Nurse-Perceived Communication Challenges and Roles on Interprofessional Care Teams
Bibliographic record
Abstract
The purpose of this study was to explore nurses’ palliative care communication, leadership, and collaborative work, as defined by the Standards of Practice for Palliative Nursing, using a 1-time cross-sectional survey nurses’ perceived difficulty with communication tasks and team collaboration skills and nurse involvement in delivery of bad news and prognosis was assessed. The survey was distributed to nurses attending 1 of 5 End-of-Life Nursing Education Consortium programs. A total of 193 nurses completed the survey. Telling others about concern over errors in care was the most difficult communication task reported, whereas sharing information during interdisciplinary team meetings was the least difficult. Nursing leadership was prominent in health care team structure, yet difficulty handling conflict with team members was reported. Reminding team members about patient goals was the most common team skill practiced, and implementing team structures and team-building process was the least common. Nurses have an essential communication role in health care, commonly serving as palliative care team leaders, yet team communication and leadership are challenging communication areas in palliative nursing. Nursing education in palliative care should include team communication and ways to implement processes to support collaboration and team building.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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".