ArticleCureus2025
Faculty Perspectives on Integrating Artificial Intelligence Into Orthodontic and Interdisciplinary Dental Education: Opportunities, Challenges, and Strategies.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Orthodontists' Perceptions, Attitudes, and Adoption of Artificial Intelligence: A Scoping Review.Dentistry journal · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionArtificial intelligence (AI) is transforming dental education by enhancing diagnostic precision and personalized learning. This study aimed to investigate faculty perspectives on integrating AI into orthodontic and interdisciplinary dental curricula and identifying opportunities, challenges, and strategies to prepare students for technology-driven practice. The objectives included exploring AI's potential in enhancing diagnostic tools and learning systems, identifying barriers such as faculty training gaps and ethical concerns, and developing evidence-based strategies for AI adoption. MATERIALS AND
methodsA cross-sectional survey was conducted in the Department of Orthodontics. A structured questionnaire developed by a multidisciplinary team comprised 12 items across three sections: opportunities, challenges, and strategies, rated on a numerical scale (-1 = Disagree, 0 = neutral and +1 = Agree). After pilot testing (Cronbach's alpha = 0.82), the survey was distributed via WhatsApp to 410 faculty members from North Indian dental colleges, targeting orthodontists and related specialties with at least two years of teaching experience. Data were analyzed using independent t-tests and one-way analysis of variance (ANOVA) for comparison (p < 0.05).
resultsA total of 250 (61%) participants responded to the survey. The study population included 140 (56%) males with a mean age of 38.11 ± 5.08 years and 110 (44%) females, with orthodontists as the largest specialty group. Females reported higher opportunity (mean = 3.14 vs. 2.82, p = 0.048) and challenge scores (mean = 3.41 vs. 3.14, p = 0.029) than males, with no significant difference in strategy perceptions (p = 0.179). Full-time academicians noted greater challenges (p = 0.013) than clinician-academicians. Orthodontists showed the highest opportunity scores (mean = 3.33) and lowest challenge scores (mean = 3.06), whereas prosthodontists reported the highest challenges (mean = 3.57, p = 0.004). Age and experience were positively correlated with opportunity and strategy perceptions, with weaker negative correlations with challenges.
conclusionThe findings revealed strong faculty support for AI integration, with perspectives influenced by sex, specialty, and role. Tailored training and curriculum redesign are needed to address these barriers and enhance AI adoption in dental education.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.