What’s in a Name? Parents’ and Healthcare Professionals’ Preferred Terminology for Pathogenic Variants in Childhood Cancer Predisposition Genes
Bibliographic record
Abstract
Current literature/guidelines regarding the most appropriate term to communicate a cancer-related disease-causing germline variant in childhood cancer lack consensus. Guidelines also rarely address preferences of patients/families. We aimed to assess preferences of parents of children with cancer, genetics professionals, and pediatric oncologists towards terminology to describe a disease-causing germline variant in childhood cancer. Using semi-structured interviews we asked participants their most/least preferred terms from; 'faulty gene,' 'altered gene,' 'gene change,' and 'genetic variant,' analyzing responses with directed content analysis. Twenty-five parents, 6 genetics professionals, and 29 oncologists participated. An equal number of parents most preferred 'gene change,' 'altered gene,' or 'genetic variant' (n = 8/25). Parents least preferred 'faulty gene' (n = 18/25). Half the genetics professionals most preferred 'faulty gene' (n = 3/6); however this was least preferred by the remaining genetics professionals (n = 3/6). Many oncologists most preferred 'genetic variant' (n = 11/29) and least preferred 'faulty gene' (n = 19/29). Participants across all groups perceived 'faulty gene' as having negative connotations, potentially placing blame/guilt on parents/children. Health professionals described challenges selecting a term that was scientifically accurate, easily understood and not distressing to families. Lack of consensus highlights the need to be guided by families' preferred terminology, while providing accurate explanations regarding implications of genetic findings.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".