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Record W4400229710 · doi:10.1371/journal.pone.0305008

A global perspective of advanced practice nursing research: A review of systematic reviews

2024· review· en· W4400229710 on OpenAlexafffund
Kelley Kilpatrick, Isabelle Savard, Li‐Anne Audet, Gina Costanzo, Mariam Seedat‐Khan, Renée Atallah, Mira Jabbour, Wentao Zhou, Kathy J. Wheeler, Elissa Ladd, Deborah C. Gray, Colette Henderson, Lori A. Spies, Heather McGrath, Melanie Rogers

Bibliographic record

VenuePLoS ONE · 2024
Typereview
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsMcGill UniversityCentre intégré universitaire de santé et de services sociaux de l'Est-de-l'Île-de-MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
FundersFonds de Recherche du Québec - SantéFaculty of Medicine and Health, University of SydneyMcGill University
KeywordsCINAHLMEDLINECritical appraisalSystematic reviewMedicineNursingGrey literatureCochrane LibraryHealth careData extractionFamily medicineMeta-analysisAlternative medicinePathologyPsychological interventionPolitical science

Abstract

fetched live from OpenAlex

INTRODUCTION: The World Health Organization (WHO) called for the expansion of all nursing roles, including advanced practice nurses (APNs), nurse practitioners (NPs) and clinical nurse specialists (CNSs). A clearer understanding of the impact of these roles will inform global priorities for advanced practice nursing education, research, and policy. OBJECTIVE: To identify gaps in advanced practice nursing research globally. MATERIALS AND METHODS: A review of systematic reviews was conducted. We searched CINAHL, Embase, Global Health, Healthstar, PubMed, Medline, Cochrane Library, DARE, Joanna Briggs Institute EBP, and Web of Science from January 2011 onwards, with no restrictions on jurisdiction or language. Grey literature and hand searches of reference lists were undertaken. Review quality was assessed using the Critical Appraisal Skills Program (CASP). Study selection, data extraction and CASP assessments were done independently by two reviewers. We extracted study characteristics, country and outcome data. Data were summarized using narrative synthesis. RESULTS: We screened 5840 articles and retained 117 systematic reviews, representing 38 countries. Most CASP criteria were met. However, study selection by two reviewers was done inconsistently and language and geographical restrictions were applied. We found highly consistent evidence that APN, NP and CNS care was equal or superior to the comparator (e.g., physicians) for 29 indicator categories across a wide range of clinical settings, patient populations and acuity levels. Mixed findings were noted for quality of life, consultations, costs, emergency room visits, and health care service delivery where some studies favoured the control groups. No indicator consistently favoured the control group. There is emerging research related to Artificial Intelligence (AI). CONCLUSION: There is a large body of advanced practice nursing research globally, but several WHO regions are underrepresented. Identified research gaps include AI, interprofessional team functioning, workload, and patients and families as partners in healthcare. PROSPERO REGISTRATION NUMBER: CRD42021278532.

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)0.083
metaresearch head score (Gemma)0.250
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.083
Threshold uncertainty score0.437

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0830.250
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0120.008
Bibliometrics0.0360.036
Science and technology studies0.0010.003
Scholarly communication0.0080.012
Open science0.0030.005
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.637
GPT teacher head0.635
Teacher spread0.002 · 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 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

Citations71
Published2024
Admission routes2
Has abstractyes

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