Prevalence, intensity and extent of Oral Impacts on Daily Performances associated with self-perceived malocclusion in 11-12-year-old children
Bibliographic record
Abstract
BACKGROUND: To determine the prevalence, intensity and extent of the Oral Impacts on Daily Performances associated with self-perceived malocclusion among Peruvian schoolchildren. METHODS: Eight hundred and five children aged 11 to 12 years attending 4 of 7 randomly selected schools linked to a Health Centre in Lima, Peru, participated in the study. The Spanish (Peru)Child-OIDP was used to assess the prevalence, intensity and extent of oral impacts on 8 daily performances (eating, speaking, teeth cleaning, sleeping, smiling, studying, emotion and social contact). Self-perceived malocclusion included complaints about position of teeth, spacing of teeth and deformity of mouth or face. The prevalence of oral impacts was compared by covariables using the Chi-square test, whereas the intensity and extent of oral impacts were compared by covariables through the Mann-Whitney test. RESULTS: Only 15.5% of children reported impacts associated with self-perceived malocclusion during the last 3 months. Of them, 18.4% reported impacts of severe or very severe intensity and 76.0% reported impacts on only one daily performance. Psychosocial activities such as smiling, emotion and social contact were the most frequently and severely impacted everyday activities. CONCLUSION: Impacts of self-perceived malocclusion primarily affected psychological and social everyday activities. These findings provide further evidence to support the importance of psychological and social components of oral health on children's lives.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".