Genetic Counsellors' Preferences for Preimplantation Genetic Diagnosis: A Discrete Choice Experiment
Bibliographic record
Abstract
Preimplantation genetic diagnosis (PGD) is a way of testing for a genetically affected embryo. Provincial PGD coverage differences along with ambiguity around scope of testing and patient inclusion criteria create a lack of clarity for public coverage options. A discrete choice experiment was undertaken with Canadian genetic counsellors (GC) to quantify their stated preferences for public PGD coverage, considering the following attributes: PGD indication, risk of the condition, fertility status, family history and number of cycles covered. The completed response rate was 41% with 126 GC completing the survey. Multinomial logit regression was used to estimate part-worth utilities. Key demographic and practice characteristics were considered as preference influences. Risk of the condition was the most important attribute. Overall, GC preferred scope of testing criteria over patient inclusion criteria. This is the first study to quantify GC preferences for PGD coverage and provides insight to help promote discussion about PGD policy.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".