A Tai Chi Program Improves Physical Performance Measures in Adolescents With Down Syndrome and Enhances Their Parents’ Psychological Well-Being: A Randomized Controlled Trial
Bibliographic record
Abstract
To investigate the effect of a 6-week tai chi (TC) training program on physical performance in adolescents with Down syndrome and its influence on the psychological well-being of their parents, in a randomized controlled design, 25 male adolescents with Down syndrome (age 14.4 ± 1.30 years) were randomly assigned to a control group (n = 10) or a training group (n = 15). Before and after the training period, lower limb explosive strength, upper limb strength, flexibility, and balance were assessed in all participants, as well as their parents' psychological well-being. Using 2 × 2 repeated-measures analysis of variance, significant Group × Time interactions (p < .05; .33<ηp2<.87) were found for physical measures and parents' depression, anxiety, and stress symptoms. A 6-week TC program significantly improved lower limb explosive strength (p < .001; d = 1.21), upper limb strength (p < .001; d = 1.49), flexibility (p < .001; d = 1.11), and static balance (p < .001; d = 1.99) and reduced depression (p < .001; d = 1.89), anxiety (p < .001; d = 1.74), and stress scores (p < .001; d = 1.88) in parents in the training group compared with those in the control group. TC programs improve physical measures in adolescents with Down syndrome and psychological well-being of their parents. Establishing TC programs in sport associations could positively impact this population's physical performance.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".