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Acceptance and trust of general population toward medical artificial intelligence across three MENA countries: A
Mohamed Fakhry Hussein1, Sally Samir Othman2, Ghada Mahmoud Ismail3
1Department of Occupational Health and Industrial Medicine, High Institute of Public Health, Alexandria University, Alexandria 21561, Egypt.
Background:
Artificial intelligence (AI) is increasingly integrated into healthcare, improving diagnostics, treatment, and healthcare management. However, public acceptance and trust are essential for its successful adoption.
Objective:
To assess and compare acceptance and trust toward using AI in healthcare among general population in three selected Arab countries in the Middle East and North Africa (MENA) region and identify their associated factors.
Methods:
A multi-country cross-sectional study was conducted between October 2025 and February 2026 among 1250 adults from Kingdom of Saudi Arabia (KSA), Egypt, and Syria. Data were collected using online and face-to-face questionnaires assessing sociodemographic characteristics, acceptance of AI use in healthcare, and trust in its medical application. Acceptance and trust scores were rescaled to a 0-100 range. Unadjusted comparisons were performed using Mann-Whitney U and Kruskal-Wallis tests, while multiple linear regression models were used to identify factors independently associated with acceptance and trust.
Results:
Participants had a median age of 23.0 years (interquartile range (IQR): 8.0)), 61.0% were women. Most participants were aware of AI applications in medicine (96.2%), and 87.7% had previously used AI in a medical context. Egypt and KSA had significantly higher acceptance (β = 14.6, 95% CI: 11.8-17.3 and β = 2.8, 95% CI: 0.3-5.2, respectively) and trust scores (β = 18.7, 95% CI: 15.7-21.7 and β = 3.1, 95% CI: 0.4-5.7 repectively) than Syria (p < 0.05). Prior use of AI in healthcare was independently associated with both greater acceptance (β = 9.7, 95% CI: 6.9-12.6), and trust (β = 3.4, 95% CI: 0.3-6.5), while AI awareness was independently associated with acceptance (β = 7.5, 95% CI: 2.7-12.3). Acceptance was higher among males (β = 2.5, 95% CI: 0.6-4.4), and those reporting sufficient income with or without savings (β = 2.4, 95% CI: 0.04-4.7 and 3.9,95% CI: 1.1-6.8 respectively). Trust was higher among married participants (β = 3.2, 95% CI: 0.2-6.3), housewives (β = 4.7, 95% CI: 1.2-8.3), skilled craftsmen (β = 6.4, 95% CI: 1.6-11.2).
Conclusion:
Public acceptance and trust toward AI use in healthcare were generally favorable but varied substantially across the three studied Arab MENA countries. Enhancing AI literacy may improve public acceptance and trust of medical AI.
