12-week Of Tai Chi Training Improves Cognitive Function In Older Adults With Mild Cognitive Impairment
Bibliographic record
Abstract
Manifestation of mild cognitive impairment (MCI) is an early sign indicative of accelerated decline in cognitive function during ageing that precedes the development of dementia. Its prevalence rate in older adults in China (≥ 60) ranges from 10% to 20%. To date, there is no documented pharmacological intervention for dementia. Preliminary studies, however, have shown that exercise can improve cognitive function. PURPOSE: This study aims to examine the effectiveness of Tai Chi training in improving cognitive function in older adults with MCI. METHODS: This randomized controlled trial was conducted between October, 2018 and May, 2019. In this two-arm, single-blinded randomized controlled trial, 20 Chinese adults aged ≥50 years with MCI [Score of Montreal Cognitive Assessment Hong Kong Version (MoCA-HK) below 7th percentile of the age and education-corrected normative data of Hong Kong] were randomly assigned to Control (CON, n=10, received no intervention) and Tai Chi (TC, n=10, received 12-week Tai Chi training) groups. Global cognitive function was the primary outcome which was assessed by MoCA-HK 12 weeks after post-randomization. Secondary outcomes including executive function, working memory, long term memory, and attention were assessed by trial making test A and B, digit span, 30-min delay recall test and attention network test respectively. Data were analyzed by generalized linear model with baseline as covariate. RESULTS: TC provoked a robust improvement in MoCA-HK score compared with CON (TC: +24% vs CON: +9%, P<0.001). TC participants also performed better in 30-min delay recall (TC: +52% vs CON: +8%, P=0.005) and trial making test B/A ratio compared with CON (TC: -21% vs CON: -2%, P=0.028). No statistical difference was observed in forward and back digit span. There was no statistical difference in reaction time, accuracy, alerting network and orienting network between the two groups. However the change in executive network was significantly different between TC and CON (TC: +19% vs CON: -24%, P<0.001). CONCLUSIONS: A 12-week Tai Chi training can improve global cognitive function in older adults with MCI. Tai Chi improves executive function and long-term memory and alters the attention network.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".