Using Newborn Screening Bloodspots for Research: Public Preferences for Policy Options
Bibliographic record
Abstract
OBJECTIVES: Retaining residual newborn screening (NBS) bloodspots for medical research remains contentious. To inform this debate, we sought to understand public preferences for, and reasons for preferring, alternative policy options. METHODS: We assessed preferences among 4 policy options for research use of residual bloodspots through a bilingual national Internet survey of a representative sample of Canadians. Fifty percent of respondents were randomly assigned to select reasons supporting these preferences. Understanding of and attitudes toward screening and research concepts, and demographics were assessed. RESULTS: Of 1102 respondents (94% participation rate; 47% completion rate), the overall preference among policy options was ask permission (67%); this option was also the most acceptable choice (80%). Assume permission was acceptable to 46%, no permission required was acceptable to 29%, and no research allowed was acceptable to 26%. The acceptability of the ask permission option was reduced among participants assigned to the reasoning exercise (84% vs 76%; P = .004). Compared with assume/no permission required, ordered logistic regression showed a significant reduction in preference for the ask permission option with greater understanding of concepts (odds ratio, 0.87; P < .001), greater confidence in science (odds ratio, 0.16; P < .001), and a perceived responsibility to contribute to research (odds ratio, 0.39; P < .001). CONCLUSIONS: Surveyed Canadians prefer that explicit permission is sought for storage and research use of NBS bloodspots. This preference was diminished when reasons supporting and opposing routine storage, and other policy options, were presented. Findings warrant consideration as NBS communities strategize to respond to shifting legislative contexts.
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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 | 0.022 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".