Effects of tai chi training in dynapenic and nondynapenic postmenopausal women
Bibliographic record
Abstract
OBJECTIVE: The purpose of the present study was to investigate the effects of a 12-week tai chi program in type I dynapenic and nondynapenic postmenopausal women. METHODS: Sixty-two postmenopausal women were recruited. Body composition, handgrip strength, functional capacities, cardiorespiratory functions (forced expiratory volume in 1 s and oxygen consumption per unit time peak), and quality of life (36-item Short-Form Health Survey) were measured before and after the intervention. RESULTS: Type I dynapenic postmenopausal women showed a significant decrease in body weight (P = 0.004), fat mass percentage (P = 0.02), and skeletal muscle mass (SM; in kilograms; P = 0.02), whereas handgrip strength (in kilograms per SMkg; P = 0.04), functional capacity test scores (P ≤ 0.050), and general health perception (P = 0.01) significantly increased. In nondynapenic postmenopausal women, we observed a significantly decreased waist circumference (P = 0.04) and a significantly increased chair-stand test (P < 0.001) and one-leg stance test (P = 0.04) scores. In addition, significantly lower systolic (P ≤ 0.001) and diastolic (P ≤ 0.005) blood pressures were observed in both groups after the intervention. Finally, type I dynapenic women showed a more pronounced general health perception increase compared with nondynapenic individuals (P = 0.03). CONCLUSIONS: Tai chi training improved body composition, muscle strength, functional capacities, and general health perception in postmenopausal women, and this last improvement was more pronounced in type I dynapenic individuals. Therefore, tai chi may be considered as an alternative physical training method in preventing the occurrence of disabilities and frailty in postmenopausal women with type I dynapenia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".