ArticleBMC nursing2026
Knowledge, attitudes, and practices related to the use of artificial intelligence in nursing education and practice: a systematic review and meta-analysis.
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 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence Literacy, Critical Thinking Disposition, and Clinical Competence Among Nursing Students: A Cross-Sectional Study.Nursing reports (Pavia, Italy) · 2026Article
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Authors and funding
2 authors.
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Abstract
backgroundThe integration of artificial intelligence (AI) into nursing education and practice has demonstrated significant potential to enhance efficiency, reduce errors, and optimize healthcare delivery. However, the successful implementation of AI requires careful consideration of the knowledge, attitudes, and practices of nursing professionals and students.
aimTo examine the association between knowledge, attitudes, and practices (KAP) regarding AI use in nursing education and clinical practice.
methodSystematic review and meta-analysis. Following PRISMA guidelines, a comprehensive search was conducted across three major databases (SCOPUS, Web of Science, and PubMed) for studies published between January 2019 and April 2025.
resultsTen qualified cross-sectional studies were identified from an initial pool of 283 records. A random-effects meta-analysis revealed a moderate positive correlation between knowledge and attitudes {Pearson's correlation (r) = 0.43, 95% confidence interval (CI) = [0.31, 0.53]}, a moderate attitude-practice relationship {Pearson's correlation (r) = 0.46, 95% CI = [0.32, 0.59]}, and a weak knowledge-practice association {Pearson's correlation (r) = 0.26, 95% CI = [0.13, 0.38]}. Significant heterogeneity was observed in the analysis [between-study variance (τ²) = 0.03-0.05; inconsistency (I²) = 89.88%-95.02%; Cochran's Q (Q) = 16.44-157.00, p < 0.001), thereby suggesting that contextual factors such as institutional policies and prior AI exposure may influence these relationships.
conclusionsThese findings partially aligned with the KAP theoretical framework, thus highlighting the significant association between AI knowledge, attitude, and clinical implementation. We recommend integrated AI education that emphasizes attitude formation, targeted training to address implementation barriers, and organizational support systems for AI integration. Future research should employ longitudinal designs to establish causal relationships and examine the contextual factors influencing AI use across diverse healthcare settings.
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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.