Effects of Tai Ji Quan training on gait kinematics in older Chinese women with knee osteoarthritis: A randomized controlled trial
Bibliographic record
Abstract
Background Although Tai Ji Quan has been shown to relieve pain and improve functional mobility in people with knee osteoarthritis (OA), little is known about its potential benefits on gait characteristics among older Chinese women who have a high prevalence of both radiographic and symptomatic knee OA. This study aims to assess the efficacy of a tailored Tai Ji Quan intervention on gait kinematics for older Chinese women with knee OA. Methods A randomized controlled trial involving 46 older women in Shanghai, China, with clinically diagnosed knee OA. Randomized (1:1) participants received either a 60 min Tai Ji Quan session ( n = 23) 3 times weekly or a 60 min bi-weekly educational session ( n = 23) for 24 weeks. Primary outcomes were changes in gait kinematic measures from baseline to 24 weeks. Secondary outcomes included changes in scores on the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and Short Physical Performance Battery (SPPB). Results After 24 weeks the Tai Ji Quan group demonstrated better performance in gait velocity (mean difference, 8.40 cm/s, p = 0.01), step length (mean difference, 3.52 cm, p = 0.004), initial contact angle (mean difference, 2.19°, p = 0.01), and maximal angle (mean difference, 2.61°, p = 0.003) of flexed knees during stance phase compared to the control group. In addition, the Tai Ji Quan group showed significant improvement in WOMAC scores ( p < 0.01) (mean difference, −4.22 points in pain, p = 0.002; −2.41 points in stiffness, p < 0.001; −11.04 points in physical function, p = 0.006) and SPPB scores (mean difference, 1.22 points, p < 0.001). Conclusion Among older Chinese women with knee OA, a tailored Tai Ji Quan intervention improved gait outcomes. The intervention also improved overall function as indexed by the WOMAC and SPPB. These results support the use of Tai Ji Quan for older Chinese adults with knee OA to both improve their functional mobility and reduce pain symptomatology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".