Artificial Intelligence in Nursing Practice Education: A Systematic Review and Meta-Analysis
Abstract
Objective: To systematically evaluate the application effect of artificial intelligence (AI) technology in nursing practice courses and to provide evidence-based guidance for the intelligent reform of nursing education.
Methods: Computerized searches were performed in PubMed, Web of Science, Embase, the Cochrane Library, CNKI, WanFang, CBM, and VIP databases for randomized controlled trials and quasi-experimental studies on the educational effectiveness of AI in nursing practice courses. The retrieval period was from the establishment of each database to February 2026. Data extraction, quality evaluation, and literature screening were carried out separately by two researchers. RevMan 5.4 was used to conduct the meta-analysis. The PROSPERO registration number for this review protocol is CRD420261403298. The PRISMA 2020 guidelines are followed in this systematic review.
Results: A total of 16 studies with a sample size of 1647 participants were included, including 7 randomized controlled trials and 9 quasi-experimental studies. The results of this meta-analysis indicate that incorporating AI into nursing practical training programs may enhance students' learning outcomes in a variety of ways, with beneficial facilitative effects noted in knowledge level (SMD = 0.72, 95% CI [0.20-1.24], p = 0.007), practical ability (SMD = 1.25, 95% CI [0.50-2.00], p = 0.001), critical thinking and clinical reasoning abilities (SMD = 0.43, 95% CI [0.21-0.65], p 2 = 91%) and practical ability…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,647 participants or records.
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