Women's thoughts on receiving and sharing genetic information: Considerations for genetic counseling
Bibliographic record
Abstract
Indications for genetic testing for inherited cancer syndromes are expanding both in the academic and the community setting. However, only a fraction of individuals who are candidates for testing pursue this option. Therefore, it is important to understand those factors that impact the uptake of genetic testing in individuals affected and unaffected with cancer. A successful translation of genomic risk stratification into clinical care will require that providers of this information are aware of the attitudes, perceived risks and benefits, and concerns of individuals who will be considering testing. The purpose of this study was to assess beliefs, attitudes and preferences for genetic risk information, by personal characteristics of women affected and unaffected by breast cancer enrolled in the Breast Cancer Family Registry Cohort. Data for this analysis came from eight survey questions, which asked participants (N = 9,048, 100% female) about their opinions regarding genetic information. Women reported that conveying the accuracy of the test was important and were interested in information related to personal level of risk, finding out about diseases that could be treated, and information that could be helpful to their families. Young women were most interested in how their own health needs might be impacted by genetic test results, while older women were more interested in how genetic information would benefit other members of the family. Interest in how the genetic test was performed was highest among Asian and Hispanic women. Women affected with breast cancer were more likely to report feeling sad about possibly passing down a breast cancer gene, while unaffected women were more uncertain about their future risk of cancer. The variety of informational needs identified has implications for how genetic counselors can tailor communication to individuals considering genetic testing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".