Foam Rolling Training Effects on Range of Motion: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: A single foam-rolling exercise can acutely increase the range of motion (ROM) of a joint. However, to date the adaptational effects of foam-rolling training over several weeks on joint ROM are not well understood. OBJECTIVE: The purpose of this meta-analysis was to investigate the effects of foam-rolling training interventions on joint ROM in healthy participants. METHODS: Results were assessed from 11 studies (either controlled trials [CT] or randomized controlled trials [RCTs]) and 46 effect sizes by applying a random-effect meta-analysis. Moreover, by applying a mixed-effect model, we performed subgroup analyses, which included comparisons of the intervention duration (≤ 4 weeks vs > 4 weeks), comparisons between muscles tested (e.g., hamstrings vs quadriceps vs triceps surae), and study designs (RCT vs CT). RESULTS: = 72.76). Subgroup analyses revealed no significant differences between study designs (p = 0.36). However, a significant difference was observed in the intervention duration in favor of interventions > 4 weeks compared to ≤ 4 weeks for ROM increases (p = 0.049). Moreover, a further subgroup analysis showed significant differences between the muscles tested (p = 0.047) in the eligible studies. Foam rolling increased joint ROM when applied to hamstrings and quadriceps, while no improvement in ankle dorsiflexion was observed when foam rolling was applied to triceps surae. CONCLUSION: Longer duration interventions (> 4 weeks) are needed to induce ROM gains while there is evidence that responses are muscle or joint specific. Future research should examine possible mechanisms underpinning ROM increases following different foam-rolling protocols, to allow for informed recommendations in healthy and clinical populations.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.027 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".