The effect of 12 weeks of yoga rehabilitation on psychological variables and lumbar and hamstring flexibility in women with chronic low back pain: A quasiexperimental study
Bibliographic record
Abstract
Background and aims: Low back pain is one of the most common and costly musculoskeletal disorders, and it is the main cause of reduced performance and disability worldwide. The present study aimed to determine the effect of twelve weeks of yoga rehabilitation on selected subjective variables and the flexibility of the muscles in the lower back and hamstrings of women suffering from non-specific chronic back pain. Methods: Twenty-eight women suffering from non-specific chronic back pain were randomly divided into two groups: a control group and an experimental group. Pain intensity, disability, stress level, depression, anxiety, and quality of life were measured using the Quebec, Oswestry, 21-question scale, and SF-36, respectively. The flexibility of the back and hamstring muscles was assessed using the flexibility box in the pre- and post-tests. The covariance test was used to analyze the data. Results: There were significant decreases in pain (p=0.001), disability (p=0.004), stress, anxiety, and depression (p=0.002), and a significant increase in some scales of quality of life, including physical performance (p=0.025), general health (p=0.043), and health change (p=0.003). There was also a significant increase in the flexibility of the muscles in the lower back and hamstrings (p=0.001). Conclusion: Performing yoga exercises has a positive effect on the physical and psychological factors of individuals with non-specific chronic back pain. It seems that coaches, specialists, physiotherapists, and even individuals can use the yoga exercise protocol as an effective intervention method to improve and treat non-specific chronic back pain during the rehabilitation phase.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".