Young and worried: Age and fear of recurrence in breast cancer survivors.
Bibliographic record
Abstract
OBJECTIVE: Fear of cancer recurrence (FCR) is a frequently cited and unmet need of cancer survivors. While the relation between age and FCR is well documented, the mechanisms that may explain this phenomenon remain to be investigated. This study examined four possible mechanisms of the relation between age and FCR: motherhood, severity of the cancer (defined as cancer stage and chemotherapy), anxiety, and illness intrusiveness. METHODS: 3,239 women with breast cancer (mean time since diagnosis: 6.6 years) completed the Concerns About Recurrence Scale (CARS), the State Trait Anxiety Inventory (STAI), and the Illness Intrusiveness Ratings Scale (IIRS) within a larger web-based study. Women were divided into four groups based on their current age: < 34, 35-49, 50-64, and >65. Multivariate analyses were performed with age category and motherhood as the independent variables and the CARS subscales as the dependent variables, controlling for age of children and relevant covariates. Severity of the cancer, anxiety, and illness intrusiveness were simultaneously tested as mediators of the relation between age and FCR. RESULTS: Results indicated that age category was related to FCR, F = 10.37, p < .001. Follow-up tests revealed that women under 34 or 35-49 expressed the highest levels of FCR. Mothers, regardless of their ages or the ages of their children, expressed greater FCR. Illness intrusiveness and to a lesser extent anxiety were mediators of the relation between age and FCR, while severity of the cancer was not. CONCLUSIONS: Younger age was associated with more FCR among breast cancer patients, regardless of motherhood status. Our findings suggest new, potentially valuable ways of managing FCR by helping affected people to reduce anxiety and illness intrusiveness.
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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) | 0.001 | 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".