Reports of information and support needs of daughters and sisters of women with breast cancer
Bibliographic record
Abstract
The aim of this study was to describe the information and support needs of women who have primary relatives with breast cancer. The Information and Support Needs Questionnaire (ISNQ) was developed and revised from previous qualitative and pilot studies. The ISNQ addressed concepts of the importance of, and the degree to which, 29 information and support needs related to breast cancer had been met. The study sample consisted of 261 community-residing women who had mothers, sisters, or a mother and sister(s) with breast cancer. Data were collected using a mailed survey. In addition to the ISNQ, additional items addressed family and health history, breast self-care practices, perception of the impact of the relative's breast cancer and other variables. Also included were established and well-validated measures of anxiety and depression. The findings document women's priority information and support needs. The information need most frequently identified as very important was information about personal risk of breast cancer. Other highly rated needs addressed risk factors for breast cancer and early detection measures. Generally, the women perceived that their information and support needs were not well met. These findings illuminate needs of women for more information and support when they have close family relatives with breast cancer and opportunities for primary care providers to assist women in addressing their needs.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".