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Record W4387167691 · doi:10.1097/jpn.0000000000000724

Parent Perceptions of Transitioning From a 6-Bed Pod to a Single Family Room in a Mixed-Room Design NICU

2023· article· en· W4387167691 on OpenAlexaff
Laura Crump, Émilie Gosselin, Melissa D'addona, Nancy Feeley

Bibliographic record

VenueThe Journal of Perinatal & Neonatal Nursing · 2023
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcGill UniversityJewish General HospitalJewish Rehabilitation Hospital
Fundersnot available
KeywordsThematic analysisNonprobability samplingNeonatal intensive care unitPerceptionQualitative researchAutonomyTransition (genetics)NursingPsychologyMedicineDevelopmental psychologyPediatricsSociologyEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: As some neonatal intensive care units (NICUs) shift toward mixed-room designs, with different room types available throughout family's stays, there is a need to better understand parent perceptions of this transition. METHODS: This study used a qualitative descriptive design to describe parent perceptions of transitioning from a 6-bed pod to a single family room in a mixed-room design NICU. Purposive sampling was used to recruit 10 mothers and 7 fathers who were regularly present on the unit before and after the transition. Semistructured telephone interviews were conducted a minimum of 2 days after the transition occurred. Interviews were transcribed and then analyzed using reflexive thematic analysis. FINDINGS: Four themes were identified: going into the unknown; approaching the finish line; becoming comfortable in the new reality and seeing the benefits; and gaining autonomy and confidence in parenting. CONCLUSION: These results further our understanding of the transition process from a 6-bed pod to a single-family room for parents in the NICU. Staff should be sensitized to this experience to provide tailored information and support for parents throughout the transition.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.783
Threshold uncertainty score0.538

Codex and Gemma teacher scores by category

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

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 head0.032
GPT teacher head0.292
Teacher spread0.260 · 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 teacher head, 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
Published2023
Admission routes1
Has abstractyes

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