Everyday Experiences of Women Posttreatment After Breast Cancer: The Role of Uncertainty, Hassles, Uplifts, and Coping on Depressive Symptoms
Bibliographic record
Abstract
Considerable research has examined the experiences of women at risk, during diagnosis, and throughout treatment of breast cancer; however, less in known about these women posttreatment. Many women report dealing with extensive long-standing ailments such as lymphedema and fatigue, as well as a fear of illness recurrence. However, women posttreatment also report finding benefit and meaning from their cancer occurrence. These orthogonal outcomes may be related to the uncertainty an individual is able to tolerate. Thus, this online study examined Canadian women who completed treatment for breast cancer (n = 42), and women in a control condition (n = 42), responses to the daily experience of hassles and uplifts, intolerance of uncertainty, coping strategies, and depressive symptoms. Although depressive symptoms and daily hassles did not differ between the two groups of women, women with a previous cancer experience reported a greater amount and frequency of daily uplifts, and hassle intensity predicted fewer depressive symptoms among women posttreatment compared to healthy controls. Furthermore, hassle intensity mediated the relationship between intolerance of uncertainty and depressive symptoms, but only for women in the control condition. Last, for women posttreatment only, the use of emotion-focused coping to deal with a fear of cancer recurrence mediated the relationship between intolerance of uncertainty and depressive symptoms, whereas problem-focused, avoidant, or cognitive-restructuring coping strategies did not. These results point to the need to provide resources to women posttreatment, but also that those women who survive breast cancer can obtain benefits from the experience.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".