Módszerek összehasonlítása

	Longitudinális narratív kutatás – Történetek nyomon követése az idő múlásával	Longitudinális kvalitatív tartalomelemzés
Tudományterület	Kvalitatív módszerek	Kvalitatív módszerek
Módszercsalád	Process / pipeline	Process / pipeline
Keletkezés éve	1990s–2000s (narrative inquiry established 1990; longitudinal application elaborated 2000s–2010s)	2000s–2010s
Megalkotó	D. Jean Clandinin & F. Michael Connelly (narrative inquiry foundations); extended into longitudinal designs by Clandinin and colleagues	Philipp Mayring (foundational QCA); longitudinal extension developed across qualitative health and social research traditions
Típus	Qualitative longitudinal research design	Qualitative analytical method
Alapmű	Clandinin, D. J., Huber, J., Huber, M., Murphy, M. S., Murray Orr, A., Pearce, M., & Steeves, P. (2006). Composing diverse identities: Narrative inquiries into the interwoven lives of children and teachers. Routledge. ISBN: 978-0415357241	Mayring, P. (2000). Qualitative content analysis. Forum: Qualitative Social Research, 1(2), Art. 20.
Alternatív nevek	longitudinal narrative inquiry, narrative longitudinal design, LNI, temporal narrative research	LQCA, longitudinal QCA, repeated qualitative content analysis, panel qualitative content analysis
Kapcsolódó	6	3
Összefoglaló	Longitudinal narrative research is a qualitative design that follows participants across multiple time points, gathering and analyzing their stories to understand how experiences, identities, and meanings evolve over time. Rooted in Clandinin and Connelly's narrative inquiry tradition, it treats human experience as fundamentally storied and temporal — what matters is not just what happened but how people narrate, revise, and make sense of their lives as circumstances change.	Longitudinal qualitative content analysis (LQCA) applies systematic content analysis to text data gathered from the same participants, settings, or documents at two or more points in time. The method preserves the interpretive rigour of qualitative content analysis while adding an explicit temporal dimension, enabling researchers to track how meanings, experiences, categories, or discourse shift, deepen, or stabilise across time rather than producing a single-point-in-time description.