Maternal Preoccupation and Parenting as Predictors of Emotional and Behavioral Problems in Children of Women With Breast Cancer
Bibliographic record
Abstract
PURPOSE: To test the hypothesis that differences between sicker and not-so-sick women in their preoccupation with their illness and parenting behavior can explain why some investigators find that children of breast cancer patients fare better than controls and other investigators find the reverse. PATIENTS AND METHODS: Forty-two women with metastasized breast cancer (sicker mothers) and 45 women with a first occurrence of nonmetastasized breast cancer (not-so-sick mothers) rated the degree of their preoccupation with the disease, their parenting behavior, mood, and social supports and the emotional and behavioral symptoms in one of their children. Their 12- to 18-year-old children rated their mothers' parenting behavior, their own emotional and behavioral symptoms, and their self-esteem. RESULTS: Sicker mothers reported relatively less preoccupation. They, and their children, reported less poor parenting and fewer externalizing symptoms in the children. Regression analyses revealed further differences between the groups. CONCLUSION: Less preoccupation with their illness and less poor parenting behavior by sicker mothers may explain why their children seem to fare better then those of not-so-sick mothers. Formulations concerning families of breast cancer patients should include consideration of the effect of the mothers' perception of the severity of their illness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".