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Artificial Intelligence Literacy Among Nursing Students: A Scoping Review of Status, Influencing Factors, and Educational Implications
ABSTRACT
Background:
Smart healthcare is evolving at a rapid pace, setting new requirements for nursing students: mastering artificial intelligence (AI) literacy has quickly become a core competency for them to establish their future careers.
Objective:
A scoping review was conducted to synthesize the literature pertaining to AI literacy among nursing students to clarify its current status, characteristics, underlying mechanisms, influencing factors, and associated challenges.
Methods:
A systematic literature search was conducted across the following electronic databases: PubMed, Embase, Web of Science Core Collection, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Data Knowledge Service Platform, China Biomedical Literature Database (CBM), and VIP Chinese Scientific Journal Database. The search period was uniformly defined from the inception of each database to September 22, 2025. Twenty eligible studies were included.
Results:
The overall level of AI literacy among nursing students was categorized as moderate to moderately low, with notable disparities in performance across different dimensions of their competency framework. Their proficiency in technical comprehension and critical evaluation remained insufficient, whereas their ability to apply AI in practical scenarios was relatively prominent. AI literacy demonstrates a significant positive correlation with core competencies, including self-efficacy, innovative thinking, and learning engagement, and exerts a mediating effect on the improvement of these core competencies by enhancing AI-specific self-efficacy. Factors influencing nursing students' AI literacy encompassed four dimensions: personal characteristics, educational support, environmental conditions, and psychological status. The advancement of AI literacy among this population was confronted with multiple practical barriers, including an underdeveloped curriculum system, inadequate supply of learning resources, anxiety regarding the application of AI technology in clinical settings, and insufficient ethical awareness of AI-related issues.
Conclusions:
The overall level of AI literacy among nursing students is modulated by multi-level interconnected factors, the establishment of a systematic, multi-tiered educational and training framework is imperative. Priority should be given to optimizing structured AI curricula, with an emphasis on integrating technical proficiency training and AI ethics education. Efforts should focus on facilitating the in-depth integration of AI technologies into nursing practice. For future research, it is critical to develop standardized assessment tools and conduct longitudinal cohort studies to further elucidate the underlying mechanisms through which AI literacy affects nursing competencies.
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