Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/173145
Title: Modeling the influence of attitudes, trust, and beliefs on endoscopists' acceptance of artificial intelligence applications in medical practice
Authors: Schulz, Peter Johannes
Lwin, May Oo
Kee, Kalya M.
Goh, Wilson Wen Bin
Lam, Thomas Y. T.
Sung, Joseph Jao Yiu
Keywords: Science::Medicine
Issue Date: 2023
Source: Schulz, P. J., Lwin, M. O., Kee, K. M., Goh, W. W. B., Lam, T. Y. T. & Sung, J. J. Y. (2023). Modeling the influence of attitudes, trust, and beliefs on endoscopists' acceptance of artificial intelligence applications in medical practice. Frontiers in Public Health, 11, 1301563-. https://dx.doi.org/10.3389/fpubh.2023.1301563
Project: AISG3-GV-2021-009 
Journal: Frontiers in Public Health 
Abstract: Introduction: The potential for deployment of Artificial Intelligence (AI) technologies in various fields of medicine is vast, yet acceptance of AI amongst clinicians has been patchy. This research therefore examines the role of antecedents, namely trust, attitude, and beliefs in driving AI acceptance in clinical practice. Methods: We utilized online surveys to gather data from clinicians in the field of gastroenterology. Results: A total of 164 participants responded to the survey. Participants had a mean age of 44.49 (SD = 9.65). Most participants were male (n = 116, 70.30%) and specialized in gastroenterology (n = 153, 92.73%). Based on the results collected, we proposed and tested a model of AI acceptance in medical practice. Our findings showed that while the proposed drivers had a positive impact on AI tools’ acceptance, not all effects were direct. Trust and belief were found to fully mediate the effects of attitude on AI acceptance by clinicians. Discussion: The role of trust and beliefs as primary mediators of the acceptance of AI in medical practice suggest that these should be areas of focus in AI education, engagement and training. This has implications for how AI systems can gain greater clinician acceptance to engender greater trust and adoption amongst public health systems and professional networks which in turn would impact how populations interface with AI. Implications for policy and practice, as well as future research in this nascent field, are discussed.
URI: https://hdl.handle.net/10356/173145
ISSN: 2296-2565
DOI: 10.3389/fpubh.2023.1301563
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
Wee Kim Wee School of Communication and Information 
School of Biological Sciences 
Research Centres: Center for Biomedical Informatics
Rights: © 2023 Schulz, Lwin, Kee, Goh, Lam and Sung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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