Adaptation and validation of the Genetic Counseling Outcome Scale for autism spectrum disorders and related conditions
Bibliographic record
Abstract
The genetics care pathway experienced by families affected by autism spectrum disorder (ASD) around the time of diagnosis is currently uncharacterized and potentially variable across contexts. The lack of consensus on outcome measures to capture the impact of genetic services for these families shows a gap in understanding and optimizing this genetics care pathway. The Genetic Counseling Outcome Scale (GCOS-24) is a validated outcome measure of clinical genetics services. The current study aims to adapt and validate the GCOS-24 as an outcome measure in the context routine genetic testing in ASD and related conditions. Families seen for their child's developmental evaluation for ASD and related conditions were invited to participate in a genomics cohort between 2016 and 2018. Families (n = 111) completed the mGCOS-24 (modified GCOS-24), adapted from the original GCOS-24 by clinicians working in the target population's routine care pathway. The mGCOS-24 has acceptable internal consistency (Cronbach's α = 0.84) and high test-retest reliability (ICC = 0.88). It also inversely correlates with stress as measured by Perceived Stress Scale (PSS-10) and distress, as measured by the Distress Thermometer, rs ≥ 0.39, ps < 0.001. The mGCOS-24 had adequate readability, as supported by cognitive interviews completed by a sub-sample of five mothers of a child with ASD. Together, our findings show that the mGCOS-24 has good validity for the target population. Preliminary characterization of the genetics care pathway in this population revealed remarkable variability in pre-test counseling and limited post-test counseling. The use of the mGCOS-24 as an outcome measure is useful in filling some of these gaps by offering a way to assess, and in the future, optimize the genetics care pathway for families affected by autism and related neurodevelopmental conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".