EUEF study examines confidence in AI-supported medical decisions
This study proposes a theoretical framework for understanding and measuring that trust .
22 September 2025
The use of Artificial Intelligence (AI) in healthcare is growing rapidly, and its implementation is expected to continue to increase in the coming years. However, mistrust of these systems continues to be a barrier to their widespread adoption .
In this context, Ramón Ortega, professor at the San Juan de Dios-Comillas University School of Nursing and Physiotherapy (EUEF), together with professors Marcos Alonso (Complutense University of Madrid) and Aníbal M. Astobiza (University of Granada) have developed the study "AI-mediated healthcare and trust. A construction framework and trust factor for empirical research", published in the journal "Artificial Intelligence Review".
This study analyses how trust in AI remains a barrier to its adoption in the healthcare sector, despite its benefits in diagnosis, treatment and clinical management .
Study development
To assess this confidence in AI, the authors reviewed the existing literature toidentify the theoretical underpinnings of AI. In addition, they have identified the factors that they consider essential to understand how trust works in healthcare contexts in which AI is involved. Finally, they have presented a model of trust factorsthat can serve as a basis for future research and practical use.
As a methodological tool, the authors have proposed the use of clinical vignettes that simulate real-life scenarios to measure the trust of patients and professionals in AI-assisted medical decisions, without compromising patients' rights and well-being. They highlight seven impact factors: function of the AI, type of outcome, type of pathology, type of treatment, health professional's disposition, format of AI presentation and the context of use .
The article finds that building strong trust in healthcareAIrequires an understanding of its interaction with human, technological and environmental factors. This approach can serve as a basis for future empirical research and the development of new healthcare technologies.
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