Factors influencing large language model adoption among dental students: a cross-sectional study

This research evaluates the factors influencing the behavioural intention (BI) to adopt large language models (LLMs) among dental students in education, clinical decision support (CDS), and research, using the original unified theory of acceptance and use of technology (UTAUT) model, representing the first application of this model in this specific context. LLM adoption among Saudi dental students is unstructured and unregulated, making empirical evidence on adoption factors an educational and governance priority. A cross-sectional, web-based survey using convenience sampling was conducted among 700 students from six universities in central Saudi Arabia (60.71% aged 18–22 years; 58.71% female; 74% undergraduate). The UTAUT constructs: performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), were assessed using a five-point Likert scale. Measurement equivalence across English and Arabic language questionnaire versions were confirmed. All UTAUT constructs showed borderline acceptable to excellent internal consistency (α = 0.678–0.907). Structural equation modelling (SEM) with bootstrapped 95% confidence intervals (CI) was used for statistical analysis. Hierarchical multiple regression was used for post-hoc sensitivity analysis to examine the moderating effects of demographic variables. The model accounted for 44.1% of the variance in BI (SEM-derived R2 = 0.441, p < 0.001). EE was the strongest significant factor influencing BI (β = 0.351, p = 0.017, 95% CI 0.056, 0.518), followed by FC (β = 0.136, p = 0.024, 95% CI 0.019, 0.183). The PE (β = 0.158, p = 0.162) was non-significant, due to its high latent correlation with EE, and SI (β = 0.090, p = 0.131) was also non-significant, consistent with absent institutional mandates. The UTAUT–BI relationships were not significantly moderated by age, gender, or academic level. The results indicate strong expressed BI to adopt LLMs among dental students; however, BI is a theoretical proxy and should not be equated with actual adoption behaviour, clinical competence, or ethical and effective LLM application. These findings offer preliminary evidence which may inform curriculum design and institutional governance for responsible LLM integration in dentistry. The tentatively proposed LLM competency framework represents theoretical concepts which require empirical validation before implementation.