The effects of a 6 week rolling and dynamic movement training intervention on tissue hardness, pain pressure threshold, knee range of motion and muscular strength
Bibliographic record
Abstract
Foam Roller (FR) intervention is popular in sports and rehabilitation settings. Recently, we showed that conventional FR (FR_rolling) as well as compression of the target muscle (knee extensors) during joint movement using FR (FR_KM) have similar acute changes. The present study aimed to expand on these findings and compare the effects of a 6-week FR_rolling and FR_KM intervention on the passive and active properties of knee extensors. The participants were 36 healthy male university students (21.9 ± 1.1 years) who were randomly assigned to either controls, FR_rolling, or FR_KM. An intervention per session of 180-sec was performed 3-time/week for 6 weeks in both FR_rolling and FR_KM groups. Measurements were tissue hardness, pain pressure threshold (PPT) of knee extensors, knee flexion ROM, maximal voluntary isometric and concentric contraction before and after the intervention. PPT and knee flexion ROM were significantly increased in the FR_rolling and FR_KM groups, with no significant differences between the two groups. No significant changes were observed in tissue hardness, and muscle strength in all groups. Long-term interventions with FR_rolling and FR_KM could effectively increase knee flexion ROM and PPT similarly. Therefore, if difficulties from trunk stabilization or rolling during the FR-rolling occur, a simpler approach could be sustained through the FR_KM.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".