Accepted for/Published in: JMIR Research Protocols
Date Submitted: Dec 12, 2025
Open Peer Review Period: Dec 16, 2025 - Feb 10, 2026
Date Accepted: Jul 7, 2026
(closed for review but you can still tweet)
Effects of artificial intelligence on nursing education: A study protocol for systematic review and meta-analysis
ABSTRACT
Background:
Artificial intelligence (AI) demonstrates considerable potential in nursing education. However, its specific effects on knowledge acquisition, practical skills, satisfaction, competence, and confidence remain inadequately characterized.
Objective:
This study aims to assess the effects of AI on nursing students’ education.
Methods:
We will follow the preferred reporting items for systematic review and meta-analysis protocol guidelines. Systematic literature searches will be conducted across six electronic databases, namely, PubMed, Web of Science, EMBASE, CINAHL, EBSCO, and the Cochrane Library. The inclusion criteria follow the PICOS framework, incorporating nursing students from academic institutions and clinical internship settings. This review examines studies comparing AI-based educational interventions with traditional teaching methodologies. The outcomes encompass (1) knowledge level, (2) practical ability, (3) satisfaction, (4) competence, and (5) confidence. Eligible study designs include randomized controlled trials (RCTs) and quasi-experimental studies. The search timeline is from the inception of each database to February 2026, with no language restriction. Two independent reviewers will screen studies and extract data. Any disputes will be resolved through discussion. Unresolved disputes will be decided by consulting the third author. For the risk of bias assessment, the Cochrane risk-of-bias (ROB) tool for RCTs and the risk of bias in non-randomized studies of intervention (ROBINS-I) tool will be used. Moreover, RevMan 5.3 is used for meta-analysis.
Results:
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Conclusions:
/ Clinical Trial: PROSPERO registration number: CRD420251170836.
Citation
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