The efficiency of Ram Thai with Nine Square dance on physical performance and cognitive functions: a model for elderly school
Bibliographic record
Abstract
Age-related declines in health-related physical fitness and cognitive function can be mitigated by a multi-movement exercise program. Therefore, the aim of this study was to determine the efficiency of Ram Thai with nine square dances on physical performance and cognitive functions in the elderly. Participants were randomly assigned into an experimental or control group. The Montreal cognitive assessment-basic (MoCA-B, Thai version) were chosen from screened volunteers and randomly assigned into 2 groups; Ram Thai with nine square dances (RTND:33) and brisk walking exercise (BWE:34) aged 65.3±2.4 years old, body mass index (BMI) 25.5±11.9 kg/m2. The physical performance parameters assessed were as follows: Back-scratch test (BST), Chair sit and reach test (CSRT), Chair stand test (CST), 30-second arm curl test (ACT), 6-minute walk test (6-WT) and timed up and go test (TUG) were conducted respectively. Our results showed the physiological revealed a reduction in body fat percentage, while significant increase in VO2max test scores observed in both groups (p≤.05). Additionally, there was an improved lower limb strength, as evidenced by statistically significant increases in scores for the CST, 6-WT, and TUG compared to pretest values (p≤.05). In terms of BST performance, the RTND group showed significantly better results compared to the BWE group (p≤.001). Moreover, we discovered that significantly superior results indicate increased variability in MoCA-B scores (24.11≈26.37) among elderly participants in the RTND group (p≤.001). The data indicates that RTND effectively enhances physiological aspects, physical performance control, and overall cognitive function in elderly individuals with mild cognitive impairment (MCI). Keywords: physical performance, cognitive function, mild cognitive impairment, elderly
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".