Ground reaction forces associated with an effective elementary school based jumping intervention
Bibliographic record
Abstract
BACKGROUND: Mechanical loading during childhood plays a critical role in normal growth and development of the skeleton. Ground reaction forces (GRFs) may provide a surrogate measure for the strain experienced by bone on landing and at take off. However, there appear to be no paediatric studies that assess GRFs across a variety of loading activities. OBJECTIVES: To measure biomechanical variables in commonly performed childhood activities used in an elementary physical education intervention study which augmented bone health in boys and girls. METHODS: Maximal GFR, maximal rates of force, and time to maximum force were measured for 12 different jumping activities on a force platform. The jumps measured were drop jumps from 10, 30, and 50 cm, all followed by a plyometric jump, submaximal and maximal jumping jacks, alternating feet jump, counter movement jumps, and side to side jumps over 10 and 20 cm foam barriers. The subjects were 70 children (36 boys and 34 girls), 8.3-11.7 years old. RESULTS: Subjects ranged in height from 128.4 to 172.6 cm and had a mass of 25.0-57.0 kg. Mean (SD) for vertical jump was 24.2 (5.5) cm and 135.2 (16.6) cm for standing long jump. The children engaged in loaded physical activity 5.7 (5.3) hours a week, on average. The highest mean maximal GRFs, normalised for body weight (BW), were generated from the plyometric portion of the drop jumps and the counter movement jump (about 5 times BW) compared with 3.5 times BW for jumping jacks. Similarly, the highest rates of change in force were 514 times BW/s for the drop jump from 10 cm and 493 times BW/s for the counter movement jump. CONCLUSIONS: Simple jumps requiring minimal equipment produce GRFs of 3.5-5 times BW and rates of force of around 500 times BW/s. As children appear to attenuate higher impact forces when jumping from increased heights, it cannot be assumed that merely increasing the height of the jump will necessarily "progress" the exercise intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".