ArticlePatient preference and adherence2026
Attitudes of the Iranian Public Toward the Clinical Use of Artificial Intelligence in Medicine: A Cross-Sectional Survey.
Article in Patient preference and adherence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Purpose: The integration of Artificial Intelligence (AI) into healthcare is a global trend, yet its success hinges on public acceptance. This study aimed to provide one of the first comprehensive assessments of awareness, trust, and preferences regarding the clinical use of medical AI among a sample of Iranian hospital visitors and to identify the key predictors shaping these views to inform national digital health policy. Patients and Methods: A descriptive-analytical, cross-sectional survey was conducted between August 2024 and March 2025 at the Imam Khomeini Hospital Complex in Tehran, Iran. A validated questionnaire was administered to a convenience sample of 388 hospital visitors (inpatients, outpatients, and their companions). Data were analyzed using descriptive statistics and multivariate logistic regression. Results: Of 388 participants, 53.6% (208/388) had heard of medical AI, yet only 2.6% claimed full knowledge. A phenomenon regarding conflicting attitudes, which we term the "trust-preference paradox", was observed: while ~87% expressed conditional trust in AI's diagnostic and therapeutic capabilities, a significant majority preferred human physicians in disagreement scenarios (Diagnosis: 66.2%; Treatment: 66.8%), primarily due to the desire for personalized care. Preference for AI diagnosis was significantly associated with being male (Odds Ratio [OR] 2.06), having a non-medical/computer science occupation (OR 2.64), and prior AI awareness (OR 1.72). The top perceived advantage was accuracy (46.1%), while the main drawback was lack of empathy (60.1%). A collaborative model where AI assists physicians was favored by 70.6%. Conclusion: Participants demonstrated high trust in AI's technical potential but strongly preferred human oversight in high-stakes decisions. Successful AI integration in Iran requires "human-in-the-loop" collaborative models and targeted education to bridge the gap between technical trust and clinical preference.
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