The Relationship of Higher Education to Substance Use Trajectories: Variations as a Function of Timing of Enrollment
Bibliographic record
Abstract
OBJECTIVE: This study examined the association between time to enrollment into postsecondary education and trajectories of heavy episodic drinking (HED) and marijuana use using a prospective longitudinal study. METHOD: Participants included 391 postsecondary students (55% female) drawn from the Victoria Healthy Youth Survey, a five-wave, multi-cohort sample interviewed biennially between 2003 and 2011. Using piecewise latent growth modeling, we compared changes in the trajectories of HED and marijuana use before and after postsecondary enrollment across three groups of young adults: (a) direct entrants (enrolled directly out of high school), (b) gap entrants (took a year off), and (c) delayed entrants (took longer than a year off). RESULTS: Heavy drinking increased after enrollment for direct entrants and gap entrants and decreased for delayed entrants. Marijuana use increased after enrollment for direct entrants, and decreased for gap entrants and delayed entrants. Yet, overall levels of marijuana use were significantly higher among the gap and delay entrants over time compared with direct entrants. Group differences in heavy drinking appeared to reflect age-related changes in drinking patterns. However, differences in marijuana use may reflect pre-existing inequities in access to higher education across groups. CONCLUSIONS: The association between postsecondary education and increased substance use may be limited to students who enroll at a postsecondary institution directly out of high school. However, students who delay enrollment have higher levels of substance use before enrollment, as well as lower high school grades and socioeconomic status compared with direct entrants, and may be particularly vulnerable to long-term substance use problems and degree noncompletion.
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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".