Identifying indicators sensitive to primary healthcare nurse practitioner practice: a review of systematic reviews protocol
Bibliographic record
Abstract
INTRODUCTION: Primary healthcare nurse practitioners (PHCNPs) practice in a wide range of clinical settings and with diverse patient populations. Several systematic reviews have examined outcomes of PHCNP roles. However, there is a lack of consistency in the definitions used for the PHCNP role across the reviews. The identification of indicators sensitive to PHCNP practice from the perspective of patients, providers and the healthcare system will allow researchers, clinicians and decision-makers to understand how these providers contribute to outcomes of care. METHODS AND ANALYSIS: A review of systematic reviews is proposed to describe the current state of knowledge about indicators sensitive to PHCNP practice using recognised role definitions. Outcomes of interest include any outcome indicator measuring the effectiveness of PHCNPs. We will limit our search to 2010 onwards to capture the most up-to-date trends. The following electronic databases will be searched: Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Library Database of Systematic Reviews and Controlled Trials Register, Database of Abstracts of Reviews of Effects, EMBASE, Global Health, Health Economics Evaluation Database, Health Evidence, HealthStar, Health Systems Evidence, Joanna Briggs Institute, Medline, PDQ-Evidence, PubMed and Web of Science. The search strategies will be reviewed by an academic librarian. Reference lists of all relevant publications will be reviewed. Grey literature will be searched from 2010 onwards, and will include: CADTH Information Services, CADTH's Grey Matters tool, OpenGrey, Organisation for Economic Co-operation and Development, ProQuest Dissertation and Theses and WHO. The PROSPERO International Prospective Register of Systematic Reviews will be searched to identify registered review protocols. The review protocol was developed using Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols recommendations. A narrative synthesis will be used to summarise study findings. ETHICS AND DISSEMINATION: No ethical approval is required for the study. The data used in the study will be abstracted from published systematic reviews. Dissemination strategies will include peer-reviewed publication, conference presentations and presentations to key stakeholders. PROSPERO REGISTRATION NUMBER: CRD42020198182.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.095 | 0.099 |
| Meta-epidemiology (narrow) | 0.009 | 0.009 |
| Meta-epidemiology (broad) | 0.026 | 0.020 |
| Bibliometrics | 0.024 | 0.024 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.008 | 0.008 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.087 | 0.015 |
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 source (direct Gemma or distilled Codex), 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".