Knowledge, attitudes, practices and ethics related to artificial intelligence among nursing students: a national cross-sectional survey in China.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare. Current and future healthcare workforce, including nursing students, require sufficient understanding of responsible AI use. However, data about knowledge, attitudes, practices and ethics regarding AI use in this population is scarce. This national study comprehensively assessed AI-related knowledge, attitudes, practices and ethics among nursing students in China, including the socio-demographic and educational factors associated with these professional domains. METHODS: A cross-sectional survey was conducted between June and August 2025 across 32 provinces, autonomous regions and municipalities in China. A total of 10,268 nursing undergraduates and vocational college students completed a newly developed 22-item Knowledge, Attitudes, Practices and Ethics questionnaire covering four domains (Cronbach's α = 0.79-0.96). Univariable analyses and multiple linear regression were used to examine socio-demographic factors of AI-related knowledge, attitudes, practices and ethics. RESULTS: Nursing students reported moderate level of AI knowledge (18.17 ± 4.90, total score 24), moderately positive attitudes (11.96 ± 2.49, total score 20), relatively good ethical awareness (11.60 ± 3.27, total score 16), but only limited engagement in practice (8.29 ± 5.04, total score 28). Of the participants, only 6.8%-9.6% reported "often" and "always" using AI tools for academic and personal tasks. In multivariable models, male gender, urban residence, higher economic status, and intention to pursue nursing as a career were independently associated with higher scores across the knowledge, attitude, and ethics domains (all P < 0.05). Compared with vocational college students, undergraduates had significantly higher scores on attitude, practice and ethics domains (all P < 0.05). Age was positively associated with all domains, although only the 19-20-year group had significantly higher scores in the practice domain (P < 0.001). CONCLUSION: The findings highlight the need for a supportive educational environment with guidance to enable nursing students to use artificial intelligence appropriately and responsibly when needed, particularly among vocational college students and those from socioeconomically disadvantaged backgrounds. Integrating AI competencies into nursing education and linking them to future career development and clinical practice may help bridge the gap between positive attitudes and limited practical use.