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

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Base large language models (LLMs) currently offer limited support for reflexive thematic analysis (RTA) and do not enhance efficiency. Human researchers remain essential for high-quality qualitative analysis and preserving epistemological integrity.

Keywords:
artificial intelligenceexploratory studyhealth sciencelarge language modelqualitative analysisreflexive thematic analysisreflexivity

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Area of Science:

  • Qualitative Research Methods
  • Artificial Intelligence in Health Sciences
  • Text Analysis

Background:

  • The advent of large language models (LLMs) like ChatGPT has spurred debate on their utility in qualitative research.
  • Reflexive thematic analysis (RTA) is a key qualitative method emphasizing researcher subjectivity for in-depth understanding.
  • Optimism exists regarding LLMs' potential, but their capacity for meaningful interpretation in qualitative analysis is questioned.

Purpose of the Study:

  • To investigate how LLMs can support reflexive thematic analysis (RTA) of health science interview data.
  • To identify effective prompt strategies for utilizing LLMs in RTA.
  • To highlight potential challenges and foster discussion on LLMs' role in qualitative research.

Main Methods:

  • An offline large language model (LLM) was used to analyze an interview text from health science research.
  • A series of tests were conducted, mirroring the phases of RTA.
  • Iterative refinement of prompts based on test insights led to a recommended prompt strategy.

Main Results:

  • Base LLMs currently provide limited support for RTA and do not increase analytical efficiency.
  • LLMs may assist in identifying gaps in researcher perspectives.
  • Effective utilization requires a defined strategy to avoid issues like misleading prompts and errors.

Conclusions:

  • High-quality RTA necessitates human involvement, comprehensive familiarization, and methodological expertise.
  • Base LLMs, in their current state, cannot replace the nuanced interpretation and epistemological integrity provided by human researchers.
  • Further research and strategic implementation are needed to explore the potential of LLMs in qualitative research.