Physical Activity and Inactivity Impacts on Cognitive and Emotional Functioning in Later Life
Bibliographic record
Abstract
Abstract Healthy aging is associated with changes in sensory, motor, cognitive, and emotional functions. Such changes depend on various factors. In particular, physical activity not only improves physical and motor but also cognitive and emotional functions. Observational (i.e., associations) and cross-sectional studies generally show a positive effect of regular physical exercise on cognition in older adults. Most longitudinal randomized controlled intervention studies also show positive effects, but the results are inconsistent due to large heterogeneity of methodological setups. Positive changes accompanying physical activity mainly impact executive functions, memory functions, and processing speed. Several factors influence the impact of physical activity on cognition, mainly the type and format of the activity. Strength training and aerobic training yield comparable but also differential benefits, and all should be used in physical activities. Also, a combination of physical activity with cognitive activity appears to enhance its effect on cognition in older age. Hence, such combined training approaches are preferable to homogeneous trainings. Studies of brain physiology changes due to physical activity show general as well as specific effects on certain brain structures and functions, particularly in the frontal cortex and the hippocampus, which are those areas most affected by advanced age. Physical activity also appears to improve cognition in patients with mild cognitive dysfunction and dementia and often ameliorates the disease symptoms. This makes physical training an important intervention for those groups of older people. Apart from cognition, physical activity leads to improvement of emotional functions. Exercise can lead to improvement of psychological well-being in older adults. Most importantly, exercise appears to reduce symptoms of depression in seniors. In future intervention studies it should be clarified who profits most from physical activity. Further, the conditions that influence the cognitive and emotional benefits older people derive from physical activity should be investigated in more detail. Finally, measures of brain activity that can be easily applied should be included as far as possible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".