The Effects of Cryotherapy on Knee Joint Position Sense and Force Production Sense in Healthy Individuals
Bibliographic record
Abstract
The proprioceptive information received from mechanoreceptors is potentially responsible for controlling the joint position and force differentiation. However, it is unknown whether cryotherapy influences this complex mechanism. Previously reported results are not universally conclusive and sometimes even contradictory. The main objective of this study was to investigate the impact of local cryotherapy on knee joint position sense (JPS) and force production sense (FPS). The study group consisted of 55 healthy participants (age: 21 ± 2 years, body height: 171.2 ± 9 cm, body mass: 63.3 ± 12 kg, BMI: 21.5 ± 2.6). Local cooling was achieved with the use of gel-packs cooled to -2 ± 2.5°C and applied simultaneously over the knee joint and the quadriceps femoris muscle for 20 minutes. JPS and FPS were evaluated using the Biodex System 4 Pro apparatus. Repeated measures analysis of variance (ANOVA) did not show any statistically significant changes of the JPS and FPS under application of cryotherapy for all analyzed variables: the JPS's absolute error (p = 0.976), its relative error (p = 0.295), and its variable error (p = 0.489); the FPS's absolute error (p = 0.688), its relative error (p = 0.193), and its variable error (p = 0.123). The results indicate that local cooling does not affect proprioceptive acuity of the healthy knee joint. They also suggest that local limited cooling before physical activity at low velocity did not present health or injury risk in this particular study group.
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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 | 0.000 | 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) | 0.001 | 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".