Aerobic physical activity and salivary cortisol levels among women with and without a history of breast cancer
Bibliographic record
Abstract
Background: Researchers have provided evidence that physical activity (PA) improves health for women with and without a history of breast cancer (BC). More specifically, they have shown that PA helps reduce cancer-related symptoms (e.g., fatigue, depression, subjective stress, anxiety) and improves overall physical functioning in women with a history of BC. Yet, few researchers have examined the relationship between PA and physiological measures of stress. Thus, the aim of this study was to determine whether self-reported aerobic PA was associated with diurnal and reactive cortisol patterns, and whether these associations differed for women with and without a history of BC. Methods: Participants were 25 women with a history of BC (M time since diagnosis = 6.5 years) and 23 women without a history of BC who self-reported their PA level. To assess salivary diurnal cortisol patterns, participants provided five saliva samples collected on two consecutive days at the following times: upon awakening, 30 minutes after waking, 12PM, 4PM, and 9PM. To measure reactive cortisol patterns, participants provided seven saliva samples collected before, during, and after the Trier Social Stress Test. Data were analyzed using two-way analysis of variance (ANOVA) and mixed-design ANOVAs. Results: Cortisol patterns differed statistically based on women's history of cancer, whereby women without a history of BC had significantly higher overall cortisol reactivity to an acute stressor, but patterns did not differ statistically based on participants' aerobic PA level. Conclusions: Findings suggest that aerobic PA may not have the same effect on women with and without a BC experience.Acknowledgments: The authors would like to thank all participants for their generous collaboration. We also would like to acknowledge funding for this study from the Canadian Breast Cancer Research Alliance.
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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 | 0.001 |
| 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) | 0.001 | 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".