Pubertal Development and the Onset of Substance Use Among Appalachian Youth: A Longitudinal Study
Bibliographic record
Abstract
Objective: We investigated the links between pubertal timing and tempo and the onset of cannabis, alcohol, and tobacco use among middle schoolers in Appalachian communities. Methods: School surveys were administered to middle school students of the 6th grade and continuing through the spring of the 8th grade (n = 2,587; 49.4% boys), beginning in the fall at six-month intervals. Youth self-reported on their pubertal development and substance use. We examined the influence of baseline levels and rate of growth in puberty as predictors of substance use onset with Latent Growth Curve Modeling (LGCM), stratified by sex/gender. Results: Our findings show that early pubertal timing was associated with an increased likelihood for onset of cannabis and alcohol use for boys, but not girls; pubertal tempo was not associated with onset. Conclusion: Early pubertal development may be a risk factor for early-onset substance use for boys. Prevention programming beginning in the first year of middle school is recommended.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".