ArticleBMC nursing2026
Cognitive status of nursing postgraduates toward Generative Artificial Intelligence: a qualitative study based on the UTAUT framework.
Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
What it found
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- AI-Powered Simulation for Nursing Education: Mixed Methods Systematic Review.Journal of medical Internet research · 2026Pooled it
- A Meta-synthesis of nursing students' experiences with generative artificial intelligence-assisted learning.Frontiers in medicine · 2026Pooled it
- The experience of nursing students using generative artificial intelligence: a qualitative meta-synthesis.BMC nursing · 2026Article
- Generative artificial intelligence literacy profiles and workforce readiness among pre-professional nursing students: a latent profile analysis.Frontiers in public health · 2026Article
- Undergraduate nursing students' attitudes and needs regarding the use of generative artificial intelligence in professional learning: a qualitative study.Frontiers in public health · 2026Article
- Intention to Use Large Language Models Among Clinical Nurses in China With Prior Familiarity With or Experience Using LLMs: A Qualitative Study.Journal of nursing management · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenerative Artificial Intelligence (GenAI) has the potential to enhance research efficiency and reduce clinical workload for nursing postgraduates, gradually transforming the development of the healthcare and nursing sectors. Understanding nursing postgraduates' experiences and perceptions of Generative Artificial Intelligence tools is essential for promoting their proper application.
aimTo comprehensively explore Chinese nursing postgraduates' perceptions, attitudes, and needs regarding GenAI using qualitative interviews.
designA qualitative study design.
methodsSemi-structured interviews were conducted among 16 nursing postgraduates. Purposeful sampling was used to select master's degree nursing students with experience in the use of artificial intelligence. Thematic analysis was performed to identify recurring patterns and codes.
resultsFive major themes emerged from the analysis: (1) performance expectancy, (2) effort expectancy, (3) social influence, (4) usage attitudes and behaviors, and (5) boundaries to Generative Artificial Intelligence adoption. The findings revealed nursing postgraduates' generally positive perceptions and usage behaviors toward Generative Artificial Intelligence, alongside the barriers and concerns they associate with its application.
conclusionsGenerative Artificial Intelligence is increasingly integrated into research and practice in healthcare and nursing. Nursing students should approach Generative Artificial Intelligence tools rationally and apply them appropriately. This study demonstrates that nursing postgraduates hold a relatively positive attitude and cognitive stance toward Generative Artificial Intelligence. In light of the current lack of Generative Artificial Intelligence-related education, the study also proposes educational strategies tailored to the Chinese context.
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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 Socratic graph.