Sociocultural determinants of children's oral health among immigrants in Canada
Bibliographic record
Abstract
OBJECTIVE: A conceptual model was designed and tested to predict immigrant children's oral health in Canada by examining parental acculturation and perceived social support (PSS) using structural equation modelling. METHODS: A convenience sample of first-generation immigrant parents and their children aged 2-12 years were recruited by multilingual community workers in Edmonton, Canada. Parents completed a validated questionnaire on demographics, child's oral health (OH) behaviours, parental acculturation and PSS. Dental examinations determined children's dental caries rate using DMFT/dmft index. Structural equation modelling (SEM) was used to analyse the data. RESULTS: A total of 336 families participated in this study. The average parental acculturation level was 10.46 with a maximum of 15, and the average PSS was 63.27 with a maximum of 75. SEM showed that 77% of the variance of DMFT/dmft scores in children was explained by parental PSS, acculturation level, immigration-related variables, socioeconomic variables and children's OH behaviours. The direct effect of parental PSS was associated with a significantly reduced rate of dental caries (β = -.076, p-value = .008) and lower sugar consumption (β = -.17, p-value = .04). While the mediation effect of parental acculturation on PSS was associated with positive OH behaviours of children (e.g., toothbrushing frequency and dental care utilization), the indirect effect was negatively associated with caries rate (β = .77, p-value = .00). CONCLUSIONS: The direct effect of Parental Perceived Stress Scale (PSS) was associated with more favourable oral health behaviours and a lower prevalence of dental caries, while the mediation effect of acculturation was linked to a higher prevalence of dental caries.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".