Walk At Least 10 Minutes a Day for Adults With Knee Osteoarthritis: Recommendation for Minimal Activity During the COVID-19 Pandemic
Bibliographic record
Abstract
The emergence of the coronavirus disease 2019 (COVID-19) has resulted in unprecedented changes in how the world socially interacts. Limits on contact with others, whether by social distancing or shelter-at-home recommendations, have negatively affected physical activity (PA); this is especially true for adults over the age of 60 who are at high risk of serious illness from COVID-19. Adults with knee osteoarthritis (OA) is one particularly vulnerable group over the age of 60. Knee OA alone affects over one-third of the general population over 60 years of age1 and is a leading cause of functional limitation (e.g., difficulty climbing stairs, getting up from a chair)2. There is no cure for OA, but rather, treatment focuses on symptom management. Medical societies and clinical practice guidelines uniformly promote exercise as a first-line treatment approach for knee OA, with exercise shown to have greater improvements on pain and fewer adverse side effects when compared to nonsteroidal antiinflammatory drugs3. However, translating seemingly straightforward recommendations for exercise into practical messages remains problematic and a major problem during COVID-19, when physical activity is reduced. While previous work has reported that motivation for PA increases when adults with knee OA are provided a specific exercise prescription that factors in their condition, health professionals often struggle in making these specific exercise recommendations, resulting in a gap between treatment guidelines and actual practice. Hence, we chose to make a minimal PA recommendation for adults with knee OA over 60 years. Our goal is to limit risk of inactivity-related … Address correspondence to D.K. White, University of Delaware, Department of Physical Therapy, 540 South College Ave, 210L, Newark, DE 19713, USA. Email: dkw{at}udel.edu.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.007 |
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".