Data from all sources were analysed and interpreted using NVivo 12 which supports analysis of mixed method studies (QSR International , Melbourne , Australia ) (Figure 2 ). As NVivo 12 software allows researchers to import and synthesise different types of quantitative and qualitative data (QSR International, 2017 ), we were able to manage data sets from all three sources in one platform. Content analysis was used to code data which requires gathered information to be organised into categories related to the research questions (Bowen, 2009 (link)). Data from all sources were categorised into ‘environmental', ‘social', and ‘economic' conditions around ICT in the Maldives. The coded sections were further categorised into the eight areas explored within each of the main categories. The first author is fluent in both languages and hence initially analysed all data which was followed by the second and third author checking the analysed data. The research team corrected errors to ensure categories and subcategories corresponded with the raw data and consensus was gained where there was disagreement.
Nvivo 12
Manufactured by Lumivero
Sourced in Australia, United States, United Kingdom
NVivo 12 is a qualitative data analysis software package. It is designed to assist researchers in organizing, analyzing, and interpreting unstructured or non-numerical data, such as interviews, focus groups, and various text-based documents.
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598 protocols using nvivo 12
1
Mixed-Methods Analysis of ICT Conditions in Maldives
2
Perspectives of Assistant Cooks on Self-Perception
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This study adopted a single-category design [20 ] where one type of participant (i.e., assistant cooks) was the primary focus of the investigation. At least three or four groups are suggested to reach theoretical saturation [20 ]. Three researchers including the same moderator and assistant researcher conducted three focus group discussions with 17 assistant cooks until adequate saturation was reached. The processes of data entry, analysis, and interpretation, as well as the final writeup, were carried out using NVivo 12 (NVivo 12, QSR International, Massachusetts, US). The data were coded and subdivided into 143 themes. Subsequently, these themes were categorized into six overarching units. To explore participants’ perspectives, an open coding method that offered researchers the space to develop codes via collaboration with the participants was used, resulting in naturally emerging themes from the raw data. This led to the establishment of a theory that explicates how the selected assistant cooks perceive themselves [21 ]. As a reporting tool, the Consolidated Criteria for Reporting Qualitative Research (COREQ) was used [22 (link)]. In addition, participant checking was done with one assistant cook who participated in the interview to receive feedback on the final results. In this process, she absolutely agreed with the findings.
3
Thematic Analysis of Interview Data
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Thematic analysis of the collected data was inductive and comparative, beginning with the English version verbatim transcription of the interviews. Open, axial, and selective coding were used to generate initial codes, search for themes, review themes, and then to classify higher-order subthemes and categories [31 ,34 (link),35 ]. The first phase of data analysis included translation and open coding of the interviews. Initial interviewing notes, comments, and memos created by the first author were generated during the open coding phase. Along this line, the groupings of initial codes and notes were organized into similar codes and initial subthemes of information during the axial coding stage. Finally, selective coding occurred as the data became saturated into major themes that clearly represented the phenomenon investigated [35 ,36 ]. Selective coding was used by the first author and the peer debriefer (O.J.C.R) to determine overall themes and categories of the data that emerged from the open and axial coding stages [31 ,35 ,36 ]. The data analysis procedure met the requirements of the 15-point checklist of criteria for thematic analysis [34 (link)]. All data were analyzed via NVivo 12© (NVivo12, QSR International, Melbourne, Australia).
4
Qualitative and Quantitative Analysis Methodology
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Data from the closed-ended questions of the questionnaire were imported into R software version 3.2.4 (R Foundation for Statistical Computing). Numerical data are presented as absolute numbers, proportions, and median (IQR). The entire roundtable discussion was audio recorded and transcribed verbatim by the AMK France professional company. Data from the roundtable discussion and open-ended questions were analyzed using thematic analysis and were coded to identify key categories, which were developed into themes using NVivo 12 software (QSR International). The analysis of questionnaires and the roundtable discussion supported cross-validation and triangulation of the findings.
5
Qualitative Analysis of Clinician and Family Experiences
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We collected basic clinical and demographic data using REDCap, an electronic data capture tool hosted at the University of Pittsburgh (14 (link), 15 (link)). We summarized these data using descriptive statistics. We used NVivo 12 software (QSR International) to analyze verbatim transcripts of telephone interviews with clinicians and families (16 ). We used a content analysis approach to develop a codebook to analyze the interviews (17 ). A single investigator (N.K.) coded all of the interview transcripts, and two other investigators (J.E. and A.S.) independently reviewed the coding for each transcript. Coding disagreements were resolved by discussion until consensus was achieved.
6
Qualitative Analysis of Participant Experiences
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An iterative inductive thematic analysis was undertaken after the data were collected, to inductively derive key codes and themes regarding participant experiences. Concurrent analysis was performed by three authors (ZO, AB and RE), including the principal investigator, who separately read through a proportion of transcripts to familiarise themselves with the data. NVivo 12 software (QSR International, Melbourne, Australia) was used to facilitate data analysis. The principal researcher (ZO) generated initial inductive codes and grouped the codes into theme headings. The codes and themes were finalised during the group discussions. This process was employed to minimise biases of any one author in interpreting data sources and generating coding and themes. A consolidated criteria for reporting qualitative research (COREQ) checklist was used as a guide to report the study findings. 31 Ethics approval was obtained for the study from the local Hospital and Health Service ethics committee (HREC/2020/QTHS/58635) and University ethics committee (H8189). All participants provided written informed consent. The study was conducted according to Good Clinical Practice and the Australian Code for the Responsible Conduct of Research.
