Coming Alongside a Patient Throughout their Cancer Journey: A Constructivist Grounded Theory of Cancer Patient Navigation from the Perspective of Registered Nurses in the Navigator Role
Bibliographic record
Abstract
Cancer patient navigation has become an important aspect of cancer care to support and guide patients through the health care system. In Canada, registered nurses commonly take on this role. The purpose of this study was to gain a better understanding of the process of cancer patient navigation from the perspective of registered nurses who work in the navigator role. Using constructivist grounded theory methodology, I interviewed nine cancer patient navigators in the province of Alberta, to examine their experiences and perspectives of their role. I analyzed the data using constant comparison and six interrelated categories emerged. This analysis led to the co-construction of the theory of Coming Alongside a Patient Throughout Their Cancer Journey. Findings from this study bring a new understanding of navigation as a process and highlight a different conceptualization of time, which sets this study apart from other 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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.041 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".