Whole-Body Vibration Impacts on the Degree of Toe Angle and Its Correlation to the Knee Osteoarthritis Index during Level Walking among Female University Students: A Randomized Controlled Trial
Bibliographic record
Abstract
Whole-body vibration (WBV) training is used for ankle rehabilitation as it stimulates muscle spindles to excite tonic vibration reflexes, and improves muscle strength, power, joint proprioception, balance, and flexibility. Thus, this study aims to determine the impact of whole-body vibration on the degree of the toe angle and the correlation between the toe angle and knee osteoarthritis index during level walking among female university students. A randomized controlled trial was conducted with 42 participants divided into two groups. The control group performed only home-based exercise (HBE) after education, and the study group received WBV with HBE. The functional status of participants to predict osteoarthritis was evaluated using the Western Ontario and McMaster osteoarthritis index (WOMAC), where the toe angle degree and WOMAC index were assessed before and six weeks after training. The results showed a significant improvement in the toe-in angle of HBE + WBV compared to the HBE group (p = 0.02), and in HBE + WBV, an improvement of the toe angle showed a 43% decrease in the WOMAC index (p = 0.001). In conclusion, WBV for the ankle and foot training program positively affected the degree of the toe angle, that directly affected the subtalar and ankle joint mechanics. Trial registration in the Pan African Clinical Trial Registry PACTR202304816093190 (registered retrospectively, date of registration: 18 April 2023).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".