Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse Thématique Réflexive Participative× | Analyse de contenu participative× | |
|---|---|---|
| Domaine | Qualitatif | Qualitatif |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 2006 (reflexive TA); participatory integration developed through 2010s–2020s | 1990s–2000s (formalized in community-based and health research contexts) |
| Auteur d'origine≠ | Virginia Braun and Victoria Clarke (reflexive thematic analysis); participatory application developed within participatory action research traditions | Developed at the intersection of participatory action research (Kurt Lewin, 1940s) and qualitative content analysis traditions |
| Type≠ | Qualitative analytic method | Qualitative research method |
| Source fondatrice≠ | Braun, V., & Clarke, V. (2021). Thematic Analysis: A Practical Guide. Sage. ISBN: 978-1473953345 | Leavy, P. (Ed.). (2014). The Oxford Handbook of Qualitative Research. Oxford University Press. ISBN: 978-0199811755 |
| Alias | Participatory RTA, collaborative reflexive thematic analysis, participant-involved thematic analysis, co-analytic reflexive thematic analysis | PCA, community-based content analysis, collaborative content analysis, participatory textual analysis |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | Participatory Reflexive Thematic Analysis (Participatory RTA) integrates Braun and Clarke's reflexive thematic analysis framework with participatory research principles, actively involving participants as co-analysts in generating, reviewing, or refining themes from qualitative data. The approach is simultaneously a method of analysis and a form of member engagement, ensuring that the themes produced are grounded in participants' own meaning-making rather than imposed solely by the researcher. | Participatory Content Analysis (PCA) is a qualitative method that integrates community members or stakeholders directly into the content analysis process. Rather than treating participants solely as data sources, PCA positions them as co-analysts who help develop coding categories, interpret textual data, and validate findings. This approach is widely used in health communication, education research, and community-based studies where insider knowledge and cultural context are essential to accurate interpretation. |
| ScholarGateJeu de données ↗ |
|
|