Test–Retest Reliability of Lower Extremity Functional Instability Measures
Bibliographic record
Abstract
OBJECTIVES: 1) To evaluate the test-retest reliability of lower extremity functional instability measures involving testing situations of varying complexity, and 2) To evaluate the interrelationships among performances observed during these tests and a maximal single-limb forward hop for distance. DESIGN: A repeated measures design, repeated on two occasions. SETTING: Postural control laboratory. PARTICIPANTS: Thirty young healthy subjects (23.5 +/- 2.0 years). MAIN OUTCOME MEASURES: Subjects performed single-limb standing balance and forward hop tests on two occasions completed within 1 week and at least 24 hours apart. Standing balance was assessed using a force platform and the following four progressively complex test situations: 1) standing on the stable platform with eyes open, 2) standing on a foam mat placed over the platform with eyes open, 3) standing on the stable platform with eyes closed, and 4) standing on the stable platform after landing from a maximal single-limb forward hop. RESULTS AND CONCLUSIONS: Intraclass correlation coefficients were moderate to excellent (0.41 to 0.91) suggesting that the standing balance tests are appropriate for distinguishing among group performances. Standard errors of measurement and associated 95% confidence intervals suggested that a change in an individual's standing balance performance of approximately 10-30% would be necessary in order to confidently state that a true change had occurred. Stronger relationships were observed between hop distance and standing balance tests performed with eyes closed (r = -0.63, p < 0.001) and after landing from a maximal hop (r = -0.53, p = 0.003), suggesting that tests that challenge postural control to a greater extent are more representative of functional performance.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".