Paediatricians’ expectations and perspectives regarding genetic testing for children with developmental disorders
Bibliographic record
Abstract
AIM: To investigate paediatricians' expectations and perspectives of genetic testing for children with developmental disorders. METHODS: Paediatricians working in a developmental clinic were surveyed each time they ordered a chromosomal microarray (CMA) for a child with developmental disorders. Clinical charts were reviewed. Results were analysed using mixed methodology. RESULTS: Ninety-seven % (73/76) of surveys were completed. Paediatricians reported that 36% of parents had difficulties understanding genetic testing and that 40% seemed anxious. The majority expected testing to have positive impacts on children/families. The themes raised were (i) clarifying the diagnosis (56%), (ii) understanding the aetiology of the condition (55%), (iii) enabling prenatal diagnosis/counselling (43%), (iv) improving medical care for the child (15%) and (v) decreasing parental guilt/anxiety (8%). Less than half anticipated negative impacts; 74% expected that the most helpful result for their patient would be an abnormal result explaining the disorder. Among the 73 children for whom CMA was ordered, 81% got tested: 66% of the results were normal, 19% were abnormal and contributed to explain the condition and 12% were abnormal but of unknown significance. CONCLUSION: Paediatricians generally expect many positive and less negative impacts of genetic testing for children with developmental disorders. Parental perspectives are needed.
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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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".