Core areas of practice and associated competencies for nurses working as professional cancer navigators
Bibliographic record
Abstract
UNLABELLED: Fillion et al. (2012) recently designed a conceptual framework for professional cancer navigators describing key functions of professional cancer navigation. PURPOSE: Building on this framework, this study defines the core areas of practice and associated competencies for professional cancer navigators. METHODS: The methods used in this study included: literature review, mapping of navigation functions against practice standards and competencies, and validation of this mapping process with professional navigators, their managers and nursing experts and comparison of roles in similar navigation programs. FINDINGS: Associated competencies were linked to the three identified core areas of practice, which are: 1) providing information and education, 2) providing emotional and supportive care, and 3) facilitating coordination and continuity of care. CONCLUSION: Cancer navigators are in a key position to improve patient and family empowerment and continuity of care. IMPLICATIONS: This is an important step for advancing the role of oncology nurses in navigator positions and identifying areas for further research.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".