“I’m going to push this door open. You can close it”: A qualitative study of the brokering work of oncology clinic nurses in introducing early palliative care
Bibliographic record
Abstract
Background: Early palliative care improves quality of life during life-prolonging treatment for patients with cancer, but the role of nurses in facilitating the early involvement of palliative care is unclear. Aim: To conceptualize the psychosocial processes involved in the introduction and provision of palliative care by oncology nurses. Design: A constructivist qualitative grounded theory study was conducted. Setting/participants: A total of 20 nurses (6 staff nurses, 10 nurse practitioners, and 4 advanced practice nurses) completed semi-structured interviews. Participants were from multiple ambulatory care oncology clinics (i.e. breast, pancreatic, hematology) in a comprehensive cancer center. Results: The core category, brokering palliative care, represented the overarching concept of the study that linked other subcategories. The other subcategories were as follows: opening the door—creating the possibility of discussing early palliative care at a time when patients show signs of being receptive to this discussion; building trust—establishing relationships with patients as a starting point for open discussions about palliative care; tackling misconceptions—addressing patients’ assumptions about palliative care as signifying death; and advocating with oncologists—seeding the process of referral by bringing patients’ concerns forward. Conclusion: Oncology nurses play a central role in “brokering” the introduction of early palliative care; this process is supported by their relational proximity to patients and their location “in between” the patient and the oncologist. Training all nurses in palliative care and empowering them to have proactive discussions in a collaborative practice context would allow greater access to early palliative care.
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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 | 0.037 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.017 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".