23: Age and the Risk of ATV-Related Injuries in Children and Adolescents: Injury Patterns and Legislative Impact Assessment Through the Chirpp Database
Bibliographic record
Abstract
Purposes of the study: 1) to determine if youth under 16 years of age are at a greater risk of severe injuries related to all terrain vehicle (ATV) use and 2) to determine if legislation for a minimum drivers age of 16 years reduces the risk of ATV-related injuries in youth. Outcomes: 1) Moderate to severe injury (concussions, injuries requiring admission to hospital, fractures, intracranial injuries, amputations and fatal injuries) versus mild injury; 2) rate of ATV injuries. Study Designs: Cross sectional surveillance study and an interrupted time series analysis. Setting. Nine pediatric and four adult emergency departments across Canada participating in the Canadian Hospitals Injury Reporting and Prevention Program (CHIRPP) between 1990 and 2009. Population: Children and adults who presented to a CHIRPP emergency department with ATV-related injuries. Exposures: (1) Less than 16 years of age at the time of injury; (2) injured in a province with legislation for a minimum drivers age for ATVs. Of the 5005 analysed presentations, 58% were <16 years of age and 35% were admitted to hospital. Among those <16 years of age (n=2883), the most common ATV-related injuries were fractures (39%) and superficial wounds (18%). There was no significant difference in the odds of a moderate to severe injury versus minor injury among ATV users <16 years of age compared with ≥16 years of age (OR 0.94 [95% CI 0.84 to 1.06]). After adjusting for confounding, children <16 years were more likely to present with a head injury (OR 1.45 [95% CI 1.19 to 1.77]) and fractures (OR 1.6 [95% CI 1.43 to 1.81]), compared to those ≥16 years. Helmets significantly reduced the odds of an isolated severe head injury compared with a non-head injury (OR 0.35 [95% CI 0.22 to 0.55]). Compared with provinces without legislation, rates of ATV-related injuries, in particular moderate to severe injuries, decreased in children <16 years of age in provinces following the enactment of legislation for a minimum drivers age for ATV use. There was no difference in the odds of a moderate to severe injury compared with mild injury for younger or older ATV users, however youth <16 years of age are at an increased risk of head injuries and fractures compared to individuals ≥16 years of age. ATV-related injuries decreased in children <16 years of age after provincial legislation for a minimum drivers age. These data support calls for a minimum drivers age as a strategy to protect children from ATV-related injuries.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".