Is Physical Exercise Beneficial for Persons with Parkinson's Disease?
Bibliographic record
Abstract
OBJECTIVE: To review existing studies evaluating the effectiveness of physical exercise on mortality, strength, balance, mobility, and activities of daily living (ADL) for sufferers of Parkinson's disease (PD). DATA SOURCES: The following databases were searched (1) Cochrane Database of Systematic Reviews, (2) Cumulative Index to Nursing and Allied Health Literature (CINAHL), (3) PubMed and (4) Medline/NARIC (National Rehabilitation Information Center) using combinations of key words Parkinson's disease and physical exercise. Only articles written in English were included. References cited were also examined. STUDY SELECTION: Studies were eligible if (1) only patients with PD were included in the intervention study (there were many studies that evaluated the benefits of exercise after stroke, cardiac arrest, sports injuries, surgery, and arthritis, but only a few for patients with PD), (2) the intervention included some form of physical or therapeutic exercise, (3) the effects of the physical exercise were evaluated, and (4) the studies were published in a refereed journal. Because few studies were found that dealt with PD patients exclusively, all studies that evaluated the effectiveness of physical exercise for only PD patients were included. Seven studies met our criteria and were selected. Three of the selected studies were randomized controlled studies, 1 was an open trial, and the other 3 relied on patients' own assessments. DATA SYNTHESIS: Outcomes in the studies were measured in terms of physical improvements in patients with PD, such as improved axial rotation, functional reach, flexibility, balance, muscle strength, short-step gait, and mobility. All studies reviewed show that exercise improves overall performance in PD patients. Improvements were measured using standardized tests and other measurement scales. CONCLUSIONS: The results of the present research synthesis support the hypothesis that patients with PD improve their physical performance and activities of daily living through exercise. Future studies should include the development of standardized exercise programs specific for problems associated with PD as well as standardized testing methods for measuring improvements in PD patients. There is also a need for longer term studies (over 1 year) to assess if improvements achieved during the intervention stage are retained long term.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".