Association between severe unaddressed dental needs and developmental health at school entry in Canada: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Dental problems are the most prevalent chronic disease worldwide, with up to half of all kindergarten children having tooth decay. However, there is a lack of evidence of whether unaddressed dental needs (UDNs) are associated with children's developmental health, a concept reflecting holistic child development - encompassing physical, emotional, and cognitive development. The objective of the current study was to evaluate the relationship between UDNs and developmental health among kindergarten children using the Early Development Instrument (EDI). METHODS: We examined associations between teacher reported UDNs and developmental vulnerability on the EDI. Children were included in the study if they were enrolled in kindergarten in publicly-funded schools in Canada between 2010 and 2015, had been in the classroom for at least one month, and had no more than 25% of missing items on the questionnaire. RESULTS: Among 576,264 children who met inclusion criteria (95.4% of eligible children), 2465 (0.4%) were identified as having UDNs by their teachers. Children with UDNs had 4.58 to 8.27 times higher odds of being vulnerable on any of the five developmental domains (physical health and well-being, social competence, emotional maturity, language and cognitive development, communication skills and general knowledge), compared to children without UDNs. CONCLUSION: In this study, teacher-reported UDNs were associated with developmental vulnerability in kindergarten children. Teacher reported unmet dental needs in kindergarten children may be a proxy for poor developmental health at school entry, and thus a marker for supporting both children's oral health and early developmental needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".