Evaluating the YMCA Move for Health Program in Individuals With Osteoarthritis and Assessing Maintenance During the COVID-19 Pandemic
Bibliographic record
Abstract
Osteoarthritis is the most common condition to co-occur with other chronic health conditions and a broad exercise program on management of chronic conditions may be suitable for this group. This study evaluated the 12-week YMCA Move for Health exercise program among adults with osteoarthritis or with/at risk of chronic health conditions using a mixed-methods study design based on the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework. Participants (n = 66) completed the exercise program at the YMCAs in Cambridge, Kitchener, and Waterloo. Assessments included physical function, health-related quality of life, symptoms of arthritis, and physical activity levels and were conducted at baseline (B), postprogram (PP), and 3-month postprogram. Due to interruption by COVID-19, a subgroup of participants completed the 3-month postprogram assessments after the onset of the pandemic. At PP, participants with OA showed significant improvements in level of disability (B = 0.63 ± 0.45 and PP = 0.55 ± 0.47; p = .049), pain (B = 4.3 ± 2.5 and PP = 3.6 ± 2.4; p = .026), fatigue (B = 3.9 ± 3.1 and PP = 2.8 ± 2.6; p = .003), and several domains related to health-related quality of life. Despite interruption by the COVID-19 pandemic and poor maintenance of physical activity levels, nearly all improvements related to level of disability, symptoms of arthritis, and health-related quality of life observed at PP were maintained 3-months postprogram. The Move for Health program proved to be a feasible and effective community program for people with osteoarthritis. Additional supports may be needed to maintain physical activity levels after the program.
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 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".