Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Продольный рефлексивный тематический анализ× | Тематический анализ× | |
|---|---|---|
| Область≠ | Качественные методы | Качественные исследования |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 2006 (RTA seminal); longitudinal application developed through 2010s | 2006 |
| Автор метода≠ | Virginia Braun & Victoria Clarke (reflexive thematic analysis); longitudinal design adapted from qualitative longitudinal research traditions (Saldaña, 2003) | Virginia Braun and Victoria Clarke |
| Тип≠ | Qualitative analytic method applied longitudinally | Method |
| Основополагающий источник | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| Другие названия≠ | longitudinal RTA, repeated-wave thematic analysis, longitudinal qualitative thematic analysis, L-RTA | TA, Reflexive Thematic Analysis |
| Связанные≠ | 5 | 3 |
| Сводка≠ | Longitudinal Reflexive Thematic Analysis (L-RTA) applies Braun and Clarke's reflexive thematic analysis framework to qualitative data collected from the same participants (or context) at two or more time points. Rather than producing a single static account, it tracks how meanings, experiences, and themes evolve, persist, or transform over time, foregrounding the researcher's active reflexive engagement at every stage of the iterative process. | Thematic Analysis (TA) is a qualitative research methodology for identifying, analyzing, and reporting patterns (themes) in qualitative data. Developed systematically by Virginia Braun and Victoria Clarke (2006), TA is flexible and accessible, applicable across diverse theoretical frameworks and data types, making it one of the most widely used qualitative methods in psychology, health research, and social sciences. |
| ScholarGateНабор данных ↗ |
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