Facilitators and Barriers of Tai Chi Practice in Community-Dwelling Older Adults: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Numerous studies have documented the beneficial effects of Tai Chi on a variety of health outcomes, especially in older adults. However, only few studies have examined how to improve the practice and adherence of this Asian-originated exercise among older adults in Western countries. OBJECTIVE: This study aimed to identify facilitators and barriers to Tai Chi practice and adherence in community-dwelling older adults. METHODS: This study analyzed the qualitative data collected from 13 participants (mean age 62.0, SD 10.3) at the end of a 15-week randomized controlled trial conducted at a day activity senior center. Semistructured interviews were conducted, recorded, and transcribed; and the data were analyzed using inductive thematic analysis. RESULTS: Four themes emerged: perceived benefit, threats, facilitators, and barriers. Perceived threats (eg, aging and side effects of medications) and perceived benefits of Tai Chi (eg, balance) inspired participants' engagement in Tai Chi exercise. On the other hand, barriers to Tai Chi practice and adherence included instructor's teaching style, the complexity of Tai Chi postures and movements, and existing health conditions (eg, hip problems). In essence, factors like Tai Chi class availability, family and peer support, as well as practicing Tai Chi with music may facilitate Tai Chi exercise adherence. CONCLUSIONS: The study findings could provide valuable information to health professionals, such as nurses and physical therapists, in developing and implementing effective Tai Chi programs in care plans. Considering health conditions, tailoring Tai Chi exercise instruction styles, encouraging social and peer support, and incorporating music may promote Tai Chi practice and adherence.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".