Returning incidental findings from genetic research to children: views of parents of children affected by rare diseases
Bibliographic record
Abstract
PURPOSE: To explore parental perceptions and experiences regarding the return of genomic incidental research findings in children with rare diseases. METHODS: Parents of children affected by various rare diseases were invited to participate in focus groups or individual telephone interviews in Montreal and Ottawa. Fifteen participants were interviewed and transcriptions were analysed using thematic analysis. RESULTS: Four emergent themes underscored parental enthusiasm for receiving incidental findings concerning their child's health: (1) right to information; (2) perceived benefits and risks; (3) communication practicalities: who, when, and how; and (4) service needs to promote the communication of incidental findings. Parents believed they should be made aware of all results pertaining to their child's health status, and that they are responsible for transmitting this information to their child, irrespective of disease severity. Despite potential negative consequences, respondents generally perceived a favourable risk-benefit ratio in receiving all incidental findings. CONCLUSIONS: Understanding how parents assess the risks and benefits of returning incidental findings is essential to genomic research applications in paediatric medicine. The authors believe the study findings will contribute to establishing future best practices, although further research is needed to evaluate the impact of parental decisions on themselves and their child.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".