357 – Characteristics of Earliest and Most Recent Injection Drug Use in a Canadian Low-threshold Methadone Maintenance Treatment Sample
Bibliographic record
Abstract
Introduction: Despite evidence that the majority of injection drug users (IDU) are polysubstance users and tend to have extensive substance use histories at time of first injection, little is known about the patterns of substance use associated with injection initiation. Aims/objectives: To determine how injection drug use was associated with specific patterns of multiple substance use. Both concurrent (any use during a defined time period) and simultaneous (same session) polysubstance use patterns were assessed. Methods: IDU receiving treatment at a low-threshold methadone maintenance clinic in Halifax, Nova Scotia, Canada completed structured interviews regarding their substance use histories. Results: Injection coincided with: concurrent heavy alcohol use; increasing use of stimulants such as cocaine; and the introduction of misused prescription medications. During their most recent injection session, participants were significantly less likely to inject a stimulant, and were significantly more likely to identify an opioid as their primary drug of injection, when compared to injection initiation. Moreover, alcohol was more likely to be co-administered at time of first-ever injection, whereas prescription sedatives and crack cocaine were more likely to be co-administered during the most recent injection. Conclusions: Initiation into injection tended to occur after an extensive and relatively consistent sequence of substance use. First ever and most recent injection drug use often occurred within a polysubstance context; however, the specific patterns of substance use changed with time. Findings suggest that specific patterns of multiple substance use may be appropriate targets for treatment and prevention of injection drug use.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.003 | 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".