AUTHOR=Zhao Yuanyuan , Yuan You , Wen Zhuosi , Leng Lanlan , Shi Lei , Hu Xinyang , Wei Xiaoman , Zuo Meng , Mou Jianghong , Luo Qian , Chen Mei , Hu Rujun , Gao Huiming 

TITLE=The current status, knowledge, attitudes, and challenges of generative artificial intelligence use among undergraduate nursing students: a single-center cross-sectional survey of western China

JOURNAL=Frontiers in Public Health

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2025.1648416

DOI=10.3389/fpubh.2025.1648416

ISSN=2296-2565

ABSTRACT=BackgroundGenerative artificial intelligence (Gen AI) is rapidly permeating the fields of education and healthcare, with increasing impact on nursing education. Understanding nursing students’ acceptance of Gen AI and the challenges they face is essential for optimizing future curriculum design.ObjectiveThis study aimed to assess the current usage, knowledge level, attitudes, and perceived challenges of Gen AI among undergraduate nursing students in western China, to inform the effective integration of AI into nursing education.MethodsA single-center, cross-sectional study was conducted using a structured, validated questionnaire that covered five domains: demographics, AI tool usage, knowledge, attitude, and challenges. Participants were undergraduate nursing students from Zunyi Medical University. Data were collected via an online platform from May to June 2025 and analyzed using SPSS 29.0 for descriptive and inferential statistics based on demographic subgroups.ResultsA total of 534 valid responses were analyzed. Females accounted for 80.15%, with a mean age of 20.88 years. Grade distribution: sophomore (30.71%), freshman (22.47%), senior (24.53%), and junior (22.28%); 64.79% of students were from urban backgrounds. About 57.86% reported frequent or consistent use of Gen AI tools, mainly via smartphones (94.76%). Most students used 2–3 tools (70.41%), with DeepSeek (72.10%) and Doubao (69.85%) being the most popular. Primary uses included problem-solving (84.46%), course support (66.29%), and academic writing (51.87%). Daily multiple usage was reported by 25.47, and 87.45% used AI for less than 30 min per session. Primary information sources were social media (78.09%) and peer recommendations (71.35%). Median scores: knowledge 3.43 (IQR 2.86–3.86), attitude 3.58 (IQR 3.33–3.83), challenges 3.50 (IQR 3.17–3.92). Only 38.01% received AI-related training; 83.33% found it challenging to ask probing or insightful questions when using Gen AI. Students demonstrated moderate knowledge and positive attitudes, but faced notable concerns, particularly regarding data privacy, tool reliability, and the impact on critical thinking skills.ConclusionUndergraduate nursing students in western China exhibit a generally positive yet cautious attitude toward Gen AI. Targeted educational interventions are recommended to address their concerns and enhance the benefits of AI in nursing education. Future research should focus on the development of AI literacy and the long-term implications of integrating AI into clinical nursing practice.