Upper and lower limb loading during weight-bearing activity in children: reaction forces and influence of body weight
Bibliographic record
Abstract
Weight bearing (WB) activity is important for healthy skeletal development. The magnitude of loading during WB activities, especially upper limb impacts, has yet to be quantified in children. This study quantifies ground reaction forces (GRF) experienced by children performing WB activities and examines the contribution of body weight (BW) to GRF. Fifty children, aged 8-12 were recruited (34 males). GRF were measured using force plates during 20 upper and lower limb activities (such as landing on the feet and hands). Sex differences in GRF and associations between peak force and BW were examined using independent sample t-tests and linear regressions (p < 0.05), respectively. Lower limb GRF varied from 2-6x BW with no significant sex differences. GRF during upper limb activities varied from 1/3-1.7x BW with males experiencing significantly greater GRF for 25% of activities. BW was significantly associated with peak force in almost all activities; however, GRF variation explained by BW was wide-ranging across activities and not dependent on limb or activity type (static vs dynamic). Therefore, factors other than BW, such as technique, may be important in determining forces experienced by children performing WB activity and should be considered when choosing activities for WB activity interventions.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".