Synthesis of Research Articles to Examine Reporting of the Educational Preparation and Practice Parameters of Emergency Nurse Practitioners
Bibliographic record
Abstract
It has been reported that the outcomes of care are affected not only by the educational preparation and experience of the practitioner but also by the parameters of his or her practice. Given differences that exist internationally in the enactment of the emergency nurse practitioner (ENP) role, a synthesis of research articles was conducted to examine the educational preparation and experience of ENPs, the role(s) they assume as determined by their patient population, and the outcomes used to evaluate their practice. The synthesis was informed by Sidani and Irvine's (1999) conceptual framework for evaluating the nurse practitioner role in acute care settings. The synthesis included 43 research articles, which were retrieved following a search of the Cumulative Index to Nursing and Allied Health Literature (CINAHL) bibliographic database. Approximately 60% of the articles were descriptive or qualitative studies, whereas only 7% were randomized controlled trials. Findings suggest that although many outcomes of care have been evaluated, no outcomes have been evaluated consistently and many are not specific to the intervention or actions of nurse practitioners. In addition, few research articles provide information on the educational preparation and experience of the ENPs or the parameters of their practice. Such information is needed to explain the variability observed in the outcomes achieved and to build a body of evidence supporting the role of nurse practitioners in the emergency department.
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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 | 0.050 | 0.236 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.007 |
| Bibliometrics | 0.044 | 0.040 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".