The effect of swedish massage combined with exercise therapy on nonspecific low back pain in the elderly: A randomized controlled clinical trial
Bibliographic record
Abstract
Aims: The aim of this study was to determine the effect of Swedish massage combined with exercise therapy on nonspecific low back pain (NSLBP) in older adults. Materials and Methods: This randomized controlled clinical trial was carried out on 70 elderly people with NSLBP. Participants were assigned randomly to the intervention and control groups. The interventional group was treated using Swedish massage combined with exercise therapy, while the control group was treated using exercise therapy alone. The Visual Analog Scale (VAS) and the Quebec Back Pain Disability Scale (QBPDS) were used to determine the severity of low back pain (LBP) and the LBP disability, respectively. All participants were completed LBP and QBPDS scales for three times (at the beginning and the end of the intervention as well as 4 weeks after completion of the intervention). Results: It was seen that the participants in the intervention and control groups were similar in baseline scores of VAS and QBPDS. Using repeated measures analysis of variance, the comparison of the mean scores of both the scales in the two groups indicated that the scores decreased significantly (P < 0.05) in the intervention group compared to the control group at the second and the third measurements. Conclusion: The findings indicated that the Swedish massage combined with exercise therapy could be more effective for reducing LBP and back pain disability compared to exercise therapy alone. Further studies are needed to reach more evidence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".