Self‐reported dental and oral injuries in a population of adults aged 18–50 years
Bibliographic record
Abstract
Few population-based studies of traumatic dental injury in adults have been undertaken. The objective of this study was to assess the prevalence and severity of injuries to the mouth and teeth among adults aged 18-50 years living in the Canadian province of Ontario. A telephone survey was undertaken based on random digit dialling and 2001 adults in the target age range were interviewed. Overall, 15.5% reported a history of injury to the mouth and teeth. Of these, one-third reported two or more episodes of injury. Males were more likely than females to report injury and to have experienced more than one injury. There was no association with age but a U-shaped relationship with education. When asked about the nature of the worst injury experienced, 85% with a history of trauma reported damage to the teeth and of these, 38.5% reported one or more teeth were chipped and 26.0% broke one or more teeth. One quarter (25.4%) reported avulsions and 6.5% reported luxations. Other types of injury were reported by 3.5%. Two-thirds of the injuries reported occurred before the age of 18 years and one-third after this age. One-fifth of those with tooth injuries had not been treated by a health professional. This was not associated with the nature of the damage that occurred; rather subjects from the lower educational groups were less likely than those from higher educational groups to have received treatment. There was a significant association between injuries to the mouth and teeth and injuries in other body locations. One-third of those reporting two or more episodes of the latter reported having experienced injuries to the mouth and teeth. The results of this self-report study indicate that dental trauma constitutes a significant health issue among adults and that a minority may be injury prone. Health promotion programmes to reduce the incidence of injury among lower socioeconomic groups are needed since these have high rates of injury and the lowest rate of receipt of treatment.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".