Transcripts were analysed using thematic coding which involved reading and re-reading the data and grouping extracts into common themes [44 (link)]. Transcripts were coded in NVivo 11 for Windows (Version 11.4.1.1064 Pro, QSR International Pty Ltd., Victoria, Australia). In first cycle coding excerpts were arranged according to topic, personal values, and processes [43 ] to inform ongoing interviews and indicate focal subjects including calf feeding. Coding was repeated to explore the topic of calf feeding in-depth and relevant interview extracts were chosen to represent the perceptions of participants relevant to the themes and explanations being constructed.
Nvivo 11 for windows
Manufactured by Lumivero
Sourced in Australia
NVivo 11 for Windows is a qualitative data analysis software that assists researchers in managing, organizing, and analyzing unstructured data. It provides tools for importing, coding, analyzing, and visualizing qualitative data from various sources, including interviews, focus groups, social media, and web content.
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4 protocols using nvivo 11 for windows
1
Thematic Coding Analysis of Calf Feeding
2
Qualitative Descriptive Analysis of Focus Group
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The qualitative descriptive method was employed to synthesise and analyse the focus group transcript. This analysis method was used because it allowed us to produce a comprehensive summary of the data in plain language and to stay close with the original meaning of the data.40 (link),41 Two members of the study team (QJZ, SN) reviewed the questionnaire data and transcript to develop a coding framework of recurrent themes. The themes were then presented to a small working group (DR, SN, AF). Through iterative discussion during the analysis phase, all themes were discussed and discrepancies were resolved verbally.
Qualitative content analysis was conducted inductively to identify emergent themes from the data and develop a framework for coding.42 (link),43 (link) Codes identified the topics in the data pertinent to the research objectives. Data were then grouped into broader themes. All qualitative data was analysed using NVivo (NVivo 11 for Windows, Version 11.0.0.300 by QSR International).
Qualitative content analysis was conducted inductively to identify emergent themes from the data and develop a framework for coding.42 (link),43 (link) Codes identified the topics in the data pertinent to the research objectives. Data were then grouped into broader themes. All qualitative data was analysed using NVivo (NVivo 11 for Windows, Version 11.0.0.300 by QSR International).
3
Qualitative Analysis of Patient Interviews
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A certified vendor translated Spanish interviews into English. The first Spanish transcripts were back-translated to establish accuracy of translation and meanings of cross-cultural concepts.17 (link) For interviews conducted in English, every tenth transcript was compared to the recording to ensure full and accurate transcription. Two trained coders conducted consensus-based thematic analysis of the transcripts, identifying relevant themes and patterns using NVivo 11 for Windows software (QSR International). Each coder independently analyzed three randomly selected interviews, then met with the qualitative research lead to compare and discuss themes. Through three such coding cycles, the coders and qualitative research lead developed the codes to conduct thematic analysis of all interviews. They repeated this process with every fifth interview to ensure consistency in coding. Once all interviews were coded, within-group analysis explored major patterns and relationships between codes to identify themes shared within groups (eg, non-adherent patients). A secondary round of coding was conducted by the qualitative research lead (SH) to identify more specific themes. Cross-group analysis was done to explore major patterns between codes to identify themes that were shared across groups (eg, Spanish-speaking patients).18
4
Exploratory Trial of Complex Intervention
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Since this was an exploratory trial of a new complex intervention, we agreed a priori to interpret the results with caution. Thus, although we undertook initial inferential statistics and hypothesis testing, our goal was to uncover any important potential associations in the study variables.37 (link) For this reason, we evaluated statistical significance at the 0.2 level using a one-sided test. Specifically, we explored changes in measures between the two groups (CST-PD and TAU) over time using ANCOVA, controlling for baseline values. All analyses were conducted on an intention-to-treat basis, on complete case data. For the qualitative analysis, using NVivo 11 for Windows software (QSR International Pty Ltd.),38 data from participant–dyad diaries, researcher field notes, and semistructured interviews were used. We triangulated the results of our quantitative findings with thematic analysis.39 Using an inductive process, we systematically extracted codes from each data source to derive key themes; these were subsequently triangulated with the quantitative outcome to establish correspondence between the qualitative and quantitative data. We arrived at the final themes by consensus of five INVEST investigators (IL, SV, SM, SS and BK).
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