Nurse Navigators’ Views on Patient and System Factors Associated with Navigation Needs among Women with Breast Cancer
Bibliographic record
Abstract
Coordinating breast cancer treatment is a complex task that can overwhelm patients and their support networks. Though the Cancer Patient Navigator (CPN) program in Nova Scotia (NS) provides professional assistance to patients, certain groups of patients may still face barriers to accessing its services. Employing interviews and a modified Delphi approach with CPN participants, this study sought to identify factors associated with the need for navigation to help better target CPN program referrals among breast cancer patients. Six CPNs were recruited directly through the CPN program manager for interviews and surveys. The CPNs identified 27 different factors, which were divided into 4 categories: sociodemographic, psychological, clinical and health systems. While these patient factors (particularly sociodemographic) are not directly modifiable, awareness of their association with the need for navigation could be used to better target patients with a high need for navigation for referral to CPN services.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".