Readiness and Attitudes of Nursing Students Towards ‎ Integrating ‎Artificial Intelligence in Radiation Protection: A Cross-Sectional Study

Abstract

Artificial intelligence (AI) is shifting from promise to routine in healthcare, whereas rigorous radiation-protection practices remain essential. We evaluated how well Libyan nursing undergraduates are prepared for both challenges. A cross-sectional study on 77 students of two different courses of study: Anesthesia and Intensive Care (n=49) and General Nursing (n=28) was undertaken at the Faculty of Nursing, University of Zawia in Libya. A structured questionnaire was employed to find data regarding their demographics and previous training, and also their self-rated knowledge level and attitudes towards AI. These findings showed extensive learning shortfalls. Specifically, 61.0% of the students were not previously trained in AI and 77.9% did not have specialized courses in radiation protection. Moreover, their self-reported knowledge revealed only moderate competency levels in AI (58.4%) and only moderate awareness of radiation dangers (41.6%). Despite this limited formal education, students reported favorable attitudes towards the adoption of AI. For instance, 54.5% were optimistic about its future deployment, while 50.6% were willing to take part in professional development courses. These findings identify a pressing need to formally enhance nursing curricula to bridge gaps in AI literacy and radiation protection, thereby preparing graduates for secure, effective, and technologically facilitated clinical practice. This study's generalizability is limited by its single‑institution setting and relatively small sample size.