Childhood physical activity body contact risk: feasibility of a novel technique for objective measurements of impact speed, frequency, and intentionality
Bibliographic record
Abstract
INTRODUCTION: Children at risk for bleeding injuries are restricted from body contact during physical activity but current recommendations are based on expert opinion. AIM: Evaluate high-speed digital video recording as an objective measure of body contact risk during physical activity. METHODS: Observational study of physical activities among healthy children, grouped according to participation in teams (vs. individual) and on their perceived risk of injury (high/low). High speed digital video recordings documented the collision target (floor/ground/ice, people, wall, equipment), estimated speed, and impact rates for team and individual activities, with and without expected body contact. RESULTS: Among 348 participating children (3-16 years, 51% female), 32% to 78% experienced at least one contact. Impact type varied significantly (chi-square, p < 0.001) by activity category. Unstructured and Team high risk activity impacts were primarily with the floor/ground, whereas Individual low risk activities were characterized by equipment impacts. Impact speeds were typically 1.0 to 2.1 m s(-1) . Higher impact speeds occurred during instructional classes (2.1 m s(-1) ), unstructured free swim (1.9 m s(-1) ) and ball hockey (1.7 m s(-1) ). Impact rates were higher during Team high risk and Team low risk sports (3.0 and 1.8 impacts per minute, respectively) compared to Individual (high or low risk) or Unstructured activities (0.2-0.3 impacts per minute). CONCLUSIONS: High speed video recordings of childhood physical activity are a feasible method for characterizing the frequency, type, direction and speed of impacts. Quantifying the impacts that occur during childhood physical activity could inform the guidelines for physical activity participation among children with identified bleeding risks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".