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Global Study Finds Trust and Demographics Key to Patient Acceptance of AI in Healthcare

A multinational study reveals that while most patients support AI in medicine, trust, health status, and tech familiarity significantly shape their views.

Yu Chi Huang
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Yu Chi Huang
Yu Chi Huang
ByYu Chi Huang
Yu Chi is a senior regulatory affairs specialist and medical researcher focusing on medical devices.
Published: June 10, 2025
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As first reported by Inside Precision Medicine, a groundbreaking study involving over 13,800 patients across 43 countries found broad support for the use of AI in healthcare—but also uncovered striking variations in acceptance based on demographics, health status, and technological literacy.

Led by researchers from the Technical University of Munich and published in JAMA Network Open, the survey is the most comprehensive global analysis of patient perspectives on AI in medicine to date. The results underscore the critical need to tailor AI implementation to the unique preferences and concerns of different populations.

Source: mh.tum.de.

The study revealed that women, individuals in poorer health, and those with lower digital literacy were less enthusiastic about AI integration in healthcare. While 57.6% of all participants had a positive view of medical AI, only 55.6% of women and just 29.2% of patients in poor health expressed favorable attitudes—compared to 59.1% of men and 94.7% of those in very good health.

In contrast, those with greater exposure to and understanding of technology demonstrated significantly higher trust levels in AI’s role, especially in areas like diagnosis and risk prediction. Still, fewer than half of respondents expressed full trust in AI-driven treatment guidance.

Notably, over 70% of patients preferred AI systems that offered clear explanations and supported, rather than replaced, physician-led decisions—even if it meant sacrificing some degree of accuracy. Many also voiced concerns around data privacy, decreased personal interaction with doctors, and the potential for rising costs.

These insights emphasize that successful AI adoption in healthcare must be as much about building trust and clarity as it is about innovation and accuracy—making patient-centric design and communication essential in future developments.

SOURCES:TUM School of Medicine and Health
VIA:Inside Precision Medicine
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Yu Chi Huang
ByYu Chi Huang
Yu Chi is a senior regulatory affairs specialist and medical researcher focusing on medical devices.

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