Do Childhood Conduct Problems Predict Negative Outcomes in Adolescence? A Longitudinal Analysis
Bibliographic record
Abstract
The primary purpose of this study was to conduct a prospective examination of the relationship between childhood conduct problems and five outcomes in adolescence– namely, Physically violent offenses; Non-violent offenses; Deviant lifestyle; Consumption of tobacco, cannabis, or alcohol; and Meeting the symptom count diagnostic criteria for Conduct Disorder (CD) – while controlling for a series of sociodemographic factors, family characteristics and adolescent experiences. Logistic regression analyses were used to determine if childhood conduct problems in the Canadian National Longitudinal Survey of Children and Youth (NLSCY) Cycle 1 contributed to negative outcomes in adolescence in NLSCY Cycle 4. This was a prospective, population-based study of 3,725 adolescents (12-15 years old) in the NLSCY Cycle 4 (2000-2001) who were 6-9 years old in NLSCY Cycle 1 (1994-95). Childhood conduct problems were found to be associated with Non-violent offenses and Consumption of tobacco, cannabis, or alcohol in adolescence, but they were not found to be associated with Physically violent offenses or Deviant lifestyle in adolescence. Furthermore, children with conduct problems before the age of 10 were more likely to meet the symptom count diagnostic criteria for CD in adolescence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".