Crystal methamphetamine initiation among street-involved youth
Bibliographic record
Abstract
Background: Although many settings have recently documented a substantial increase in the use of methamphetamine-type stimulants, recent reviews have underscored the dearth of prospective studies that have examined risk factors associated with the initiation of crystal methamphetamine use. Objectives: Our objectives were to examine rates and risk factors for the initiation of crystal methamphetamine use in a cohort of street-involved youth. Methods: Street-involved youth in Vancouver, Canada, were enrolled in a prospective cohort known as the At-Risk Youth Study (ARYS). A total of 205 crystal methamphetamine-naïve participants were assessed semi-annually and Cox regression analyses were used to identify factors independently associated with the initiation of crystal methamphetamine use. Results: Among 205 youth prospectively followed from 2005 to 2012, the incidence density of crystal methamphetamine initiation was 12.2 per 100 person years. In Cox regression analyses, initiation of crystal methamphetamine use was independently associated with previous crack cocaine use (adjusted relative hazard [ARH] = 2.24 [95% CI: 1.20–4.20]) and recent drug dealing (ARH = 1.98 [95% CI: 1.05–3.71]). Those initiating methamphetamine were also more likely to report a recent nonfatal overdose (ARH = 3.63 [95% CI: 1.65–7.98]) and to be male (ARH = 2.12 [95% CI: 1.06–4.25]). Conclusions: We identified high rates of crystal methamphetamine initiation among this population. Males those involved in the drug trade, and those who used crack cocaine were more likely to initiate crystal methamphetamine use. Evidence-based strategies to prevent and treat crystal methamphetamine use are urgently needed.
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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 | 0.001 |
| 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 | 0.000 |
| 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".