Effects of Massage as a Combination Therapy with Lumbopelvic Stability Exercises as Compared to Standard Massage Therapy in Low Back Pain: a Randomized Cross-Over Study
Bibliographic record
Abstract
BACKGROUND: Little is known about the effects of providing massage as a combination therapy (CT) with lumbopelvic stability training (LPST) in management of chronic nonspecific low back pain (CLBP) among elite female weight lifters. It is unclear whether massage therapy (MT) together with LPST has any additional clinical benefits for individuals with CLBP. PURPOSE: The current study compares the therapeutic effects of CT against MT as a stand-alone intervention on pain intensity (PI), pain pressure threshold (PPT), tissue blood flow (TBF), and lumbopelvic stability (LPS) among elite weight lifters with CLBP. SETTING: The study was conducted at the campus for National Olympic weight lifting training camp. PARTICIPANTS: A total of 16 professional female elite weight lifting athletes who were training for Olympic weight lifting competition participated in the study. RESEARCH DESIGN: A within-subject, repeated measures, crossover, single-blinded, randomized allocation study. INTERVENTION: The athletes were randomized into three sessions of CT and MT with a time interval of 24 hrs within sessions and a wash out period of four weeks between the sessions. MAIN OUTCOME MEASURES: The PI, PPT, TBF, and LPS were measured before and after each session repeatedly in both groups of intervention. The changes in the PI, PPT, TBF, and LPS were analyzed using repeated measures analysis of variance (ANOVA). RESULTS: < .001). CONCLUSION: The combination therapy of massage therapy and LPST is likely to provide more clinical benefits in terms of PI, PPT, and TBF when compared to massage as a stand-alone therapy among individuals with chronic nonspecific low back pain.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".