Attitudes of Healthcare Professionals Toward Artificial Intelligence in Clinical Decision-Making: A Cross-Sectional Survey in Iran

Abstract

Artificial intelligence (AI) technologies are increasingly being integrated into clinical settings worldwide. Understanding healthcare professionals’ attitudes toward AI, particularly in the context of clinical decision-making, is critical for successful implementation. However, there is limited empirical evidence in Iran regarding clinicians' trust, readiness, and perceived barriers to AI adoption. This study aimed to assess the attitudes, perceived utility, trust, and concerns of Iranian healthcare professionals toward the use of AI in clinical decision support systems (AI-CDSS). A cross-sectional survey of 300 healthcare professionals was conducted across public and private institutions in Iran. A total of 280 completed surveys were included in the final analysis. The questionnaire included items measuring trust, perceived utility, perceived risk, training exposure, and willingness to use AI tools. Quantitative data were analyzed using descriptive statistics, composite scoring, and regression analysis. Most participants (71.4%) reported moderate or high familiarity with AI, but only 27.1% had prior hands-on experience. While 88.9% agreed that AI improves diagnostic accuracy, 72.5% reported concern over algorithm transparency, and only 21.4% felt adequately prepared to use AI tools. Trust and perceived utility were strong positive predictors of intention to adopt AI-CDSS, whereas perceived risk negatively affected adoption intentions (p < 0.001). Lack of training was the most frequently reported barrier (73.6%). Iranian clinicians show overall positive attitudes toward AI in clinical decision-making but express concerns around training, trust, and transparency. Addressing these gaps is key to facilitating AI integration in healthcare practice.

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