Early cannabis initiation: Substance use and mental health profiles of service‐seeking youth
Bibliographic record
Abstract
INTRODUCTION: Early cannabis use is associated with mental health and substance use (MHSU) challenges into adulthood. Given the vulnerability of youth who use cannabis, it is important to understand their clinical profiles and markers of risk. This cross-sectional descriptive study examines youth who began using cannabis during early adolescence compared to those who initiated at an older age. METHODS: 634 youth and emerging adults (age M = 19.5, SD = 2.3; 46.5% female) were assessed at intake in a Canadian youth mental health and concurrent disorder out-patient service. Measures of demographic characteristics and MHSU were compared for youth who initiated cannabis use under the age of 14 versus 14 years or over. RESULTS: Nearly 30% of youth initiated cannabis use before age 14. Those who initiated cannabis early were younger and had distinct psychosocial risk factors. They were more likely to use cannabis (p = .005), tobacco (p = .006), powder cocaine (p = .030), and/or benzodiazepines (p = .033) at a high frequency. If they used other substances, they were more likely to have begun using them younger (all p < .001). Early initiators had more externalizing mental health symptoms (p = .024), crime/violence concerns (p < .001), and past trauma (p = .001). CONCLUSIONS: Distinct, clinically meaningful differences emerged between youth who initiated cannabis use early versus later. Early cannabis use is associated with multiple, overlapping needs. Cannabis use and concurrent MHSU should be systematically assessed from an early age, and prevention/promotion efforts should take early onset into account.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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".