Expanding the Australian Newborn Blood Spot Screening Program using genomic sequencing: do we want it and are we ready?
Bibliographic record
Abstract
Since the introduction of genome sequencing in medicine, the factors involved in deciding how to integrate this technology into population screening programs such as Newborn Screening (NBS) have been widely debated. In Australia, participation in NBS is not mandatory, but over 99.9% of parents elect to uptake this screening. Gauging stakeholder attitudes towards potential changes to NBS is vital in maintaining this high participation rate. The current study aimed to determine the knowledge and attitudes of Australian parents and health professionals to the incorporation of genomic sequencing into NBS programs. Participants were surveyed online in 2016 using surveys adapted from previous studies. The majority of parents (90%) self-reported some knowledge of NBS, with 77% expressing an interest in NBS using the new technology. This was significantly lower than those who would utilise NBS using current technologies (99%). Although, many health professionals (62%) felt that new technologies should currently not be used as an adjunct to NBS, 79% foresaw the use of genomic sequencing in NBS by 2026. However, for genomic sequencing to be considered, practical and technical challenges as well as parent information needs were identified including the need for accurate interpretation of data; pre-and post-test counselling; and appropriate parental consent and opt-out process. Therefore, although some support for implementing genomic sequencing into Australian NBS does exist, there is a need for further investigation into the ethical, social, legal and practical implications of introducing this new technology as a replacement to current NBS methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".