Fear of health insurance loss among individuals at risk for Huntington disease
Bibliographic record
Abstract
Genetic testing in Huntington disease, an inherited ultimately fatal neurodegenerative disorder, is infrequent despite wide availability. Factors influencing the decision to pursue testing are largely unknown. We conducted a prospective longitudinal observational study of 1,001 individuals in North America who were at risk for Huntington disease who had not pursued genetic testing prior to enrollment. We evaluated the rationale for remaining untested at baseline, determined the concerns of those who eventually pursued testing, and assessed the population's psychological attributes. We contrasted responses between those who did and did not pursue testing, and between United States and Canadian residents. The principal reasons for remaining untested were comfort with risk and uncertainty and the inability to "undo" knowledge gained. After enrollment, 83 individuals [8.3%] pursued genetic testing. Their greatest concern was losing health insurance, and 41.6% of them [vs. 6.7% of those who did not pursue testing; P < 0.001] reported paying out of pocket for testing or other medical services to conceal their genetic risk from their insurer/employer. Among individuals who were tested, more United States residents [46.1%] than Canadian residents [0.0%; P = 0.02] paid out of pocket for health services or genetic testing. Psychological attributes were similar among individuals who did and did not pursue testing. Individuals at risk for Huntington disease who pursued genetic testing feared losing medical insurance, and many paid out of pocket for medical services. Alleviating the fear of health insurance loss may help those who want to pursue genetic testing for many other conditions. [ClinicalTrials.gov number, NCT0052143].
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".