7
Analysis of Race-Based Medicine Perceptions
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The research team analyzed the open-ended short-answer questions via content and thematic analyses. First, three researchers (MJ, IO, EAB) independently coded the participants' definition of "race-based medicine" [7] as correct or incorrect; this variable was dichotomized (yes = 1, no = 0) for statistical analysis. Second, the research team performed content analysis by marking and categorizing key words, phrases, and texts to identify codes that described students' experiences with race-based medicine in order to facilitate thematic analysis and illustrated patterns across the data [15, 16] . The investigators revised, discussed, and resolved coding discrepancies through consensus to establish inter-coder reliability [17] . The Cohen's kappa coefficient between the three coders was 0.957, indicating almost perfect agreement [18] . After the transcripts were coded and reviewed, one member of the research team (EAB) entered the coded transcripts in NVivo 12 software (QSR International, Victoria Australia) to organize the data and derive themes. The selected themes described examples of race-based medicine and support vs opposition for the teaching of race-based medicine in medical school. The research team derived themes from data that occurred multiple times, both within and across short-answer responses.
8
Qualitative Evaluation of Supportive Supervision
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Verbatim transcription of the recordings was performed in English by an independent consulting firm. The five FGDs that were conducted in a mixture of Arabic and English were also transcribed verbatim in English by one of the co-investigators (ZMG) fluent in both languages and were reviewed by BAK. For the three non-audio recorded interviews, comprehensive notes were taken. The first (GWL) and second authors (LJS) checked all the transcripts for accuracy and completeness. All the transcripts and field notes were imported into NVivo 12 software (QSR International) [31 ] for coding and analysis. Coding was performed deductively based on the conceptual framework in Fig. 1 . Two researchers (JOY and BAK) independently reviewed the codes and the subcategories. Thematic content analysis was performed by the first (GWL) and second authors (LJS). Content analysis aided in identifying the common patterns and trends arising from the data regarding practice and the experiences with supportive supervision in the counties. Narratives were written on the main themes and subthemes, and some quotes were used for illustration in the results section. FGD and SSI data were triangulated to enhance the quality and reliability of the findings.
9
Evaluation of an Intervention Protocol
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Quantitative data will be analysed using descriptive statistics displayed with 95% confidence intervals. Changes in outcomes between the intervention arm and control, estimate parameters using means and standard deviations will be descriptively compared and will inform a sample size calculation for a full RCT. All quantitative data will be analysed in STATA 15 (StataCorp, TX: StataCorp LLC) [58 ].
Qualitative interview transcripts will be managed using NVivo 12 software (QSR International Pty Ltd., Doncaster, VIC, Australia) and analysed using the five stages of framework analysis [59 ]: familiarisation, developing a thematic framework, indexing, charting and mapping and interpretation. During the first stage (familiarisation) the researcher will become immersed in the data, by reading and re-reading the transcripts. Next, a thematic framework will be developed. After this, transcripts will be indexed (coded) line by line using the thematic framework but remaining open to new themes that emerge. Next, the data will be entered into a chart, so that coded extracts can be attributed to individual participants. Finally, participants’ views will be compared and contrasted, and the data presented schematically (mapping). Contrasting explanations will be explored.
Qualitative interview transcripts will be managed using NVivo 12 software (QSR International Pty Ltd., Doncaster, VIC, Australia) and analysed using the five stages of framework analysis [59 ]: familiarisation, developing a thematic framework, indexing, charting and mapping and interpretation. During the first stage (familiarisation) the researcher will become immersed in the data, by reading and re-reading the transcripts. Next, a thematic framework will be developed. After this, transcripts will be indexed (coded) line by line using the thematic framework but remaining open to new themes that emerge. Next, the data will be entered into a chart, so that coded extracts can be attributed to individual participants. Finally, participants’ views will be compared and contrasted, and the data presented schematically (mapping). Contrasting explanations will be explored.
10
Qualitative Analysis of Rodent Infestation and Waste Disposal
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The researcher led the interviews using English, isiZulu and Sesotho, and recorded the interviews. Qualitative research produces data that are connected to the opinions, values and behaviours of people in a social context, through textual data obtained in the form of transcripts and observational field notes. The textual data were analysed using some variant of thematic analysis [12 ]. The recorded data were transcribed verbatim into English, isiZulu and Sesotho language transcripts. The IsiZulu and Sesotho transcripts were translated into English and the transcripts were read carefully by the researcher. A code list was established for coding of the data into themes. To identify key themes, a thematic analysis was conducted using NVIVO 12 software (QSR International Inc., Burlington, MA 01803, USA). The English versions of all twenty transcripts were imported into NVIVO 12 software for analysis. They were then grouped into similar concepts and contexts for interpretation. Details of the results were then discussed in a form of coded themes and sub-themes, as a representation of the experiences of households with respect to rodent infestation and waste disposal practices.
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