Comparing the effects of acute aerobic exercise on cognition in older adults
Bibliographic record
Abstract
In a rapidly aging Canadian society, the prevalence of chronic disease has become a major health concern. With a large number of the population be over the age of 55, Canada is experiencing a surge of age-related declines in cognitive functioning including memory, attention, and processing speed, with an increase in cognitive disorders, such as Alzheimer's. Pharmaceutical options have been explored, however, this is placing a cost-burden on the Canadian Healthcare System. Safe and cost-effective alternatives need to be implemented to reduce this burden and improve overall quality of life. It is well-known that regular physical activity has immense physiological and psychological benefits. Aerobic training, in particular, can improve central and peripheral aspects of cardiorespiratory fitness. It has also been found that moderate and high intensity aerobic exercise can improve cognitive functioning in older adults, specifically executive function. This is important for slowing cognitive decline, as executive function is the first aspect of cognition to deteriorate, but it is also the first to improve with exercise. An acute bout of high intensity interval exercise (HIIE) and moderate intensity continuous training (MICE) have been found to improve cognitive function in older adults, however the appropriate intensity and duration remains unclear, as well as the mechanisms explaining these improvements. This study is looking to investigate the differences in cognitive performance following an acute bout of HIIE and MICE, with the aim of discovering the safest and most promising dose-response relationship to slow cognitive decline.
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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 | 0.001 |
| 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".