Individual, social, and environmental factors associated with initiating methamphetamine injection : implications for drug use and HIV prevention strategies
Bibliographic record
Abstract
The purpose of this study was to determine the incidence and predictors of initiating methamphetamine injection among a cohort of injection drug users (IDU). We conducted a longitudinal analysis of IDU participating in a prospective study between June 2001 and May 2008 in Vancouver, Canada. IDU who had never reported injecting methamphetamine at the study's commencement were eligible. We used Cox proportional hazards models to identify the predictors of initiating methamphetamine injection. The outcome was time to first report of methamphetamine injection. Time-updated independent variables of interest included sociodemographic characteristics, drug use patterns, and social, economic and environmental factors. Of 1317 eligible individuals, the median age was 39.9 and 522 (39.6%) were female. At the study's conclusion, 200 (15.2%) participants had initiated injecting methamphetamine (incidence density: 4.3 per 100 person-years). In multivariate analysis, age (adjusted hazard ratio [aHR]: 0.96 per year older, 95%CI: 0.95-0.98), female sex (aHR: 0.58, 95%CI: 0.41-0.82), sexual abuse (aHR: 1.63, 95%CI: 1.18-2.23), using drugs in Vancouver's drug scene epicentre (aHR: 2.15 95%CI: 1.49-3.10), homelessness (aHR: 1.43, 95%CI: 1.01-2.04), non-injection crack cocaine use (aHR: 2.06, 95%CI: 1.36-3.14), and non-injection methamphetamine use (aHR: 3.69, 95%CI: 2.03-6.70) were associated with initiating methamphetamine injection. We observed a high incidence of methamphetamine initiation, particularly among young IDU, stimulant users, homeless individuals, and those involved in the city's open drug scene. These data should be useful for the development of a broad set of interventions aimed at reducing initiation into methamphetamine injection among IDU.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".