Over-the-Counter Drugs and Other Substances Used in Attempted Suicide Presented to Emergency Departments in Montreal, Canada
Bibliographic record
Abstract
Abstract. Background: Over-the-counter (OTC) analgesics are frequently used in suicide attempts. Accessibility, toxicity, and unsupervised acquisition of large amounts may be facilitators. Aims: To identify patient characteristics associated with OTC drug use as a suicide attempt method among adults. Method: A cross-sectional study was conducted using chart review of all individuals who presented to the emergency department (ED) of two adult general hospitals following a suicide attempt during 2009–2010 in Montreal, Canada. Results: Among the 369 suicide attempters identified, 181 used overdosing, 47% of whom used OTC drugs. In logistic regression, women and those with medical comorbidity were more likely to use overdosing, while those with substance use disorders were less likely to do so. Among those who overdosed, women were more likely to use OTC drugs, while those who were Caucasian, had children, comorbidities, diagnoses with substance use disorders, and made attempts in the Fall were less likely to do so. Substances most frequently used were: acetaminophen among OTC drugs (30%); antidepressants (37%), anxiolytics (30%), opioids (10%), and anticonvulsants (9%) among prescription drugs; and cocaine (10%) among recreational drugs. Limitations: Reasons for the suicide method choice were not available. Conclusion: OTC drugs, in particular acetaminophen, are frequently used in suicide attempts. Accessibility to these drugs may be an important contributor.
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 | 0.003 |
| 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) | 0.005 | 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".