Roy, Pompi
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Perceptions and Acceptance of Artificial Intelligence in Dentistry: A Comprehensive Examination of Dentists' Attitudes and Behavioural Intentions Towards AI Integration in Clinical Setting Rizwana; Singh, Padmalini; Muralidhar, Shubha; Roy, Pompi
Public Health of Indonesia Vol. 11 No. 3 (2025): July - September
Publisher : YCAB Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36685/phi.v11i3.955

Abstract

Background: The integration of Artificial Intelligence(AI) in dental care presents numerous benefits. However, fostering a proactive attitude is essential to ensure that these advancements lead to positive developments within dental practices. This study primarily focuses on examining the acceptance of AI technologies among dental professionals. Objective: The present study aims to explore the perceptions and acceptance of dentists towards the integration of AI in dentistry through Technology Acceptance Model (TAM) as a theoretical framework. Methods: By adopting descriptive research design, the study involved systematic collection of primary data from dental professionals to gain insights into their perceptions, attitudes, and acceptance of AI technologies in their professional environment. Using judgmental sampling, the researcher selected participants with first-hand experience relevant to the study’s topic. Consequently, a sample of 200 dental professionals who are actively using or planning to use AI technologies have been considered as prospective respondents. Results: The findings of the study reveal that dental professionals are aware about the usage of AI in dentistry and AI implementation is most notable in Orthodontics at 34%, followed by a significant use in Endodontics and Prosthodontics at 18.5% and 17.5% respectively. The results based on Structural Equation Modelling (SEM) indicate that the variable “perceived ease of use” positively influences dental professionals' attitudes towards its use in dentistry. Furthermore, the positive attitude has significantly influenced their behavioural intention to use, which in turn positively affected the actual usage of AI in dental practices. Conclusion: Though the overall impact of AI in dentistry is largely positive, it is notable that perceived usefulness did not significantly influence dentists' attitudes. This discrepancy indicates that the majority of dentists are aware of the benefits of integrating AI in dentistry, conflicting with expectations, the variable perceived usefulness did not have a significant impact on the attitudes of dental professionals towards AI.  Keywords: artificial intelligence; dentistry; diagnostics; technology acceptance model (TAM)