Perceptions of genetic discrimination among people at risk for Huntington's disease: a cross sectional survey
Bibliographic record
Abstract
OBJECTIVE: To assess the nature and prevalence of genetic discrimination experienced by people at risk for Huntington's disease who had undergone genetic testing or remained untested. DESIGN: Cross sectional, self reported survey. SETTING: Seven genetics and movement disorders clinics servicing rural and urban communities in Canada. PARTICIPANTS: 233 genetically tested and untested asymptomatic people at risk for Huntington's disease (response rate 80%): 167 underwent testing (83 had the Huntington's disease mutation, 84 did not) and 66 chose not to be tested. MAIN OUTCOME MEASURES: Self reported experiences of genetic discrimination and related psychological distress based on family history or genetic test results. RESULTS: Discrimination was reported by 93 respondents (39.9%). Reported experiences occurred most often in insurance (29.2%), family (15.5%), and social (12.4%) settings. There were few reports of discrimination in employment (6.9%), health care (8.6%), or public sector settings (3.9%). Although respondents who were aware that they carried the Huntington's disease mutation reported the highest levels of discrimination, participation in genetic testing was not associated with increased levels of genetic discrimination. Family history of Huntington's disease, rather than the result of genetic testing, was the main reason given for experiences of genetic discrimination. Psychological distress was associated with genetic discrimination (P<0.001). CONCLUSIONS: Genetic discrimination was commonly reported by people at risk for Huntington's disease and was a source of psychological distress. Family history, and not genetic testing, was the major reason for genetic discrimination.
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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 | 0.002 |
| 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 | 0.001 |
| 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".