Associations of changes in physical activity and well-being among cancer survivors during the COVID-19 pandemic
Bibliographic record
Abstract
Purpose: Meeting the physical activity (PA) guidelines (i.e., ≥ 150 min/week of aerobic PA and/or 2 days/week of resistance training) is beneficial for cancer survivors’ well-being. However, the impact of changes in PA participation during the COVID-19 pandemic on well-being of cancer survivors remains unknown. Accordingly, the purpose of this study was to examine the associations between changes in PA and well-being in cancer survivors during the COVID-19 pandemic. Methods: Cancer survivors participated in a cross sectional, online survey globally. The 20-Item Short Form Survey and the modified Godin Leisure Time Exercise Questionnaire assessed well-being and PA, respectively. Separate analysis of covariance examined well-being across PA change categories: abstainers, adopters, relapsers and maintainers. Results: Cancer survivors (N = 495; Mage=48.7 ± 15.5 years) were predominantly diagnosed with breast cancer (28.8 %). PA abstainers had significantly worse physical functioning (−19.3 points, p < 0.01; −14.0 points, p < 0.01), and role functioning (−16.6 points, p = 0.02; −12.9 points, p < 0.01) outcomes compared to adopters and maintainers, respectively. Whereas adopters had significantly less pain compared to abstainers (−13.4 points, p < 0.01) and relapsers (−11.1 points, p = 0.01) as well as better health perception than abstainers (14.2 points, p < 0.01) and relapsers (13.8 points, p < 0.01). Age (≥50 years), time since diagnosis (≥5 years), and time since treatment (<5 years) moderated the relationship between abstained or relapsed PA behavior and poor well-being outcomes. Conclusion: PA declines during the COVID-19 pandemic negatively impacted well-being outcomes in cancer survivors. Declines in well-being and PA were heightened in long-term cancer survivors who were older in age and within 5 years of treatment. Future research should identify the PA barriers specific to these cancer survivors.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".