Prospective longitudinal associations between household smoke exposure in early childhood and antisocial behavior at age 12
Bibliographic record
Abstract
Young children exert little control over household tobacco smoke exposure, which is considered a developmental neurotoxicant. Using the Quebec Longitudinal Study birth cohort, we examine prospective associations between early childhood smoke exposure and later antisocial behavior. Parents of 1035 children reported on the presence of household smokers at seven follow-ups from ages 1.5 to 7.5. At age 12, children self-reported on five aspects of early antisocial dispositions. After adjusting for confounders, every standard deviation increase in household smoke exposure was prospectively associated with a 19% standard deviation unit increase in conduct problems (β=0.07; 95% confidence interval [CI] from 0.04 to 0.09), a 11% standard deviation unit increase in proactive aggression (β=0.04; 95% CI from 0.01 to 0.07), a 13% standard deviation unit increase in reactive aggression (β=0.07; 95% CI from 0.03 to 0.12), a 14% standard deviation unit increase in school indiscipline (β=0.13; 95% CI from 0.05 to 0.20), and a 10% standard deviation unit increase in dropout risk (β=0.07; 95% CI from 0.01 to 0.12). These long-term findings warrant fostering parental awareness of developmental risks by policy-makers/health practitioners. School curricula can equally integrate these ideas into their curriculum.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".