Knowledge, attitudes, and practices toward artificial intelligence among health sciences students: A cross-sectional study in Palestine - Nesreen Alqaissi; Mohammad Qtait; Khalaf Awwad; Zeenat Mesk; Fuad Farajalla; Yasmeen Ziad; Farah Abu-Salameh; Amani Hmedat; Rawan Halayka; Maysam Ajlouni; Yasmeen Shareef (PLoS ONE, 2026)
Background Artificial intelligence (AI) is increasingly integrated into healthcare education and clinical practice. Understanding health sciences students’ knowledge, attitudes, and practices (KAP) toward AI is important for informing curriculum development, particularly in resource-limited educational settings. Objective To assess knowledge, attitudes, and practices toward artificial intelligence among health sciences students at a Palestinian university. Methods A cross-sectional study was conducted during the 2024–2025 academic year among 666 undergraduate students from nursing, medicine and health sciences, and dentistry programs. Data were collected using a structured questionnaire assessing AI knowledge (7 items), attitudes (10 items), and practices (7 items). Descriptive statistics were calculated. Independent-samples t-tests and one-way analysis of variance (ANOVA) were used to examine group differences. Effect sizes were reported using Cohen’s d and eta squared (η²). Statistical significance was set at p < 0.05. Results The overall AI knowledge accuracy rate was 42.9% (mean 3.00 ± 1.61), indicating limited foundational understanding, particularly regarding machine learning and deep learning concepts. Attitudes toward AI were generally positive (mean 3.60 ± 0.44), with high endorsement of ethical awareness. AI practice levels were moderate (mean 3.32 ± 0.70), with frequent use for assignments and research activities. Formal AI training was associated with higher knowledge scores (t(664)=7.45, p < 0.001, d = 0.69) and slightly more positive attitudes (t(664)=2.59, p = 0.010, d = 0.23), but not with practice frequency (p = 0.807). Differences across colleges and academic years demonstrated small effect sizes (η² ≤ 0.03). Conclusion Health sciences students demonstrated positive attitudes and regular academic use of AI tools despite limited foundational knowledge. These findings suggest the potential benefit of structured AI literacy integration within health sciences curricula.