Multimodal Balance Training Supported by Rhythmic Auditory Stimuli in Parkinson Disease: Effects in Freezers and Nonfreezers
Bibliographic record
Abstract
OBJECTIVE: To fulfill the potential of nonpharmacological interventions for people with Parkinson disease (PD), individually tailored treatment is needed. Multimodal balance training supported by rhythmic auditory stimuli (RAS) can improve balance and gait in people with PD. The purpose of this study was to determine whether both freezers and nonfreezers benefit. METHODS: A secondary analysis was conducted on a large randomized controlled trial that included 154 patients with PD (Hoehn & Yahr Stages 1-3 while ON-medication) who were assigned randomly to 3 groups: (1) multimodal balance training with RAS delivered by a metronome (RAS-supported multimodal balance training); (2) regular multimodal balance training without rhythmic auditory cues; and (3) a control intervention (involving an educational program). Training was performed for 5 weeks, twice per week. The primary outcome was the Mini-BESTest score directly after the training period. Assessments were performed by a single, masked assessor at baseline, directly postintervention, and after 1-month and 6-month follow-up. Outcomes were analyzed in 1 analysis, and the results were presented separately for freezers and nonfreezers with a linear mixed model, adjusted for baseline Mini-BESTest scores, Unified Parkinson's Disease Rating Scale scores, and levodopa equivalent dose. RESULTS: In both freezers and nonfreezers, both RAS-supported multimodal training and regular training significantly improved the Mini-BESTest scores compared with baseline scores and with the control group scores. The improvement was larger for RAS-supported training compared with regular training, for both freezers and nonfreezers. Only the RAS-supported training group retained the improvements compared with baseline measurements at 6-month follow-up, and this was true for both freezers and nonfreezers. CONCLUSIONS: RAS-supported multimodal training is effective in improving balance performance in both freezers and nonfreezers. IMPACT: Until this study, it was unknown whether both freezers and nonfreezers could benefit from multimodal balance training. With this information, clinicians who work with people with PD will be better able to apply personalized gait rehabilitation. LAY SUMMARY: Adding rhythmic auditory stimuli (RAS) to balance training is beneficial for both freezers and nonfreezers, at least in persons with mild to moderate disease stages. This RAS-supported multimodal training has good potential for a wider clinical implementation with good long-term effects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".