of the international rural placement experience. Thematic analysis occurred at multiple levels: (1) motivations for applying, (2) identification of transformative elements, (3) processes of integration of transformative experiences and (4) impact of experience on longer-term learning and clinical practice.
Nvivo version 12
Manufactured by Lumivero
Sourced in Australia, United States, United Kingdom
NVivo version 12 is a software tool designed for qualitative and mixed-method research. It provides features for organizing, analyzing, and visualizing unstructured data, such as interview transcripts, documents, and multimedia files.
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Nvivo software, by Lumivero (2 mentions)
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Sas version 9, by SAS Institute (2 mentions)
Sas 9, by SAS Institute (1 mentions)
Stata version 12, by StataCorp (1 mentions)
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Spss statistics version 25, by IBM (1 mentions)
Spss version 25, by IBM (1 mentions)
Spss statistics for windows version 26, by IBM (1 mentions)
Sas statistical software version 9, by SAS Institute (1 mentions)
Stata se 16, by StataCorp (1 mentions)
Stata version 15, by StataCorp (1 mentions)
Spss statistics version 27, by IBM (1 mentions)
Spss version 27, by IBM (1 mentions)
Stata se 14, by StataCorp (1 mentions)
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Spss statistics version 26, by IBM (1 mentions)
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113 protocols using nvivo version 12
1
Exploring Transformative Rural Placements
2
Thematic Analysis of Qualitative Data
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All audio-recordings were transcribed into local language before translating the transcripts into English. Data were analyzed using thematic analysis. First, the transcripts were read several times aiming to get familiar with the data. Second, data were coded manually and using NVivo version 12 software (QSR International). The codes were both data driven and concept driven, (39 ,40 ) and were grouped into themes to form thematic maps.(41 (link)) Divergent views were noted.
3
Thematic Analysis of Qualitative Interviews
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Thematic analysis of the data (audio-recordings, transcripts and notes taken at the time of the interview) was informed by the framework analytic approach [17] . This involved an initial process of familiarisation with the data by listening back to interview audio recordings, and reading transcripts and field notes. Each transcript was read line by line and codes developed and applied inductively.
Codes were grouped into categories. DT and JM met to discuss the categories and codes applied across 3 initial interview transcripts to form a working coding framework. This was applied and refined iteratively across the data. Charting of codes and illustrative quotes facilitated associative analysis within the sample and the development of thematic descriptions. This was shared with paediatric burns nurses (CT & LH) and public involvement partners who reviewed and helped to refine the analysis. Initial thematic interpretations were discussed amongst the team and with other qualitative researchers and refined with the aid of descriptive accounts of the data. Coding and data management was undertaken using QSR International's NVivo version 12 software [18] .
Codes were grouped into categories. DT and JM met to discuss the categories and codes applied across 3 initial interview transcripts to form a working coding framework. This was applied and refined iteratively across the data. Charting of codes and illustrative quotes facilitated associative analysis within the sample and the development of thematic descriptions. This was shared with paediatric burns nurses (CT & LH) and public involvement partners who reviewed and helped to refine the analysis. Initial thematic interpretations were discussed amongst the team and with other qualitative researchers and refined with the aid of descriptive accounts of the data. Coding and data management was undertaken using QSR International's NVivo version 12 software [18] .
4
Qualitative Analysis of Interview Transcripts
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Interview transcripts were de-identified and coded via the qualitative analysis software NVivo Version 12 (QSR International, Victoria, Australia). An inductive thematic analysis approach was used, guided by Braun and Clarke [32 ]. The first four transcripts were read and line-by-line coded by two researchers (A. Morrow and P. Chan), who then met to compare codes and develop an initial coding framework for subsequent transcripts. All remaining transcripts were then analyzed separately by A. Morrow and P. Chan, who met regularly throughout the transcript analysis process to review and refine the coding tree. Any discrepancies in coding were discussed with a third reviewer (N. Taylor). A. Morrow reviewed the codes and grouped them into themes and subthemes. Themes and subthemes were refined based on discussion among members of the analysis team (A. Morrow, P. Chan, N. Taylor, E. Hogden).
5
Qualitative Feedback Analysis Protocol
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We recorded participant feedback and screen activity using GoToMeeting screen sharing software, version 10.5 (LogMeIn Inc). The audio component of the recordings was exported and transcribed by a professional transcription service. The transcripts were analyzed using NVivo, version 12 (QSR International), a qualitative analysis software. We followed a 3-step approach to analyze the transcripts.
