Evaluation of Health Science Students’ Knowledge, Attitudes, and Practices Toward Artificial Intelligence in Northern Saudi Arabia: Implications for Curriculum Refinement and Healthcare Delivery - ALruwail BF; Alshalan AM; Thirunavukkarasu A; Alibrahim A; Alenezi AM; Aldhuwayhi TZA (Journal of Multidisciplinary Healthcare)
Bashayer Farhan ALruwail,1 Afrah Muteb Alshalan,2 Ashokkumar Thirunavukkarasu,1 Alaa Alibrahim,3 Anfal Mohammed Alenezi,4 Tahalil Zamil A Aldhuwayhi5 1Department of Family and Community Medicine, College of Medicine, Jouf University, Sakaka, Aljouf, Saudi Arabia; 2Department of Otolaryngology-Head and Neck Surgery, College of Medicine, Jouf University, Sakaka, Aljouf, Saudi Arabia; 3Department of Internal Medicine, College of Medicine, Jouf University, Sakaka, Aljouf, Saudi Arabia; 4Department of Surgery, College of Medicine, Jouf University, Sakaka, Aljouf, Saudi Arabia; 5Medical Intern, College of Medicine, Jouf University, Sakaka, Aljouf, Saudi ArabiaCorrespondence: Bashayer Farhan ALruwail, Department of Family and Community Medicine, College of Medicine Jouf University, Sakaka, 72388, Saudi Arabia, Tel +966551913665, Email bfalrwili@ju.edu.saBackground and Aim: As the integration of artificial intelligence (AI) in healthcare delivery becomes increasingly prevalent, understanding the knowledge, attitudes, and practices of health science students towards AI is crucial. However, limited evidence exists regarding the readiness of health science students, particularly in northern Saudi Arabia (KSA), to integrate AI into their future practices, highlighting the need for focused evaluation. We evaluated northern Saudi health science students’ knowledge, attitude, practice, and associated factors toward AI.Participants and Methods: The present cross-sectional study was conducted among 384 health science students aged 18 years and above from Jouf University, KSA. The study employed a validated data collection form with four sections: demographics, knowledge (AI principles and applications), attitudes (perceptions and ethical concerns), and practices (usage and confidence in AI tools). The three domains’ scores were categorized as low (< 60%), medium (60– 80%) and high (> 80%) based on their total scores. We utilized Spearman correlation test to ascertain the strength and direction of correlation among each subscale. Additionally, multivariate analysis was employed to identify associated factors.Results: The present study demonstrated low knowledge, attitude, and practices among 55.7%, 37.0%, and 50.3% of health science students. We observed a positive correlation between knowledge and attitude (rho = 0.451, p = 0.001), knowledge and practice (rho = 0.353, p = 0.001), and attitude and practice (rho = 0.651, p = 0.001). Knowledge (p = 0.001) and practice (p = 0.002) were significantly higher among the students who participated in a formal AI training program. Females had a significantly higher level of attitude (p = 0.001) and practice (p = 0.030) than males.Conclusion: In light of these findings, refining the curriculum to incorporate AI emerges as a critical strategy for addressing gaps in AI knowledge, attitudes, and practices among health science students. Therefore, formal and integrated training programs tailored to suit the local setting can effectively prepare health science students to adopt AI technologies in ways that enhance patient care.Keywords: artificial intelligence, Vision 2030, curriculum refinement, AI training program, nursing, AI readiness