Alcohol and other drugs in suicide in Canada: opportunities to support prevention through enhanced monitoring
Bibliographic record
Abstract
The use of alcohol and other drugs has been identified as a significant factor related to suicide through multiple pathways. This paper highlights current understanding of their contributions to suicide in Canada and identifies opportunities for enhancing monitoring and prevention initiatives. Publications from 1998 to 2018 about suicide in Canada and that referred to alcohol or other drugs were identified using PubMed and Google Scholar. A second literature search restricted to articles including results of toxicology testing was conducted by a librarian. We summarised the literature identified on ecological analyses, attributable fractions and deaths, and research including the results of toxicological analyses. Our literature search yielded 5230 publications, and 164 documents were identified for full-text screening. We summarised the findings from 30 articles. Ecological analyses support the association between alcohol sales, annual per capita alcohol consumption and suicide rates. Based on published estimates, approximately a quarter of suicide deaths in Canada are alcohol-attributable, while the estimated attributable fraction for illegal drugs is more variable. Finally, there is a dearth of literature examining the role of acute alcohol and/or drug consumption prior to suicide based on toxicological findings. The proportion of suicide decedents with drugs or alcohol present at the time of death varies widely. While there is evidence on the role of alcohol and drugs in suicide deaths, there is not a large body of research about the acute use of these substances at the time of death among suicide decedents in Canada. Our understanding of the role of alcohol and other drugs in suicide deaths could be enhanced through systematic documentation, which in turn could provide much needed guidance for clinical practice, prevention strategies and policy initiatives.
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 | 0.011 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.010 | 0.014 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".