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

Artificial Intelligence in Medicine Program Mass General Brigham Harvard Medical School Boston Massachusetts

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

Center for Medical Education and Clinical Research National Council for Scientific and Technical Research Autonomous City of Buenos Aires Argentina

Centre for Eye Research Australia Royal Victorian Eye and Ear Hospital Melbourne Victoria Australia

Charité Lab for Artificial Intelligence in Medicine Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin Berlin Germany

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 Radiology AHEPA General University Hospital Aristotle University of Thessaloniki Thessaloniki Greece

Department of Clinical Sciences College of Dentistry Ajman University Ajman United Arab Emirates

Department of Clinical Sciences College of Pharmacy and Health Sciences 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 School of Medicine and Health Klinikum rechts der Isar TUM University Hospital Technical University of Munich Munich Germany

Department of Diagnostic and Interventional Radiology University Hospital Aachen Aachen Germany

Department of Diagnostic and Therapeutic Imaging Escuela de Tecnologias en Salud Universidad de Costa Rica San José Costa Rica

Department of Diagnostic Imaging Center for Medical Education and Clinical Research Norberto Quirno Autonomous City of Buenos Aires Argentina

Department of Gastroenterology Lakeshore Hospital Kochi India

Department of Gastroenterology National Institute of Medical Sciences and Nutrition Salvador Zubirán Mexico City Mexico

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 Centro Hospitalar Vila Nova de Gaia Espinho Vila Nova de Gaia Portugal

Department of Medical Oncology Dr B R A Institute Rotary Cancer Hospital All India Institute of Medical Sciences New Delhi India

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 Neurology National Institute of Medical Sciences and Nutrition Salvador Zubirán Mexico City Mexico

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 and Visual Sciences Kyoto University Graduate School of Medicine Kyoto Japan

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 Radiation Oncology Dana Farber Cancer Institute and Brigham and Women's Hospital Boston Massachusetts

Department of Radiology Alfred Health Melbourne Victoria Australia

Department of Radiology Algarve University Hospital Center Faro Portugal

Department of Radiology and Nuclear Medicine Radboud University Medical Center Nijmegen the Netherlands

Department of Radiology Azienda Ospedaliero Universitaria di Cagliari Polo di Monserrato s s 554 Monserrato Cagliari Italy

Department of Radiology Charité Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin Berlin Germany

Department of Radiology Dana Farber Cancer Institute and Brigham and Women's Hospital Boston Massachusetts

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 Jinling Hospital Affiliated Hospital of Medical School Nanjing University Nanjing China

Department of Radiology McGill University Health Center Montreal Quebec Canada

Department of Radiology Molecular Imaging Program at Stanford Stanford University School of Medicine Stanford California

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 Respiratory Medicine and Allergology Nicolae Testemițanu State University of Medicine and Pharmacy Chișinău Republic of Moldova

Department of Rheumatology Shanghai Jiao Tong University School of Medicine Renji Hospital Shanghai 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 Faculty of Health Sciences Brandenburg Brandenburg Medical School Theodor Fontane Brandenburg an der Havel Germany

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 Radiology and Nuclear Medicine German Heart Center Munich Technical University of Munich Munich Germany

Institute for Research in Ophthalmology Foundation for Ophthalmology Development Poznań Poland

Instituto Global de Excelencia Clínica Grupo de investigación Traslacional Keralty Bogotá D C Colombia

Lab of Medical Physics and Digital Innovation School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece

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

Research Cooperation Unit Research Department National Institute of Research in Medicine and Health Nicolae Testemițanu State University of Medicine and Pharmacy Chișinău Republic of Moldova

School of Health Sciences Londonderry Northern Ireland United Kingdom

School of Medicine and Health Institute for Cardiovascular Radiology and Nuclear Medicine German Heart Center Munich TUM University Hospital Technical University of Munich Munich Germany

Society of Radiography of Uganda Mulago National Referral Hospital Mulago Kampala Uganda

St Karidad MHAT Karidad Medical Health Center Cardiology Plovdiv Bulgaria

Subdirection of Diagnosis and Treatment National Institute of Cardiology Ignacio Chávez Mexico City Mexico

Unidad de Calidad National Institute of Cardiology Ignacio Chávez Mexico City Mexico

Unit of Liver Transplantation National Institute of Medical Sciences and Nutrition Salvador Zubirán Mexico City Mexico

University Clinic for Physical Medicine and Rehabilitation Ss Cyril and Methodius University Skopje Republic of North Macedonia

University Clinic for State Cardiac Surgery Ss Cyril and Methodius University Skopje Republic of North Macedonia

