Feasibility of a 6-Month Exercise and Recreation Program to Improve Executive Functioning and Memory in Individuals With Chronic Stroke
Bibliographic record
Abstract
BACKGROUND: Physical activity is beneficial for improving cognitive function in healthy older adults. However, research results on the benefits of physical activity on cognitive performance after stroke are limited. OBJECTIVE: To determine if a combined exercise and recreation program can improve the executive functioning and memory of individuals with chronic stroke. METHODS: In all, 11 ambulatory participants with chronic stroke (mean age 67 ± 10.8 years) participated in a 6-month program of exercise for 2 hours and recreation for 1 hour weekly. Executive functions and memory were assessed at baseline and at 3 and 6 months by a battery of standard neuropsychological tests, including response inhibition, cognitive flexibility, dual task (motor plus cognitive), and memory. Motor ability was also assessed. Nonparametric statistics were used to obtain the differences between the 3 assessments. RESULTS: At baseline, substantial deficits in all aspects of executive functioning were revealed. From baseline to 3 months, the mean improvement was 10% ± 14% for the dual task (Walking While Talking), -3% ± 22% (χ(2) = 2.4; P > .05) for response inhibition (Stroop Test), and 61% ± 69% for memory (Rey Auditory Verbal Learning Test-long delay). From baseline to 6 months, the mean improvement was 7% ± 7.5% for response inhibition (Stroop Test). In addition, knee strength and walking speed improved significantly at 3 months. CONCLUSIONS: This pilot study suggests that exercise and recreation may improve memory and executive functions of community-dwelling individuals with stroke. Further studies require a larger sample size and a control group.
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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 | 0.001 | 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".