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Record W2614648243 · doi:10.1177/0844562117706882

Guidelines for the Institutional Implementation of Developmental Neuroprotective Care in the Neonatal Intensive Care Unit. Part A

2017· review· en· W2614648243 on OpenAlexaffvenueabout
Isabelle Milette, Marie-Josée Martel, Margarida Ribeiro da Silva

Bibliographic record

VenueCanadian Journal of Nursing Research · 2017
Typereview
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsMcGill University Health CentreUniversité du Québec à Trois-RivièresQuebec Network for Research on AgingCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsOperationalizationAccreditationNeonatal intensive care unitMedicineHealth careNursingIntensive careMedical educationPediatricsIntensive care medicinePolitical science

Abstract

fetched live from OpenAlex

The use of age-appropriate care as an organized framework for care delivery in the neonatal intensive care unit is founded on the work of Heidelise Als, PhD, and her synactive theory of development. This theoretical construct has recently been advanced by the work of Gibbins and colleagues with the "universe of developmental care" conceptual model and developmental care core measures which were endorsed by the National Association of Neonatal Nurses in their age-appropriate care of premature infant guidelines as best-practice standards for the provision of high-quality care in the neonatal intensive care unit. These guidelines were recently revised and expanded. In alignment with the Joint Commission's requirement for health-care professionals to provide age-specific care across the lifespan, the core measures for developmental care suggest the necessary competencies for those caring for the premature and critically ill hospitalized infant. Further supported by the Primer Standards of Accreditation and Health Canada, the institutional implementation of theses core measures requires a strong framework for institutional operationalization, presented in these guidelines. Part A of this article will present the background and rationale behind the present guidelines and their condensed table of recommendations.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.955
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.507
GPT teacher head0.556
Teacher spread0.048 · 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 designOther design
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

Citations33
Published2017
Admission routes3
Has abstractyes

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