Disparities in oral health‐related quality of life in a population of Canadian children
Bibliographic record
Abstract
OBJECTIVES: To assess socioeconomic disparities in the oral health-related quality of life in a group of Canadian children. METHODS: Data were obtained as part of a study designed to assess the functional and psychosocial impact of traumatic dental injury. Clinical data were collected on a random sample of children during a school-based dental screening program that included measures of dental decay experience, treatment needs, dental trauma, fluorosis, and malocclusion. Children with dental trauma and a comparison group of trauma-free children were selected for follow-up. Their parents were mailed a questionnaire concerning the child's personal and family characteristics. Also enclosed was a questionnaire for the child that contained a short form of the Child Perceptions Questionnaire (CPQ) 11-14. Bivariate and multivariate analyses were undertaken to determine whether there were disparities in oral health-related quality of life according to household income. RESULTS: Complete data were collected from 370 children. Mean CPQ11-14 scores showed a gradient across income categories with children from low income households having poorer oral health-related quality of life. Children from households containing only one adult also had higher scores than children living with two or more adults. In both linear and logistic regression analyses household income and family structure remained significant predictors of CPQ11-14 scores after controlling for oral disease variables. Further analyses suggested that oral disorders had little impact on the health-related quality of life of higher income children but a marked impact on lower income children. The highest mean CPQ11-14 scores were observed among low income children with the more severe levels of oral disease. CONCLUSION: The data indicate that in this group of children there were socioeconomic disparities in oral health-related quality of life. A potential explanation may be differences in psychological assets and psychosocial resources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".