Rehabilitation of Falls in Parkinson’s Disease: Self-Perception vs. Objective Measures of Fall Risk
Bibliographic record
Abstract
Falls are an important cause of injury and increased hospital/long-term care facility stays and has been reported in 70% of people with Parkinson’s disease (PD), yet there is limited effectiveness of medications for reducing falls. As an adjunct, many exercise therapies succeed in objectively reducing the number of falls, but this may not translate to improved quality of life (QOL). Importantly, self-perceived fall risk has a greater influence on activities of daily living and QOL, making it important to evaluate in the rehabilitation of PD. The purpose of this study was to examine the influence of a 10-week exercise intervention (PD SAFE × TM) on self-perceived (according to balance confidence measures) and objective measures of gait that are commonly linked to fall risk in PD. Participants (N = 44) with PD completed PD SAFE × TM. Pre-/post-assessment involved the Activities-specific Balance Confidence Scale (perception), objective falls characteristics (stride time, stride width, stride length, and stride variability), and symptom severity (Unified Parkinson’s Disease Rating Scale motor subsection III (UPDRS-III)) after participants were stratified into a mild (no-balance impairment) vs. severe (balance impairment) groups. Overall disease severity (F (1, 43) = 8.75, p < 0.003) and all objective fall parameters improved (p < 0.05) in both groups, yet self-perceived fall risk improved in only the severe PD group F (1, 43) = 9.86, p < 0.022. Given that self-perceived fall risk and objective fall risk both play a role in the quality of life, identifying strategies to improve both aspects may be important in improving the overall quality of life.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".