Associations between household educational attainment and adolescent positive mental health in Canada
Bibliographic record
Abstract
, is a new research direction with important implications for population health promotion. Past research suggests that mental health develops in early childhood and that social factors including highest household educational attainment may play an important role. The current study examined the association between household educational attainment and adolescent self-reported positive mental health in a nationally representative Canadian sample using data from the 2011-12 Canadian Community Health Survey. The sample included 10,091 adolescents aged 12 to19 living at home with at least one parent. Household educational attainment was obtained from a Statistics Canada derived variable documenting the highest level of education in the household. Adolescent positive mental health was assessed using the Mental Health Continuum scale. Multivariable logistic regression analyses showed that after adjusting for household income, single parent status, and household size, adolescents had lower odds of experiencing positive mental health in households in which attempted but not completed post-secondary was the highest education level compared to completed post-secondary education (OR = 0.64, 95% CI = 0.44, 0.95). This association was strongest in adolescents aged 12 to14 (OR = 0.43, 95% CI = 0.21, 0.84) and females (OR = 0.50, 95% CI = 0.29, 0.88). Contrary to expectations, we did not find an incremental increasing association between adolescent positive mental health and household educational attainment. Instead, results suggested that common underlying factors may have contributed both to uncompleted post-secondary education in the household and adolescents' diminished positive mental health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".