Patients’ attitudes toward artificial intelligence in dentistry and their trust in dentists


BAHADIR H. S., KESKİN N. B., Çakmak E. Ş. K., Güneç G., Cesur Aydin K., PEKER F.

Oral Radiology, 2024 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2024
  • Doi Number: 10.1007/s11282-024-00775-1
  • Journal Name: Oral Radiology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, MEDLINE
  • Keywords: Artificial intelligence, Communication, Dentist trust, Diagnosis, Machine learning, Patients
  • Istanbul Medipol University Affiliated: Yes

Abstract

Objectives: This study intended to evaluate patients’ attitudes toward the use of AI in dental radiographic detection of occlusal caries and the impact of AI-based diagnosis on their trust in dentists. Methods: A total of 272 completed questionnaires were included in this study. In the first part of the study, approval was obtained from the patients, and data were collected about their socio-demographic characteristics. In the second part the 11-item Dentist Trust Scale was applied. In the third and fourth parts, there were questions about two clinical scenarios, the patients’ knowledge of attitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performed using a Likert-type scale. Data were analyzed with the Chi-square, one-way ANOVA, and ordinal logistic regression tests (p < 0.05). Results: The patients believed that “AI is useful” (3.86 ± 1.03) and were not afraid of the use of AI in dentistry (2.40 ± 1.05). Educational level was considerably related to the patients’ attitudes to the use of AI for dental diagnostics (p < 0.05). The patients stated that “dentists are extremely thorough and careful” (4.39 ± 0.77). Conclusions: The patients displayed a positive attitude to AI-based diagnosis in the dental field and appear to exhibit trust in dentists. The use of Al in routine clinical practice can provide important benefit to physicians as a clinical decision support system in dentistry and understanding patients’ attitudes may allow dentists to shape AI-supported dentistry in the future.