Influence of Active Release Technique on Quadriceps Inhibition and Strength: A Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To determine if Active Release Technique (ART) protocols could be used as an effective way to influence strength and muscle inhibition in the quadriceps muscles of athletes with anterior knee pain. DESIGN: Pilot clinical outcome study. METHODS: The sample consisted of 9 athletes (4 male athletes, 5 female athletes) who were identified as suffering from unilateral anterior knee pain. A Biodex dynamometer and the interpolated twitch technique were used to determine isometric strength and inhibition in the quadriceps muscles, respectively. The treatment intervention consisted of the Active Release Technique treatment protocols for anterior knee pain. The experimental leg and contralateral leg were tested pretreatment and posttreatment, and the experimental leg was tested a third time approximately 20 minutes posttreatment. RESULTS: Knee extensor moments were calculated by multiplying the moment arm by the forces measured by the Biodex dynamometer. Percentage of muscle inhibition was calculated by dividing the interpolated twitch torque (ITT) by the resting twitch torque (RTT), that is (ITT/RTT*100). A repeated measures analysis of variance (ANOVA) was used to compare pretreatment and posttreatment values for strength and muscle inhibition for the experimental and contralateral knees. The results showed no statistical significance. CONCLUSION: ART protocols did not reduce inhibition or increase strength in the quadriceps muscles of athletes with anterior knee pain. Further study is required.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".