Comparison of the Effectiveness of Group Therapy Based on Acceptance and Commitment and Amantadine on Pain, Fatigue and Quality of Life in Patients with Multiple Sclerosis
Bibliographic record
Abstract
Introduction: Multiple sclerosis (MS) is the most common progressive neurological disease in which the myelin of the central nervous system is destroyed and causes many problems for the affected person and is one of the most important life-changing diseases, especially at a young age which causes a severe reduction in the level of individual performance. The aim of this study was to compare the effectiveness of group therapy based on acceptance and commitment and amantadine on pain, fatigue and quality of life in patients with MS. Methods: The present quasi-experimental study was performed with a pre- and post-test design. Statistical population included all people with MS in Hamadan province, Iran; 60 female patients who met the inclusion criteria were randomly selected and divided into two equal groups undergoing treatment based on acceptance and commitment (act) and taking amantadine for 3 months. Subjects completed the fatigue severity scale (FSS-9), multiple sclerosis impact scale (MSIS-29), and McGill Pain before and after treatment. Data were analyzed using ANOVA, covariance, Kruskal-Wallis, LSD and Bonferroni statistical methods using SPSS software version 22. Results: The findings showed that the difference between amantadine consumption and act with the superiority of amantadine effect over act on pain, fatigue and quality of life was not significant (P<0.001). Conclusion: It can be concluded that non-pharmacological therapies can also be used as adjunctive therapy along with medical therapies.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.001 |
| 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".