Cognitive Effects of Combined Aerobic Exercise and Cognitive Training in Older Adults with Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: Combined Aerobic exercise and Cognitive Training (ACT) may have synergistic effects on cognition, capitalizing on their different mechanisms of action. However, combined physical and cognitive activities showed mixed effects due to widely differing intervention components. To this end, the ACT Trial tested the efficacy of a 6-month combined cycling and speed of processing (SOP) cognitive training on cognition in community-dwelling older adults with amnestic mild cognitive impairment. METHODS: The ACT Trial used a 2x2 factorial design to randomize participants equally to four arms: control, cycling only, SOP only, and ACT (cycling+SOP). Executive function and episodic memory were measured with EXAMINER and Brief Visuospatial Memory Test-Revised (BVMT-R) at baseline, 3, 6, 12, and 18 months by trained data collectors blinded to group allocation. The mean of z-transformed scores of EXAMINER and BVMT-R was used to assess global cognition. Data were analyzed under intention-to-treat using linear mixed models with multiple imputed datasets in R. RESULTS: The sample (n = 146; 48% women; 91.8% White) was on average 73.72±5.73 years old, had 16.87±2.88 years of education, and scored 23.45±2.16 on Montreal Cognitive Assessment. All groups showed modest declines in outcomes from 3 months to 18 months (Cohen's ds=0.03-0.04 for executive function; ds=0.18-0.25 for delayed recall; ds=0.07-0.18 for global cognition). Baseline-adjusted ACT group means on outcomes (0.18 for executive function, 41.7 for memory, and 0.00 for global cognition at 6 months; 0.02, 42.5, 0.20, respectively at 18 months) did not differ significantly from those for cycling only (ps = .19, .56, and .90, respectively at 6 months; ps = .66, .81, and .65, respectively at 18 months) or SOP only (ps=.59, .13, and .56, respectively at 6 months; ps = .72, .43, and .48, respectively at 18 months). There were 10 possibly study-related, mild-to-moderate adverse events that did not differ between groups. CONCLUSION: ACT did not show statistically significant superior effects on cognition relative to its components among older adults with aMCI, although observed values trended in the desired directions. The COVID-19 pandemic contributed to higher attrition and lower dose delivery, especially in the ACT group, leading to smaller effect sizes than expected.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".