Promoting Sensitive Mother-Infant Interactions in the Neonatal Intensive Care Unit: Development and Design of a Nursing Intervention Using a Theory and Evidence-Based Approach
Bibliographic record
Abstract
Introduction: Sensitive mother-infant interactions are important predictors of long-term mother-infant relationship, which is one factor having a positive impact on infant development. Considering preterm infants’ immaturity, mother-infant interactions and maternal sensitivity may not develop optimally. A systematic review showed that current evidence on the effectiveness of parent-infant interventions promoting parental sensitivity in the neonatal intensive care unit (NICU) is of low to very low quality. Objective: The objective of this paper is to report the development process of a novel nursing intervention, using a theory and evidence-based approach, to enhance maternal sensitivity and preterm infant neurodevelopment in the NICU. Methods: The Medical Research Council’s guidance to develop and evaluate complex health interventions, that is an evidence and theory-based approach, was used for this study. Thus, based on the MRC framework, three main steps were conducted: 1- Identifying existing empirical evidence; 2- Identifying and developing theory; 3- Modeling processes and outcomes. Results: We developed a guided participation intervention for mothers to participate in their preterm infant’s care and positioning (‘GP_Posit’). ‘GP_Posit’ is based upon the Attachment theory, the Guided Participation theory as well as the Synactive theory of development. Conclusion: This novel intervention is being tested in a pilot randomized controlled trial (NCT03677752).
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".