Behavioural change as a theme that integrates behavioural sciences in dental education
Bibliographic record
Abstract
The behavioural sciences curriculum in dental education is often fragmented and its clinical relevance is not always apparent to learners. Curriculum integration is vital to understand behavioural subjects that are interrelated but frequently delivered as separate issues in dental programmes. In this commentary, we discuss behavioural change as a curricular theme that can integrate behavioural sciences in dental programmes. Specifically, we discuss behavioural change in the context of dental education guidelines and describe four general phases of behavioural change (defining the target behaviour, identifying the behavioural determinants, applying appropriate behavioural change techniques and evaluating the behavioural intervention) to make the case for content that can be covered within this curricular theme, including its sequencing. This commentary is part of ongoing efforts to improve the behavioural sciences curriculum in dental education in order to ensure that dental students develop the behavioural competencies required for entry-level general dentists.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".