Sentinel surveillance of substance-related self-harm in Canadian emergency departments, 2011 − 19
Bibliographic record
Abstract
INTRODUCTION: Self-harm is a public health concern that can result in serious injury or death. This study provides an overview of emergency department (ED) visits for patients presenting with substance-related self-harm. METHODS: Cases of self-harm in the electronic Canadian Hospitals Injury Reporting and Prevention Program (eCHIRPP) database were extracted (April 2011 to September 2019; N = 15,682), using various search strategies to identify substance-related self-harm cases for patients 10 years and older. Cases involving alcohol, cannabis, illicit drugs, or medications (or any combinations of these) were included. Additional variables, including age and sex, location and the severity of injury (hospital admission) were examined. Proportionate injury ratios (PIR) were used to compare emergency department outcomes of self-harm and unintentional injuries involving substance use. Time trends were quantified using Joinpoint regression. For cases requiring hospital admission, text fields were analyzed for contextual factors. RESULTS: A total of 9470 substance-related self-harm cases were reported (28.1% of all intentional injury cases), representing 820.0 records per 100,000 eCHIRPP records. While age patterns for both sexes were similar, the number of cases for females was significantly higher among 15-19 year olds. Over half (55%) of cases that identified substance type involved medications, followed by multi-type substance use (19.8%). In the ED, there were proportionally more treatments, observations, and admissions presenting with substance-related self-harm compared to substance-related unintentional injury cases. Among those aged 20+ years, a statistically significant increasing trend of 15.9% per year was observed, while among those aged 10-19 years a significant annual percent change of 16.9% was noted (2011 to 2019). Text field analysis demonstrated suicide attempt or ideation was a reoccurring theme among all age groups. Poor mental health status or conflict with family or an intimate partner were reported stressors, depending on age group. Additional self-harming injuries, such as cutting, were reported among all age groups. CONCLUSION: Our study found that hospital admission for substance-related self-harm was highest for patients aged 15-19 years, especially females, and that they were more likely to use medications. The statistically significant increasing trend of cases found between 2011 and 2019 is notable. Patients showed multiple types of adversities, demonstrating the complexity of this issue.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".