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Record W4410761363 · doi:10.1097/cnq.0000000000000562

Improving the Endotracheal Tube Cuff Pressure Control Management Knowledge of Medical and Surgical Intensive Care Nurses

2025· article· en· W4410761363 on OpenAlexaff
Selda Karaveli̇ Çakır, Özlem Er, Elmas YILMAZ

Bibliographic record

VenueCritical Care Nursing Quarterly · 2025
Typearticle
Languageen
FieldMedicine
TopicAirway Management and Intubation Techniques
Canadian institutionsWeyerhauser (Canada)
Fundersnot available
KeywordsMedicineCuffPresentation (obstetrics)Intensive careEndotracheal tubeIntubationNursingIntensive care medicineAnesthesiaSurgery

Abstract

fetched live from OpenAlex

The knowledge level of nurses' endotracheal tube (ETT) cuff pressure control management is important for patient safety. The aim of this study is to assess how the knowledge level of intensive care (ICU) nurses is affected by ETT cuff pressure control training delivered using 2 alternative teaching techniques. The research was conducted with 88 medical and surgical nurses working in ICUs. The nurses in the groups were given education with presentation techniques in line with evidence-based guidelines on ETT cuff pressure control management. In addition to the nurses in the experimental group, 4 one-on-one follow-up visits were made using the demonstration technique. A statistically significant difference was found between the total scores of the knowledge level of ETT cuff pressure control after training in the experimental group and control group (P < .001). It was determined that presentation and demonstration teaching techniques increased the knowledge level of nurses on ETT cuff pressure control management, and the use of demonstration and one-to-one follow-up strategies were most effective.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.564

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 studies0.0000.001
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 head0.011
GPT teacher head0.343
Teacher spread0.333 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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