ArticleBMC medical education2026
Artificial intelligence related anxiety among dental students: associations with demographics and AI use behaviors.
Article in BMC medical education, 2026. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) is increasingly integrated into dental diagnostics and education, including AI-assisted radiograph interpretation, caries detection, digital treatment planning, and virtual simulation-based training. While these technologies may improve precision, they may also provoke cognitive and emotional responses, such as AI-related anxiety. Understanding the determinants of this anxiety is essential for designing pedagogical strategies that support effective digital adaptation.
methodsThis descriptive, cross-sectional study was conducted among dental students at Uşak University between August and October 2025. Of 336 invited students, 322 completed the survey (response rate: 95.8%). Data were collected via an online questionnaire comprising demographic variables and the Artificial Intelligence Anxiety Scale (AIAS), adapted into Turkish by Akkaya et al. The 16-item AIAS assesses four subscales: Learning Anxiety, Job Replacement Anxiety, Sociotechnical Blindness, and AI Configuration Anxiety. Group differences were examined using Welch's ANOVA with Games-Howell post hoc tests, and statistical significance was set at p < 0.05.
resultsParticipants were predominantly female (66.1%). Most used the internet for 3-6 h daily (76.7%) and interacted with AI tools for less than one hour per day (49.7%). Overall AI anxiety was mid-range (AIAS total score, mean ± SD: 44.74 ± 10.03; range: 16-80), placing the sample near the theoretical midpoint (48). Female students reported significantly higher total anxiety (p = 0.012), Sociotechnical Blindness (p = 0.006), and AI Configuration Anxiety (p < 0.001). Anxiety levels decreased with increasing academic seniority (p = 0.040). Maternal education level was associated with overall anxiety (p = 0.023). Daily AI usage duration was associated with the Learning Anxiety (p = 0.024) and AI Configuration Anxiety (p = 0.026) subscales.
conclusionIn this sample, dental students exhibited mid-range AI anxiety. Higher anxiety levels were associated with female gender, lower academic seniority, lower maternal education, and shorter daily AI-use duration. Integrating structured AI literacy and ethics-focused frameworks into dental curricula may help address these concerns. Given the cross-sectional design, causal inferences cannot be made; future longitudinal studies are warranted to examine these associations over time.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.