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. 2023 Nov 28:11:1301563.
doi: 10.3389/fpubh.2023.1301563. eCollection 2023.

Modeling the influence of attitudes, trust, and beliefs on endoscopists' acceptance of artificial intelligence applications in medical practice

Peter J Schulz #  1   2 , May O Lwin #  2 , Kalya M Kee  1   2 , Wilson W B Goh  1   3   4 , Thomas Y T Lam  5 , Joseph J Y Sung  1
Affiliations

Modeling the influence of attitudes, trust, and beliefs on endoscopists' acceptance of artificial intelligence applications in medical practice

Peter J Schulz et al. Front 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.

Keywords: acceptance; artificial intelligence; attitudes; gastroenterology; trust.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Final model for the acceptance model – graphical representation of final model for acceptance of AI-specific applications in gastroenterology. Variables: General expectations regarding AI (expectp), general attitudes towards AI (attiai), trust in AI (trust), beliefs in AI (belief), acceptance of AI (accept). Legend: Straight lines represent the presumed causal paths, rectangles denote measured variables, numbers in the mid of the line are unstandardized path coefficients, values in brackets represent their standard errors, the values pointing to each endogenous construct indicate the residual variance of each construct with their standard error in brackets.
See this image and copyright information in PMC

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