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Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients
F. Busch, L. Hoffmann, L. Xu, LJ. Zhang, B. Hu, I. García-Juárez, LN. Toapanta-Yanchapaxi, N. Gorelik, V. Gorelik, GA. Rodriguez-Granillo, C. Ferrarotti, NN. Cuong, CAP. Thi, M. Tuncel, G. Kaya, SM. Solis-Barquero, MC. Mendez Avila, NG. Ivanova,...
Language English Country United States
Document type Journal Article
NLK
Directory of Open Access Journals
from 2018
ProQuest Central
from 2018-01-01
Health & Medicine (ProQuest)
from 2018-01-01
ROAD: Directory of Open Access Scholarly Resources
from 2018
- MeSH
- Adult MeSH
- Trust MeSH
- Internationality MeSH
- Middle Aged MeSH
- Humans MeSH
- Hospitals MeSH
- Delivery of Health Care * MeSH
- Cross-Sectional Studies MeSH
- Surveys and Questionnaires MeSH
- Aged MeSH
- Artificial Intelligence * MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
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.
2nd Department Orthopaedic Hospital Vienna Speising Vienna Austria
Associação de Investigação de Cuidados de Suporte em Oncologia Vila Nova de Gaia Portugal
AXA Chair in Healthcare Quality CIEE National Institute of Public Health Cuernavaca Mexico
Berlin University of Applied Sciences and Technology Berlin Germany
Centre for Eye Research Australia Royal Victorian Eye and Ear Hospital Melbourne Victoria Australia
Clinical Pharmacology and Therapeutics KIST Medical College and Teaching Hospital Kathmandu Nepal
Comprehensive Health Research Center University of Évora Évora Portugal
Dawson College Montreal Quebec Canada
Department of 1 Surgical Diseases Azerbaijan Medical University Baku Azerbaijan
Department of Advanced Biomedical Sciences University of Naples Federico 2 Naples Italy
Department of Anesthesia University of Ilorin Teaching Hospital Ilorin Nigeria
Department of Cardiology Chiba University Hospital Chiba Japan
Department of Cardiology Hospital Universitario Fundación Jiménez Díaz Madrid Spain
Department of Cardiovascular Medicine Chiba University Graduate School of Medicine Chiba Japan
Department of Clinical Physiology Clinical Sciences Lund University Lund Sweden
Department of Clinical Physiology Research and Development Växjö Central Hospital Växjö Sweden
Department of Clinical Sciences College of Dentistry Ajman University Ajman United Arab Emirates
Department of Clinical Surgical Diagnostic and Pediatric Sciences University of Pavia Pavia Italy
Department of Collective Health Federal University of Rio Grande do Norte Natal Brazil
Department of Computing Science Umeå University Umeå Sweden
Department of Dermatology Hiroshima Citizens Hospital Hiroshima Japan
Department of Diagnostic and Imaging Services Fondazione IRCCS Policlinico S Matteo Pavia Italy
Department of Diagnostic and Interventional Radiology University Hospital Aachen Aachen Germany
Department of Gastroenterology Lakeshore Hospital Kochi India
Department of General Medicine Medical University of Plovdiv Plovdiv Bulgaria
Department of Hematology Clinical Hospital Dubrava Zagreb Croatia
Department of Imaging A C Camargo Cancer Center São Paulo Brazil
Department of Infectious Diseases Faculty of Medicine Masaryk University Brno Czech Republic
Department of Infectious Diseases University Hospital Brno Brno Czech Republic
Department of Internal Medicine School of Medicine University of Zagreb Zagreb Croatia
Department of Medical Imaging and Physiology Skåne University Hospital Malmö Sweden
Department of Medical Oncology Hospital Universitario 12 de Octubre Madrid Spain