Comment In

doi: 10.1001/jamanetworkopen.2025.14460 PubMed

See more in PubMed

Peres RS, Jia X, Lee J, Sun K, Colombo AW, Barata J. Industrial artificial intelligence in industry 4.0 - systematic review, challenges and outlook. IEEE Access. 2020;8:220121-220139. doi: 10.1109/ACCESS.2020.3042874 DOI

Choudhury A, Shamszare H. Investigating the impact of user trust on the adoption and use of ChatGPT: survey analysis. J Med Internet Res. 2023;25:e47184. doi: 10.2196/47184 PubMed DOI PMC

Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94-98. doi: 10.7861/futurehosp.6-2-94 PubMed DOI PMC

Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol. 2017;2(4):230-243. doi: 10.1136/svn-2017-000101 PubMed DOI PMC

Ferrari R, Mancini-Terracciano C, Voena C, et al. MR-based artificial intelligence model to assess response to therapy in locally advanced rectal cancer. Eur J Radiol. 2019;118:1-9. doi: 10.1016/j.ejrad.2019.06.013 PubMed DOI

Paul D, Sanap G, Shenoy S, Kalyane D, Kalia K, Tekade RK. Artificial intelligence in drug discovery and development. Drug Discov Today. 2021;26(1):80-93. doi: 10.1016/j.drudis.2020.10.010 PubMed DOI PMC

Adams LC, Truhn D, Busch F, et al. Leveraging GPT-4 for post hoc transformation of free-text radiology reports into structured reporting: a multilingual feasibility study. Radiology. 2023; 307(4):e230725. doi: 10.1148/radiol.230725 PubMed DOI

Sahni NR, Stein G, Zemmel R, Cutler DM. The potential impact of artificial intelligence on healthcare spending. In: Agrawal A, Gans J, Goldfarb A, Tucker CT, eds. The Economics of Artificial Intelligence: Health Care Challenges. University of Chicago Press; 2024:192.

Artificial intelligence and machine learning (AI/ML)-enabled medical devices. US Food and Drug Administration. 2023. Accessed October 19, 2024. https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices

Ethics and governance of artificial intelligence for health: WHO guidance: executive summary. World Health Organization; 2021.

Sauerbrei A, Kerasidou A, Lucivero F, Hallowell N. The impact of artificial intelligence on the person-centred, doctor-patient relationship: some problems and solutions. BMC Med Inform Decis Mak. 2023;23(1):73. doi: 10.1186/s12911-023-02162-y PubMed DOI PMC

Adus S, Macklin J, Pinto A. Exploring patient perspectives on how they can and should be engaged in the development of artificial intelligence (AI) applications in health care. BMC Health Serv Res. 2023;23(1):1163. doi: 10.1186/s12913-023-10098-2 PubMed DOI PMC

Bjerring JC, Busch J. Artificial intelligence and patient-centered decision-making. Philos Technol. 2021;34:349-371. doi: 10.1007/s13347-019-00391-6 DOI

Rosen R. How is technology changing clinician-patient relationships? BMJ. 2024;384:q574. doi: 10.1136/bmj.q574 PubMed DOI

Martin LR, Williams SL, Haskard KB, Dimatteo MR. The challenge of patient adherence. Ther Clin Risk Manag. 2005;1(3):189-199. PubMed PMC

Lee YY, Lin JL. How much does trust really matter? a study of the longitudinal effects of trust and decision-making preferences on diabetic patient outcomes. Patient Educ Couns. 2011;85(3):406-412. doi: 10.1016/j.pec.2010.12.005 PubMed DOI

Young AT, Amara D, Bhattacharya A, Wei ML. Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review. Lancet Digit Health. 2021;3(9):e599-e611. doi: 10.1016/S2589-7500(21)00132-1 PubMed DOI

Robertson C, Woods A, Bergstrand K, Findley J, Balser C, Slepian MJ. Diverse patients’ attitudes towards artificial intelligence (AI) in diagnosis. PLOS Digit Health. 2023;2(5):e0000237. doi: 10.1371/journal.pdig.0000237 PubMed DOI PMC

Fritsch SJ, Blankenheim A, Wahl A, et al. Attitudes and perception of artificial intelligence in healthcare: a cross-sectional survey among patients. Digit Health. 2022;8:20552076221116772. doi: 10.1177/20552076221116772 PubMed DOI PMC

Armero W, Gray KJ, Fields KG, Cole NM, Bates DW, Kovacheva VP. A survey of pregnant patients’ perspectives on the implementation of artificial intelligence in clinical care. J Am Med Inform Assoc. 2022;30(1):46-53. doi: 10.1093/jamia/ocac200 PubMed DOI PMC

Ibba S, Tancredi C, Fantesini A, et al. How do patients perceive the AI-radiologists interaction? results of a survey on 2119 responders. Eur J Radiol. 2023;165:110917. doi: 10.1016/j.ejrad.2023.110917 PubMed DOI

