Prioritising preventive measures for unintentional sport and recreation-related deaths in Québec, Canada, based on a 14-year review
Bibliographic record
Abstract
OBJECTIVES: This study analysed sport and recreation-related fatalities in Québec, Canada, from January 2006 to December 2019, focusing on the six activities with the highest mortality frequencies. It aimed to identify activity-specific risk factors to inform prevention priorities. METHODS: In this descriptive retrospective study, data extracted from the database of the Bureau du coroner du Québec were analysed. The characteristics and mechanisms of fatalities in all-terrain vehicles, snowmobiles, cycling, swimming, motorised navigation and non-motorised navigation activities were presented. Incidence rates were calculated using Canadian census data. RESULTS: Male fatalities predominated, ranging from 83% to 91%, in the six activities. Traumatic brain injuries or cranial traumas were reported in 55.7% of land-based activities-related deaths, particularly in 70.1% of cycling fatalities. In 44.2% of cycling-related cases, victims were not wearing a helmet, while in 44.1% of cases involving all-terrain vehicles, victims either wore a helmet improperly or did not wear one at all. Cycling deaths mainly occurred on roads (82.9%), with 63.9% involving collisions with motor vehicles. Alcohol-impaired driving was observed in 29.8% of victims involved in all-terrain vehicle and snowmobile activities combined. Natural water accounted for 67.1% of swimming fatalities. Alcohol consumption was documented in 28.8% of deaths related to water-based activities. Personal flotation devices were not worn in 61.5% of navigation-related fatalities. CONCLUSION: Activity-specific prevention priorities have been highlighted. A thorough examination of coroners' recommendations is now necessary to understand their characteristics, as this information can guide both the identification and implementation of preventive measures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".