Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients.
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Busch Felix, Hoffmann Lena, Xu Lina, Zhang Long Jiang, Hu Bin, García-Juárez Ignacio, Toapanta-Yanchapaxi Liz N, Gorelik Natalia, Gorelik Valérie, Rodriguez-Granillo Gaston A, Ferrarotti Carlos, Cuong Nguyen N, Thi Chau A P, Tuncel Murat, Kaya Gürsan, Solis-Barquero Sergio M, Mendez Avila Maria C, Ivanova Nevena G, Kitamura Felipe C, Hayama Karina Y I, Puntunet Bates Monserrat L, Torres Pedro Iturralde, Ortiz-Prado Esteban, Izquierdo-Condoy Juan S, Schwarz Gilbert M, Hofstaetter Jochen G, Hide Michihiro, Takeda Konagi, Peric Barbara, Pilko Gašper, Thulesius Hans O, Lindow Thomas, Kolawole Israel K, Olatoke Samuel Adegboyega, Grzybowski Andrzej, Corlateanu Alexandru, Iaconi Oana-Simina, Li Ting, Domitrz Izabela, Kepczynska Katarzyna, Mihalcin Matúš, Fašaneková Lenka, Zatonski Tomasz, Fulek Katarzyna, Molnár András, Maihoub Stefani, da Silva Gama Zenewton A, Saba Luca, Sountoulides Petros, Makowski Marcus R, Aerts Hugo J W L, Adams Lisa C, Bressem Keno K, COMFORT consortium, Navarro Álvaro Aceña, Águas Catarina, Aineseder Martina, Alomar Muaed, Al Sliman Rashid, Anand Gautam, Angkurawaranon Salita, Aoki Shuhei, Arkoh Samuel, Ashraf Gizem, Astri Yesi, Bakhshi Sameer, Bayramov Nuru Y, Billis Antonis, Bitencourt Almir G V, Bolejko Anetta, Bollas Becerra Antonio J, Bwambale Joe, Capela Andreia, Cau Riccardo, Chacon-Acevedo Kelly R, Chaunzwa Tafadzwa L, Chojniak Rubens, Clements Warren, Cuocolo Renato, Dahlblom Victor, Sousa Kelienny de Meneses, Villarrubia Jorge Esteban, Desai Vijay B, Dhakal Ajaya K, Dignum Virginia, Andrade Rubens G Feijo, Ferraioli Giovanna, Ganguly Shuvadeep, Garg Harshit, Savevska Cvetanka Gjerakaroska, Radovikj Marija Gjerakaroska, Gkartzoni Anastasia, Gorospe Luis, Griffin Ian, Hadamitzky Martin, Ndahiro Martin Hakorimana, Hering Alessa, Hochhegger Bruno, Huseynova Mehriban R, Ishida Fujimaro, Jha Nisha, Jiang Lili, Kader Rawen, Kavnoudias Helen, Klein Clément, Kolostoumpis George, Koshy Abraham, Kruger Nicholas A, Löser Alexander, Lucijanic Marko, Mantziari Despoina, Margue Gaelle, McFadden Sonyia, Miyake Masahiro, Morakote Wipawee, Ngabonziza Issa, Nguyen Thao T, Niehues Stefan M, Nortje Marc, Palaian Subish, Pentara Natalia V, de Almeida Rui P Pereira, Poma Gianluigi, Purwoko Mitayani, Pyrgidis Nikolaos, Rafailidis Vasileios, Rainey Clare, Ribeiro João C, Agudelo Nicolás Rozo, Sado Keina, Saidman Julia M, Saturno-Hernandez Pedro J, Suryadevara Vidyani, Schulz Gerald B, Soric Ena, Soto-Pérez-Olivares Javier, Stanzione Arnaldo, Struck Julian Peter, Takaoka Hiroyuki, Tanioka Satoru, Huyen Tran T M, Truhn Daniel, van Dijk Elon H C, van Wijngaarden Peter, Wang Yuan-Cheng, Weidlich Matthias, Zhang Shuhang
Аннотация
OBJECTIVES: 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.
RESULTS: In total, 13 806 patients participated, including 8951 (64.8%) in the Global North and 4855 (35.2%) in the Global South. Their median (IQR) age was 48 (34-62) years, and 6973 (50.5%) were male. The survey results indicated a predominantly favorable general view of AI in health care, with 57.6% of respondents (7775 of 13 502) expressing a positive attitude. However, attitudes exhibited notable variation based on demographic characteristics, health status, and technological literacy. Female respondents (3511 of 6318 [55.6%]) exhibited fewer positive attitudes toward AI use in medicine than male respondents (4057 of 6864 [59.1%]), and participants with poorer health status exhibited fewer positive attitudes toward AI use in medicine (eg, 58 of 199 [29.2%] with rather negative views) than patients with very good health (eg, 134 of 2538 [5.3%] with rather negative views). Conversely, higher levels of AI knowledge and frequent use of technology devices were associated with more positive attitudes. Notably, fewer than half of the participants expressed positive attitudes regarding all items pertaining to trust in AI. The lowest level of trust was observed for the accuracy of AI in providing information regarding treatment responses (5637 of 13 480 respondents [41.8%] trusted AI). Patients preferred explainable AI (8816 of 12 563 [70.2%]) and physician-led decision-making (9222 of 12 652 [72.9%]), even if it meant slightly compromised accuracy.
CONCLUSIONS AND RELEVANCE: In this cross-sectional study of patient attitudes toward AI use in health care across 6 continents, findings indicated that tailored AI implementation strategies should take patient demographics, health status, and preferences for explainable AI and physician oversight into account.