Knowledge, attitudes, practices, and barriers toward artificial intelligence integration among nursing and health sciences students: A cross-sectional study.

Objectives: Artificial intelligence (AI) is increasingly transforming healthcare delivery and health professions education, creating a need for future healthcare professionals to develop adequate knowledge, practical skills, and ethical awareness. However, many students remain exposed to AI tools without receiving structured academic preparation. This study aimed to assess knowledge, attitudes, practices, and perceived barriers toward AI among nursing and health sciences students. Methods: A descriptive cross-sectional study was conducted among 242 undergraduate students at a public university in Palestine between January and February 2025. Data were collected using a structured self-administered questionnaire adapted from previous literature and refined through expert review and pilot testing. The survey assessed sociodemographic characteristics, AI-related knowledge and exposure, attitudes, practices, and perceived barriers. Descriptive statistics were used to summarize the data, while Mann-Whitney U and Kruskal-Wallis tests examined subgroup differences. Results: Participants had a mean age of 20.4 ± 2.28 years, and 77.3% were female. Most students reported using AI tools (83.1%), whereas only 31.0% had received formal AI training. Overall knowledge/exposure scores were moderate (2.78 ± 1.12), attitudes were generally positive (3.64 ± 0.61), and practice levels were moderate (3.18 ± 0.72). No significant differences in knowledge or practice scores were observed across demographic variables (p > .05). Students with formal AI training demonstrated significantly higher attitude scores (p = .019). The most frequently reported barriers were ethical and privacy concerns (44.2%), limited curriculum integration (42.6%), and lack of knowledge or expertise (38.4%). Conclusions: Students demonstrated substantial exposure to AI technologies but limited structured preparedness for their effective and ethical use. Positive attitudes toward AI suggest readiness for educational adoption; however, moderate knowledge and practice levels indicate the need for formal curriculum integration, faculty development, and competency-based training. Addressing ethical concerns and institutional barriers is essential to support responsible AI implementation in nursing and health sciences education.