Predictors of empowerment in parents of children with autism and related neurodevelopmental disorders who are undergoing genetic testing
Bibliographic record
Abstract
BACKGROUND: There is limited empirical data quantifying the utility of genetic testing for families of children with autism spectrum disorder (ASD) or related neurodevelopmental disorders (NDD). We assessed the utility of clinical chromosomal microarray analysis (CMA), defined by diagnostic yield and parental empowerment, in population-based sample of parents of affected children; and explored child, family, and health services factors predictive of empowerment. METHODS: Participants were families of children undergoing diagnostic assessments, between 2016 and 2019. Diagnostic yield of CMA in affected children was determined. Parental empowerment was measured through adapted version of the Genetics Counseling Outcome Scale-24. Parents completed questionnaires to capture child, family, and health service factors. RESULTS: The diagnostic yield of CMA was 2.8% for pathogenic variants. Parental empowerment was significantly correlated with family functioning and aspects of perceived family-centeredness of care. The model accounted for 49.8% of the variation in parental empowerment, F (10,37) = 3.67, p = 0.002. After accounting for other predictors, parental perception of the provision of general information remained significantly associated with empowerment. CONCLUSION: The informational needs of families play an important role in their empowerment during genetic testing. Meeting these needs and monitoring empowerment can aid genomic technologies integration in personalized healthcare for ASD/NDD.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".