Effects of task-specific training on motor activity, cognitive function, and quality of life among individuals with Parkinson’s disease: a quasi-experimental pilot study
Bibliographic record
Abstract
Introduction. The second most prevalent neurological condition in adults over 50 years is Parkinson’s disease (PD). Individu-als with PD(IwPD) experience motor and non-motor symptoms during disease progression. One of the most significant vari-ables in non-motor symptoms is cognitive impairment, andthe disease may lead to dementia. Even though the cognitive impair-ment in IwPD is mild, there should be concern regarding its rehabilitation because there is no pharmacological management for cognitive impairment, and just a handful of studies on functional cognitive training for IwPD have been published. This raises the prospect of task-specific training among IwPD and functional rehabilitation of cognitive function.Methods. Thisquasi-experimental study involved 30 participants, who were assessed and selected based on inclusion and exclu-sion criteria. Pre-test and post-test values were obtained using the Montreal Cognitive Assessment (MoCA), Unified Parkinson’s Disease Rating Scale (UPDRS) Part III, and Parkinson’s Disease Questionnaire (PDQ)-39. All subjects underwent task-specific training with cognitive training for 8 weeks.Results. Statistical analysisshowed significant improvements in motor activity, cognitive function, and quality of life. The p-value of each outcome measure was < 0.0001 after analysingpre-test and post-test data.Conclusions. According to the findings ofthis study, task-specific training combined with cognitive training significantly improved motor activity, cognitive function, and quality of life among IwPD.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".