Vertaile menetelmiä

	Vertaileva temaattinen analyysi – Ryhmien välinen temaattinen analyysi	Refleksiivinen temaattinen analyysi
Tieteenala	Laadulliset menetelmät	Laadulliset menetelmät
Menetelmäperhe	Process / pipeline	Process / pipeline
Syntyvuosi	2000s–2010s (as an explicit comparative variant of thematic analysis)	2006 (seminal paper); explicitly named 'reflexive' from ~2019
Kehittäjä	Virginia Braun & Victoria Clarke (thematic analysis foundation); comparative extension developed in applied policy and cross-cultural qualitative research traditions	Virginia Braun & Victoria Clarke
Tyyppi	Qualitative comparative analytical strategy	Qualitative research method
Alkuperäislähde	Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.	Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Rinnakkaisnimet	cross-group thematic analysis, comparative TA, multi-group thematic analysis, comparative qualitative thematic analysis	RTA, reflexive TA, Braun and Clarke thematic analysis, qualitative thematic analysis
Liittyvät	6	6
Tiivistelmä	Comparative Thematic Analysis applies the structured procedures of thematic analysis across two or more distinct groups, sites, or time points, with the explicit aim of identifying both shared patterns and meaningful differences. Rather than producing a single composite account of experience, it yields a layered analysis that maps where themes converge and diverge across comparison units — making it especially valuable for policy-relevant, cross-cultural, or multi-site qualitative studies.	Reflexive Thematic Analysis (RTA) is a widely used qualitative method for identifying, analysing, and interpreting patterns of shared meaning — called themes — across a dataset. Developed by Virginia Braun and Victoria Clarke, it is theoretically flexible, works across epistemological positions, and foregrounds the researcher's active, interpretive role rather than treating themes as features that simply emerge from data. It differs from older 'codebook' approaches by treating the analyst's subjectivity as a resource rather than a source of bias to be suppressed.