Dietary Change After Breast Cancer: Extent, Predictors, and Relation With Psychological Distress
Bibliographic record
Abstract
PURPOSE: Some women may try to cope with breast cancer by making lifestyle modifications, possibly in the hope of improving disease outcome. We assessed extent, predictors, and effect on psychological distress of dietary changes in the year after diagnosis among 250 women with newly diagnosed, nonmetastatic breast cancer. PATIENTS AND METHODS: Data came from medical records, and from interviews 3 days and 12 months after initial treatment. RESULTS: At 12 months, 41% (n = 103) reported dietary changes at some time since diagnosis, with decreases in meat (77%) and increases in fruit and vegetable intake (72%) being the most frequent. Women reporting changes were more likely to be younger, to have positive nodes, to be receiving adjuvant therapy, and to be more distressed initially. The mean 0 to 12 month decrease in psychological distress was greater in women who reported changes (9 points) than those who did not (4.7 points) (P = .03), although regression toward the mean cannot be excluded. CONCLUSION: A sizable proportion of women made dietary changes on their own initiative. Most changes reported were generally consistent with current scientific hypotheses about dietary changes that might favorably affect prognosis. The profile of women reporting changes suggests a group with more concerns about recurrence, who may have initiated dietary change to help cope with and gain a sense of control over the disease, and possibly to improve prognosis. Our results suggest that newly diagnosed women could be receptive to explicit attention to diet as part of psychosocial care. However, this interest in dietary change may not, as yet, have been maximally channeled into trying to improve the care and quality of life of women facing diagnosis, treatments, and fears about recurrence.
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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 | 0.001 | 0.001 |
| 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".