Illuminating the Clinical Nurse Specialist Role of Advanced Practice Nursing: A Qualitative Study
Bibliographic record
Abstract
As the advanced practice nursing initiative in Canada gains momentum, effort is being directed towards clarifying and defining advanced practice roles. A qualitative study was undertaken to increase understanding of the clinical nurse specialist role of advanced practice. Sixteen nurses who worked in advanced practice roles, organizing and providing healthcare for children with complex health needs and their families across the continuum of care, participated in in-depth conversations about the nature of their practice, the knowledge that informs it and the factors that influence it. Findings suggest that clinical nurse specialists have a unique role in the organization and delivery of healthcare for specialized populations with complex health needs in their dual focus on the system level of healthcare and on population health needs. Initiatives directed to children and families within the study participants' specialties included program development, consultation and educational outreach and the development of clinical guidelines and policies. Although the nurses described their practice as focusing both on individual children and families and on the population of children and families within their specialty, it is at the population level that they see their greatest potential for contributing to the delivery of high-quality, cost-effective healthcare.
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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 | 0.023 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".