Sammenlign metoder
Gennemgå dine valgte metoder side om side; rækker, der afviger, er fremhævet.
| Deltagende dokumentanalyse× | Deltagende Indholdsanalyse× | |
|---|---|---|
| Fagområde | Kvalitativ | Kvalitativ |
| Familie | Process / pipeline | Process / pipeline |
| Oprindelsesår≠ | 1940s–2000s (synthesis of participatory tradition and systematic document analysis) | 1990s–2000s (formalized in community-based and health research contexts) |
| Ophavsperson≠ | Rooted in participatory action research (Kurt Lewin, 1940s); document analysis formalized by Glenn Bowen (2009) | Developed at the intersection of participatory action research (Kurt Lewin, 1940s) and qualitative content analysis traditions |
| Type≠ | Qualitative research design | Qualitative research method |
| Oprindelig kilde≠ | Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. DOI ↗ | Leavy, P. (Ed.). (2014). The Oxford Handbook of Qualitative Research. Oxford University Press. ISBN: 978-0199811755 |
| Aliasser | PDA, collaborative document analysis, participatory archival analysis, community-based document analysis | PCA, community-based content analysis, collaborative content analysis, participatory textual analysis |
| Relaterede≠ | 4 | 5 |
| Resumé≠ | Participatory Document Analysis is a qualitative research approach that systematically examines existing documents — such as policy records, reports, correspondence, and community archives — while actively involving community members or stakeholders as co-researchers in the selection, interpretation, and meaning-making processes. It merges the rigor of established document analysis techniques with the democratic ethos of participatory action research, ensuring that those most affected by the documents have voice in shaping what those documents mean. | 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. |
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