Dual-Task Walking Capacity Mediates Tai Ji Quan Impact on Physical and Cognitive Function
Bibliographic record
Abstract
PURPOSE: Emerging evidence indicates exercise training improves mobility and cognition and reduces falls in older adults, but underlying mechanisms are not well understood. This study tested the hypothesis that change in dual-task walking capacity mediates the positive effect of Tai Ji Quan and multimodal exercise on physical performance, activity confidence, global cognition, and falls among community-dwelling older adults at high risk of falling. METHODS: We conducted a secondary analysis of a 6-month randomized clinical trial comparing Tai Ji Quan: Moving for Better Balance (TJQMBB) and multimodal exercise to stretching exercise in a sample of 670 adults older than 70 yr who had a history of falls or impaired mobility. Distal outcome measures, ascertained at a 12-month follow-up, were the Short Physical Performance Battery, Activities-Specific Balance Confidence, Montreal Cognitive Assessment, and falls. The mediator hypothesized to account for the intervention effects was dual-task cost estimated by calculating changes in gait speed from single-task to dual-task walking from baseline to the end of intervention. RESULTS: At 12 months, compared with stretching exercise, multimodal exercise significantly improved Short Physical Performance Battery and Activities-Specific Balance Confidence outcomes and reduced the number of falls (P < 0.05). However, it did not lower dual-task cost or mediate the intervention effects on distal outcomes. In contrast, TJQMBB significantly reduced dual-task cost relative to multimodal and stretching exercises (P < 0.05) which in turn resulted in improvements in lower-extremity physical performance, activity confidence, global cognitive function, and reductions in falls (P < 0.05) during follow-up. CONCLUSIONS: Enhanced dual-task walking capacity as a result of Tai Ji Quan training mediated improvements in physical and cognitive outcomes in older adults at high risk of falling.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".