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Record W4413745622 · doi:10.2196/71930

Promoting Equity in Parent Presence and Participation in Neonatal Intensive Care: Protocol for a Prospective Cohort Study

2025· article· en· W4413745622 on OpenAlexvenueno aff
Marliese Dion Nist, Abigail B. Shoben, Leif D. Nelin, Lisa S. Segre, Rita H. Pickler

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Child Health and Human DevelopmentNational Institutes of HealthOhio State University
KeywordsEquity (law)Protocol (science)MedicineCohortCohort studyFamily medicinePsychologyPolitical scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Parents of infants born preterm experience many barriers to their presence in the neonatal intensive care unit (NICU) and participation in infant caregiving. Parents from historically marginalized backgrounds or with limited social or economic resources may experience even more profound barriers, creating a significant source of health inequity for these parents and their infants. While the specific barriers and facilitators of parent presence and participation (PPP) in caregiving are unknown, PPP may be critical for improving clinical outcomes and neurodevelopment for infants born preterm. OBJECTIVE: This study aims to (1) longitudinally determine the barriers and facilitators affecting PPP specific to parents with diverse sociodemographic characteristics, (2) determine the effect of PPP on infant clinical outcomes and neurodevelopment and the potential mediating effect of parent-infant responsiveness, and (3) determine the moderation effect of PPP on the relationship between infant stress exposure and infant clinical outcomes and neurodevelopment. We hypothesize that barriers and facilitators of PPP will vary based on sociodemographic characteristics and will change over the duration of a NICU hospitalization. We expect that higher levels of PPP will be associated with better infant outcomes. METHODS: Parents (N=375) of infants born preterm, at <32 weeks' gestational age, will be enrolled in a prospective cohort study. The parents will complete a daily survey documenting the amount of time spent in the NICU and the caregiving activities performed. The parents will also complete surveys at regular intervals during their infant's admission to report barriers and facilitators of PPP, NICU-related stress, depressive symptoms, experiences of discrimination, and engagement with NICU staff. Additional data will be collected throughout each infant's hospitalization, including invasive procedures, infant clinical data, and nursing documentation of PPP. The parents will complete the maternal-infant responsiveness instrument at the time of NICU discharge and at 3 months' corrected age (CA). Infant clinical outcomes include the achievement of feeding milestones and the length of NICU stay. The infants will be assessed at 3 months' CA using the test of infant motor performance and at 12 months' CA using the Bayley scales of infant and toddler development, fourth edition. RESULTS: Funding was awarded in August 2024. Data collection and analysis are expected to be completed by July 2029. CONCLUSIONS: By identifying the important barriers and facilitators of PPP over the duration of hospitalizations of infants born preterm and differences in these factors based on sociodemographic characteristics, time- and population-targeted interventions can be developed to remove system-level barriers and enhance facilitators. These efforts may increase PPP and promote health equity for diverse families. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/71930.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.036
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.036
Threshold uncertainty score0.190

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.022
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0030.004
Science and technology studies0.0050.002
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0300.006

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.

Opus teacher head0.215
GPT teacher head0.597
Teacher spread0.382 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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