An Integrative Review on the Oncology Nurse Navigator Role in the Canadian Context
Bibliographic record
Abstract
Several Canadian provincial cancer agencies have adopted a nurse-led model of patient navigation to decrease care fragmentation in the system. The scope of competencies of the oncology nurse navigator (ONN) in Canada has evolved over the years in response to emerging cancer care challenges. This integrative review aimed to outline the scope of competencies of the ONN role in Canada. Three databases were searched since its inception to identify Canadian studies or theoretical papers on the role of ONNs. The search yielded 62 articles of which 39 were included in the review. Three interdependent role domains were identified. The first domain of care coordinator highlighted the ONN as a coordinator of health and practical needs along the care journey. The second framed the ONN as a change agent, through increasing patients' health literacy, creating partnerships, and trusting relationships. ONNs were also described as a supporter of wellbeing, or a champion of emotional, multidimensional needs, and a transformer of the context of care. All domains were central to the navigator's success in addressing inequities in care and improving patient outcomes across care settings.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.011 | 0.019 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".