Khullar D, Casalino LP, Qian Y, Lu Y, Krumholz HM, Aneja S. Perspectives of patients about artificial intelligence in health care. JAMA Netw Open. 2022;5(5):e2210309. doi: 10.1001/jamanetworkopen.2022.10309 PubMed DOI PMC

Parry MW, Markowitz JS, Nordberg CM, Patel A, Bronson WH, DelSole EM. Patient perspectives on artificial intelligence in healthcare decision making: a multi-center comparative study. Indian J Orthop. 2023;57(5):653-665. doi: 10.1007/s43465-023-00845-2 PubMed DOI PMC

Yap A, Wilkinson B, Chen E, et al. Patients perceptions of artificial intelligence in diabetic eye screening. Asia Pac J Ophthalmol (Phila). 2022;11(3):287-293. doi: 10.1097/APO.0000000000000525 PubMed DOI

Wickham H, Averick M, Bryan J, et al. Welcome to the Tidyverse. J Open Source Softw. 2019;4(43):1686. doi: 10.21105/joss.01686 DOI

Rosseel Y. lavaan: an R package for structural equation modeling. J Stat Softw. 2012;48(2):1-36. doi: 10.18637/jss.v048.i02 DOI

Revelle W. psych: procedures for psychological, psychometric, and personality research [version 2.2.9]. Published September 29, 2022. Accessed January 10, 2023. https://cran.r-project.org/web/packages/psych/index.html

Christensen R. ordinal: regression models for ordinal data [version 2023.12-4]. Published September 29, 2022. Accessed May 12, 2024. https://cran.r-project.org/web/packages/ordinal/index.html

Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67(1):1-48. doi: 10.18637/jss.v067.i01 DOI

Global South countries (group of 77 and China). United Nations, Finance Center for South-South Cooperation .http://www.fc-ssc.org/en/partnership_program/south_south_countries

United Nations, Department of Economic and Social Affairs, Statistics Division . Standard Country or Area Codes for Statistics Use, 1999 (Revision 4). United Nations; 1999.

Jutzi TB, Krieghoff-Henning EI, Holland-Letz T, et al. Artificial intelligence in skin cancer diagnostics: the patients’ perspective. Front Med (Lausanne). 2020;7:233. doi: 10.3389/fmed.2020.00233 PubMed DOI PMC

Moussavi S, Chatterji S, Verdes E, Tandon A, Patel V, Ustun B. Depression, chronic diseases, and decrements in health: results from the World Health Surveys. Lancet. 2007;370(9590):851-858. doi: 10.1016/S0140-6736(07)61415-9 PubMed DOI

Von Korff M, Gruman J, Schaefer J, Curry SJ, Wagner EH. Collaborative management of chronic illness. Ann Intern Med. 1997;127(12):1097-1102. doi: 10.7326/0003-4819-127-12-199712150-00008 PubMed DOI

Wolf RM, Abramoff MD, Channa R, Tava C, Clarida W, Lehmann HP. Potential reduction in healthcare carbon footprint by autonomous artificial intelligence. NPJ Digit Med. 2022;5(1):62. doi: 10.1038/s41746-022-00605-w PubMed DOI PMC

Saenz AD, Harned Z, Banerjee O, Abràmoff MD, Rajpurkar P. Autonomous AI systems in the face of liability, regulations and costs. NPJ Digit Med. 2023;6(1):185. doi: 10.1038/s41746-023-00929-1 PubMed DOI PMC

Abramoff MD, Whitestone N, Patnaik JL, et al. Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial. NPJ Digit Med. 2023;6(1):184. doi: 10.1038/s41746-023-00931-7 PubMed DOI PMC

Lennartz S, Dratsch T, Zopfs D, et al. Use and control of artificial intelligence in patients across the medical workflow: single-center questionnaire study of patient perspectives. J Med Internet Res. 2021;23(2):e24221. doi: 10.2196/24221 PubMed DOI PMC

Yang K, Zeng Z, Peng H, Jiang Y. Attitudes of Chinese cancer patients toward the clinical use of artificial intelligence. Patient Prefer Adherence. 2019;13:1867-1875. doi: 10.2147/PPA.S225952 PubMed DOI PMC

de Veer AJE, Peeters JM, Brabers AEM, Schellevis FG, Rademakers JJDJM, Francke AL. Determinants of the intention to use e-Health by community dwelling older people. BMC Health Serv Res. 2015;15:103. doi: 10.1186/s12913-015-0765-8 PubMed DOI PMC

Rahimi B, Nadri H, Lotfnezhad Afshar H, Timpka T. A systematic review of the technology acceptance model in health informatics. Appl Clin Inform. 2018;9(3):604-634. doi: 10.1055/s-0038-1668091 PubMed DOI PMC