Related Experiment Video
Updated: Sep 26, 2026

Reliability of Artificial Intelligence-Based Cone Beam Computed Tomography Integration with Digital Dental Images
Published on: February 23, 2024
Patients' Perspectives on Artificial Intelligence and Digital Transformation in Dental Practice: A Cross-Sectional
Alin Flavius Cozmescu1, Ana Cernega1, Andreea Cristiana Didilescu2
1Department of Organization, Professional Legislation and Management of the Dental Office, Faculty of Dental Medicine, "Carol Davila" University of Medicine and Pharmacy, 17-23 Plevnei Street, 020021 Bucharest, Romania.
Abstract:
Background/Objectives: The integration of artificial intelligence (AI) and digital technologies into dental practice is reshaping clinical workflows, administrative processes, and, increasingly, the patient experience and the doctor-patient relationship. While prior research has documented the attitudes of clinicians and practice managers, the perspective of the patient remains comparatively underexplored. This study examined how dental patients perceive AI integration and digital tools across the dental care pathway, together with the associated implications for data security, cost, and the human dimension of care. Methods: A cross-sectional, questionnaire-based study was conducted among 200 dental patients in Bucharest, Romania, and the surrounding region. The instrument assessed perceived difficulty and availability regarding digital technology, current use of digital tools, demographic and educational characteristics (age, gender, practice environment, educational level), and two attitudinal dimensions, namely digital prudence and concern for technological sustainability, across five subdomains of the dental care pathway: scheduling, diagnosis, treatment planning, feedback, and follow-up (dispensarization). Responses were analyzed using non-parametric tests and exploratory principal component analysis with internal-consistency validation. Results: Patients expressed moderate-to-high interest in AI support during the diagnostic (median = 3.3, IQR = 2.7-3.9) and feedback (median = 3.11, IQR = 2.78-3.67) stages and the lowest interest in scheduling (median = 2.7, IQR = 2.0-3.3). A marked level of digital prudence was observed (median = 3.24, IQR = 2.82-3.61), reflecting concerns about data security, automation, and a possible weakening of the clinician-patient bond. Younger and academically educated patients reported lower perceived difficulty, higher availability, and greater current use of digital tools (all p ≤ 0.001); counterintuitively, the same patients scored significantly higher on digital prudence (Spearman's ρ = -0.260, p < 0.001). Greater familiarity with digital tools was therefore accompanied by a more critical awareness of their informational risks rather than by uncritical acceptance. Conclusions: Dental patients approach AI through a dual lens of openness and informed caution, welcoming efficiency gains in the clinical and continuity-of-care stages while voicing measured concerns about data security, affordability, and the preservation of human contact. To interpret this profile, we propose two conceptual contributions: a mapping of patient needs onto Maslow's hierarchy in the context of AI-mediated care and the Informational VUCA framework, which characterizes the volatility, uncertainty, complexity, and ambiguity that patients face when navigating AI-generated information. The findings point to a clear practical agenda of transparent communication, robust data governance, and education strategies adapted to patients' educational and demographic profiles, so that AI-enhanced workflows strengthen rather than erode the doctor-patient relationship.