Investigating the Effect of Comprehensive Therapeutic Exercise on Cognitive and Motor Performance in People with Parkinson Disease
Bibliographic record
Abstract
Propose:The purpose of this study is to investigate the effect of comprehensive exercise therapy on cognitive and motor performance in patients with Parkinson's disease.Methods:Twenty individuals (15 male, 5 female) with Parkinson's disease (age range: 62.30±9.48 years, weight: 70.40±10.20 kg, height: 166.55±8.63 cm) participated in quasi-experimental study. Before the start of the intervention, the Montreal cognitive assessment questionnaire was completed by the each participant, and functional tests including time up and go test (TUG), time up and go test motor (TUGM) and cognitive (TUGC) were taken from the participants. These tests were also taken from the participants after all sessions. The course of therapeutic exercise included 16 one-hour sessions that took place 4 times a week for one month. The data were analyzed using the paired t-test and SPSS version 20 software at a significance level of 0.05.Result:In the present study, a statistically significant improvement was observed on cognitive and motor performance. The results of the paired t-test showed that there is a significant difference in the scores of the Montreal Cognitive Assessment Questionnaire before and after the treatment (p<0.001). Also, the results of three functional tests of TUG, TUGM and TUGC before and after treatment showed statistically significant differences (p<0.001).Conclusion:Application of comprehensive therapeutic exercises in physiotherapy can help improve the cognitive and motor performance of patients with Parkinson̕ disease.
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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 | 0.001 |
| 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".