An Exploratory Study on Exemplary Practice of Nurse Consultants
Bibliographic record
Abstract
PURPOSE: To examine the exemplary practice of nurse consultants (NCs) and derive a model to illustrate the highest level of advanced nursing practice. DESIGN: A descriptive study was conducted to examine the practice and outcomes of seven NC roles in varied clinical specialties in Hong Kong. Exemplary practice was examined in relation to competencies for advanced practice nursing in Hong Kong and the United Kingdom. METHODS: Data about NC characteristics and their practices were collected using a structured questionnaire and analyzed using descriptive statistics. Health service documents and clinical notes were analyzed using the framework approach. FINDINGS: All NCs demonstrated the competence expected of an advanced practice nurse with impacts on patients, nursing profession, and the organization as identified in the advanced nursing practice framework in Hong Kong. NCs also performed at the highest level of practice delineated by Skills for Health in the United Kingdom. They were involved in diagnostic and therapeutic practice, and identified patient satisfaction and symptom management as key outcomes. CONCLUSIONS: This study provides new insight into levels of advanced practice and illustrates the exemplary work of NCs to demonstrate how they have developed and shaped services to bring about positive patient and organizational outcomes. Career laddering that places NCs at the highest level of advanced practice is important for making the best use of nursing expertise to achieve optimal patient and organizational outcomes. CLINICAL RELEVANCE: This study addresses a knowledge gap to enrich our current understanding of the impact of advanced practice nursing roles by linking NC role practices and competencies to key outcomes.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".