ArticleBMC nursing2026
The experience of nursing students using generative artificial intelligence: a qualitative meta-synthesis.
Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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Authors and funding
8 authors.
Funding
Abstract
objectiveThis study systematically integrated qualitative research regarding nursing students' experiences using Generative Artificial Intelligence (GAI). It aimed to provide an evidence-based basis to facilitate the safe, appropriate, and effective use of GAI among nursing students.
designA qualitative systematic review. DATA SOURCES: PubMed, Web of Science, The Cochrane Library, CINAHL, Embase, CNKI, Wanfang, VIP, and SinoMed were searched for qualitative studies addressing nursing students' experiences with GAI, covering the period from January 1, 2015, to January 29, 2026.
methodsThe methodological quality of included studies was evaluated using qualitative research quality appraisal criteria developed by the JBI Centre for Evidence-Based Health Care (Australia). A meta-synthesis approach was used to synthesize findings, and the ConQual tool was applied to assess confidence in the results.
resultsTwenty-four studies were included, producing 41 findings grouped into 11 sub-themes and subsequently synthesized into four themes: perceived benefits, perceived shortcomings, perceived risks, and perceived needs.
conclusionsNursing students' experiences with GAI were found to be complex and sometimes contradictory. Therefore, educational institutions, educators, and technology developers should enhance relevant technical, educational, and policy support frameworks to ensure the appropriate, safe, and effective use of GAI tools among nursing students. CLINICAL TRIAL NUMBER: Not applicable.
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Registered trials
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