6
Thematic Analysis of VICKY Tool Acceptability
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Qualitative data collected through the interviews were analyzed in Spanish following a three-step thematic data analysis conducted by two independent coders and a third senior-level qualitative data researcher, all of whom are bilingual (Spanish/English) speakers. The first step involved independent open coding of 12 transcripts performed by two coders. The goal of this step was to identify major thematic areas and to develop the codebook containing the codes and sub-codes that would be used to analyze and interpret the collected data. The narrow scope of the interview guide (i.e., assessing tool acceptability and usability) resulted in a thematic codebook that closely matches the interview guide. Nonetheless, the goal of the thematic analysis was to extract passages that captured participants’ perceptions of and experiences using VICKY. Once the final codebook was established and the two coders reached agreement (k = 0.81), the remaining interviews were coded by a single coder (second step). All coding was conducted using NVivo version 12 (QSR International, Melbourne, Australia). The third step involved identifying relationships and patterns among the open codes by a senior qualitative data researcher who reviewed all coded interviews in order to qualitatively determine whether users of Spanish VICKY deemed the tool acceptable and useable.
7
Content Analysis of Focus Group Discussions
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A content analysis approach was used to analyze the information from the FGDs. The audio-recorded FGD sessions were transcribed verbatim. Transcripts were imported into a textual analysis software (NVivo, version 12, QSR International) and coded using line-by-line coding. Codes were generated a priori based on the specific research objectives, and adjusted as new themes emerged through the coding process. Themes were identified throughout the iterative coding process using an applied thematic approach, and relevant data were extracted and categorized based on the thematic content. Three researchers (E.F.K., A.H.C., and R.P.R.) coded the data and fixed discrepancies. Lastly, summaries of the key themes were developed along with representative quotes. Data from the paper-based surveys were extracted to MS Excel (Microsoft), cleaned up, and checked for errors. Analysis of quantitative data was performed using STATA, version 12 (StataCorp). Univariate descriptive statistics were used to summarize sociodemographic characteristics, sexual risk behaviors, perceived mental health and wellbeing, and health care seeking behaviors. Data analyses were conducted from 30 November 2021 to 20 February 2022.
8
Qualitative Thematic Analysis Protocol
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The transcribed interviews were the main data source for this study. We used an inductive approach to thematic analyses that included familiarisation with the interviews, development of codes, collating codes into themes and overcoming coding conflicts between researchers. 11, 14, (link)15 (link) First, we analysed the transcripts to develop a coding guide, following grounded theory recommendations. 11, 16 (link) Primary coding was then carried out independently by two researchers using NVivo version 12 (QSR International, Melbourne, Vic., Australia). Coding conflicts were discussed in person and agreed upon by at least two researchers. To enable easy discussion of this study's findings, we used qualifying terminology from previous studies. 14, (link)16 (link) When a concept was discussed by ,3 participants, we referred to 'a few'; for 4-5 participants we referred to 'some'; for 6-7 participants we referred to 'most'; for 8-9 participants we referred to 'almost all'; and for 10 participants, we referred to 'all'.
9
Qualitative Data Analysis in Research
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Inductive thematic analysis, supported by NVivo version 12 (QSR International, 2018) , was used to analyse the data. This followed Braun & Clarke's (2006) (link) six stages of becoming familiar with the data, generating initial codes, searching for themes, reviewing themes, defining themes and writing up. Transcripts were initially coded independently by three members of the study team followed by discussions with an additional two members of the study team to gain consensus on the emergent themes.
To ensure trustworthiness and reflexivity, the research team shared analysis of the data in regular meetings. The team included members from a range of professional backgrounds, all with experience in qualitative analysis. To enhance credibility, particular attention was paid to negative cases during the analysis (Bitsch, 2005) (link) and the COREQ (COnsolidated Criteria for REporting Qualitative research) checklist (Tong et al., 2007) (link) was used in reporting the study to demonstrate rigour, credibility and transparency. (Please see Supplementary file 1).
To ensure trustworthiness and reflexivity, the research team shared analysis of the data in regular meetings. The team included members from a range of professional backgrounds, all with experience in qualitative analysis. To enhance credibility, particular attention was paid to negative cases during the analysis (Bitsch, 2005) (link) and the COREQ (COnsolidated Criteria for REporting Qualitative research) checklist (Tong et al., 2007) (link) was used in reporting the study to demonstrate rigour, credibility and transparency. (Please see Supplementary file 1).
10
Qualitative Data Analysis Framework Methodology
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Data analysis was conducted in accordance with the Framework method, described by Ritchie and Spencer (1994) . Following familiarisation with the transcripts, a thematic framework/coding strategy was developed., where the first few transcripts were initially coded. During this initial coding, a priori study objectives and interview topics were employed as "overarching categories" (Gale et al., 2013) (link), with the narratives of participants being used to develop codes within each category. The process was repeated until no new codes were generated and the final thematic framework/coding strategy was agreed between three researchers (LSG, CT, SJH). In the indexing stage, the finalised thematic framework/coding strategy was systematically applied to all remaining transcripts by one researcher (LSG) using qualitative data analysis software (NVivo Version 12, QSR International). In the charting stage, a matrix was created for each overarching category and transcript/participant by collating and summarising the underlying codes. Finally, the matrices were used to guide interpretation of the data set, where connections between codes and participant responses were examined in relation to the original objectives and inductively derived concepts and issues. From here, codes were grouped to develop themes within each overarching category.
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