Effects of Exergaming-Based Tai Chi on Cognitive Function and Dual-Task Gait Performance in Older Adults With Mild Cognitive Impairment: A Randomized Control Trial
Bibliographic record
Abstract
Background: Declined cognitive function interferes with dual-task walking ability and may result in falls in older adults with mild cognitive impairment (MCI). The mind-body exercise, Tai Chi (TC), improves cognition and dual-task ability. Exergaming is low-cost, safe, highly scalable, and feasible. Whether the effects of exergaming-based TC is beneficial than traditional TC has not been investigated yet. Objectives: The objective of this study was to investigate effects of exergaming-based TC on cognitive function and dual-task walking among older adults with MCI. Methods: Fifty patients with MCI were randomly assigned to an exergaming-based TC (EXER-TC) group, a traditional TC (TC) group, or a control group. The EXER-TC and TC groups received 36 training sessions (three, 50-min sessions per week) during a 12-week period. The control group received no intervention and were instructed to maintain their usual daily physical activities. The outcome variables measured included those related to cognitive function, dual-task cost (DTC), and gait performance. Results: The EXER-TC and TC groups performed better than the control group on the Chinese version of the Stroop Color and Word Test, the Trail Making Test Parts A and B, the one-back test, gait speed, and DTC of gait speed in cognitive dual-task conditions after training. However, there were no significant differences between the EXER-TC and TC groups. Compared with the control group, only the EXER-TC group experienced beneficial effects for the Montreal Cognitive Assessment. Conclusion: EXER-TC was comparable to traditional TC for enhancement of dual-task gait performance and executive function. These results suggested that the EXER-TC approach has potential therapeutic use in older adults with MCI.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".