The relationship between physical activity and stress within women treated for breast cancer
Bibliographic record
Abstract
The diagnosis and related treatments for cancer can increase breast cancer survivors' experiences of stress, which is especially detrimental given the negative physical and mental health consequences of stress. Participation in physical activity may aid in the reduction of stress, as it has been negatively associated with correlates of stress (e.g., fatigue, depression) in women treated for breast cancer. As such, in order to further explore the protective effects of physical activity after treatment for breast cancer, a better understanding of the relationship between physical activity and stress in active breast cancer survivors is valuable. Using an experience sampling method, the purpose of the present study was to examine the between- and within- associations between physical activity and stress. Women (N = 20; Mean Age = 58) provided measures of stress six times per day for seven days and wore an accelerometer for seven days to measure their time spent in moderate-to-vigorous physical activity (MVPA). Multilevel modeling was used to test for daily MVPA as a predictor of stress. Contrary to expectations, daily MVPA was not a significant predictor of stress at the same time point (p > .05). However, there was a significant time by MVPA interaction with stress (gamma = -0.38, p < .05), indicating that when women engaged in more MVPA than their average, their stress decreased over time. These results demonstrate that physical activity is an important behaviour to target in interventions used to reduce experiences of stress among breast cancer survivors.Acknowledgments: CGS-M: SSHRC
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".