Investigating the Comparative Effectiveness of Yoga and Relaxation Therapy on Chronic Pain and Chronic Fatigue in MS Patients
Bibliographic record
Abstract
Introduction: Many MS patients report dissatisfaction with pain management programs, and it is urgent to identify other treatments that impact pain and chronic fatigue in these patients. The objective of this investigation is to compare the effectiveness of yoga and relaxation therapy in improving chronic pain and fatigue in MS patients. Materials and Methods: The current research is designed to be semi-experimental, consisting of a pre-test, post-test, two-month follow-up, and a four-month follow-up phase. Three groups were studied, including two yoga therapy test groups (with a sample size of 15), a relaxation therapy group (with a sample size of 16), and a control group (with a sample size of 17). The statistical population of this research consisted of all MS patients who were referred to the Iranian MS Association in Tehran between May and October 2023. The statistical sample was made up of 60 individuals who were chosen through purposive sampling and assigned randomly to the research groups. The yoga therapy group received twelve 90-minute sessions twice a week, while the relaxation therapy group received six 90-minute sessions weekly. The McGill Pain Questionnaire (MPQ) and the Chronic Fatigue Syndrome Questionnaire (CFS) were used as research tools. Repeated measures ANOVA, Bonferroni, and Tukey post hoc tests, MANCOVA, and Kruskal-Wallis H were used for statistical analysis of the research data by using SPSS.27 software. Results: According to the current research, the Emotional Dimension component (P=0.113) was not significantly different between the Yoga therapy and Relaxation therapy groups. However, there was a significant difference between the experimental groups and the control group (P<0.001). Relaxation therapy had a more lasting effect on chronic fatigue, with a significant difference between the experimental groups and the control group (p< 0.001). Conclusion: The study concluded that both yoga therapy and relaxation therapy have an impact on sensory, emotional, and chronic fatigue, and can reduce them. Despite the comparison between yoga therapy and relaxation therapy, relaxation therapy had a more lasting impact on sensory dimensions and chronic fatigue.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".