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Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients

Busch, Felix ; Hoffmann, Lena ; Xu, Lina ; Zhang, Long Jiang ; Hu, Bin ; García-Juárez, Ignacio ; Toapanta-Yanchapaxi, Liz N ; Gorelik, Natalia ; Gorelik, Valérie and Rodriguez-Granillo, Gaston A , et al. (2025) In JAMA Network Open 8(6). p.1-23
Abstract

IMPORTANCE: 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.

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... (More)

IMPORTANCE: 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.

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.

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keywords
Humans, Male, Female, Cross-Sectional Studies, Middle Aged, Artificial Intelligence, Adult, Surveys and Questionnaires, Trust, Aged, Delivery of Health Care, Hospitals, Internationality
in
JAMA Network Open
volume
8
issue
6
article number
e2514452
pages
1 - 23
publisher
American Medical Association
external identifiers
  • pmid:40493367
  • scopus:105008143370
ISSN
2574-3805
DOI
10.1001/jamanetworkopen.2025.14452
language
English
LU publication?
yes
id
2b5df5f2-3ede-4fb3-a2b7-a618abf0eb41
date added to LUP
2025-06-12 09:07:57
date last changed
2025-07-17 04:01:32
@article{2b5df5f2-3ede-4fb3-a2b7-a618abf0eb41,
  abstract     = {{<p>IMPORTANCE: 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.</p><p>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.</p><p>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.</p><p>EXPOSURE: Information sheets and paper surveys handed out by hospital staff and posted in conspicuous hospital locations.</p><p>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.</p><p>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.</p><p>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.</p>}},
  author       = {{Busch, Felix and Hoffmann, Lena and Xu, Lina and Zhang, Long Jiang and Hu, Bin and García-Juárez, Ignacio and Toapanta-Yanchapaxi, Liz N and Gorelik, Natalia and Gorelik, Valérie and Rodriguez-Granillo, Gaston A and Ferrarotti, Carlos and Cuong, Nguyen N and Thi, Chau A P and Tuncel, Murat and Kaya, Gürsan and Solis-Barquero, Sergio M and Mendez Avila, Maria C and Ivanova, Nevena G and Kitamura, Felipe C and Hayama, Karina Y I and Puntunet Bates, Monserrat L and Torres, Pedro Iturralde and Ortiz-Prado, Esteban and Izquierdo-Condoy, Juan S and Schwarz, Gilbert M and Hofstaetter, Jochen G and Hide, Michihiro and Takeda, Konagi and Peric, Barbara and Pilko, Gašper and Thulesius, Hans O and Lindow, Thomas and Kolawole, Israel K and Olatoke, Samuel Adegboyega and Grzybowski, Andrzej and Corlateanu, Alexandru and Iaconi, Oana-Simina and Li, Ting and Domitrz, Izabela and Kepczynska, Katarzyna and Mihalcin, Matúš and Fašaneková, Lenka and Zatonski, Tomasz and Fulek, Katarzyna and Molnár, András and Maihoub, Stefani and da Silva Gama, Zenewton A and Saba, Luca and Sountoulides, Petros and Makowski, Marcus R and Aerts, Hugo J W L and Adams, Lisa C and Bressem, Keno K and Aceña Navarro, Álvaro and Dahlblom, Victor and Bolejko, Anetta and Zhang, Shuhang}},
  issn         = {{2574-3805}},
  keywords     = {{Humans; Male; Female; Cross-Sectional Studies; Middle Aged; Artificial Intelligence; Adult; Surveys and Questionnaires; Trust; Aged; Delivery of Health Care; Hospitals; Internationality}},
  language     = {{eng}},
  month        = {{06}},
  number       = {{6}},
  pages        = {{1--23}},
  publisher    = {{American Medical Association}},
  series       = {{JAMA Network Open}},
  title        = {{Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients}},
  url          = {{http://dx.doi.org/10.1001/jamanetworkopen.2025.14452}},
  doi          = {{10.1001/jamanetworkopen.2025.14452}},
  volume       = {{8}},
  year         = {{2025}},
}