Comparison of functional fitness outcomes in experienced and inexperienced older adults after 16-week tai chi program.
Bibliographic record
Abstract
CONTEXT: The positive effects of physical activity on the well-being of older adults have been well documented. Tai chi is a suitable form of physical activity, with known physical and psychological benefits for older adults. OBJECTIVE: The objective of the current study was to compare the effects of participation in a 16-wk tai chi program on the functional fitness of older adults with and without previous tai chi experience. DESIGN: The research team designed a prospective cohort study. Participants who had practiced tai chi previously for ≥1 y at baseline were classified as experienced; all others were considered inexperienced. SETTING: The study took place at 2 community centers in 2 locations in the Greater Toronto area of Ontario, Canada. PARTICIPANTS: Participants were residents of the 2 communities. INTERVENTION: Participants were instructed to attend two 1-h sessions of Yang-style tai chi per wk. OUTCOME MEASURES: Data on functional fitness- strength, endurance, speed, and flexibility-were collected at baseline and after completion of the tai chi program. RESULTS: Of the 143 participants who completed the study, 20.5% were classified as experienced. Experienced participants had significantly higher ratings on functional fitness tests at baseline compared with the inexperienced group. At the end of the study, inexperienced participants had experienced significant improvements in all measures of functional fitness, although experienced participants had shown significant improvements only in measures of endurance and speed. CONCLUSION: Tai chi appears to be an optimal mode of physical activity for older adults regardless of previous experience with tai chi.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".