Virtual Group Music Therapy for Apathy in Parkinson’s Disease: A Pilot Study
Bibliographic record
Abstract
Objective To evaluate the effect of virtual group music therapy on apathy in people with Parkinson’s disease (PD). Introduction Apathy affects 40% of people with PD, lacks effective therapies, and independently predicts poorer quality of life and greater caregiver burden. Music therapy is the clinical application of music to address a person’s physical or emotional needs and is effective in treating apathy in dementia. Methods People with idiopathic PD and apathy (Movement Disorders Society-Unified Parkinson’s Disease Rating Scale, apathy item ≥ 2) and their caregivers participated in twelve, weekly virtual group music therapy sessions, with session attendance signifying adherence. Participants completed pre- and post-intervention assessments of apathy (Apathy Scale (AS)), quality of life (Parkinson’s Disease Questionnaire-short form), functional ability (Schwab & England Activities of Daily Living Scale), depression (Beck Depression Inventory (BDI-II)), and cognition (Montreal Cognitive Assessment-Blind). Among secondary outcomes, we assessed caregiver burden (Zarit Burden Interview-short form) and strain (Multidimensional Caregiver Strain Index). Results Sixteen PD participants (93.8% men, mean age 68.3 ± 8.4 years, median 6 years PD duration) and their caregivers (93.8% women, mean age 62.6 ± 11 years) completed the study. All PD participants and 88% of caregivers were >70% adherent to the intervention. Apathy (AS, effect size = 0.767, P = 0.002) and depression (BDI-II, effect size = 0.542, P = 0.03) improved, with no change in caregiver measures. Conclusion Group music therapy is an effective treatment for apathy in PD and may improve mood. The virtual format is a feasible alternative to in-person sessions with high adherence and satisfaction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".