Accidental substance-related acute toxicity deaths among youth in Canada: a descriptive analysis of a national chart review study of coroner and medical examiner data
Bibliographic record
Abstract
INTRODUCTION: Substance-related acute toxicity deaths (ATDs) are a public health crisis in Canada. Youth are often at higher risk for substance use due to social, environmental and structural factors. The objectives of this study were to understand the characteristics of youth (aged 12-24 years) dying of accidental acute toxicity in Canada and examine the substances contributing to and circumstances surrounding youth ATDs. METHODS: Data from a national chart review study of coroner and medical examiner data on ATDs that occurred in Canada between 2016 and 2017 were used to conduct descriptive analyses with proportions, mortality rates and proportionate mortality rates. Where possible, youth in the chart review study were compared with youth in the general population and youth who died of all causes, using census data. RESULTS: Of the 732 youth who died of accidental acute toxicity in 2016-2017, most (94%) were aged 18 to 24 years. Youth aged 20 to 24 who were unemployed, unhoused or living in collective housing were overrepresented among accidental ATDs. Many of the youth aged 12 to 24 who died of accidental acute toxicity had a documented history of substance use. Fentanyl, cocaine and methamphetamine were the most common substances contributing to death, and 38% of the deaths were witnessed or potentially witnessed. CONCLUSION: The findings of this study point to the need for early prevention and harm reduction strategies and programs that address mental health, exposure to trauma, unemployment and housing instability to reduce the harms of substance use on Canadian youth.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".