Protective roles of home and school environments for the health of young Canadians
Bibliographic record
Abstract
BACKGROUND: The relationships of home and school environments, health risk behaviours and two sentinel adolescent health outcomes were examined in an aetiological analysis. The analysis focused on determinants of the health of young people and the role of school settings in the optimisation of health. METHODS: Records were examined from the Canadian sample of the Health Behaviour in School-aged Children (HBSC) Survey. 3402 young people in Ontario, Canada were administered this survey in 2006, of which 1966 were re-administered the survey 1 year later and supplied complete data. Individual items and factor-analytically derived scales were used to examine potential aetiological relationships in a series of structural equation models. Health outcomes examined were serious injury and psychosomatic symptoms. Models developed from cross-sectional data were confirmed longitudinally. RESULTS: Adolescents who reported negative home and school environments reported higher levels of substance use, psychosomatic symptoms and serious injuries (the latter identified in longitudinal analysis only). Engagement in health risk behaviour partially mediated the link between these two environments and the sentinel health outcomes. Positive school environments were protective in that they moderated associations between negative home environments and engagement in health risk behaviours. The effects observed in longitudinal analyses were generally consistent with those observed cross-sectionally. CONCLUSIONS: Negative home environments clearly place adolescents at risk for engagement in health risk behaviours and associated physical health outcomes. Positive school environments can in part moderate these relationships. Optimisation of school social environments therefore remains warranted as a population health strategy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".