Reducing the psychosocial impact of a false positive newborn screen for inborn errors of metabolism
Bibliographic record
Abstract
Newborn screening (NBS) is standard practice for neonatal care in Canada and screens for over 20 inborn errors of metabolism (IEM). Education about NBS is meant to mitigate parental anxiety following an initial positive screen and reduce the inappropriate medicalization of children after a false positive result. Parents of 482 children who had NBS done by Cadham Provincial Laboratory in Winnipeg, MB between 2011-2017 and who screened positive for an IEM were invited to participate in an online survey and follow-up interview. Although only 21 online survey responses were completed (5.06% response rate), these data allowed for a more detailed understanding of the demographic characteristics of the interviewed sample. Eleven respondents completed semi-structured telephone interviews designed to identify how communication of a positive result and educational resources can be improved; explore how parents are accessing educational information about IEMs after being notified of their result; and determine when in the NBS process parents feel that they will benefit most from these educational messages. Overall, participants felt that clinicians downplayed the significance of their result and provided them with limited information about the IEM. Immediately after being notified, parents sought information online as a source of comfort and wanted to learn more about the likelihood of a false positive result, follow-up process, prognosis of the IEM, and management guidelines. In hindsight, parents felt unaware of the potential outcomes of NBS because of a lack of education about the program prior to being notified of their result. Additionally, parents indicated that their local healthcare providers, emergency departments, and medical laboratories had inadequate knowledge about NBS that led to multiple redraws and unnecessary challenges in follow-up. Based on interpretive description, evidence-based strategies for improving the experience of a positive NBS result for IEMs are described.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".