Impact of the COVID-19 Pandemic on Physical Activity and Sedentary Behaviour: A Qualitative Study in a Canadian City
Bibliographic record
Abstract
Public health measures introduced to combat the COVID-19 pandemic have impacted the physical activity, health, and well-being of millions of people. This grounded theory study explored how the COVID-19 pandemic has affected physical activity and perceptions of health among adults in a Canadian city (Calgary). Twelve adults (50% females; 20-70 years) were interviewed between June and October (2020) via telephone or videoconferencing. Using a maximum variation strategy, participants with a range of sociodemographic characteristics, physical activity levels, and perceptions of seriousness and anxiety related to COVID-19 were selected. Semi-structured interviews captured participant perceptions of how their physical activity and perceptions of health changed during the pandemic. Using thematic analysis, four themes were identified: (1) Disruption to Daily Routines, (2) Changes in Physical Activity, (3) Balancing Health, and (4) Family Life. Participants experienced different degrees of disruption in their daily routines and physical activity based on their individual circumstances (e.g., pre-pandemic physical activity, family life, and access to resources). Although participants faced challenges in modifying their daily routines and physical activity, many adapted. Some participants reported enhanced feelings of well-being. Public health strategies that encourage physical activity and promote health should be supported as they are needed during pandemics, such as COVID-19.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".