Motivations and psychosocial impact of genetic testing for HNPCC
Bibliographic record
Abstract
A type of hereditary colorectal cancer (CRC) known as hereditary nonpolyposis colorectal cancer (HNPCC) is associated with MLHI and MSH2 gene mutations. This study consists of a pilot, cross-sectional study of 50 individuals who were engaged in the genetic testing process for HNPCC. The study investigated the motivations and attitudes around genetic testing and current psychosocial functioning through the use of standardized measures, as well as obtained information on disclosure patterns associated with test results. The mean age of the sample was 44.3 years. (SD = 15.0). Twenty-three individuals were identified as "carriers" (13 had a previous history of CRC), seven were "non-carriers" and 20 individuals were still awaiting test results. The primary motivations for participating in genetic testing were similar to previous reports and included: wanting to know if more screening tests were needed, obtaining information about the risk for offspring and increasing certainty around their own risk. The psychosocial scores demonstrated that a subgroup of individuals exhibited distress, with greater distress for those individuals awaiting results or testing positive. There was a high level of satisfaction associated with the experience of testing. Individuals in this study tended to disclose their test results to a variety of family and non-family members. Disclosure was primarily associated with positive experiences however, some individuals reported regret around disclosure of their results. These preliminary findings should be further explored in a larger prospective study design over multiple time points.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".