Family nurture intervention for preterm infants facilitates positive mother–infant face-to-face engagement at 4 months.
Bibliographic record
Abstract
Although preterm infants are at risk for social deficits, interventions to improve mother-infant interaction in the neonatal intensive care unit (NICU) are not part of standard care (SC). Study participants were a subset from a randomized controlled trial of a new intervention for premature infants, the Family Nurture Intervention (FNI), designed to help mothers and infants establish an emotional connection. At infants' 4 months corrected age, mother-infant face-to-face interaction was filmed and coded on a 1-s time base for mother touch, infant vocal affect, mother gaze, and infant gaze. Time-series models assessed self- and interactive contingency. Comparing FNI to SC dyads, FNI mothers showed more touch and calmer touch patterns, and FNI infants showed more angry-protest but less cry. In maternal touch self-contingency, FNI mothers were more likely to sustain positive touch and to repair moments of negative touch by transitioning to positive touch. In maternal touch interactive contingency, when infants looked at mothers, FNI mothers were likely to respond with more positive touch. In infant vocal affect self-contingency, FNI infants were more likely to sustain positive vocal affect and to transition from negative to positive vocal affect. In maternal gaze interactive contingency, following infants' looking at mother, FNI mothers of male infants were more likely to look at their sons. In maternal gaze self-contingency, following mothers' looking away, FNI mothers of male infants were more likely to look at their sons. Documentation of positive effects of the FNI for 4-month mother-infant face-to-face communication is useful clinically and has important implications for an improved developmental trajectory of these infants. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".