Knowledge, attitudes, and practices toward artificial intelligence among health sciences students: A cross-sectional study in Palestine

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.

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PLoS ONE
Published
2026-06-26
DOI
https://doi.org/10.1371/journal.pone.0352785
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00

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article

Knowledge, attitudes, and practices toward artificial intelligence among health sciences students: A cross-sectional study in Palestine

Mohammad Qtait, Fuad Farajalla, Khalaf Awwad, Maysam Ajlouni et al.
PLoS ONE
Artificial Intelligence in Healthcare and Education
article

Knowledge, attitudes, and practices toward artificial intelligence among health sciences students: A cross-sectional study in Palestine

Mohammad Qtait, Fuad Farajalla, Khalaf Awwad, Maysam Ajlouni, Farah Abu-Salameh, Rawan Halayka, Nesreen Alqaissi, Amani Hmedat, Zeenat Mesk, Yasmeen Ziad, Yasmeen Shareef
article en

Abstract

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.

PLoS ONEVol. 21(6)
Palestine Polytechnic University (PS)
Palestine Polytechnic University
Quality Education
Openalex Percentile: Top 10%
Artificial Intelligence in Healthcare and Education
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