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Record W3110113953 · doi:10.1111/apa.15705

Improving the uptake of Kangaroo Mother Care in neonatal units: A narrative review and conceptual framework

2020· review· en· W3110113953 on OpenAlexaff
Victoria R. Gill, Helen G. Liley, Carmina Erdei, Sarbattama Sen, Ruth Davidge, Amy Wright, Samudragupta Bora

Bibliographic record

VenueActa Paediatrica · 2020
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeConceptual frameworkNarrative reviewAffect (linguistics)Intervention (counseling)Health careConceptual modelKangaroo careNursingPsychologyMedicineSociologyComputer scienceIntensive care medicineCommunicationPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Kangaroo Mother Care is a beneficial intervention for high-risk infants; however, global uptake is lacking. Recent systematic reviews have collated the numerous studies that identify diverse barriers and enablers to the use of Kangaroo Mother Care. In this narrative review, we combine the findings of these systematic reviews with more recent studies to propose a conceptual framework, encompassing factors that may affect the initiation and maintenance of Kangaroo Mother Care in neonatal units. CONCLUSION: This conceptual framework includes parental, healthcare professional, and healthcare system factors, and highlights the potential interplay between them. In line with this, we suggest strategies to improve the uptake of Kangaroo Mother Care in neonatal units.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.291
Teacher spread0.269 · 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 designNot applicable
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

Citations40
Published2020
Admission routes1
Has abstractyes

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