Oral pain and its covariates: findings of a Canadian population-based study.
Bibliographic record
Abstract
OBJECTIVE: To describe the prevalence of oral pain in Canada and to identify its covariates. METHODS: Data were derived from the 2007-2009 Canadian Health Measures Survey. Data were analyzed for a total of 5284 respondents (2558 males, 2726 females) aged 6-79 years. The outcome variable was self-reported pain in the mouth in the past 12 months. Bivariate and multivariate analyses were used to investigate the relationship between oral pain and 4 sets of covariates: socio-demographic factors, dental service utilization, oral health behaviours and clinical oral health. RESULTS: Oral pain in the past 12 months was reported by 11.7% of respondents. Oral pain was slightly, but not significantly, more prevalent among females than males (13.6% vs. 10.0%). The lowest and highest prevalence of oral pain were reported by children and young adults, respectively. Multivariate analyses suggested that oral pain was significantly more prevalent among adolescents and adults, those in the lowest income groups, those who avoided a dental professional because of the cost and those with untreated decayed teeth. CONCLUSION: Canadians with financial barriers to accessing dental care and those with untreated dental decay were at risk of having dental pain. These findings have important implications for the provision of dental care in Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".