Anonymized data Survey Study Claudia M. Witt, Jiahui An, Markus Christen: Who wants to use AI and a "digital twin" for health? – Evidence on the influence of healthcare utilization behaviour from a representative Swiss population survey

Background: The increasing development of artificial intelligence (AI) and digital twin technologies in healthcare raises important questions about their future ac-ceptance. Investigating how healthcare utilization behaviour influences openness to such future digital innovations can support the design of health systems that align with user preferences and expectations.Methods: A nationally representative online survey of 1,486 adults in Switzerland was conducted in 2023. Participants were categorized into five groups based on their healthcare utilization behaviour: conventional medicine users, complemen-tary medicine users, integrative medicine users, self-treatment users, and phar-macy users. The survey assessed digital literacy, current use of digital tools, and attitudes toward AI and digital twins. Digital twin understanding was ensured through an explanatory video and comprehension checks. Weighted analyses and regression models were used to evaluate differences between groups. (no health care intervention on human participants; no requirement for trial registration or ethics approval).Results: Across all healthcare utilization behaviour groups, the majority of partic-ipants reported a willingness to use digital twin services, with significantly higher agreement among self-treatment users. This group also demonstrated the high-est digital literacy, most frequent use of health-related apps, and strongest famil-iarity with AI tools such as ChatGPT. They rated the potential benefits of digital twins more highly and expressed greater trust in both public and private institu-tions offering these services. Complementary and integrative medicine users re-ported lower digital literacy and were less likely to consider digital twins benefi-cial across domains such as cost reduction, therapy validation, and disease pre-diction. Conventional medicine users expressed specific concerns about digital twins replacing physicians, rated predictive features less favourably, and showed the lowest support for independent personal use of digital twins. Pharmacy us-ers showed moderate willingness, with relatively high trust in institutions and greater appreciation for the coordination and predictive functions of digital twins.Conclusion: This study demonstrates that attitudes toward AI-based health tech-nologies are closely tied to existing patterns of healthcare usage. While digital twins are generally well received, differences in acceptance highlight the need to tailor implementation strategies to specific user profiles.