Exercise and Language Performance in Healthy Aging, Stroke and Neurodegenerative Conditions: a Scoping Review
Bibliographic record
Abstract
Background: While the benefits of exercise on cognitive functions have already been reviewed, little is known about the impact of exercise on language performance. This scoping review was conducted to identify existing evidence on exercise-induced changes in language performance in healthy aging individuals and adults with stroke or neurodegenerative conditions. Methods & Results: Using the Arksey and O'Malley framework, 29 studies were included. Eleven studies in healthy aging indicated enhanced language performance, with 72.72% having significant improvement in semantic/phonological Verbal Fluency (VF) following exercise. Among 18 studies on older adults with stroke or neurodegenerative conditions, 11 reported better language performance, with 44.44% having significant improvement in picture naming/description and semantic/phonological VF by exercise. The seven remaining studies reported no significant change in language performance in persons with stroke or neurodegenerative conditions. Conclusion: Overall, exercise interventions showed improvement in language performance in healthy aging, while selective enhancement was shown for language performance in persons with either stroke or neurodegenerative conditions.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".