aceUsing Artificial Intelligence in Qualitative Lupus Pregnancy Research: The Potential of Large Language Models and Prompting Strategies
Objective Our objective was to evaluate the ability of different large language models (LLMs) to translate and analyze qualitative interviews describing pregnancy experiences among women with systemic lupus erythematosus (SLE). An additional objective was to compare themes identified by LLMs with those identified by human researchers. Methods We analyzed 26 semi‐structured interviews originally conducted in Portuguese by Rodrigues et al. among women with SLE exploring their perinatal care experiences. Three prom…
Four LLMs generated themes closely aligned with human researchers from Portuguese interviews with women with lupus, and few-shot prompting gave the most comprehensive and coherent theme extraction.
The study judged LLM output with an LLM-as-a-judge framework on a single set of 26 interviews, and the authors position LLMs only as complements to human interpretation.
Evidence
- Peer-reviewedArthritis Care & Research2026-10-20
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Truvace Impact Record TRV-2026-2098, v1: “Using Artificial Intelligence in Qualitative Lupus Pregnancy Research: The Potential of Large Language Models and Prompting Strategies.” Truvace, 2026-10-21. /record/TRV-2026-2098 (accessed at citation time). sha256 72fc9e26b05655d8…
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