Alcohol Use Growth Trajectories in Young Adolescence: Pathways and Predictors
Bibliographic record
Abstract
New analytical tools have facilitated the exploration of the trajectories of alcohol use; however, there are a limited number of studies that explore early adolescence. A sample of 5,903 youths followed from sixth through eighth grade was used to (1) examine the trajectories of alcohol use and (2) determine the degree to which common correlates predicted these trajectories. Our models provided the most support for a four trajectory group solution with nearly half of the sample (49.3%) largely abstaining, more than a quarter of the sample (29.4%) experimenting and exhibiting small increases, 15.0% initiating early and exhibiting a consistent level of low use, and a small percentage (6.3%) rapidly progressing to a heavy level of drinking across the three-year period. Perceived behavioral control was the most consistent predictor of trajectory type, but peer norms and positive attitudes toward alcohol also played a role. The implications and limitations of these findings are discussed.
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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 | 0.005 |
| 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 | 0.000 | 0.001 |
| 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".