Study Reveals Patients with Poorer Health Are Less Trusting of Medical AI
A large international study reveals that patients with poorer health are significantly less likely to trust and accept the use of AI in medical care, highlighting the need for explainability and transparency in AI applications.
Recent research conducted by a team at the Technical University of Munich (TUM) has shed light on patient perceptions of artificial intelligence (AI) in healthcare. The study, encompassing a survey of approximately 14,000 patients across 74 clinics spanning 43 countries and involving various radiology departments, aimed to understand how different health conditions influence attitudes toward AI in medicine.
The key finding indicates that individuals who rate their health as poor are significantly more likely to reject the use of AI in their medical care. Over 57% of participants viewed AI positively; however, acceptance varied notably with health status. Patients in excellent health showed much higher approval rates, while those with severe illnesses displayed markedly negative attitudes, with more than half rating AI as "extremely" or "rather negative." This trend suggests that health status plays a crucial role in shaping trust in AI applications.
Researchers hypothesize that factors such as previous healthcare experiences, psychological burden, and the overall impact of illness might influence these perceptions. Interestingly, the study found that familiarity with technology and self-rated understanding of AI boosted acceptance, with over 83% of highly knowledgeable respondents expressing positive views.
Patients’ preferences highlight a demand for transparency and control in AI deployment. A majority want AI solutions to be "explainable," meaning they should clearly demonstrate how conclusions are reached. Additionally, most respondents see AI as a supportive tool rather than an autonomous decision-maker, emphasizing the importance of physicians making final judgments.
The study also identified that attitudes have shifted rapidly over time, especially with advances in large language models, underscoring the need for ongoing research. The team plans to follow up with further surveys to better align AI development with patient needs.
Overall, the findings underscore that improving patient trust in AI and addressing concerns—especially among those in poorer health—are vital for the successful integration of AI technologies into healthcare systems.
Source: https://medicalxpress.com/news/2025-09-patients-poorer-health-medical-ai.html
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