Evaluating the Effects of A Twelve-Week Structured Exercise Program on Cognitive Performance and Brain Health in Older Adults
Bibliographic record
Abstract
This study investigates the impact of a 12-week structured exercise program on cognitive function and brain health in older adults. A total of 100 participants aged 60 and above, with no severe cognitive impairment, were randomly assigned to an experimental group (n = 50) and a control group (n = 50). The experimental group participated in a program combining aerobic exercise, resistance training, and balance exercises, while the control group maintained their usual daily activities. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Trail Making Test (TMT), and brain health was measured through blood-derived brain-derived neurotrophic factor (BDNF) levels and transcranial Doppler ultrasonography to evaluate cerebral blood flow. Pre-test and post-test data were analyzed using paired t-tests, independent samples t-tests, and ANCOVA to account for baseline differences. Results indicated significant improvements in cognitive performance, BDNF levels, and cerebral blood flow in the experimental group compared to the control group (p < 0.05). This study demonstrates that regular, structured exercise can effectively enhance cognitive function and brain health in older adults, addressing a significant gap in the literature regarding the role of multifaceted exercise programs in cognitive aging. These findings suggest that exercise may be a promising intervention to prevent cognitive decline and improve brain health in aging populations.
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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) | 0.000 | 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 | 0.000 |
| 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".