Development of a Clinical Static and Dynamic Standing Balance Measurement Tool Appropriate for Use in Adolescents
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: There is a need in sports medicine for a static and dynamic standing balance measure to quantify balance ability in adolescents. The purposes of this study were to determine the test-retest reliability of timed static (eyes open) and dynamic (eyes open and eyes closed) unipedal balance measurements and to examine factors associated with balance. SUBJECTS: Adolescents (n=123) were randomly selected from 10 Calgary high schools. METHODS: This study used a repeated-measures design. One rater measured unipedal standing balance, including timed eyes-closed static (ECS), eyes-open dynamic (EOD), and eyes-closed dynamic (ECD) balance at baseline and 1 week later. Dynamic balance was measured on a foam surface. Reliability was examined using both intraclass correlation coefficients (ICCs) and Bland and Altman statistical techniques. Multiple linear regressions were used to examine other potentially influencing factors. RESULTS: Based on ICCs, test-retest reliability was adequate for ECS, EOD, and ECD balance (ICC=.69, .59, and .46, respectively). The results of Bland and Altman methods, however, suggest that caution is required in interpreting reliability based on ICCs alone. Although both ECS balance and ECD balance appear to demonstrate adequate test-retest reliability by ICC, Bland and Altman methods of agreement demonstrate sufficient reliability for ECD balance only. Thirty percent of the subjects reached the 180-second maximum on EOD balance, suggesting that this test is not appropriate for use in this population. Balance ability (ECS and ECD) was better in adolescents with no past history of lower-extremity injury. DISCUSSION AND CONCLUSION: Timed ECD balance is an appropriate and reliable clinical measurement for use in adolescents and is influenced by previous injury.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".