Impact of dental health on children’s oral health-related quality of life: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: To assess the impact of children's dental health status (DHS) on their oral health-related quality of life (OHRQoL). METHODS: Participants were 11- and 12-year-old children attending public schools in the Kuwait Capital Region. Children's DHS was evaluated by clinical examinations and presented using decayed, missed, filled teeth/surface (DMFT/dmft, DMFS/dmfs); restorative (RI), plaque (PI); and pulp, ulcers, fistula, abscess (PUFA) indices. Children's OHRQoL was assessed using Child's Perception Questionnaire 11-14 (CPQ11-14). Means (SD) and frequencies were used for data description. Different factors were analyzed as predictors of OHRQoL by logistic regression analysis. RESULTS: A total of 440 children aged 11-12 years (50.7 % females) participated in this cross-sectional study. Mean (SD) DMFT/dmft, RI, PI, and PUFA scores were 2.91(2.75), 0.21 (0.34), 3.59 (1.63), 0.31 (0.85), respectively. The mean total CPQ11-14 was 20.72 (16.81). Mean scores of oral-symptoms, functional-limitations, emotional and social well-being were 4.26 (3.32), 5.40 (4.92), 5.48 (6.15), and 5.33 (6.05), respectively. Children with more than four fillings were 95 % less likely to have had oral symptoms than those with no fillings. Children with a DMFT/dmft of 2-3 were 2.8 times more likely to have functional limitation than those with a DMFT/dmft of 0, while children with a DMFT/dmft of more than 4 were 4.4 times more likely to experience limitations. Having two or three non-cavitated lesions reduced the odds of having functional-limitation by 58 %. Children with more than four missing teeth were 45 % more likely to experience emotional stress. Having more than four fissure sealants reduced the odds of having emotional stress by 46 %. CONCLUSIONS: The increase in the number of carious teeth was associated with a limitation in oral functions. Preventive treatment had a positive impact on children's emotional well-being and restorative treatments improved their oral function.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".