COVID transmission-related concerns impact on physical activity behavior: data from the iCare study.
Bibliographic record
Abstract
Objective: We explored the relationship between COVID-19 transmission-related concerns and reduced physical activity during COVID (RPAC). Methods: We analyzed data from 2,543 participants across Argentina, Brazil, Colombia, Canada, and the USA with at least 200 participants per country. The two primary concerns assessed were: a) fear of being infected, and 2) concern about personal health if infected. Participants were asked to report changes in their physical activity (PA) behavior since COVID-19 pandemic started. Results: The sample was predominantly female (75.7%), with 66.9% aged between 30-64 years. The prevalence of participants who reported RPAC remained stable in South American countries but increased in Canada (+7.8 percentage points [p.p.]; p = 0.001) and decreased in the USA (-9.7 pp; p = 0.003). Concerns about personal health were significantly associated with RPAC in South America (PR = 1.47; 95% CI: 1.09; 1.97), while no association was found in North America. Notably, participants from Colombia (PR = 1.90; 95% CI: 1.09; 3.31), and the USA (PR = 1.48; 95% CI: 1.01; 2.17) were more likely to report RPAC due to COVID-19 concerns. Conclusion: While participants reduced their PA behavior in South American countries and Canada during the first 15 months of the pandemic, COVID 19-related concerns stayed high. In contrast in the USA less participants reported RPAC, as concerns decreased, suggesting a shift in PA behavior as COVID-19-related concerns lessened.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".