Reliability of Selected Health-Related Fitness Tests for Children With Developmental Coordination Disorder
Bibliographic record
Abstract
Aim: To quantify test-retest reliability and minimal detectable change for 90 and 95% confidence levels (90MDC, 95MDC) for health-related fitness tests in children with developmental coordination disorder (DCD). Methods: Lower limb muscle strength [hand-held dynamometry (HHD), unilateral heel rise test (UHRT), standing broad jump (SBJ)], muscle endurance [Muscle Power Sprint Test (MPST)] and cardiorespiratory endurance [20-metre Shuttle Run Test (20mSRT)] were evaluated twice (2–7 day interval) in 31 children with DCD (20 males, 9.4 years old ± 2.0). Results: Test-retest reliability was reported as intraclass correlation coefficient (ICC) (2, 1) 95% confidence interval lower bounds. Values were excellent for MPST (peak and mean power: 0.93, 0.95), good for HHD (0.81–0.88), SBJ (0.82), and the 20mSRT (0.87) and moderate for UHRT (0.74). For HHD, the 90MDC and 95MDC were the largest for hip extensors (14.47, 12.14 Nm) and the smallest for ankle dorsiflexors (1.55, 1.30 Nm). For UHRT, SBJ, MPST and the 20mSRT, these MDC values were 11.90, 9.98 repetitions; 25.49, 21.38 cm; 4.70, 3.94 W (mean power), and 6.45, 5.42 W (peak power) and 0.87, 0.73 (number of stages), respectively. Conclusion: These tests yield reliable test-retest results that can be used to evaluate fitness changes in this group.
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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 | 0.002 | 0.011 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".