SynthesisFrontiers in public health2026
Registered nurses' experiences with generative artificial intelligence: a meta-synthesis of qualitative studies.
Synthesis in Frontiers in public health, 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To synthesize qualitative evidence on registered nurses' experiences of using generative artificial intelligence (GAI) in clinical practice and nursing research, and to identify perceived benefits, challenges, and support needs for its standardized implementation in nursing. Methods: A qualitative meta-synthesis was conducted using the Joanna Briggs Institute meta-aggregation approach. PubMed, CINAHL, Embase, PsycINFO, Scopus, Web of Science, the Cochrane Library, CNKI, Wanfang, VIP, and the China Biomedical Literature Database were searched from inception to April 25, 2026. Two reviewers independently screened studies, extracted data, and assessed methodological quality using the JBI Critical Appraisal Checklist for Qualitative Research. Synthesized findings were assessed using the JBI ConQual approach. Results: Six qualitative studies involving 113 registered nurses were included. Thirty-eight findings were extracted and aggregated into eight categories, which generated three synthesized findings: (1) GAI may enhance work efficiency and professional competence; (2) nurses encounter ethical, cultural, and operational challenges when using GAI; and (3) nurses require training, institutional support, and clear guidance for standardized GAI use while maintaining positive expectations for future applications. Conclusion: The available qualitative evidence suggests that registered nurses perceive GAI as a potentially supportive tool for improving efficiency, assisting clinical and research decision-making, and promoting professional development. However, the current evidence base remains limited, and the findings should be interpreted as preliminary. Further research across diverse healthcare systems and cultural contexts is needed to clarify how GAI can be safely and responsibly integrated into nursing practice. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420261365306, Identifier CRD420261365306.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.