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Record W4361190542 · doi:10.11124/jbies-22-00312

Integration of primary care education into undergraduate nursing programs: a scoping review protocol

2023· review· en· W4361190542 on OpenAlexaff
Deanne Curnew, Julia Lukewich, Maria Mathews, Marie-Ève Poitras, Kristen Romme

Bibliographic record

VenueJBI Evidence Synthesis · 2023
Typereview
Languageen
FieldNursing
TopicNursing education and management
Canadian institutionsWestern UniversityUniversité de SherbrookeSt. John’s Health Sciences CentreMemorial University of Newfoundland
Fundersnot available
KeywordsNursingNurse educationContext (archaeology)WorkforceMedicineMedical educationInclusion (mineral)LicensureCurriculumPsychologyPedagogy

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to examine and map literature related to primary care education in undergraduate nursing programs and to describe the attributes and extent of primary care education. INTRODUCTION: Primary care is a model of first-contact, continuous, comprehensive, and coordinated health care. Registered nurses are integral in successful collaborative team models of primary care. However, it is unclear how undergraduate nursing programs offer opportunities to learn about nursing practice within primary care settings. A better understanding of the attributes and extent of primary care education in undergraduate nursing programs will direct research, inform teaching-learning, and develop a stronger primary care nursing workforce. INCLUSION CRITERIA: This review will consider articles that include faculty/administrators, preceptors, or students of nursing programs that qualify graduates for entry-level registered nursing practice. Articles that report on undergraduate teaching-learning related to primary care will also be considered. Practical nursing, advanced practice, and post-licensure programs will be excluded. Teaching-learning related to settings other than primary care will also be excluded. METHODS: The Framework of Effective Teaching-Learning in Clinical Education will be the organizing framework for this scoping review. A 3-step search strategy will be followed to identify published and unpublished literature. Articles published in English or French will be included. Data extracted from eligible articles will include details on the study design/method, participants, context, type of teaching-learning activity, attributes associated with dimensions of the teaching-learning environment, and relevant outcomes. The results will be reported in tabular and/or diagrammatic format, accompanied by a narrative summary. REVIEW REGISTRATION NUMBER: Open Science Framework: https://osf.io/cw5r3.

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)0.118
metaresearch head score (Gemma)0.081
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.118
Threshold uncertainty score0.622

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1180.081
Meta-epidemiology (narrow)0.0050.006
Meta-epidemiology (broad)0.0120.011
Bibliometrics0.0270.022
Science and technology studies0.0060.005
Scholarly communication0.0100.009
Open science0.0070.009
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0500.014

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 head0.072
GPT teacher head0.452
Teacher spread0.380 · 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 designNot applicable
Domainnot available
GenreProtocol

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 routes1
Has abstractyes

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