Evaluation of an Online Physician Education Module for the Assessment and Management of Non-traumatic Dental Pain and Infection
Bibliographic record
Abstract
Background: Tooth pain and infections encountered by physicians in Ontario, Canada are a common occurrence, where definitive treatment is often unfeasible. This often leads to the prescription of unwarranted antibiotic and opioid analgesics for initial management. Objective: To evaluate the effectiveness of an online educational module on Ontario physicians’ knowledge and confidence when assessing and managing non-traumatic dental emergencies. Methods: 39 participants completed a 1-hour online on-demand educational workshop featuring a cognitive aid, as well as pre- and post-module self-evaluations and clinical case scenario tests. Results: Confidence in all areas pertaining to the initial management of non-traumatic tooth pain and infection was improved and knowledge was gained, with adjusted scores for the total group, specifically in theoretical antibiotic stewardship and local anesthesia application. Conclusion: The online educational module is an effective education tool to enhance the confidence and knowledge of physician participants on the management of tooth pain and infection.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".