Preadolescent individual, familial, and social risk factors associated with longitudinal patterns of adolescent alcohol, cannabis, and other illicit drug use in a population-representative cohort.
Bibliographic record
Abstract
= 1,593; 48.4% male). Age 12-17 years self-reports of alcohol, cannabis, and other illicit drug use were collected. Latent growth modeling was used to analyze developmental patterns of single- or polysubstance use (SU/PSU), and multinomial regression examined their association with risk factors assessed at age 10-12 years. Five developmental patterns were revealed, including nonusers (12.8% sample) and four classes reflecting different levels of SU/PSU (5.8%-37.5%), varying in severity based on onset, frequency, and type of substances used. Boys and girls were similarly represented throughout SU/PSU patterns. In comparisons with nonusers, several preadolescent risk factors were associated with increasing severity of SU/PSU. Possibly indexing fearlessness/disinhibition, low internalizing symptoms were common to all adolescent users. An earlier onset of substance use and increasing use of substances throughout adolescence were linked with having deviant peers for all user classes but later-onset users. Preadolescents manifesting externalizing problems and exposed to family adversity in addition to the above risk factors showed the earliest onset and most frequent adolescent SU/PSU, especially those also exposed to less appropriate parenting. Consistent with the developmental model of substance use, the nature, number, and severity of preadolescent risk factors distinguished between the type and severity of SU/PSU patterns in adolescence and call for a consistent strategy of universal, selective, and indicated preventive interventions. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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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 | 0.000 |
| 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".