Hearing from parents: The impact of receiving the diagnosis of Williams syndrome in their child
Bibliographic record
Abstract
Healthcare providers often share difficult or life-altering news with their patients yet this challenging and delicate process is frequently met with dissatisfaction by those receiving this news. Articles and guidelines exist to aid providers in sharing diagnoses such as Down syndrome, but relatively few have focused on rare genetic conditions often diagnosed years after birth. For this reason, we sought to learn about the experience of receiving a diagnosis from parents of children with Williams syndrome. We asked members of the Williams Syndrome Association to complete an anonymous online survey about recollections related to the diagnostic process. Responses, both close-ended and open-ended, were received from 600 families across the United States. Analysis revealed a high proportion of families (59.91%) with at least some negative recollections about the experience (and nearly half of those with negative recollections denied recalling anything positive). Factors influencing a more positive overall perception of the experience included receiving written information about Williams syndrome and seeing a genetic counselor. Analysis of open-ended responses identified additional positive and negative themes; for example, nearly one quarter of respondents expressed a desire to be given hope when receiving the diagnosis. Based on these analyses, we offer several specific recommendations for improving the diagnostic process in the future.
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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 | 0.032 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".