Effect of Model of Neonatal Care on Neurodevelopment at the 18 Month Follow-Up in Moderate and Late Preterm Infants
Bibliographic record
Abstract
Background: Preterm birth, even for moderate or late preterm infants (MLPIs), is associated with longer-term developmental challenges. Family Integrated Care (FICare) models of care, like Alberta FICare, aim to improve outcomes by integrating parents into neonatal care during hospitalization. This follow-up study examined the association between models of care (Alberta FICare versus standard care) and risk of child developmental delay at 18 months corrected age (CA) and explored the influences of maternal psychosocial distress. Methods: We assessed 257 mothers and 298 infants from a cluster randomized controlled trial (ID: NCT0279799) conducted in ten Level II NICUs in Alberta, Canada. Risk of delay was assessed using developmental screening tests. Maternal psychosocial distress was assessed using self-reported measures of depressive symptoms, anxiety, parenting stress, and self-efficacy. Results: There was no association between model of care and risk of developmental delay. Higher maternal parenting stress was associated with increased risk of developmental delay. Conclusions: Alberta FICare was not associated with decreased risk of developmental delay at 18 months CA. Maternal parenting stress may play an important role in the development of MLPIs and should be addressed post-discharge.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".