A global perspective of advanced practice nursing research: A review of systematic reviews
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".