Higher Quadriceps Roller Massage Forces Do Not Amplify Range-of-Motion Increases nor Impair Strength and Jump Performance
Bibliographic record
Abstract
Grabow, L, Young, JD, Alcock, LR, Quigley, PJ, Byrne, JM, Granacher, U, Škarabot, J, and Behm, DG. Higher quadriceps roller massage forces do not amplify range-of-motion increases nor impair strength and jump performance. J Strength Cond Res 32(11): 3059-3069, 2018-Roller massage (RM) has been reported to increase range of motion (ROM) without subsequent performance decrements. However, the effects of different rolling forces have not been examined. The purpose of this study was to compare the effects of sham (RMsham), moderate (RMmod), and high (RMhigh) RM forces, calculated relative to the individuals' pain perception, on ROM, strength, and jump parameters. Sixteen healthy individuals (27 ± 4 years) participated in this study. The intervention involved three 60-second quadriceps RM bouts with RMlow (3.9/10 ± 0.64 rating of perceived pain [RPP]), RMmod (6.2/10 ± 0.64 RPP), and RMhigh (8.2/10 ± 0.44 RPP) pain conditions, respectively. A within-subject design was used to assess dependent variables (active and passive knee flexion ROM, single-leg drop jump [DJ] height, DJ contact time, DJ performance index, maximum voluntary isometric contraction [MVIC] force, and force produced in the first 200 milliseconds [F200] of the knee extensors and flexors). A 2-way repeated measures analysis of variance showed a main effect of testing time in active (p < 0.001, d = 2.54) and passive (p < 0.001, d = 3.22) ROM. Independent of the RM forces, active and passive ROM increased by 7.0% (p = 0.03, d = 2.25) and 15.4% (p < 0.001, d = 3.73) from premeasure to postmeasure, respectively. Drop jump and MVIC parameters were unaffected from pretest to posttest (p > 0.05, d = 0.33-0.84). Roller massage can be efficiently used to increase ROM without substantial pain and without subsequent performance impairments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".