SURVEY OF SPORT PARTICIPATION AND SPORT INJURY IN ELEMENTARY SCHOOL CHILDREN
Bibliographic record
Abstract
Background Participation rates in youth sport in Canada are high. Sport injury epidemiology studies in youth primarily focus on adolescents (ages 13–18). There is a paucity of literature examining sport injury risk in children where injury prevention practices require development and evaluation. Objective To examine sport participation and sport injury rates in elementary school students (ages 9–12). Design Cross-sectional study. Setting A survey was sent home with students in randomly selected Calgary (Canada) elementary schools (grades 4–6). Participants Elementary schools in Calgary (Canada) were randomly selected to participate (N=26 schools). A survey was completed by 540 children and parent/guardian. Risk factor assessment The primary risk factors of interest include age, sport of choice, and time spent participating in sport. Main outcome measures Sport injury was defined as any injury sustained in the previous year that required medical attention. Results Overall, 81% of participants reported participating in sport in the past year. The highest sport-specific participation was reported in soccer (18.9%), swimming (13.5%), and dance (10.8%). The overall injury incidence proportion (IIP) was 28.3 injuries/100 children/year. The medical attention IIP was 9.8 injuries/100 children/year for males and 11.4 injuries/100 children/year for females. The highest IIP for males occurred in soccer (26.0%), cycling (19.5%) and hockey (9.1%). The highest IIP for females occurred in basketball (10.6%), soccer (10.6%), and dance (9.1%). Conclusions The IIP (28.3%) and medical attention IP (10.6%) was lower than previously reported in adolescents (ages 12–18), suggesting less severe injuries in younger children. The greatest burden of sport injury occurred in soccer, cycling, and basketball. This study will inform the development of future targeted interventions within specific sports as well as within school-based curriculums to prevent sport injury in children.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".