Family practice registered nurses: The time has come.
Bibliographic record
Abstract
OBJECTIVE: To provide a picture of the unique role and competencies of family practice registered nurses (FP-RNs). DESIGN: Case-study approach using interviews and focus groups. SETTING: Ontario. PARTICIPANTS: Seven FP-RNs identified as exemplary by family medicine and nursing peers. METHODS: An e-mail was sent to 9200 health care providers from nursing and family medicine, asking them to identify names of exemplary family practice nurses. Using a purposive sampling methodology, 7 exemplary FP-RNs were selected, taking into consideration the number of years in practice as a nurse, location of practice, length of practice as an FP-RN, and type of family practice. Individual interviews were held, and focus groups were organized with colleagues. Narratives were analyzed iteratively by the project team. MAIN FINDINGS: Four main themes emerged: The first theme relates to the relationship-centred approach to care delivered by FP-RNs, founded upon trust. The second theme highlights the FP-RN's unique skills in balancing the priorities of patients, colleagues, and the clinic as a whole. The third theme capitalizes on the nurses' commitment to advancing their learning to enhance their abilities to be FP-RNs. The fourth theme illuminates the perspectives shared by FP-RNs that family practice is uniquely different from acute care in the manner in which care is delivered. We draw attention to the approach and role of FP-RNs in Ontario. The 4 themes that emerged have striking similarities to stories shared by family physicians and to the evolutionary development of the discipline of family medicine. CONCLUSION: We believe the findings from this paper can help shape the role of the FP-RN within clinical practice and that they will propagate discussion among nursing educators to consider the necessary educational preparation required to develop the FP-RNs needed in this country.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".