Current status and influencing factors of AI literacy among nursing students: A scoping review

With the rapid adoption of artificial intelligence (AI) technologies in the healthcare sector, AI literacy has become one of the core competencies for nursing students. However, the existing evidence regarding the factors influencing AI literacy among nursing students is currently fragmented and lacks systematic synthesis.

To systematically review the factors influencing AI literacy among nursing students, identify research gaps, and provide a reference for nursing education interventions.

This scoping review followed Arksey and O'Malley's methodology framework and the PRISMA-ScR guidelines. We searched six electronic databases (PubMed, CINAHL, Web of Science, Scopus, CNKI, and Wanfang Data), covering the period from the inception of each database to 25 March 2026. Original studies reporting on the influencing factors of AI literacy among nursing students were included. Two researchers independently screened the literature and extracted data, using a thematic synthesis approach to classify and summarise the influencing factors.

A total of 19 studies were included, comprising 11 from China, 5 from Turkey and 3 from the United States; these included 17 quantitative studies and 2 qualitative studies. Nursing students' AI literacy was generally at a moderately high level, but significant individual differences and dimensional imbalances were observed. Nursing students' AI literacy is influenced by multiple factors, which can be summarised into four categories: demographic factors, psychological and cognitive factors, educational and environmental factors, and social and organisational factors.

Understanding these multi-level influencing factors is crucial for enhancing nursing students' AI literacy. The dynamic relationships between these factors should be explored in depth to identify key drivers and formulate more effective management strategies.