Parents' experiences of receiving their child's genetic diagnosis: A qualitative study to inform clinical genetics practice
Bibliographic record
Abstract
Little is currently known about how parents experience the medical genetics appointment at which their child receives a genetic diagnosis. We conducted semi-structured in-person interviews with 13 parents of 10 index children to explore their experience in the medical genetics appointment in which they received their child's genetic diagnosis. Guided by grounded theory, we used a constant comparative approach to data analysis. Transcribed interviews were coded and sorted, and thematic categories identified. Sixty-one and a half percent of parents experienced the diagnosis session as negative, 23% felt the experience was positive, and 15.5% were ambivalent. Receiving emotional support, an outline of the follow-up plans, and messages of hope and perspective during the session seemed to positively influence parents' experience, while feeling that their role was as a passive receiver of information and the use of difficult medical terminology negatively influenced parents' overall experience. Parental preparedness for the information, and the parents' emotional reaction to the diagnosis were also factors that influenced the parental experience. Few participants understood the role of the genetic counselor. Our results provide in-depth insight into the parental experience of the pediatric medical genetics diagnosis session. We propose a mechanism through which parental experience shapes their perception of the medical genetics session.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".