Should Genetic Testing be Offered for Children? The Perspectives of Adolescents and Emerging Adults in Families with Li‐Fraumeni Syndrome
Bibliographic record
Abstract
Whether children should be offered genetic testing for cancer risk is much debated but young voices are rarely heard in these conversations. The current study explored perspectives of genetic testing held by adolescents and emerging adults in families with Li Fraumeni syndrome (LFS). Twelve 12- to 25-year-olds in families with LFS completed qualitative interviews for this study. All believed that testing should be offered for children but many qualified this statement saying parental approval would be needed and testing should be optional. Genetic testing was seen as way to learn of risk status, allow for disease prevention efforts, and reduce uncertainty and anxiety. Perceived disadvantages included negative emotions associated with the testing result. Participants generally felt that children should be involved in the testing decision, but that parents could unilaterally decide to have a child tested in certain circumstances (e.g., young age, high risk). All who were aware of having been tested and of their test result (n = 7; 4 positive) said testing had no negative impact on their outlook and they agreed with the decision to undergo testing. Implications of these findings for clinical practice and future research are discussed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".