The mental-attention Tai Chi effect with older adults
Bibliographic record
Abstract
BACKGROUND: Tai Chi practice has some fitness, wellness, and general cognitive effects in older adults. However, benefits of Tai Chi on specific mental-attentional executive processes have not been investigated previously. We studied older Canadian adults of Chinese and non-Chinese origin and from low socioeconomic areas. METHODS: Sixty-four adults (51-87 years old) took part in a 16-week Tai Chi program. There were two groups: Chinese-background (n = 35) and Non-Chinese-background (n = 29). They received four mental-attention executive tasks before and after the 16-week period. These tasks measured visuospatial reasoning, mental-attentional activation (working memory), attentional inhibition, and balance between these attention factors (field-dependence-independence). RESULTS: Chinese participants showed significant gain on Figural Intersections Task (mental-attentional capacity), Antisaccade (attentional inhibition), and Matrix Reasoning (fluid intelligence measure). Both groups evidenced gain on the Water Level Task (attentional balance). CONCLUSIONS: These gains suggest that Tai Chi can improve mental-attentional vigilance and executive control, when practitioners are sufficiently motivated to pursue this practice, and apply themselves (as our Chinese participants seem to have done). We found that Tai Chi enhanced mental attentional executives in the Chinese sample. The largely negative results with Non-Chinese participants might be explained by less strong motivation and by the relatively short Tai Chi practice period, which contrasts with the prior familiarity with Tai Chi of the Chinese participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".