Dual-Task Exercise Reduces Cognitive-Motor Interference in Walking and Falls After Stroke
Bibliographic record
Abstract
Background and Purpose- Functional community ambulation requires the ability to perform mobility and cognitive task simultaneously (dual-tasking). This single-blinded randomized controlled study aimed to examine the effects of dual-task exercise in chronic stroke patients. Methods- Eighty-four chronic stroke patients (24 women; age, 61.2±6.4 years; time since stroke onset, 75.3±64.9 months) with mild to moderate motor impairment (Chedoke-McMaster leg motor score: median, 5; interquartile range, 4-6) were randomly allocated to the dual-task balance/mobility training group, single-task balance/mobility group, or upper-limb exercise (control) group. Each group exercised for three 60-minute sessions per week for 8 weeks. The dual-task interference effect was measured for the time to completion of 3 mobility tests (forward walking, timed-up-and-go, and obstacle crossing) and for the correct response rate during serial-3-subtractions and verbal fluency task. Secondary outcomes included the Activities-specific Balance Confidence Scale, Frenchay Activities Index, and Stroke-specific Quality of Life Scale. The above outcomes were measured at baseline, immediately after, and 8 weeks after training. Fall incidence was recorded for a 6-month period posttraining. Results- Only the dual-task group exhibited reduced dual-task interference in walking time posttraining (forward walking combined with verbal fluency [9.5%, P=0.014], forward walking with serial-3-subtractions [9.6%, P=0.035], and the timed-up-and-go with verbal fluency [16.8%, P=0.001]). The improvements in dual-task walking were largely maintained at the 8-week follow-up. The dual-task cognitive performance showed no significant changes. The dual-task program reduced the risk of falls and injurious falls by 25.0% (95% CI, 3.1%-46.9%; P=0.037) and 22.2% (95% CI, 4.0%-38.4%; P=0.023), respectively, during the 6-month follow-up period compared with controls. There was no significant effect on other secondary outcomes ( P>0.05). Conclusions- The dual-task program was effective in improving dual-task mobility, reducing falls and fall-related injuries in ambulatory chronic stroke patients with intact cognition. It had no significant effect on activity participation or quality of life. Clinical trial registration- URL: https://www.clinicaltrials.gov . Unique identifier: NCT02270398.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| 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".