Licit and illicit substance use among people who inject drugs and the association with subsequent suicidal attempt
Bibliographic record
Abstract
AIM: To estimate associations between recent licit and illicit substance use and subsequent suicide attempt among people who inject drugs (PWID). DESIGN: Secondary analysis of longitudinal data from a prospective cohort study of PWID followed bi-annually between 2004 and 2011. SETTING: Montréal, Canada. PARTICIPANTS: Seven hundred and ninety-seven PWID who reported injection drug use in the previous 6 months, contributing to a total of 4460 study visits. The median number of visits per participant was five (interquartile range: 3-8). MEASUREMENTS: An interviewer-administered questionnaire eliciting information on socio-demographic factors, detailed information on substance use patterns and related behaviours, mental health markers and suicide attempt. The primary exposure variables examined were past-month use of alcohol [heavy (≥ 60 drinks); moderate (one to 59 drinks); none], sedative-hypnotics, cannabis, cocaine, amphetamine and opioids [regular (≥ 4 days); occasional (1-3 days); none]. The outcome was a binary measure of suicide attempt assessed in reference to the previous 6 months. FINDINGS: In multivariate analyses, a positive association was found among licit substances between heavy alcohol consumption [adjusted odds ratio (AOR) = 2.05; 95% confidence interval (CI) = 1.12-3.75], regular use of sedative-hypnotics (AOR = 1.89; 95% CI = 1.21-2.95) and subsequent attempted suicide. Among illicit substances, occasional use of cannabis (AOR = 1.84; 95% CI = 1.09-3.13) had a positive association with subsequent suicide attempt. No statistically significant association was found for the remaining substances. CONCLUSION: Among people who inject drugs, use of alcohol, sedative-hypnotics and cannabis, but not cocaine, amphetamine or opioids, appears to be associated with an increased likelihood of later attempted suicide.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".