Efficacy of supervised Tai Chi exercises versus conventional physical therapy exercises in fall prevention for frail older adults: a randomized controlled trial
Bibliographic record
Abstract
Purpose: To compare the effectiveness of supervised Tai Chi exercises versus the conventional physical therapy exercises in a personalized rehabilitation program in terms of the incidence and severity of falls in a frail older population. Method: The participants were frail older adults living in the community, admitted to the day hospital program in Sherbrooke, Quebec, Canada (n = 152). They were randomized to receive a 15-week intervention, either by supervised Tai Chi exercises (n = 76) or conventional physical therapy (n = 76). Fall incidence and severity were assessed using both the calendar technique and phone interviews once a month during 12 months following the end of the intervention. Other variables were collected at baseline to compare the two groups: age, comorbidity, balance, sensory interaction on balance, and self-rated health. Results: Both interventions demonstrated a protective effect on falls but Tai Chi showed a greater one (RR = 0.74; 95% CI = 0.56–0.98) as compared to conventional physical therapy exercises. Conclusions: Supervised Tai Chi exercises as part of a rehabilitation program seem to be a more effective alternative to the conventional physical therapy exercises for this specific population.Implications for RehabilitationSeniors who have fallen have a 50% chance of falling again during the following year, leading them to reduce their outings and thus decrease their social activities.Frail older people could benefit more from an individualized intervention than the regular group program generally used in a Tai Chi intervention.Tai Chi exercises seems to be a good alternative to regular physiotherapy exercises as a part of a multidisciplinary intervention in preventing a subsequent fall over a 12-month period.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".