Felix Busch, Lena Hoffmann, Lina Xu, Longjiang Zhang, Bin Hu, Ignacio García-Juárez, Liz N Toapanta-Yanchapaxi, Natalia Gorelik, Valérie Gorelik, Gaston A Rodriguez-Granillo, Carlos Ferrarotti, Nguyen N Cuong, Chau AP Thi, Murat Tuncel, Gürsan Kaya, Sergio M Solis-Barquero, Maria C Mendez Avila, Nevena G Ivanova, Felipe C Kitamura, Karina YI Hayama, Monserrat L Puntunet Bates, Pedro Iturralde Torres, Esteban Ortiz-Prado, Juan S Izquierdo-Condoy, Gilbert M Schwarz, Jochen G Hofstaetter, Michihiro Hide, Konagi Takeda, Barbara Perić, Gašper Pilko, Hans O Thulesius, Thomas A Lindow, Israel K Kolawole, Samuel Adegboyega Olatoke, Andrzej Grzybowski, Alexandru Corlateanu, Oana-Simina Iaconi, Ting Li, Izabela Domitrz, Katarzyna Kępczyńska, Matúš Mihalčin, Lenka Fašaneková, Tomasz Zatoński, Katarzyna Fułek, András Molnár, Stefani Maihoub, Zenewton A da Silva Gama, Luca Saba, Petros Sountoulides, Marcus R Makowski, Hugo JWL Aerts, Lisa C Adams, Keno K Bressem, COMFORT consortium
{"title":"Multinational attitudes towards AI in healthcare and diagnostics among hospital patients","authors":"Felix Busch, Lena Hoffmann, Lina Xu, Longjiang Zhang, Bin Hu, Ignacio García-Juárez, Liz N Toapanta-Yanchapaxi, Natalia Gorelik, Valérie Gorelik, Gaston A Rodriguez-Granillo, Carlos Ferrarotti, Nguyen N Cuong, Chau AP Thi, Murat Tuncel, Gürsan Kaya, Sergio M Solis-Barquero, Maria C Mendez Avila, Nevena G Ivanova, Felipe C Kitamura, Karina YI Hayama, Monserrat L Puntunet Bates, Pedro Iturralde Torres, Esteban Ortiz-Prado, Juan S Izquierdo-Condoy, Gilbert M Schwarz, Jochen G Hofstaetter, Michihiro Hide, Konagi Takeda, Barbara Perić, Gašper Pilko, Hans O Thulesius, Thomas A Lindow, Israel K Kolawole, Samuel Adegboyega Olatoke, Andrzej Grzybowski, Alexandru Corlateanu, Oana-Simina Iaconi, Ting Li, Izabela Domitrz, Katarzyna Kępczyńska, Matúš Mihalčin, Lenka Fašaneková, Tomasz Zatoński, Katarzyna Fułek, András Molnár, Stefani Maihoub, Zenewton A da Silva Gama, Luca Saba, Petros Sountoulides, Marcus R Makowski, Hugo JWL Aerts, Lisa C Adams, Keno K Bressem, COMFORT consortium","doi":"10.1101/2024.09.01.24312016","DOIUrl":null,"url":null,"abstract":"The successful implementation of artificial intelligence (AI) in healthcare is dependent upon the acceptance of this technology by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes. This international, multicenter, cross-sectional study assessed the attitudes of hospital patients towards AI in healthcare across 43 countries. A total of 13806 patients at 74 hospitals were surveyed between February and November 2023, with 64.8% from the Global North and 35.2% from the Global South. The findings indicate a predominantly favorable general view of AI in healthcare, with 57.6% of respondents expressing a positive attitude. However, attitudes exhibited notable variation based on demographic characteristics, health status, and technological literacy. Female respondents and those with poorer health status exhibited fewer positive attitudes towards AI use in medicine. Conversely, higher levels of AI knowledge and frequent use of technology devices were associated with more positive attitudes. It is noteworthy that less 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. Patients exhibited a strong preference for explainable AI and physician-led decision-making, even if it meant slightly compromised accuracy. This large-scale, multinational study provides a comprehensive perspective on patient attitudes towards AI in healthcare across six continents. Findings suggest a need for tailored AI implementation strategies that consider patient demographics, health status, and preferences for explainable AI and physician oversight. All study data has been made publicly available to encourage replication and further investigation.","PeriodicalId":501454,"journal":{"name":"medRxiv - Health Informatics","volume":"3 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.01.24312016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The successful implementation of artificial intelligence (AI) in healthcare is dependent upon the acceptance of this technology by key stakeholders, particularly patients, who are the primary beneficiaries of AI-driven outcomes. This international, multicenter, cross-sectional study assessed the attitudes of hospital patients towards AI in healthcare across 43 countries. A total of 13806 patients at 74 hospitals were surveyed between February and November 2023, with 64.8% from the Global North and 35.2% from the Global South. The findings indicate a predominantly favorable general view of AI in healthcare, with 57.6% of respondents expressing a positive attitude. However, attitudes exhibited notable variation based on demographic characteristics, health status, and technological literacy. Female respondents and those with poorer health status exhibited fewer positive attitudes towards AI use in medicine. Conversely, higher levels of AI knowledge and frequent use of technology devices were associated with more positive attitudes. It is noteworthy that less 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. Patients exhibited a strong preference for explainable AI and physician-led decision-making, even if it meant slightly compromised accuracy. This large-scale, multinational study provides a comprehensive perspective on patient attitudes towards AI in healthcare across six continents. Findings suggest a need for tailored AI implementation strategies that consider patient demographics, health status, and preferences for explainable AI and physician oversight. All study data has been made publicly available to encourage replication and further investigation.