Impact of Dance or Music and Meditation on the Progression of Parkinson Disease With Mild or Moderate Severity: Protocol for a Pilot Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Parkinson disease (PD) is a progressive neurodegenerative disorder characterized by motor dysfunctions and nonmotor symptoms. Current treatments do not alter disease progression, highlighting the need for alternative therapies. Music, dance, and mindfulness meditation have shown the potential to improve symptoms and quality of life in patients with PD. OBJECTIVE: This study aims to evaluate the effectiveness of dance or music and meditation on PD progression, cognitive functions, mood, behavior, and caregiver burden. METHODS: This study is a single-blinded, longitudinal, parallel, randomized controlled trial. The participants consist of 30 patients with mild to moderate PD residing in Mumbai, India, who can physically participate in the activities. The exclusion criteria include advanced PD, severe balance issues, age >80 years, and other movement disorders. Participants in the intervention group will engage in dance or music sessions and guided meditation thrice weekly for 6 months. The control group will continue their usual activities and medication. The primary outcome is the progression of PD symptoms, measured using the Unified Parkinson's Disease Rating Scale I-III, and quality of life, measured using the Parkinson's Disease Questionnaire-39. The secondary outcomes include cognitive functions (Mini-Mental State Examination), mood (Beck Depression Inventory and Parkinson Anxiety Scale), mobility (timed up and go and Berg Balance Test), behavioral disorders (Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease Rating Scale), and caregiver burden (Zarit Burden Interview and Parkinson's Disease Questionnaire-Carer). RESULTS: Data collection was completed in February 2024, with 28 participants finishing the study (intervention group: n=15, 54% and control group: n=13, 46%). Data analysis is underway, with results expected to be published in December 2024. CONCLUSIONS: This study aims to provide significant insights into the effectiveness of dance or music and meditation in improving the quality of life and slowing the progression of PD. The findings are anticipated to support using these nonpharmaceutical therapies as complementary approaches to managing PD. TRIAL REGISTRATION: CTRI/2023/03/051064; https://tinyurl.com/2xdus53j. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59018.
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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 | 0.018 | 0.015 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.007 |
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".