Non-Injection Drug Use Patterns and History of Injection among Street Youth
Bibliographic record
Abstract
AIMS: Efforts to prevent youth from initiating injection drug use require an understanding of the drug use patterns that predispose to injecting. Here we identify such patterns and describe the circumstances of first injection among street youth. METHODS: From October 2005 to November 2007, data were collected for the At Risk Youth Study, a prospective cohort of 560 street-recruited youth aged 14-26 in Vancouver, Canada. Non-injection drug use behaviors were compared between those with and without a history of injection through multiple logistic regression. The circumstances of first injection were also examined in gender-stratified analyses. RESULTS: Youth who had previously injected were more likely to have engaged in non-injection use of heroin or of crystal methamphetamine. Daily users of marijuana were less likely to have injected. Among prior injectors, the median age of first injection was lower among females. Females were also more likely to have had a sexual partner present at first injection and to have become a regular injector within one week of initiation. CONCLUSION: Preventing transition to injection among street youth may require special attention to predisposing drug use patterns and should acknowledge gender differences in the circumstances of first injection.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".