Department of Medicine and Optometry Linnaeus University Kalmar Sweden
Department of Medicine Surgery and Dentistry University of Salerno Baronissi Italy
Department of Medicine Universidad Autónoma de Madrid Madrid Spain
Department of Neurology Bielanski Hospital Warsaw Poland
Department of Neurology Faculty of Medicine and Dentistry Medical University of Warsaw Warsaw Poland
Department of Neurology Faculty of Medicine Universitas Muhammadiyah Palembang Palembang Indonesia
Department of Neuroscience Monash University Central Clinical School Melbourne Victoria Australia
Department of Neurosurgery Mie Chuo Medical Center Tsu Japan
Department of Neurosurgery Mie University Graduate School of Medicine Tsu Japan
Department of Nuclear Medicine Faculty of Medicine Hacettepe University Ankara Turkey
Department of Oncosurgery Max Institute of Cancer Care Vaishali Delhi India
Department of Ophthalmology Alrijne Hospital Leiderdorp the Netherlands
Department of Ophthalmology Leiden University Medical Center Leiden the Netherlands
Department of Orthopaedics and Trauma Surgery Medical University of Vienna Vienna Austria
Department of Otolaryngology Coimbra University and Medical School Coimbra Portugal
Department of Otolaryngology Head and Neck Surgery Wroclaw Medical University Wroclaw Poland
Department of Otorhinolaryngology Head and Neck Surgery Semmelweis University Budapest Hungary
Department of Pediatrics KIST Medical College and Teaching Hospital Kathmandu Nepal
Department of Radiology Alfred Health Melbourne Victoria Australia
Department of Radiology Algarve University Hospital Center Faro Portugal
Department of Radiology Faculty of Medicine Chiang Mai University Chiang Mai Thailand
Department of Radiology Hiroshima Citizens Hospital Hiroshima Japan
Department of Radiology Hospital Italiano de Buenos Aires Autonomous City of Buenos Aires Argentina
Department of Radiology Hospital Italiano de Buenos Aires Ciudad Autónoma de Buenos Aires Argentina
Department of Radiology McGill University Health Center Montreal Quebec Canada
Department of Radiology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil
Department of Radiology Ramón y Cajal University Hospital IRYCIS Madrid Spain
Department of Radiology Universidade Federal de São Paulo São Paulo Brazil
Department of Radiology University of Algarve Faro Portugal
Department of Radiology University of Florida Gainesville
Department of Radiology University of Medicine and Pharmacy Hue University Hue Vietnam
Department of Radiology Wenchi Methodist Hospital Wenchi Ghana
Department of Radiology Zhongda Hospital Southeast University Nanjing China
Department of Surgery Monash University Central Clinical School Melbourne Victoria Australia
Department of Surgery University of Ilorin Teaching Hospital Ilorin Nigeria
Department of Surgical Oncology Institute of Oncology Ljubljana Ljubljana Slovenia
Department of Urology Aristotle University of Thessaloniki Thessaloniki Greece
Department of Urology Bordeaux Pellegrin University Hospital Bordeaux France
Department of Urology Medical University of Plovdiv Plovdiv Bulgaria
Department of Urology Oncology and Robotic Surgery Max Institute of Cancer Care Vaishali Delhi India
Department of Urology University Hospital Ludwig Maximilians University of Munich Munich Germany
Diagnostic Radiology Department of Translational Medicine Lund University Malmö Sweden
Diagnósticos da América SA São Paulo Brazil
Division of Surgery and Interventional Sciences University College London London United Kingdom
European Cancer Patient Coalition Brussels Belgium
Faculty of Medicine University of Ljubljana Ljubljana Slovenia
