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Reflecting on LLM Support in Reflexive Thematic Analysis: An Exploratory Study

Vikan, Magnhild et al. (2025)

Published
Sep 8, 2025
Journal
Qualitative Health Research · Vol. 36 · No. 2-3
DOI
10.1177/10497323251365211

At a GlanceAI

Testing finds base LLMs offer limited help for reflexive thematic analysis and cannot replace human interpretation.

SummaryAI

This exploratory study directly tests whether a base LLM can support reflexive thematic analysis (RTA), a qualitative approach in which researchers’ situated interpretation is central. Using an offline model on a health-science interview, the authors developed and refined prompts across RTA phases and identified pitfalls including misleading prompts, self-referential outputs, translation problems, and errors. They conclude that current base models do not improve RTA efficiency, though they may help reveal gaps in researchers’ perspectives. The work argues that careful human familiarization and methodological competence remain necessary to preserve RTA’s epistemological integrity.

Method SnapshotAI

The authors tested an offline base LLM on a health-science interview across reflexive thematic analysis phases, iteratively refining prompts.

BackgroundAI

Basic qualitative research methods, especially reflexive thematic analysis and the role of researcher reflexivity.

Wrong models, wrong method, wrong results...

ES