A framework for nursing practice in rural and remote Canada
Bibliographic record
Abstract
INTRODUCTION: Despite the increased understanding of Canadian rural and remote nursing practice in the past two decades, a synthesis of nursing frameworks to guide practice has been missing from the literature. In this article, the process undertaken to develop a nursing practice framework is described. The purpose of the project was to integrate existing rural and remote nursing evidence into a framework to guide rural nursing practice; inform the actions of rural communities, other health professionals, educators, policymakers and regulators; and support the health of Canadian residents who live in rural and remote areas. METHODS: Two consultants (DE, JK) worked with the Canadian Association for Rural & Remote Nursing (CARRN) Executive to plan and implement a process to develop a rural and remote nursing framework. An external advisory group, representing regulated nurses, and six expert rural nursing researchers were invited to critique project outcomes. A focused international review of the literature was conducted to determine which rural nursing frameworks existed. Electronic database platforms (ProQuest and the Cumulative Index of Allied Health Literature and Medline) were searched, with literature limited to English-only articles. Each article was analyzed to determine relevant key components and elements. RESULTS: The literature review generated 22 full-text articles that were analyzed and synthesized into five main categories: larger society/determinants of health, role of place/the rural or remote context, rural and remote peoples/communities, rural and remote nursing, and health outcomes. A draft document describing the creation of the framework and two different graphic designs of the framework were developed, then sent to the advisory group for critique. All critiques were reviewed and the document was revised as appropriate. The framework design, which used concentric circles to depict relationships between the five identified categories, was selected by a majority of the advisory group reviewers as being representative of their practice and experience. CONCLUSION: It is envisioned that, by using the framework, practicing nurses can identify the tightly woven interconnections within the rural context affecting the health of their clients. Nursing assessments and practice can then be strengthened from consideration of the framework. Nursing programs with dedicated rural nursing content potentially could incorporate the rural and remote nursing practice framework document into classroom and clinical discussions. Due to resource and time restrictions, Indigenous and Francophone nurses were not part of the framework discussions, nor were community members living in rural or remote Canada. Ongoing critique from relevant rural groups will be beneficial for future input and revisions. CARRN is developing a knowledge mobilization strategy to begin this process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.014 | 0.031 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".