Determinants of Physicians' Adoption of AI in the Diagnosis and Treatment of Dermatological and Aesthetic Diseases: A Theoretical Analytical Study in Light of the UTAUT Model

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Abstract

This study aimed to analyze the factors influencing physicians' adoption of artificial intelligence in the diagnosis and treatment of dermatological diseases and aesthetic medicine applications, through reviewing and analyzing relevant scientific literature and organizing it within the framework of the Unified Theory of Acceptance and Use of Technology (UTAUT). The study adopted the descriptive-analytical approach of a theoretical nature, analyzing the conceptual foundations of medical adoption, the role of performance expectancy and effort expectancy, social influence and facilitating conditions, in addition to complementary factors specific to medical AI, such as trust, explainability, privacy, and professional responsibility. The study concluded with an integrated theoretical framework suggesting that physicians' adoption of AI is not determined solely by the technical capabilities of the system, but is shaped through the interaction of four main determinants (performance expectancy, effort expectancy, social influence, facilitating conditions), with the influence of complementary factors that acquire particular significance in the medical field. The implications of this framework for the Jordanian context were discussed, indicating growing interest in the potential of AI within the Jordanian health sector, along with a continued need for training, infrastructure, and institutional and regulatory frameworks. The study recommended conducting future field studies to test the proposed framework among dermatologists and aesthetic medicine physicians in Jordan.

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