Family Practice Nursing in Newfoundland and Labrador: Are Reported Roles Reflective of Professional Competencies for Registered Nurses in Primary Care?
Bibliographic record
Abstract
BACKGROUND: Family practice nurses are Registered Nurses who work collaboratively in primary care and deliver a range of services. Professional competency statements have been developed to describe the skills and knowledge of family practice nurses as a distinct field. PURPOSE: We conducted a secondary analysis of qualitative interview data to examine how family practice nurse roles/activities relate to recently developed professional competencies. METHODS: Family physicians and family practice nurses in Newfoundland and Labrador (NL) participated in semi-structured interviews, during which they discussed roles/activities and scope of practice surrounding family practice nursing. For this secondary analysis, we used competency statements to inform thematic coding of the transcribed interviews. RESULTS: For the initial study, a total of 8 participants (5 family practice nurses; 3 family physicians) were interviewed from diverse practices. All transcripts from the original study (n = 8) were included in the secondary analysis and analysed across 47 competencies encompassing 6 domains (Professionalism; Clinical Practice; Communication; Collaboration and Partnership; Quality Assurance, Evaluation and Research; Leadership). Roles/activities reported by participants were reflective of the competencies, but with substantial variation in expression. CONCLUSIONS: Family practice nursing competency statements reflect the actual activities of family practice nurses in NL. The professional competencies can serve as a framework to examine contributions of family practice nurses and identify areas warranting further training. The use of competencies to explore family practice nurses' roles and activities can assist with optimizing scope of practice.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".