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Record W2242649913 · doi:10.1177/1054773815584138

Registered Nurses and Discharge Planning in a Taiwanese ED

2015· article· en· W2242649913 on OpenAlex
Wen Chang, Suzanne Goopy, Chun‐Chih Lin, Alan Barnard, Hsueh‐Erh Liu, Chin‐Yen Han

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Nursing Research · 2015
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsUniversity of Calgary
FundersChang Gung Medical Foundation
KeywordsDischarge planningWorkloadEmergency departmentNursingPerspective (graphical)PerceptionMedicineQualitative researchPsychologyMedical educationSociologyManagementComputer science

Abstract

fetched live from OpenAlex

Published research on discharge planning is written from the perspective of hospital wards and community services. Limited research focuses on discharge planning in the emergency department (ED). The objective of this study was to identify ED nurses' perceptions of factors influencing the implementation of discharge planning. This qualitative study collected data from 25 ED nurses through in-depth interviews and a drawing task in which participants were asked to depict on paper the implementation of discharge planning in their practice. Factors influencing discharge planning were grouped into three categories: discharge planning as a neglected issue in the ED, heavy workload, and the negative attitudes of ED patients and their families. The study highlighted a need for effective discharge planning to be counted as an essential clinical competency for ED nurses and factored into their everyday workload. Nurses perceived that organizational culture, and parents' and relatives' attitudes were barriers to implementing discharge teaching in the ED.

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.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.383
GPT teacher head0.586
Teacher spread0.202 · 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