Physical Activity, Sedentary Behavior and Well-Being of Adults with Physical Disabilities and/or Chronic Diseases during the First Wave of the COVID-19 Pandemic: A Rapid Review
Bibliographic record
Abstract
Background: People with physical disabilities and/or chronic diseases report lower levels of physical activity and well-being than the general population, which potentially is exacerbated through the COVID-19 pandemic. This study explored the international literature on physical activity, sedentary behavior and well-being in adults with physical disabilities and/or chronic diseases during the first wave of the pandemic. Method: In a rapid review, we included studies reporting on physical activity, sedentary behavior and/or well-being in adults with physical disabilities and/or chronic diseases. Four databases (Pubmed, CINAHL, PsycInfo, Embase) were searched for studies published until 30 September 2020. Results: We included twenty-nine studies involving eleven different types of disabilities or health conditions from twenty-one different countries. Twenty-six studies reported on physical activity, of which one reported an increase during the COVID-19 pandemic, four studies reported no difference, and twenty-one studies reported a decrease. Thirteen studies reported a decline in well-being. Only one study measured sedentary behavior, reporting an increase. Conclusion: Despite the variety in methods used, almost all studies reported negative impacts on physical activity and well-being in people with physical disabilities and/or chronic disease during the first wave of the pandemic. These findings highlight the importance of supporting this population, especially in times of crisis.
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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 | 0.006 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".