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A Realist Approach to Analysis in a Participatory Research Project
Background:
Realist reviews have shown the effectiveness of participatory action research but the realist approach has not been used in combination with a participatory approach in qualitative data analysis.
Objectives:
To study the links between preexisting conditions in neighborhoods and the kind of actions taken at the community level during the coronavirus disease 2019 pandemic in Toronto, a community-university research partnership used a critical realist approach to analyze qualitative interviews with grassroots leaders. This article describes the procedures developed to enable participation of the full community- academic team in the analysis.
Methods:
One analyst coded paragraphs in all 46 interviews for preexisting conditions (contexts), actions taken (intervention components), the often implicit factors that underpinned the actions (mechanisms), and observed results (outcomes) as stated by the interviewees. Each interview was summarized in terms of the contexts (C), actions (I), mechanisms (M) and outcomes (O) identified and one to seven midrange CIMO hypotheses were developed for each interview. A second level of analysis involved sense-making workshops with the community partner and a cross-section of interviewees using the CIMO statements.
Conclusions:
This article describes the realist approach to analysis and the changes that were made to enable a mixed team of community leaders and academics to generate overall statements of impact. This is a novel approach to qualitative data analysis, with a range of implications for the use of this technique in participatory research.
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