Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients
TUM Klinikum · Technical University of Munich · +111 more institutions
Abstract
The successful implementation of artificial intelligence (AI) in health care depends on its acceptance by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes.
To survey hospital patients to investigate their trust, concerns, and preferences toward the use of AI in health care and diagnostics and to assess the sociodemographic factors associated with patient attitudes. Design, Setting, and Participants: This cross-sectional study developed and implemented an anonymous quantitative survey between February 1 and November 1, 2023, using a nonprobability sample at 74 hospitals in 43 countries. Participants included hospital patients 18 years of age or older who agreed with voluntary participation in the survey presented in 1 of 26 languages. Exposure: Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations. Main Outcomes and Measures: The primary outcome was participant responses to a 26-item instrument containing a general data section (8 items) and 3 dimensions (trust in AI, AI and diagnosis, preferences and concerns toward AI) with 6 items each. Subgroup analyses used cumulative link mixed and binary mixed-effects models.
Citation impact
- FWCI
- 22.63
- Percentile
- 100%
- References
- 36
Authors
146- FBFelix BuschCorresponding
TUM Klinikum, Technical University of Munich
- LHLena Hoffmann
Humboldt-Universität zu Berlin, Freie Universität Berlin, Charité - Universitätsmedizin Berlin
- LXLina Xu
Humboldt-Universität zu Berlin, Freie Universität Berlin, Charité - Universitätsmedizin Berlin
- LJLong Jiang Zhang
Nanjing General Hospital of Nanjing Military Command, Nanjing University
- BHBin Hu
Nanjing General Hospital of Nanjing Military Command, Nanjing University
Topics & keywords
- Multinational corporation
- Health care
- Family medicine
- Psychology
- Medicine
- Political science
- Law