Examining physicians acceptance of artificial intelligence technologies through the Theory of Planned Behavior, Technology Acceptance Model and trust framework

This study aims to determine the acceptance levels, perceptions, understanding, and readiness of physicians towards the use of artificial intelligence in healthcare, which has the potential to lead to an evolutionary transformation in the healthcare sector and has been one of the significant discussion topics in recent years. The study aims to provide a resource for institutions and organizations providing healthcare services in their strategy determination, raise awareness for technology entrepreneurs, and contribute to future research and literature. This study uses a quantitative method approach to develop and test a model based on the theory of planned behavior, technology acceptance model, and trust integration. The data were collected through an online survey from physicians serving in public and private hospitals in our country. A total of 414 physicians participated in the survey. Structural Equation Modeling (SEM) and the SmartPLS v.3.1.5 software program were used in the analysis process of the obtained data. The study results revealed that the theory of planned behavior, technology acceptance model, and trust have a significant impact on physicians' intentions to use artificial intelligence technologies. According to the study results, it was found that attitude, perceived benefit, perceived ease of use, and trust have a significant effect on the intention to use, while perceived behavioral control and subjective norm do not have a significant effect. Additionally, trust was found to mediate the relationship between subjective norm, perceived benefit, perceived ease of use, and behavioral intention; however, it was not found to have a mediating role in the relationship between perceived behavioral control and attitude with behavioral intention. In conclusion, this study highlights the variables affecting the acceptance of AI-supported technologies by physicians and provides valuable information on the potential benefits of integrating AI technologies into the system. The model developed by integrating the theory of planned behavior, technology acceptance model, and trust provides a framework for future research in this field and guides the development of more user-friendly AI technologies. Additionally, it contributes to the literature by offering a simple, applicable, and valid tool for measuring and improving the acceptance of AI technologies in the healthcare system.