Binge Drug Injection in a Cohort of People Who Inject Drugs in Montreal: Characterizing the Substances and Social Contexts Involved
Bibliographic record
Abstract
We describe binge drug injection in a longitudinal cohort study of people who inject drugs (PWID) in Montreal, Canada (eligibility: age ≥ 18, past-6-month injection drug use; follow-up: 3-monthly interviews). Bingeing was defined as injecting large quantities of drugs over a limited period, until participants ran out or were unable to continue, in the past 3 months. We recorded substances and circumstances typically involved in binge episodes. Eight hundred five participants (82% male, median age 41) provided 8158 observations (2011-2020). Thirty-six per cent reported bingeing throughout follow-up. Binges involved a diverse range of substances and social contexts. Cocaine was involved in a majority of recent binges (73% of visits). Injection of multiple drug classes (24% of visits) and use of non-injection drugs (63% of visits) were common, as were opioid injection (42%) and injecting alone (41%). Binge drug use may thus be an important yet overlooked trigger of overdose and other harms among PWID. This understudied high-risk behavior warrants further research and public health attention. Supplementary Information: The online version contains supplementary material available at 10.1007/s11469-023-01207-7.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".