Applying an extended theoretical approach to identifying Canadian dental students’ acceptance of teledentistry: A cross-sectional study
Why this work is in the frame
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Bibliographic record
Abstract
Objective: Teledentistry is a promising innovation for improving service quality and patient outcomes. While studies have shown the relevance of theoretical frameworks in understanding behaviour change predictors for telehealth implementation efforts, their application in dentistry is limited. This study aimed to test different theoretical approaches to identify the factors affecting dental students' behavioural intention to use teledentistry. Methods: This cross-sectional study involved students in their final two years of undergraduate dental programmes, from three Canadian provinces (Quebec, Nova Scotia, and Saskatchewan) using an electronic self-reported questionnaire. Following descriptive analyses, we tested three theoretical models (the technology acceptance model, psychosocial model, and integrated model) using path analysis and multiple linear regression analysis. We analyzed the modifying effect of sociodemographic characteristics and prior use of teledentistry. Results: < 0.001) were the most significant predictors of behavioural intention to use. Prior use of teledentistry modified the association between control beliefs and behavioural intention to use teledentistry. Conclusions: The original technology acceptance model was a good predictive model of behavioural intention to use teledentistry with perceived use as the strongest predictor. However, the integrated model performed the best in highlighting the relevance of training and education to foster teledentistry implementation in dental schools. The generalizability of the findings is constrained by the modest sample size, warranting larger studies for validation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it