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Record W2079049099 · doi:10.1097/ncq.0000000000000035

Patients' Views on Bedside Nursing Handover

2013· article· en· W2079049099 on OpenAlexaff
Lianne Jeffs, Susan Beswick, Ashley Acott, Elisa Simpson, Roberta Cardoso, Heather Campbell, Terri Irwin

Bibliographic record

VenueJournal of Nursing Care Quality · 2013
Typearticle
Languageen
FieldMedicine
TopicHospital Admissions and Outcomes
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsHandoverNursingPerceptionPatient safetyMedicineQualitative researchMEDLINEPsychologyHealth careComputer scienceSociology

Abstract

fetched live from OpenAlex

A study was undertaken to explore patients' experiences and perceptions associated with implementation of bedside nursing handover. Interviews were conducted with patients and analyzed using a directed content analysis. Three themes emerged through which patients described their experience with bedside nursing handover as follows: (1) creating a space for personal connection; (2) "bumping up to speed"; and (3) varying preferences. Health care leaders and nurses can use study findings to tailor strategies to engage patients, taking into account their preferences, in bedside nursing handover.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.059
GPT teacher head0.412
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), 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

Citations56
Published2013
Admission routes1
Has abstractyes

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