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Record W101479941

A survey of nurses' perceptions of the intensive care delirium screening checklist.

2012· article· en· W101479941 on OpenAlexaff
Tyler J. Law, Nicole Leistikow, Laura Hoofring, Sharon Krumm, Karin J. Neufeld, Dale M. Needham

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDeliriumChecklistMedicineIntensive careNursingEmergency medicineIntensive care medicinePsychology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: Delirium in critically ill patients is common and is associated with increased morbidity and mortality. Routine delirium screening is recommended by the Society of Critical Care Medicine. The Intensive Care Delirium Screening Checklist (ICDSC) is one validated and commonly-used tool, but little is known about nurses'perceptions of using the ICDSC, and of barriers to delirium assessment and treatment. DESIGN: A survey was administered to 189 critical care-trained nurses working on four oncology inpatient units, where the ICDSC has been used for greater than five years. RESULTS: Eighty-four nurses (44%) responded to the survey. Respondents indicated that they had knowledge of delirium, confidence in the ICDSC, and that the ICDSC was useful. Respondents perceived that physicians did not value the ICDSC results. Similar to prior nurse surveys for other delirium screening tools, physicians were the most frequently identified barrier to both delirium assessment and treatment, with other frequent barriers being lack of time, feedback on performance, and knowledge of delirium. CONCLUSIONS: The ICDSC is viewed favourably by nurses with experience using the tool. Future delirium screening programs should encourage physician engagement early in the planning process to help address perceived barriers to delirium assessment and treatment.

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)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.026
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 head0.035
GPT teacher head0.285
Teacher spread0.250 · 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.

Study designObservational
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

Citations19
Published2012
Admission routes1
Has abstractyes

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