方法对比
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| Comparative Reflexive Thematic Analysis× | Braun & Clarke 的反思性主题分析法× | |
|---|---|---|
| 领域 | 质性 | 质性 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 2006 (reflexive TA); comparative application formalised ~2019–2021 | 2006 (seminal paper); explicitly named 'reflexive' from ~2019 |
| 提出者 | Virginia Braun & Victoria Clarke | Virginia Braun & Victoria Clarke |
| 类型≠ | Qualitative analytic approach | Qualitative research method |
| 开创性文献≠ | Braun, V., & Clarke, V. (2021). Thematic Analysis: A Practical Guide. Sage. ISBN: 978-1473953406 | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| 别名 | Comparative RTA, cross-group thematic analysis, comparative TA, comparative qualitative thematic comparison | RTA, reflexive TA, Braun and Clarke thematic analysis, qualitative thematic analysis |
| 相关≠ | 4 | 6 |
| 摘要≠ | Comparative Reflexive Thematic Analysis (CRTA) applies Braun and Clarke's reflexive thematic analysis framework to data drawn from two or more distinct groups, time points, or contexts, with the explicit goal of contrasting thematic patterns across those groups. The reflexive element means the analyst continuously interrogates how their own perspectives and positioning shape the themes they construct, while the comparative element directs attention to differences and similarities between data sets rather than seeking a single unified account. | 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. |
| ScholarGate数据集 ↗ |
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