Effects of Cognitive Task Type and Complexity on Dual-Task Interference During Level-Ground Walking and Obstacle Negotiation in Individuals with Stroke
Bibliographic record
Abstract
Background Compromised dual-task walking ability reduces functional independence in community-dwelling individuals after stroke. Objective. To examine the influence of mobility task and cognitive task type and complexity, and their interaction on dual-task level-ground walking and obstacle-crossing after stroke. Methods Ninety-three individuals with chronic stroke (mean [SD] age = 62.4 [6.7] years, stroke duration = 67.7 [53.5] months) participated in this observational study with repeated measures. For each dual-task testing condition, a mobility task (level-ground walking or obstacle-crossing) was performed concurrently with 1 of 5 cognitive tasks (serial-subtractions, category naming, clock test, auditory discrimination, and shopping-list recall). Each cognitive task involved low and high complexity levels, yielding 20 dual-task conditions in total. Dual-task effect (DTE = [single-task − dual-task]× 100 /single-task) on walking distance (mobility-DTE) and number of correct responses (cognitive-DTE) were calculated for each dual-task condition. Results Medium to large interaction effects were observed between cognitive task type and complexity on cognitive ( F = 12.0-15.8, P < .001, ηp 2 = 0.12-0.15) and mobility performance ( F = 3.2-5.5, P < .05, ηp 2 = 0.03-0.06) during dual-task level-ground walking and obstacle-crossing. Among the cognitive tasks, serial-subtraction had the greatest interference effect on both cognitive (Mean DTE = −9.2 to −21.5%) and mobility performance (Mean DTE = −18.7 to −19.1%). Overall, “mobility interference” (decrement in walking distance without a decrement in cognitive performance) was the most common dual-task effect pattern observed. Conclusion The type and complexity level of the mobility and cognitive tasks interact to influence the degree and pattern of dual-task effects, with the serial-subtraction task inducing the greatest effect. Standardized assessments involving distinct cognitive domains are necessary for profiling dual-task interference during walking among individuals with chronic stroke.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".