A survey of amalgam use to guide dental education curriculums
Bibliographic record
Abstract
OBJECTIVES: To identify behavioral, preferential, and professional factors influencing the use of amalgam in private practices; and to compare the incidence of the placement of amalgam versus composite resin restorations in the province of Ontario and its pedagogical implications on dental curricula. METHODS: Participants responded anonymously to a 23-question online survey about their current use of dental amalgam and composite resins as well as their opinions regarding both dental materials. The explanatory variables were associated bivariately with the outcome variables, and the most significant predictors were identified using the multivariate analysis. RESULTS: Higher percentages of amalgam use were reported among clinicians who trained in Canada only (P = .009), who graduated before 1980 (p = <.001) and who work outside private practice (p = <.001). Familiarity with amalgam was higher among clinicians who are female (p = <.001), older (p = <.001), trained only in Canada (p = .017), who graduated prior to 2000 (p = <.001), and who work in locations with populations over 100,000 (p = .042). Familiarity with composite resin was higher among clinicians who graduated more recently (p = .002). A higher percentage of females (p = <.001), younger clinicians (p = <.001), recent graduates (p = <.001), and clinicians who work in private practice (p = .043) suggested that over 50% of dental student training time be allocated to amalgam. CONCLUSIONS: Decreased amalgam use was reported by later dental graduates and private practitioners; this may be impacted by familiarity with dental amalgam. As amalgam remains a safe and effective dental material, its removal may not be prudent. Dental educators play a crucial role in the future of amalgam opinion and use.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".