VP07.03: Preferences of women and their partners regarding access to and use of non‐invasive prenatal tests in Québec, Canada
Bibliographic record
Abstract
Cell-free DNA-based non-invasive prenatal tests (NIPT) have been available in Canada since 2012. Currently, NIPT is publicly covered for high-risk pregnancies (as a second-tier test) in the provinces of Ontario, British Columbia and the Yukon Territory; other patients who desire NIPT must pay out of pocket and/or fund through private insurance. The objective of this study was to survey pregnant and soon-to-be-pregnant women and their partners, to assess their motivations and preferences regarding NIPT use and coverage by the public health insurance system. A web-based survey was conducted between July 12-25, 2019 among Québec residents. A total of 760 subjects from four groups were surveyed: pregnant women (n = 250), their partners (n = 126), women wishing to become pregnant in the next five years (n = 258), and their partners (n = 126). Although most individuals surveyed (82%) felt their risk of giving birth to a child with Down's syndrome was low, the vast majority (93%) valued knowing their risk of fetal aneuploidy as early in pregnancy as possible. Of the 88% of respondents who intended to request NIPT during pregnancy, the most commonly cited motivations were decrease in stress and the possibility of making an informed decision on the continuation of pregnancy. Almost all of the respondents (94%) believed public funding should cover the cost of NIPT. In Québec, the vast majority of expecting parents and couples who wish to have a baby in the near future desire aneuploidy screening with NIPT even though they self-identify as low-risk. They value knowing their screening result early in pregnancy and feel NIPT will enable them to make an informed decision and reduce their anxiety. There is a notable discrepancy between the risk status of the population who feels will benefit from NIPT (low-risk) and current public funding plans in Canada, which only cover NIPT for high-risk pregnancies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".