Current Trends in Care for Infants Diagnosed with Neonatal Abstinence Syndrome in Canada: A Discussion Paper
Bibliographic record
Abstract
Introduction: Neonatal abstinence syndrome (NAS) is a growing epidemic across the globe. Infants diagnosed often require resource-intensive nursing care and are at risk for future complex health conditions. A shift in approaches to care for this population has been identified as a priority health care need across Canada. Objectives: This discussion paper aims to highlight the current shift in care for the NAS population, focusing on the Finnegan Neonatal Abstinence Scoring Tool (FNAST) and the Eat, Sleep, Console (ESC) model of care. Methods: A comprehensive search strategy was developed to explore the current trend in care for infants diagnosed with NAS: the transition from the FNAST to the ESC model of care. Four scholarly databases (CINAHL, PubMed, Cochrane, and Google Scholar) were searched. Relevant articles were critically analyzed for their implications on infant and family health, family experience, health system outcomes, and nursing practice. Discussion: In our review of the literature, the FNAST was the most used tool when caring for infants diagnosed with NAS. Although this tool has guided care for infants for decades, it presents some limitations, including subjectivity, invasive and lengthy assessments, and lack of collaboration. Many facilities across Canada are shifting to the ESC model of care as an alternative model. It has potential to address challenges of the care guided by the FNAST, with the ESC model emphasizing non-pharmacological care, a focus on the birth-parent–infant dyad, and dedication to a function-based assessment. Conclusion: Further efforts are needed to support the real-world implementation of evidence-based models of care for this population.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".