Background Artificial 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. Methods This 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. Results Participants 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. Conclusion In 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.

Artificial intelligence related anxiety among dental students: associations with demographics and AI use behaviors

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发表日期：

2026年4月29日

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Fatih Karaaslan,
Yaren Eri̇şken

摘要

Background

Artificial 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.

Methods

This 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.

Results

Participants 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.

Conclusion

In 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.