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Record W4380291820 · doi:10.1002/nop2.1880

Family centered nursing practices towards women and their families in the birthing context: A qualitative systematic review

2023· review· en· W4380291820 on OpenAlexafffund
Isabelle Landry, Caroline René, Francine deMontigny

Bibliographic record

VenueNursing Open · 2023
Typereview
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsUniversité du Québec en Outaouais
FundersRéseau de recherche portant sur les interventions en sciences infirmières du Québec
KeywordsCINAHLPsycINFOCritical appraisalChecklistScopusThematic analysisQualitative researchContext (archaeology)NursingFeelingMEDLINEPsychologyQualitative propertyMedicineMedical educationSocial psychologyAlternative medicinePsychological interventionSociology

Abstract

fetched live from OpenAlex

AIM: Synthesize qualitative evidence examining how nurses' attitudes, beliefs, and sense of efficacy and the context surrounding birth facilitate or hinder family-centered nursing practice. DESIGN: Thematic synthesis of qualitative studies. METHODS: A literature search was conducted in CINAHL, MEDLINE, PsycINFO, SCOPUS, SCIENCE DIRECT, REPÈRES, CAIRN, and ÉRUDIT from October 2020 to June 2021. The PRISMA guidelines were followed, and studies were critically appraised using the Critical Appraisal Skills Programme checklist. Data were extracted by two independent reviewers, and Thomas and Harden's qualitative thematic synthesis method was performed for data analysis. RESULTS: Thirteen studies were included. Three analytical themes were generated: (1) sharing power: opposing beliefs, (2) feeling a sense of efficacy in fulfilling one's role, and (3) managing a challenging work environment. PATIENT OR PUBLIC CONTRIBUTION: Synthesizing nurses' experience is essential to promote implementation of favourable changes for care that is more focused on the needs of families.

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)0.010
metaresearch head score (Gemma)0.023
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.099
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.002
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 head0.556
GPT teacher head0.595
Teacher spread0.039 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations6
Published2023
Admission routes2
Has abstractyes

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