Cannabis use disorder trajectories and their prospective predictors in a large population‐based sample of young Swiss men
Bibliographic record
Abstract
BACKGROUND AND AIMS: Cannabis use disorder (CUD) is frequent in adolescence and often goes into remission towards adulthood. This study aimed to estimate trajectories of CUD severity (CUDS) in Swiss men aged from 20 to 25 years and to identify prospective predictors of these trajectories. DESIGN: Latent class growth analysis of self-reported CUDS in a cohort study with three data collection waves. SETTING: A general population sample of young Swiss men. PARTICIPANTS: A total of 5987 Swiss men assessed longitudinally at the mean ages of 20, 21.5 and 25 years. MEASUREMENTS: Latent CUDS in the last 12 months was measured at each wave with the Cannabis Use Disorders Identification Test-Revised (CUDIT-R). Predictors of CUDS trajectories, measured at age 20, were from six domains: factors related to cannabis use, family, peers, other substance use, mental health and personality. FINDINGS: We distinguished four CUDS trajectories: stable-low (88.2%), decreasing (5.2%), stable-high (2.6%) and increasing (4.0%). Predictors were generally associated with higher odds of membership in the decreasing and stable-high trajectory (versus the stable-low), and to a lesser degree with higher odds of membership in the increasing trajectory. Bivariate predictors of persistent high CUDS (stable-high versus decreasing trajectory) were major depression severity [odds ratio (OR) = 1.19, 95% confidence interval (CI) = 1.01, 1.40], attention deficit hyperactivity disorder severity (OR = 1.25, 95% CI = 1.04, 1.51), antisocial personality disorder severity (OR = 1.18, 95 % CI = 1.04, 1.34), relationship with parents (OR = 0.74, 95% CI = 0.63, 0.88), number of friends with drug problems (OR = 1.33, 95% CI = 1.11, 1.60) and the personality dimensions neuroticism-anxiety (OR = 1.35, 95% CI = 1.11, 1.65) and sociability (OR = 0.78, 95% CI = 0.62, 0.97). CONCLUSIONS: Factors associated with persistent cannabis use disorder in young Swiss men include cannabis use, cannabis use disorder severity, mental health problem severity, relationship with parents (before the age of 18), peers with drug problems and the personality dimensions neuroticism-anxiety and sociability at or before age 20. Effect sizes may be small, and predictors are mainly associated with persistence via higher severity at age 20 years.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".