Feasibility of online PD SAFEx™ exercise rehabilitation for symptom improvements of Parkinson’s disease: A pilot study
Bibliographic record
Abstract
BACKGROUND: Parkinson's Disease (PD) is a neurodegenerative disorder affecting both motor and cognitive symptoms. While medications show some improvement in motor symptoms, cognitive symptoms can worsen. In-person exercise programs, such as PD SAFEx™, are an important adjunct therapy in improving symptoms. However, coronavirus disease 2019 (COVID-19) limited in-person exercise interventions. Therefore, there is a need to investigate the effectiveness of online exercise delivery. OBJECTIVE: To identify (1) whether an online exercise intervention can achieve similar results to an identical in-person intervention and (2) if online PD SAFEx™ can alter the cognitive decline of PD patients. METHODS: 20 participants with idiopathic PD participated in a 12-week online PD SAFEx™ program and were compared to 73 participants from in-person PD SAFEx™. The primary outcome measure was the Unified Parkinson's Disease Rating Scale-III measured before/after intervention. Three secondary cognitive measures were collected with the online group. RESULTS: Main effect of time on UPDRS-III scores of both groups were found (F(1,92) = 35.555, p < 0.001). No interaction was found between in-person and online groups (F(1,1) = 0.052, p = 0.820). TMT B in the online group showed significant improvements in executive function (F(1,17) = 7.095, p = 0.016). CONCLUSIONS: Online and in-person PD SAFEx™ both achieved clinically significant UPDRS-III improvement and are statistically equivalent. Online PD SAFEx™ reduced cognitive symptoms seen during COVID-19.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".