An Exploration of the Patient Navigator Role: Perspectives of Younger Women With Breast Cancer
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To delineate the role of the oncology patient navigator, drawing from the experiences and descriptions of younger women with breast cancer. RESEARCH APPROACH: Interpretive, descriptive, qualitative research design. SETTING: Participants' homes, researcher's home, and via telephone, all in Winnipeg, Manitoba, Canada. PARTICIPANTS: 12 women aged 50 years or younger who were diagnosed with breast cancer within the last three years. METHODOLOGIC APPROACH: Face-to-face semistructured interviews explored patient experiences with the cancer care system, including problems encountered, unmet needs, and opinions about the functions of the patient navigator role. The audio-recorded interviews were transcribed and data were broken down and inductively coded into four categories. Constant comparative techniques also were used during analysis. FINDINGS: The role of the oncology patient navigator included two facets: "Processual facets," with the subthemes assigned to me at diagnosis, managing the connection, mapping the process, practical support, and quarterbacking my entire journey; and "Personal qualities: The essentials," with the subthemes empathetic care tenor, knowing the cancer system, and understanding the medical side of breast cancer. CONCLUSIONS: Despite the tremendous effort directed toward enhancing care for younger women undergoing treatment for breast cancer, gaps continue to exist. Younger women with breast cancer require a care approach providing ongoing dialogue, teaching, and emotional support from the point of diagnosis through treatment, including transitions of care within the oncology setting and back to their primary care practitioner. INTERPRETATION: Oncology nurse navigators are well positioned to provide patients with anticipatory guidance from diagnosis to the end of treatment.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".