The Effect of in Water Selective Exercises on Muscle Strength in Patients with Muscle Dystrophy
Bibliographic record
Abstract
Muscular dystrophy syndrome refers to a group of genetic diseases resulting in muscle weakness and low functional capacity. This purpose of this study is to investigate the effect of an eight-week selective training on muscle strength of patients with muscular dystrophy. A quasi-experimental method was used in this study. Eleven patients with muscular dystrophy were selected through purposive sampling and divided into two groups randomly including in water selective exercises (n = 6) and control groups (n = 5) respectively. The study conducted under the supervision of researcher for eight weeks, three sessions per week, and the time allocated was between 60-45 minutes. Moreover, a t-test was used for statistical analysis and the significant level was set at p < 0.05 level. After an eight-week training a significant increase (P < 0.05) was observed in extensor muscle strength in patients with muscular dystrophy. However, no significant difference was observed in the control group (p ≥0.05). Comparing the changes made during eight weeks (difference between pre-test and post-test) a significant difference (P < 0.05) was observed between intervention and control groups. According to obtained findings in this study, in water selective exercise is an effective way to improve muscular strength in patients with muscular dystrophy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".