Tai Chi workplace program for improving musculoskeletal fitness among female computer users
Bibliographic record
Abstract
BACKGROUND: Workplace computer use has increased dramatically in recent years and has been linked to musculoskeletal disorders, a leading cause of work disability and productivity losses in industrialized nations. Tai Chi is a simple, convenient workplace intervention that may promote musculoskeletal health without special equipment or showering, yet no study has investigated Tai Chi as a workplace physical exercise for health promotion. OBJECTIVE: To examine the effects of a workplace Tai Chi (TC) intervention on musculoskeletal fitness and psychological well-being among female university employees who are computer users. METHODS: The exercise program consisted of two 50 minute TC classes per week for 12 consecutive weeks during the months of May-August 2007. Fifty-two participants were enrolled in a class conducted on campus by a professional TC practitioner during the lunch hour. Socio-demographic characteristics, including information on age, marital status, ethnicity, job category and perceived overall health were collected from all participants. Fitness testing conducted by qualified personnel was assessed pre- and post-program. The tests included resting heart rate, resting blood pressure, anthropometric measures, musculoskeletal fitness and back fitness. Psychological well-being was assessed by the Perceived Stress Scale pre- and post-program. RESULTS: There were significant positive results in several areas including resting heart rate, waist circumference and hand grip strength. Results showed that the TC program was effective in improving musculoskeletal fitness and psychological well-being. CONCLUSIONS: Significant improvements in physiological and psychological measures were observed, even at the large class sizes tested here, suggesting that TC has considerable potential as an economic, effective and convenient workplace intervention.
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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 | 0.001 |
| 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) | 0.005 | 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".