What is in a Name? Parent, Professional and Policy-Maker Conceptions of Consent-Related Language in the Context of Newborn Screening
Bibliographic record
Abstract
Abstract Newborn bloodspot screening programs are some of the longest running population screening programs internationally. Debate continues regarding the need for parents to give consent to having their child screened. Little attention has been paid to how meanings of consent-related terminology vary among stakeholders and the implications of this for practice. We undertook semi-structured interviews with parents (n = 32), healthcare professionals (n = 19) and policy decision makers (n = 17) in two Canadian provinces. Conceptions of consent-related terms revolved around seven factors within two broad domains, decision-making and information attainment. Decision-making comprised: parent decision authority; voluntariness; parent engagement with decision-making; and the process of enacting choice. Information ascertainment comprised: professional responsibilities (including disclosure of information and time to review); parent responsibilities; and the need for discussion and understanding prior to a decision. Our findings indicate that consent-related terms are variously understood, with substantive implications for practice. We suggest that consent procedures should be explained descriptively, regardless of approach, so there are clear indications of what is expected of parents and healthcare professionals. Support systems are required both to meet the educational needs of parents and families and to support healthcare professionals in delivering information in a manner in keeping with parent needs.
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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 | 0.068 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.062 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".