Effect of Upper Limb Motor Rehabilitation on Cognition in Parkinson’s Disease: An Observational Study
Bibliographic record
Abstract
Parkinson's disease is characterized by motor and cognitive deficits that usually have an impact on quality of life and independence. To reduce impairment, various rehabilitation programs have been proposed, but their effects on both cognitive and motor aspects have not been systematically investigated. Furthermore, most intervention is focused on lower limb treatment rather than upper limbs. In the present study, we investigated the effect of 3-week upper limb vibratory stimulation training on cognitive functioning in 20 individuals with Parkinson's disease. We analyzed cognitive (Montreal Cognitive Assessment, Trial Making Test, Digit Symbol, Digit Span Forward and Backward and Alertness) and motor performance (Unified Parkinson's Disease Rating Scale-part III; Disability of the Arm, Shoulder and Hand Questionnaire) before treatment, at the end of treatment and one month post treatment. After rehabilitation, a statistically significant improvement was observed in terms of global cognitive status, attention, global motor functioning and disability. The results suggest an impact of upper limb motor rehabilitation on cognition in Parkinson's disease. Future studies on neuromotor interventions should investigate their effects on cognitive functioning to improve understanding of cognitive motor interaction in Parkinson's 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".