Combined Dual-Task Gait Training and Aerobic Exercise to Improve Cognition, Mobility, and Vascular Health in Community-Dwelling Older Adults at Risk for Future Cognitive Decline
Bibliographic record
Abstract
This 6-month experimental case series study investigated the effects of a dual-task gait training and aerobic exercise intervention on cognition, mobility, and cardiovascular health in community-dwelling older adults without dementia. Participants exercised 40 min/day, 3 days/week for 26 weeks on a Biodex GaitTrainer2 treadmill. Participants were assessed at baseline (V0), interim (V1: 12-weeks), intervention endpoint (V2: 26-weeks), and study endpoint (V3: 52-weeks). The study outcomes included: cognition [executive function (EF), processing speed, verbal fluency, and memory]; mobility: usual & dual-task gait (speed, step length, and stride time variability); and vascular health: ambulatory blood pressure, carotid arterial compliance, and intima-media thickness (cIMT). Fifty-six participants [age: 70(6) years; 61% female] were included in this study. Significant improvements following the exercise program (V2) were observed in cognition: EF (p = 0.002), processing speed (p < 0.001), verbal fluency [digit symbol coding (p < 0.001), phonemic verbal fluency (p < 0.001)], and memory [immediate recall (p < 0.001) and delayed recall (p < 0.001)]; mobility: usual & dual-task gait speed (p = 0.002 and p < 0.001, respectively) and step length (p = 0.001 and p = 0.003, respectively); and vascular health: cIMT (p = 0.002). No changes were seen in the remaining outcomes. In conclusion, 26 weeks of dual-task gait training and aerobic exercise improved performance on a number of cognitive outcomes, while increasing usual & dual-task gait speed and step length in a sample of older adults without dementia.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".