Development of a 12-Week Unsupervised Online Tai Chi Program for People With Hip and Knee Osteoarthritis: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis is a leading contributor to global disability. While evidence supports the effectiveness of Tai Chi in improving symptoms for people with hip/knee osteoarthritis, access to in-person Tai Chi classes may be difficult for many people. An unsupervised online Tai Chi intervention for people with osteoarthritis can help overcome accessibility barriers. The Approach to Human-Centered, Evidence-Driven Adaptive Design (AHEAD) framework provides a practical guide for co-designing such an intervention. OBJECTIVE: This study aims to develop an unsupervised online Tai Chi program for people with hip/knee osteoarthritis. METHODS: An iterative process was conducted using the AHEAD framework. Initially, a panel of Tai Chi instructors and people with osteoarthritis was assembled. A literature review was conducted to inform the content of a survey (survey 1), which was completed by the panel and additional Australian Tai Chi instructors to identify Tai Chi movements for potential inclusion. Selection of Tai Chi movements was based on 3 criteria: those that were appropriate (for people with hip/knee osteoarthritis aged 45+ years), safe (to be performed at home unsupervised), and practical (to be delivered online using prerecorded videos). Movements that met these criteria were then ranked in a second survey (survey 2; using conjoint analysis methodology). Survey findings were discussed in a focus group, and the Tai Chi movements for program use were identified. A draft of the online Tai Chi program was developed, and a final survey (survey 3) was conducted with the panel to rate the appropriateness and safety of the proposed program. The final program was developed, and usability testing (think-aloud protocol) was conducted with people with knee osteoarthritis. RESULTS: The panel consisted of 10 Tai Chi instructors and 3 people with osteoarthritis. The literature review identified Yang Style 24 as a common and effective Tai Chi style used in hip/knee osteoarthritis studies. Surveys 1 (n=35) and 2 (n=27) produced a ranked list of 24 Tai Chi movements for potential inclusion. This list was refined and informed by a focus group, with 10 Tai Chi movements being selected for inclusion (known as the Yang Style 10 form). Survey 3 (n=13) found that 92% (n=12) of the panel members believed that the proposed draft Tai Chi program was appropriate and safe, resulting in its adoption. The final program was produced and hosted on a customized website, "My Joint Tai Chi," which was further refined based on user feedback (n=5). "My Joint Tai Chi" is currently being evaluated in a randomized controlled trial. CONCLUSIONS: This study demonstrates the use of the AHEAD framework to develop an unsupervised online Tai Chi intervention ("My Joint Tai Chi") for people with hip/knee osteoarthritis. This intervention is now being tested for effectiveness and safety in a randomized controlled trial.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".