Rhythmic auditory stimulation for reduction of falls in Parkinson’s disease: a randomized controlled study
Bibliographic record
Abstract
Objective: To test whether rhythmic auditory stimulation (RAS) training reduces the number of falls in Parkinson’s disease patients with a history of frequent falls. Design: Randomized withdrawal study design. Subjects: A total of 60 participants (aged 62–82 years) diagnosed with idiopathic Parkinson’s disease (Hoehn and Yahr stages III or IV) with at least two falls in the past 12 months. Intervention: Participants were randomly allocated to two groups and completed 30 minutes of daily home-based gait training with metronome click–embedded music. The experimental group completed 24 weeks of RAS training, whereas the control group discontinued RAS training between weeks 8 and 16. Main measures: Changes in clinical and kinematic parameters were assessed at baseline, weeks 8, 16, and 24. Results: Both groups improved significantly at week 8. At week 16—after the control group had discontinued training—significant differences between groups emerged including a rise in the fall index for the control group ( M = 10, SD = 6). Resumption of training reduced the number of falls so that group differences were no longer significant at week 24 ( M experimental = 3, SD = 2.6; M control = 5, SD = 4.4; P > 0.05). Bilateral ankle dorsiflexion was significantly correlated with changes in gait, fear of falling, and the fall index, indicating ankle flexion as a potential kinematic mechanism RAS addresses to reduce falls. Conclusion: RAS training significantly reduced the number of falls in Parkinson’s disease and modified key gait parameters, such as velocity and stride length.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".