方法对比
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| 纵向扎根理论× | 纵向主题分析× | |
|---|---|---|
| 领域 | 质性 | 质性 |
| 方法族 | Process / pipeline | Process / pipeline |
| 起源年份≠ | 1990s–2000s (as a recognized variant of grounded theory) | 2000s–2010s (formalized alongside longitudinal qualitative research methods) |
| 提出者≠ | Kathy Charmaz and longitudinal qualitative researchers (building on Glaser & Strauss) | Built on Braun & Clarke (2006) thematic analysis; longitudinal adaptation developed across qualitative health and social science research communities |
| 类型≠ | Qualitative longitudinal research design | Qualitative analysis approach |
| 开创性文献≠ | Charmaz, K. (2006). Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. Sage. ISBN: 978-0761973522 | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| 别名 | LGT, longitudinal GT, temporal grounded theory, grounded theory longitudinal design | LTA, longitudinal TA, repeated thematic analysis, temporal thematic analysis |
| 相关≠ | 5 | 4 |
| 摘要≠ | Longitudinal grounded theory is a qualitative research design that applies grounded theory's inductive, iterative logic to data collected from the same participants or settings across multiple time points. It is used to build substantive theory that accounts not only for social processes but also for how those processes unfold, shift, and are renegotiated over time. The approach is particularly suited to studying change, trajectory, and temporal experience in social and health research. | Longitudinal Thematic Analysis (LTA) extends standard thematic analysis to data collected at multiple time points from the same participants or contexts. Rather than producing a single cross-sectional account, LTA maps how themes emerge, persist, transform, or disappear over time, enabling researchers to understand change, continuity, and process in qualitative terms. It is widely used in health, education, and social science research where lived experience unfolds over months or years. |
| ScholarGate数据集 ↗ |
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