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But sometimes you can discern a theme from each interview.
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Themes from each perspective are categorized and serve as a basis for commentary on initial theory-based research propositions.
Working from the written transcripts, we used an open-coding process to distill prominent themes from each transcript.
Analyzing and coding the three open-ended interview questions yielded qualitative data on the percentage of identified themes from each of the three reasoning patterns present in respondents' explanations.
The major themes and sub-themes from each reviewer were then compared and the lists merged.
Themes from each coder were compared to examine consistency of themes.
The co-authors read three interviews, then met and discussed preliminary themes from each interview.
Common patterns and divergences were then looked for across all themes from each transcript.
An independent researcher extracted key points and themes from each transcription to create a one-page summary for each interview.
2. We then reviewed the data in Table 1 and isolated emergent themes from each study's findings.
The themes from each data set were arranged according to their reference to context, interventions, outcomes and mechanisms.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com