Where there is no genetic counselor: An online decision-aid supports the majority of parents’ diagnostic genomic testing choices for their children
Bibliographic record
Abstract
PURPOSE: We evaluated DECIDE, an online pretest decision-support tool for diagnostic genomic testing, in nongenetics specialty clinics where there are no genetic counselors (GCs). METHODS: Families of children offered genomic testing were eligible to participate. Fifty-six parents/guardians completed DECIDE at home, at their convenience. DECIDE includes an integrated knowledge quiz and decisional conflict screen. Six months later, parents were offered follow-up questionnaires and interviews about their experiences. RESULTS: Forty parents (71%) had sufficient knowledge and no decisional conflict surrounding their testing decision, but 6 of this group had residual questions. These 6, plus 16 with decisional conflict or insufficient knowledge, saw a GC. At follow-up, little-to-no decisional regret and few negative emotions were identified in any parents. Most chose testing and described their decision as easy, yet stressful, and described many motivations for sequencing. Parents appreciated the simple comprehensive information DECIDE provided and the ability to view it in a low-stress environment. CONCLUSION: DECIDE provides adequate decision-support to enable most parents to make value-consistent choices about genetic testing for their child. Parents reported that DECIDE helped to clarify motivations for pursuing (or declining) testing. DECIDE is a timely, well-tested, and accessible tool in clinical settings without GCs.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".