Impaired Trunk and Ankle Stability in Subjects with Functional Ankle Instability
Bibliographic record
Abstract
PURPOSE: To examine differences between subjects with and without functional ankle instability (FAI) for measures of trunk and ankle stability. METHODS: Twelve healthy individuals and 12 individuals with FAI participated. Subjects were assessed for self-rated disability, time to stabilization (TTS), and muscle reflex responses to sudden trunk perturbation. TTS results were calculated using an unbounded third-order polynomial. Trunk reflexes to a sudden unloading task were tested during flexion and extension movements. Loads were 65 N for males and 40 N for females. ANOVA procedures were used to compare TTS times, latency times, and trunk displacement data between groups. Regression analyses were used to determine the relationship between TTS and trunk latency times. RESULTS: Subjects with FAI had worse perceptions of their ankle disability but had the same vertical jump height. TTS times were delayed in the FAI group (6.0 +/- 2.8 vs 2.9 +/- 1.0 s; F(1,22) = 12.7, P = 0.002). Trunk muscle onsets were delayed in FAI subjects in both flexion (F(1,22) = 7.6, P = 0.01) and extension (F(1,22) = 4.5, P = 0.04). Regression and analysis identified x-axis TTS times as significantly associated with extension latency times (r2 = 0.19, P = 0.043). CONCLUSIONS: This study has provided evidence for proximal nervous system adaptations associated with FAI. Delayed trunk reflexes have been shown to predispose individuals to developing low back pain. A cause or effect relationship between trunk and ankle instability has not been established here.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".