Early childhood factors in the development of oral health behaviours in adolescence: A structural equation modelling approach
Bibliographic record
Abstract
OBJECTIVES: Oral health behaviour is a learning process that begins in the early years of an individual's life. The aim of this study was to evaluate the associations between demographic, socioeconomic, and psychosocial factors and oral health behaviours during the transition period from childhood to adolescence. METHODS: This was a cohort study with a follow-up of 7 years. The baseline assessment occurred in 2010 with a random sample of 639 preschool children from southern Brazil. Demographic, socioeconomic and psychosocial oral health conditions were assessed at baseline. Oral health habit variables were collected at follow-up and included questions regarding dental care and oral hygiene behaviours. Structural equation modelling was performed to assess the direct and indirect relationships between predictors at baseline in oral health behaviours at follow-up. RESULTS: A total of 449 children were re-examined at follow-up (70.3% cohort retention rate). Factors directly related to poorer oral health behaviours (lower use of dental services, dental visits for emergency reasons and lower frequency of toothbrushing) were lower household income, lower maternal education, lower frequency of visits to neighbours or friends, and male sex. Considering indirect pathways, the household income and maternal education at baseline influenced oral health behaviours at follow-up via visits to neighbours or friends. CONCLUSIONS: Our findings suggest that household income, maternal education and social capital play an important role in the development of oral health behaviours during the transition from childhood to adolescence. Acquisition of healthy oral behaviours is an important factor to consider in childhood. With this knowledge, public health policies can be developed to intervene in specific causal factors and improve oral health during this transitional period.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".