Factors associated with changes in illicit opioid use during the COVID-19 pandemic among incarcerated people who use drugs in Quebec, Canada
Bibliographic record
Abstract
PURPOSE: People who use drugs (PWUD) have been disproportionately affected by the COVID-19 pandemic. This study aims to examine changes in illicit opioid use and related factors among incarcerated PWUD in Quebec, Canada, during the pandemic. DESIGN/METHODOLOGY/APPROACH: The authors conducted an observational, cross-sectional study in three Quebec provincial prisons. Participants completed self-administered questionnaires. The primary outcome, "changes in illicit opioid consumption," was measured using the question "Has your consumption of opioid drugs that were not prescribed to you by a medical professional changed since March 2020?" The association of independent variables and recent changes (past six months) in opioid consumption were examined using mixed-effects Poisson regression models with robust standard errors. Crude and adjusted risk ratios with 95% confidence intervals (95% CIs) were calculated. FINDINGS: A total of 123 participants (median age 37, 76% White) were included from January 19 to September 15, 2021. The majority (72; 59%) reported decreased illicit opioid consumption since March 2020. Individuals over 40 were 11% less likely (95% CI 14-8 vs 18-39) to report a decrease, while those living with others and with a history of opioid overdose were 30% (95% CI 9-55 vs living alone) and 9% (95% CI 0-18 vs not) more likely to report decreased illicit opioid consumption since March 2020, respectively. ORIGINALITY/VALUE: The authors identified possible factors associated with changes in illicit opioid consumption among incarcerated PWUD in Quebec. Irrespective of opioid consumption patterns, increased access to opioid agonist therapy and enhanced discharge planning for incarcerated PWUD are recommended to mitigate the harms from opioids and other drugs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".