Psychosocial Impact of Genetic Testing for Hemochromatosis in The HEIRS Study: A Comparison of Participants Recruited in Canada And in The United States
Bibliographic record
Abstract
The Hemochromatosis and Iron Overload Screening (HEIRS) Study screened 101,168 participants recruited from primary-care clinics in Canada and the United States. The present study investigated differences in the psychological effects of genetic screening for hemochromatosis (HFE mutation analysis) in participants from each country. Study participants comprised a subset of 2,654 individuals who donated blood for HFE mutation analysis. The initial screening and 1-month post-result questionnaires included measures of General Health, Mental Health (SF-36), and a measure of the percentage of individuals who experienced at least one example of worry in response to the genetic testing. Participants reported similar changes in general health and mental health, regardless of mutation result, or country. Although a significantly lower percentage of Canadian participants than U.S. participants indicated at least one negative emotional response to the genetic testing, greater than 50% of C282Y homozygote participants (the gene mutation most strongly associated with hemochromatosis) from both countries experienced such in response to testing. Thus, although not serious enough to affect individuals' mental or physical health, there was evidence of at least one element of negative emotional response to the genetic testing. These findings suggest that population screening for common HFE mutations associated with hemochromatosis risk has similar psychological effects on Canadian and U.S. individuals, although fewer Canadians may experience a negative response to such testing.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".