Age and the risk of All-Terrain Vehicle-related injuries in children and adolescents: a cross sectional study
Bibliographic record
Abstract
BACKGROUND: The study was designed to determine if youth <16 years are at a greater risk of serious injuries related to all-terrain vehicle (ATV) use compared to older adolescents and adults. METHODS: We performed cross sectional study of children and adults presenting to pediatric and adult emergency departments between 1990 and 2009 in Canada. The primary exposure variable was age <16 years and the primary outcome measure was moderate to serious injury determined from physician report of type and severity of injury. RESULTS: Among 5005 individuals with complete data, 58% were <16 years and 35% were admitted to hospital. The odds of a moderate to serious injury versus minor injury among ATV users <16 years of age was not different compared with those ≥16 years of age (OR: 0.94; 95% CI: 0.84, 1.06). After adjusting for era, helmet use, sex and driver status, youth <16 years were more likely to present with a head injury (aOR: 1.45; 95% CI: 1.19-1.77) or fractures (aOR: 1.60; 95% CI: 1.43-1.81), compared with those ≥16 years. Male participants (aOR: 1.21; 95% CI: 1.06-1.38) and drivers (aOR: 1.30, 95% CI: 1.12-1.51) were more likely to experience moderate or serious injuries than females and passengers. Helmet use was associated with significant protection from head injuries (aOR: 0.59; 95% CI: 0.44-0.78). CONCLUSIONS: Youth under 16 years are at an increased risk of head injuries and fractures. For youth and adults presenting to emergency departments with an ATV-related injury, moderate to serious injuries associated with ATV use are more common among drivers and males. Helmet use protected against head injuries, suggesting minimum age limits for ATV use and helmet use are warranted.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".