Comparison of Square-Stepping and Strengthening Exercises via Telerehabilitation in Individuals with COPD: A Randomised Trial
Bibliographic record
Abstract
Background/Objectives: Chronic obstructive pulmonary disease (COPD) is a common, treatable condition causing respiratory symptoms and systemic effects. Physical activity can improve cognitive function in individuals with COPD, with Square-Stepping Exercise (SSE), a multitasking program combining cognitive and physical tasks, showing potential benefits. This study compares the effects of SSE and strengthening exercises (SE) on cognitive function and balance in individuals with COPD via telerehabilitation. Methods: This randomized clinical trial involved 34 male individuals with COPD divided into SSE and SE groups (n=17 each). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), and balance was measured with the Biodex Balance System. Both interventions were conducted over 8 weeks through telerehabilitation. Results: Both groups showed significant improvement in cognitive function (p=0.01). However, the SSE group showed greater improvements in balance, particularly in the overall stability index and anterior/posterior stability index (p=0.014 and p=0.05). The SE group had minor improvements in specific balance parameters, such as the "eyes open, firm surface" condition (p=0.029). Although cognitive gains were similar between the groups, balance improvement was more pronounced in the SSE group. Conclusions: AThis randomized trial revealed that both SSE and SE, delivered via telerehabilitation, significantly improved cognitive function in individuals with COPD, with SSE offering superior balance enhancement. These findings suggest that multitasking exercises like SSE may have a synergistic effect on both cognitive and physical functions, reducing the risk of falls in individuals with COPD.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".