Physical Activity Intervention In Older Adults
Bibliographic record
Abstract
There are well documented positive effects of physical activity on general health and wellbeing throughout the lifespan. Next to it, beneficial effects of physical exercise interventions at improving brain health and functioning in older adults are also well reported whereas individual differences and mechanisms to gain functional capacities related to cognitive baseline level need to be investigated. PURPOSE: To investigate the influence of cognitive baseline level on gaining functional performance in older adults after 3-month of physical exercise intervention. METHODS: Thirty older adults (68±5y, 27% men) were enrolled in 3-month twice per week physical exercise program and were randomly divided into experimental (EG; N=19) or control group (CON; N=11). For further analysis we took into account EG with low cognitive [LC; Montreal Cognitive Assessment (MoCA) score <23; N=6] and high cognitive (HC; MoCA score >28; N=8) score. Functional performance was assessed by the means of Senior Fitness Test. RESULTS: We found a significant interaction of time/group (P=.004). Post hoc comparison showed differences in pre to post measurements between LC and CON in Time Up to Go test (TUG; P=.002), while no differences were found between HC and CON (P=.159) as well as for LC and HC (P=.127). Moreover, the percent of change analysis showed pre to post improvements (P<0.05) for both, LC and HC (-22% vs -10%), except the CON (-1%). Finally, other sub-tests from Senior Fitness Test battery presented tendencies but failed to reach significance level. CONCLUSION: Although direct comparison (pre to post change) failed to demonstrate difference between two EG, comparison of both EG with CON, confirmed our hypothesis that older adults with lower baseline cognitive function were able to achieve more functional capacity gains after 3 month of physical training intervention, as compared to those with higher baseline cognitive function.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".