Generative Artificial Intelligence for Qualitative Methods in Health Research: Rapid Review
Abstract
Background: Generative AI (GAI) is rapidly transforming research practices, including qualitative methods in health research. While these tools offer efficiency in processing large volumes of textual data, concerns remain regarding their methodological rigor, interpretive capacity, equity, and ethical implications.
Objective: This rapid review aimed to synthesize the current evidence on the use of GAI in health-related qualitative research, focusing on its applications, performance relative to human analysis, and implications for rigor, ethics, and equity.
Methods: We conducted a rapid review following Joanna Briggs Institute and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Peer-reviewed studies published between 2022 and December 2025 were identified through searches in PubMed, Web of Science, and Scopus. Eligible studies included qualitative or mixed methods research that used GAI tools (eg, ChatGPT, Gemini, and Claude) during qualitative analysis, including studies that compared GAI-generated outputs with human researchers, coders, or traditional qualitative analytic approaches. Data were extracted using a structured template and synthesized descriptively. Study quality was assessed using the Critical Appraisal Skills Programme (CASP) checklist. This rapid review was registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD420261280832). The review adhered to the registered PROSPERO protocol; no…
Read the paper
Related studies
- Regulation of nucleolus assembly by non-coding RNA polymerase II transcripts
- For a Healthy Histone Code, a Little SUMO in the Tail Keeps the Acetyl Away
- Discovering a binary CTCF code with a little help from BORIS
- Article Commentary: Stabilizing the Code–-Methods to Preserve RNA Prove Their Worth
- Foreword to the Special Issue for the RINTC (The Implicit Seismic Risk of Code-Conforming Structures) Project
- Commentary: Promoting Health and Well-being in Pediatric Primary Care Settings: Using Health and Behavior Codes at Routine Well-child Visits
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.