Story-Telling Attention-Refocusing (STAR) intervention to alleviate acute stress in parents of infants in the NICU
Bibliographic record
Abstract
Introduction Admission of an infant to the neonatal intensive care unit (NICU) is a stressful event for parents. The physical separation and inability to hold their child due to minimal handling protocols or infection control such as in the recent COVID-19 pandemic is a major contributor to parental stress. Knowledge on a contact-free parent administered intervention to reduce the stress of parents whose infant necessitates neonatal intensive care is lacking. Objective To assess the effect of a contact-free, Story-Telling Attention-Refocusing (STAR) intervention on the acute stress of parents whose infant is in the NICU. Methods A block-randomized controlled single-blind trial was conducted in a level II–III NICU. Parents in the experimental group provided the STAR intervention which consisted of designated prompts to share stories with their infants over a ten-minute period, three times per week, for 1 week. Parent acute stress was measured using the PSS:NICU questionnaire before and after the STAR intervention period, and differences in acute stress between mothers and fathers were assessed as well as parent satisfaction. Results Twenty-one parents completed the study. Results revealed that overall PSS:NICU stress scores lowered significantly within the intervention group ( p = 0.04), and the intervention mediated acute stress of mothers and fathers differently ( p = 0.01). Parents reported feeling overall satisfied with the STAR program and they felt less stressed in the hospital and more connected to their infants. Conclusion The STAR program provides parents a unique opportunity to interact with their infant in a positive meaningful manner and may reduce acute stress in parents during their infants NICU stay.
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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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".