The effect of single-task versus dual-task assessment on muscle strength and performance in individuals with knee osteoarthritis
Bibliographic record
Abstract
Background Dual-task activities, which involve performing two separate tasks simultaneously, often result in reduced motor function and daily activity performance among individuals with knee osteoarthritis (OA).Objective This study aimed to investigate the impact of single- and dual-task conditions on muscle strength and performance in individuals with knee OA and examine how cognitive load influences physical task performance in this population.Methods Sixty patients with knee OA were included. Baseline data included demographic characteristics, pain (Visual Analog Scale), and physical function (Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)). Muscle strength and performance were assessed using isokinetic and sit-to-stand tests, initially under single-task conditions, and then under dual-task conditions three days later. Dual-tasking involved physical tasks with varying cognitive exercises (changed between sessions) and familiarization sessions to minimize learning effects.Results The investigation revealed that individuals with knee OA showed reduced muscle strength and impaired sit-to-stand performance during dual-task activities, with lower peak torque (p = .0025), total work (p = .026), and longer time to peak torque (p = .011). Decreased muscle performance correlated with worse WOMAC scores (p ≤ .01, r = -0.506), particularly in dual-task conditions. Regression analysis identified extension total work and the sit-to-stand test as key predictors of dual-task performance, explaining 32.2% of the variance.Conclusion Dual-task performance impairs muscle strength and physical function in individuals with knee OA, demonstrated by reduced peak torque, total work, and sit-to-stand performance. Extension total work and sit-to-stand test emerged as key predictors of dual-task performance, emphasizing the need to address cognitive load in rehabilitation strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".