Association between Binge Drug use and Suicide Attempt among People who Inject Drugs
Bibliographic record
Abstract
BACKGROUND: People who inject drugs (PWID) have an elevated risk of suicide attempt. Although different substances are associated with suicide attempt, the overall risk posed by binge behavior, a high-risk pattern of drug use, remains unclear. The objective of this study is to assess the association between binge drug use and suicide attempt in a prospective cohort of PWID in Montreal, Canada. METHODS: Participants answered a biannual interviewer-administered questionnaire compiling information on sociodemographics, pattern of substance use (cocaine, amphetamine, opioids, sedative-hypnotics, alcohol, and cannabis), and psychosocial stressors and related markers. The relationship between suicide attempt and binge behavior was modeled using generalized estimating equations (GEEs), controlling for type and pattern of substance use, sociodemographic characteristics, and significant mental health markers. RESULTS: Among 1240 participants (mean age ± SD: 38.2 ± 9.8) at baseline, 222 (17.9%) reported binge during the past 6-months. PWID reporting binge were significantly younger (P < .001), less educated (P = .012), less likely male (P = .047), and had shorter history of injection (P < .001). In addition, they were younger at first injection (P = .014), reported higher rates of prostitution and psychological disorders (P = .003), and were more likely to use other drugs except cannabis and alcohol. Binge was independently associated with attempted suicide in the GEE multivariate model (adjusted odds ratio [aOR 95% CI] = 1.91 [1.38-2.65], P < .001). CONCLUSIONS: Among PWID at high risk of suicide attempt, those who binge represent a particularly vulnerable subgroup. Although the exact mechanisms underlying this finding remain unresolved, several hypothesis pertaining to the neurobiological and psychosocial consequences of binge, as well as common personality traits, warrant further investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".