Effect of a Perturbation-Based Balance Training Program on Compensatory Stepping and Grasping Reactions in Older Adults: A Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Compensatory stepping and grasping reactions are prevalent responses to sudden loss of balance and play a critical role in preventing falls. The ability to execute these reactions effectively is impaired in older adults. OBJECTIVE: The purpose of this study was to evaluate a perturbation-based balance training program designed to target specific age-related impairments in compensatory stepping and grasping balance recovery reactions. DESIGN: This was a double-blind randomized controlled trial. SETTING: The study was conducted at research laboratories in a large urban hospital. PARTICIPANTS: Thirty community-dwelling older adults (aged 64-80 years) with a recent history of falls or self-reported instability participated in the study. INTERVENTION: Participants were randomly assigned to receive either a 6-week perturbation-based (motion platform) balance training program or a 6-week control program involving flexibility and relaxation training. MEASUREMENTS: Features of balance reactions targeted by the perturbation-based program were: (1) multi-step reactions, (2) extra lateral steps following anteroposterior perturbations, (3) foot collisions following lateral perturbations, and (4) time to complete grasping reactions. The reactions were evoked during testing by highly unpredictable surface translation and cable pull perturbations, both of which differed from the perturbations used during training. RESULTS: /b> Compared with the control program, the perturbation-based training led to greater reductions in frequency of multi-step reactions and foot collisions that were statistically significant for surface translations but not cable pulls. The perturbation group also showed significantly greater reduction in handrail contact time compared with the control group for cable pulls and a possible trend in this direction for surface translations. LIMITATIONS: Further work is needed to determine whether a maintenance program is needed to retain the training benefits and to assess whether these benefits reduce fall risk in daily life. CONCLUSION: Perturbation-based training shows promise as an effective intervention to improve the ability of older adults to prevent themselves from falling when they lose their balance.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".