Impact of a Light Volleyball Intervention Program on Improving Physical Attributes of Older Adults in Hong Kong: Preliminary Study of a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Physical inactivity, which increases the risk of chronic diseases in older adults, is prevalent among older adults in Hong Kong. To address this problem, the Hong Kong government has been proactively promoting active aging. Objective: Following the World Health Organization's strategy to prevent chronic diseases in older adults and aligning with the global goal of active aging, this study evaluated the effects of a 16-week light volleyball (LVB) intervention program on the physical health of older adults in Hong Kong. Methods: A total of 276 participants aged ≥60 years were recruited and randomly assigned to 1 of 3 groups: an LVB intervention group, a Taichi control group (ie, with light physical activity), and a control group. Tests on components of fitness were conducted before and after the intervention. Results: Participants from the LVB intervention group exhibited significant improvements in lower body strength (F2,272= 7.23, P=.001, η2=.05), agility (F2,272= 6.05, P=.003, η2=.043), and dynamic balance (F2,272= 9.41, P=.001, η2=.065) when compared with those from the Taichi active control group and control group. Conclusions: To promote active aging among older adults in Hong Kong, the findings of this preliminary study, along with forthcoming follow-up tests, will provide health specialists and practitioners with valuable insights regarding the health benefits of the LVB community program for older adults.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.001 |
| Research integrity | 0.001 | 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".