Colorectal cancer survivors undergoing genetic testing for hereditary non‐polyposis colorectal cancer: motivational factors and psychosocial functioning
Bibliographic record
Abstract
Hereditary non-polyposis colorectal cancer (HNPCC) represents about 1-3% of all cases of colorectal cancer (CRC). The objectives of the study were to examine motivational factors, expectations and psychosocial functioning in a sample of CRC survivors undergoing genetic testing for HNPCC. A cross-sectional survey of 314 colorectal cancer patients recruited through a population-based colon cancer family registry was conducted. Motivations for genetic testing for hereditary cancer were similar to those of clinic-based samples of CRC patients and included learning of the increased risk to offspring and finding out if additional screening was needed. While age at diagnosis and sex were associated with psychological functioning, significant predictors of post-counseling distress were perceived lower satisfaction with social support, an escape-avoidant coping style and the anticipation of becoming depressed if a mutation was present. Most cancer survivors anticipated disclosing test results to relatives and physicians. Cancer survivors reported several motivations for genetic testing for HNPCC that varied by sex. A subgroup of survivors with lower satisfaction with social support and an escape-avoidant coping style were worried about the potential impact of genetic test results and demonstrated more distress following counseling. Findings have implications for future research and potential support needs during the genetic counseling and testing process.
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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 | 0.001 |
| 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".