Fraunhofer MEVIS Institute for Digital Medicine Bremen Germany
Hanoi Medical University Hanoi Vietnam
Institute for Research in Ophthalmology Foundation for Ophthalmology Development Poznań Poland
Medical Biology Faculty of Medicine Universitas Muhammadiyah Palembang Palembang Indonesia
Michael Ogon Laboratory for Orthopaedic Research Hospital Vienna Speising Vienna Austria
Ministry of Health Byumba Hospital Byumba Rwanda
National Trauma Research Institute Melbourne Victoria Australia
One Health Research Group Faculty of Health Science Universidad de Las Américas Quito Ecuador
Ophthalmology Department of Surgery University of Melbourne Melbourne Victoria Australia
Orthopaedic Department University of Cape Town Cape Town South Africa
Radiology and Nuclear Medicine CARIM and GROW Maastricht University Maastricht the Netherlands
Radiology Center Hanoi Medical University Hospital Hanoi Hanoi Vietnam
Research and Development Department Region Kronoberg Växjö Sweden
School of Health Sciences Londonderry Northern Ireland United Kingdom
Society of Radiography of Uganda Mulago National Referral Hospital Mulago Kampala Uganda
St Karidad MHAT Karidad Medical Health Center Cardiology Plovdiv Bulgaria
Unidad de Calidad National Institute of Cardiology Ignacio Chávez Mexico City Mexico
References provided by Crossref.org
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- $a Multinational Attitudes Toward AI in Health Care and Diagnostics Among Hospital Patients / $c F. Busch, L. Hoffmann, L. Xu, LJ. Zhang, B. Hu, I. García-Juárez, LN. Toapanta-Yanchapaxi, N. Gorelik, V. Gorelik, GA. Rodriguez-Granillo, C. Ferrarotti, NN. Cuong, CAP. Thi, M. Tuncel, G. Kaya, SM. Solis-Barquero, MC. Mendez Avila, NG. Ivanova, FC. Kitamura, KYI. Hayama, ML. Puntunet Bates, PI. Torres, E. Ortiz-Prado, JS. Izquierdo-Condoy, GM. Schwarz, JG. Hofstaetter, M. Hide, K. Takeda, B. Peric, G. Pilko, HO. Thulesius, T. Lindow, IK. Kolawole, SA. Olatoke, A. Grzybowski, A. Corlateanu, OS. Iaconi, T. Li, I. Domitrz, K. Kepczynska, M. Mihalcin, L. Fašaneková, T. Zatonski, K. Fulek, A. Molnár, S. Maihoub, ZA. da Silva Gama, L. Saba, P. Sountoulides, MR. Makowski, HJWL. Aerts, LC. Adams, KK. Bressem, COMFORT consortium, ÁA. Navarro, C. Águas, M. Aineseder, M. Alomar, R. Al Sliman, G. Anand, S. Angkurawaranon, S. Aoki, S. Arkoh, G. Ashraf, Y. Astri, S. Bakhshi, NY. Bayramov, A. Billis, AGV. Bitencourt, A. Bolejko, AJ. Bollas Becerra, J. Bwambale, A. Capela, R. Cau, KR. Chacon-Acevedo, TL. Chaunzwa, R. Chojniak, W. Clements, R. Cuocolo, V. Dahlblom, KM. Sousa, JE. Villarrubia, VB. Desai, AK. Dhakal, V. Dignum, RGF. Andrade, G. Ferraioli, S. Ganguly, H. Garg, CG. Savevska, MG. Radovikj, A. Gkartzoni, L. Gorospe, I. Griffin, M. Hadamitzky, MH. Ndahiro, A. Hering, B. Hochhegger, MR. Huseynova, F. Ishida, N. Jha, L. Jiang, R. Kader, H. Kavnoudias, C. Klein, G. Kolostoumpis, A. Koshy, NA. Kruger, A. Löser, M. Lucijanic, D. Mantziari, G. Margue, S. McFadden, M. Miyake, W. Morakote, I. Ngabonziza, TT. Nguyen, SM. Niehues, M. Nortje, S. Palaian, NV. Pentara, RPP. de Almeida, G. Poma, M. Purwoko, N. Pyrgidis, V. Rafailidis, C. Rainey, JC. Ribeiro, NR. Agudelo, K. Sado, JM. Saidman, PJ. Saturno-Hernandez, V. Suryadevara, GB. Schulz, E. Soric, J. Soto-Pérez-Olivares, A. Stanzione, JP. Struck, H. Takaoka, S. Tanioka, TTM. Huyen, D. Truhn, EHC. van Dijk, P. van Wijngaarden, YC. Wang, M. Weidlich, S. Zhang
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- $a 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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