G003 Emotional reactions to genotype negative results for Huntington’s disease: a scoping review of qualitative findings
Bibliographic record
Abstract
Introduction While much attention has been given to understanding the emotional responses of individuals whose genetic test is positive for Huntington’s disease (HD), less is known about the experiences of those who test negative. This scoping review aims to address this gap by synthesizing qualitative findings on the emotional reactions to genetic testing for non-carriers of HD. Methods A search of CINAHL, Scopus, OVID MEDLINE and PsycInfo databases was conducted from inception to March 15th 2024, to identify qualitative findings from mixed methods research, qualitative research and narrative literature on emotional reactions to a negative genetic test for HD. Utilizing review management software Rayyan and the PRISMA-ScR scoping review guidelines, article inclusion and themes were identified by multiple authors. Results 26 articles were found that met our criteria. The articles were published during 1991-2021 with 12 from North America, 11 from Europe, and 3 from Australia. An overrepresentation of females was observed in the reported gender ratios. Four major themes emerged: direct emotional response (e.g. relief, shock, disbelief), readjustment of self (e.g. shifting identity, catalyst for change), impact on relationships with family and community, and the desire for more support. Conclusion Our scoping review highlights the complexity of emotional responses to a negative genetic test for HD. Findings from this review will inform healthcare providers, genetic counsellors, and researchers about the specific challenges and support needs of non-carriers for HD, facilitating more tailored person-centred care and support.
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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 | 0.087 | 0.193 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.017 | 0.023 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".