Childhood behaviours and adverse economic and social outcomes – can we improve detection and prevention?
Bibliographic record
Abstract
Introduction Disruptive behaviours underpin the most prevalent and costly psychiatric disorders in youth including ADHD and conduct disorder. Yet the association between childhood behavioural problems and economic and social outcomes in adulthood are rarely examined in a population-based samples where early detection and prevention may be possible. Objectives To examine the association childhood behavioural problems and economic and social outcomes from age 18-35 years across three studies. Methods This study daws on 30-year Canadian birth cohort (n=3017) linked to government tax return records. Behavioural assessments – for inattention, hyperactivity, opposition, aggression, anxiety and prosociality – were prospectively obtained from teachers when children were aged 6-12 years. Regression models were used to link behavioural assessments in kindergarten (age 5/6 years) to earnings at age 33-35 years (Study 1) and to trajectories of welfare receipt (Study 2), while behaviour at age 10-12 years was linked to trajectories of partnering. Children’s IQ and family background were adjusted for. Results Inattention, aggression-opposition (males only) and low low-prosociality in kindergarten were associated with lower earnings at age 33-35 years (Study 1), inattention, aggression-opposition and low prosociality in kindergarten predicted following a chronic welfare receipt trajectory from age 18-35 (Study 2), and inattention, aggression-opposition, anxiety and low-prosociality at age 10-12 years were associated with increased likelihood of being unpartnered and with partnership dissolution from age 18-35 years (Study3). Conclusions Behavioural assessments made by schoolteachers can identify children at risk of adverse economic and social outcomes in adulthood. The implications of for early screening and prevention will be discussed. Disclosure No significant relationships.
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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 | 0.012 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".