ArticleFrontiers in public health2026
Exploring the application of generative artificial intelligence in nursing: a cross-sectional study.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- The effectiveness of GAI-assisted teaching methods in medical education: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study aims to systematically investigate the application of Generative Artificial Intelligence (GAI) in nursing practice within China. It seeks to map current usage patterns, identify perceived benefits and implementation challenges, and uncover the functional needs of nursing staff regarding GAI. Additionally, the research will assess the real-world performance and adoption of emerging local GAI platforms. The findings are expected to provide foundational evidence to guide the scientifically sound and contextually appropriate development of GAI in nursing. Methods: The convenience sampling method was used to select nurse interns, staff nurses, and nurse managers from 20 provinces between April and June 2025 as survey respondents. We designed the questionnaire through a literature review as well as evidence extraction. A panel of experts assessed the content validity of the questionnaire. Results: According to a survey of 181 nurses, GAI has achieved a high adoption rate (92.81%), which was not significantly associated with any demographic factors (all Conclusion: This study establishes that GAI adoption among Chinese nurses is widespread but nuanced, marked by a preference for local platforms and role-specific benefits. The primary barriers to integration-concerns about content accuracy and clinical autonomy-underscore the need for clinically validated and trustworthy systems. These findings advocate for targeted training and ethically aware design to fully realize GAI's potential as a collaborative tool in nursing.
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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.