Adolescent Alcohol Use Trajectories: Risk Factors and Adult Outcomes
Bibliographic record
Abstract
OBJECTIVES: Adolescents often display heterogenous trajectories of alcohol use. Initiation and escalation of drinking may be important predictors of later harms, including alcohol use disorder (AUD). Previous conceptualizations of these trajectories lacked adjustment for known confounders of adolescent drinking, which we aimed to address by modeling dynamic changes in drinking throughout adolescence while adjusting for covariates. METHODS: = 1813) were used to model latent class alcohol use trajectories over 5 annual follow-ups (mean age = 13.9 until 17.8 years). Regression models were used to determine whether child, parent, and peer factors at baseline (mean age = 12.9 years) predicted trajectory membership and whether trajectories predicted self-reported symptoms of AUD at the final follow-up (mean age = 18.8 years). RESULTS: = 295). Having more alcohol-specific household rules reduced risk of early-onset heavy drinking compared with late-onset moderate drinking (relative risk ratio: 0.31; 99.5% confidence interval [CI]: 0.11-0.83), whereas having more substance-using peers increased this risk (relative risk ratio: 3.43; 99.5% CI: 2.10-5.62). Early-onset heavy drinking increased odds of meeting criteria for AUD in early adulthood (odds ratio: 7.68; 99.5% CI: 2.41-24.47). CONCLUSIONS: Our study provides evidence that parenting factors and peer influences in early adolescence should be considered to reduce risk of later alcohol-related harm. Early initiation and heavy alcohol use throughout adolescence are associated with increased risk of alcohol-related harm compared with recommended maximum levels of consumption (late-onset, moderate drinking).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".