Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Поздовжній інтерпретаційний феноменологічний аналіз (L-IPA)× | Тематичний аналіз× | |
|---|---|---|
| Галузь≠ | Якісні методи | Якісні дослідження |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 2000s–2010s (IPA from mid-1990s; longitudinal variant formalised ~2009–2014) | 2006 |
| Автор методу≠ | Jonathan A. Smith and colleagues; longitudinal extension developed by Smith, Flowers, and Larkin | Virginia Braun and Victoria Clarke |
| Тип≠ | Qualitative research design and analysis approach | Method |
| Основоположне джерело≠ | Smith, J. A., Flowers, P., & Larkin, M. (2009). Interpretive Phenomenological Analysis: Theory, Method and Research. Sage. ISBN: 978-1412908344 | Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. DOI ↗ |
| Інші назви≠ | L-IPA, longitudinal IPA, repeated-interview IPA, temporal IPA | TA, Reflexive Thematic Analysis |
| Пов'язані≠ | 4 | 3 |
| Підсумок≠ | Longitudinal Interpretive Phenomenological Analysis (L-IPA) extends the IPA tradition by interviewing the same participants at multiple time points, allowing researchers to trace how the meaning of a lived experience evolves over time. Grounded in phenomenology and hermeneutics, L-IPA preserves idiographic depth at each wave while adding a temporal dimension that cross-sectional IPA cannot provide. It is used widely in health psychology, illness adjustment studies, and any domain where experience unfolds across a significant time span. | 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. |
| ScholarGateНабір даних ↗ |
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