Validity of field assessments to predict peak muscle power in preschoolers
Bibliographic record
Abstract
Field-based fitness assessments are time- and cost-efficient. However, no studies to date have reported the predictive value of field-based musculoskeletal fitness assessments in preschoolers. The purpose of this study was to determine the validity of 2 field assessments to predict peak muscle power in preschool-aged children. Four-hundred and nineteen 3- to 5-year olds participated (208 girls, 211 boys; mean age: 4.5 ± 0.9 years). Peak power (PP) was evaluated using a modified 10-s Wingate protocol as the criterion standard. Standing long-jump was measured in inches to the back of the heel using a 2-footed takeoff and landing. Shuttle-run time was measured using a shuttle-run protocol, which required children to sprint 50 feet (15.2 m), pick up a small block, and sprint back, with time measured to the closest tenth of a second. Regression modelling was used to calculate the predictive power of each field-based measurement, adjusting for weight (kg), age, and sex. Both standing long-jump distance and shuttle-run time were significantly correlated with PP (r = 0.636, p < 0.001, and r = –0.684, p < 0.001, respectively). Linear regression analysis determined that a child’s PP can be predicted from the child’s weight, age, and sex and either standing long-jump or shuttle-run time (adjusted R 2 = 0.79, p < 0.001, and 0.81, p < 0.001, respectively). The standing long-jump and the Bruininks Oseretsky Test of Motor Proficiency 2nd Edition shuttle-run are both significant predictors of peak muscle power in preschool children. Either measure can be used as a cost- and time-efficient estimate of musculoskeletal fitness in preschoolers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".