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Record W4416400320 · doi:10.1016/j.jnn.2025.101757

Make room for daddy: enhancing paternal self-efficacy following preterm birth through Kangaroo Care

2025· article· en· W4416400320 on OpenAlexafffundabout
Natalia Varela, Tamarha Pierce

Bibliographic record

VenueJournal of Neonatal Nursing · 2025
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversité Laval
FundersFonds de Recherche du Québec-Société et CultureFonds de recherche du QuébecUniversité Laval
KeywordsKangaroo careCompetence (human resources)Longitudinal studyPremature birthPath analysis (statistics)Premature newborn

Abstract

fetched live from OpenAlex

Background The premature birth of a child is a stressful experience for fathers and represents a threat to their parental self-efficacy. Aim This longitudinal study aimed to examine the contribution of fathers’ participation in Kangaroo Care (KC) for their preterm infant to the increase of their self-efficacy over time. Methods 42 fathers of premature infants (up to 33 weeks) were recruited from a Quebec NICU. Paternal self-efficacy was measured using the 'Parenting Sense of Competence Scale' on three occasions: before KC, at NICU discharge, and three months post-discharge. Results Path analysis showed that the father-to-mother KC frequency ratio in the NICU predicted greater paternal self-efficacy after hospitalization (controlling for baseline), and its persistence three months post-discharge. Conclusion Results highlight the importance of fathers' involvement with their preterm infant through KC to enhance their parental self-efficacy. Mothers and medical staff can facilitate this by encouraging fathers’ active care in the NICU.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.301
Teacher spread0.290 · 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
GenreEmpirical

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

Citations2
Published2025
Admission routes3
Has abstractyes

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