Gender and the first‐time provision of injection initiation assistance among people who inject drugs across two distinct North American contexts: Tijuana, Mexico and Vancouver, Canada
Bibliographic record
Abstract
INTRODUCTION: Injection drug use initiation is commonly facilitated by other people who inject drugs (PWID). We investigated how the gender of PWID influences their risk of providing initiation assistance to others across two distinct geo-cultural settings. METHODS: Data were drawn from two prospective cohorts in Tijuana, Mexico and Vancouver, Canada which conducted semi-annual interviews within the PReventing Injecting by Modifying Existing Responses (PRIMER) study. Participants consisted of PWID who had reported never providing injection initiation assistance at baseline. We then conducted site-specific discrete-time survival analyses assessing the relationship between gender and other relevant covariates (e.g. age and past 6-month sex work) on the risk of the first reported instance of providing initiation assistance. RESULTS: Of 1988 PWID (Tijuana: n = 596; Vancouver: n = 1392), 256 (43%) and 511 (36.7%) participants were women, and 42 (1.7%) and 78 (1.6%) reported recent injection initiation assistance across a median of three and two follow-up visits, respectively. Women had a lower risk of providing injection initiation assistance for the first time in Tijuana (adjusted hazard ratio = 0.52, 95% confidence interval 0.27-0.99), but not in Vancouver. Gendered pathways, like sex work, were associated with providing initiation assistance for the first time in Vancouver (adjusted hazard ratio = 1.97, 95% confidence interval 1.08-3.61). DISCUSSION AND CONCLUSIONS: Women in Tijuana, but not Vancouver, were less likely to provide first-time initiation assistance among PWID. These results can inform gender- and site-specific prevention efforts aimed at reducing transitions into drug injecting across geographic contexts.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".