Exercise Leads to Faster Postural Reflexes, Improved Balance and Mobility, and Fewer Falls in Older Persons with Chronic Stroke
Bibliographic record
Abstract
OBJECTIVES: To determine the effect of two different community-based group exercise programs on functional balance, mobility, postural reflexes, and falls in older adults with chronic stroke. DESIGN: A randomized, clinical trial. SETTING: Community center. PARTICIPANTS: Sixty-one community-dwelling older adults with chronic stroke. INTERVENTION: Participants were randomly assigned to an agility (n=30) or stretching/weight-shifting (n=31) exercise group. Both groups exercised three times a week for 10 weeks. MEASUREMENTS: Participants were assessed before, immediately after, and 1 month after the intervention for Berg Balance, Timed Up and Go, step reaction time, Activities-specific Balance Confidence, and Nottingham Health Profile. Testing of standing postural reflexes and induced falls evoked by a translating platform was also performed. In addition, falls in the community were tracked for 1 year from the start of the interventions. RESULTS: Although exercise led to improvements in all clinical outcome measures for both groups, the agility group demonstrated greater improvement in step reaction time and paretic rectus femoris postural reflex onset latency than the stretching/weight-shifting group. In addition, the agility group experienced fewer induced falls on the platform. CONCLUSION: Group exercise programs that include agility or stretching/weight shifting exercises improve postural reflexes, functional balance, and mobility and may lead to a reduction of falls in older adults with stroke.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".