Physical Exercise Training Effect and Mediation Through Cardiorespiratory Fitness on Dual-Task Performances Differ in Younger–Old and Older–Old Adults
Bibliographic record
Abstract
OBJECTIVE: It has often been reported that dual-task (DT) performance declines with age. Physical exercise can help improve cognition, but these improvements could depend on cognitive functions and age groups. Moreover, the mechanisms supporting this enhancement are not fully elucidated. This study investigated the impacts of physical exercise on single- and dual-task performance in younger-old (<70) and older-old (70+) adults. The study also assessed whether the training effect on cognition was mediated by improvement in cardiorespiratory fitness. METHODS: One hundred forty-three participants (65-89 years) took part in a physical exercise intervention for 3 months or were assigned to a control group. All participants completed a DT paradigm and an estimated measure of cardiorespiratory fitness. Regression models were used to test the training effect on these outcomes, and mediation analyses were used to determine whether the training-related cognitive changes were mediated by changes in cardiorespiratory fitness. RESULTS: In 70+, training predicted improved processing speed (βc = -.33) and cardiorespiratory fitness (βa = .26) and the effect of training on processing speed was fully mediated by change in cardiorespiratory fitness (βab = -.12). In <70, training predicted improvement in task-set cost (βc = -.26) and change in cardiorespiratory fitness (βa = .30) but improvement in task-set cost was not entirely mediated by change in cardiorespiratory fitness. DISCUSSION: Results are discussed in terms of the mechanisms supporting DT performance improvement following physical exercise training in older adults.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".