Bibliographic record
Abstract
OBJECTIVE: To summarize the evidence on the health benefits of tai chi. SOURCES OF INFORMATION: A literature review was conducted on the benefits of tai chi for 25 specific conditions, as well as for general health and fitness, to update a 2014 review of systematic reviews. Systematic reviews and recent clinical trials were assessed and organized into 5 different groups: evidence of benefit as excellent, good, fair, or preliminary, or evidence of no direct benefit. MAIN MESSAGE: During the past 45 years more than 500 trials and 120 systematic reviews have been published on the health benefits of tai chi. Systematic reviews of tai chi for specific conditions indicate excellent evidence of benefit for preventing falls, osteoarthritis, Parkinson disease, rehabilitation for chronic obstructive pulmonary disease, and improving cognitive capacity in older adults. There is good evidence of benefit for depression, cardiac and stroke rehabilitation, and dementia. There is fair evidence of benefit for improving quality of life for cancer patients, fibromyalgia, hypertension, and osteoporosis. Current evidence indicates no direct benefit for diabetes, rheumatoid arthritis, or chronic heart failure. Systematic reviews of general health and fitness benefits show excellent evidence of benefit for improving balance and aerobic capacity in those with poor fitness. There is good evidence for increased strength in the lower limbs. There is fair evidence for increased well-being and improved sleep. There were no studies that found tai chi worsened a condition. A recent systematic review on the safety of tai chi found adverse events were typically minor and primarily musculoskeletal; no intervention-related serious adverse events have been reported. CONCLUSION: There is abundant evidence on the health and fitness effects of tai chi. Based on this, physicians can now offer evidence-based recommendations to their patients, noting that tai chi is still an area of active research, and patients should continue to receive medical follow-up for any clinical conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.078 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".