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Record W4291913383 · doi:10.11124/jbies-21-00443

Capability as a concept in advanced practice nursing and education: a scoping review protocol

2022· review· en· W4291913383 on OpenAlexaff
Martha M. Whitfield, Paulina Bleah, Jovina Concepcion Bachynski, Danielle Macdonald, Tracy Klein, Amanda Ross‐White, Rosemary Wilson

Bibliographic record

VenueJBI Evidence Synthesis · 2022
Typereview
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsQueen's University
Fundersnot available
KeywordsNursing practiceNursingNurse educationHealth careScope (computer science)Clinical PracticePsychologyMedical educationMedicineComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this scoping review is to identify and map how the concept of capability in advanced practice nursing and education is described in the literature. INTRODUCTION: Advanced practice nursing and education is often described in terms of the achievement of competencies. The concept of capability has been proposed as a more accurate description of the attributes of advanced practice nursing. Definitions of capability in advanced practice nursing vary, but often focus on the integration of prior knowledge, skills, resources, judgment, and experience when solving unanticipated problems or working in new situations. INCLUSION CRITERIA: This review will consider studies addressing the concept of individual capability in any setting related to advanced practice nursing education and practice. The working definition of capability in this review is a combination of knowledge, skills, experience, and competencies that enables advanced practice nurses to provide appropriate care for patients in both familiar and unfamiliar clinical settings. Advanced practice nurses will include nurses with both graduate education and an expanded scope of practice. METHODS: Eight academic databases will be searched for qualitative, quantitative, and mixed methods study designs. The gray literature search will include policy and practice documents from nursing and health organization websites. Two reviewers will independently complete title and abstract screening prior to full-text review and data extraction. Articles published in English from 1975 to the present will be included. Other languages will be included if translations are available.

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)0.006
metaresearch head score (Gemma)0.060
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.094
GPT teacher head0.574
Teacher spread0.480 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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