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Record W2329956750 · doi:10.1097/njh.0000000000000160

Nurse-Perceived Communication Challenges and Roles on Interprofessional Care Teams

2015· article· en· W2329956750 on OpenAlexaff
Elaine Wittenberg, Joy Goldsmith, Tammy Neiman

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2015
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsNursingPalliative careHealth careTeamworkPsychologyNurse educationMedicine

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.125
GPT teacher head0.441
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2015
Admission routes1
Has abstractyes

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