Associations between the self-reported happy home lives and health of Canadian school-aged children: An exploratory analysis with stratification by level of relative family wealth.
Bibliographic record
Abstract
BACKGROUND: Connections between home life, level of family wealth, happiness and health are strong, yet these relationships are complex and for Canadian adolescents not well studied. The objective of this investigation was to explore associations between aspects of health and self-reported happy home life among Canadian adolescents aged 10-16 years and to determine if level of self-reported relative family wealth modified associations. MATERIAL AND METHODS: This was a secondary analysis of Canadian data from the 2018 Health Behaviour in School-aged Children (HBSC) study (n=21,745). Theory drove the selection of 26 health-related HBSC variables. Bivariate analyses and calculation of adjusted odds ratios, considering level of self-reported relative family wealth in a stratified analysis, were undertaken. RESULTS: Overall, proximal, micro-level factors were most strongly associated with reports of a happy home life, with distal, macro-level factors less strongly associated. Differences existed between the health and home-life associations for adolescents of different levels of self-reported relative family wealth indicating effect modification. Family support and levels of adolescent self-reported overall health and mental health were common factors that were strongly associated with reporting a happy home life. CONCLUSION: We believe happy home lives are central and critical for thriving youth and families. This was an exploratory analysis. Many of the factors and relationships in this study are potentially modifiable and represent important possible areas of future focus for adolescent and family health improvement.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".