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Record W4393147359 · doi:10.5430/jnep.v14n7p18

Impact of pressure injury education on nurses’ knowledge in an acute care setting

2024· article· en· W4393147359 on OpenAlexafffundvenue
Jane Mathews

Bibliographic record

VenueJournal of Nursing Education and Practice · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsHeadwaters Health Care Centre
FundersRegistered Nurses' Association of Ontario
KeywordsAcute careNursingMedicinePressure injuryPsychologyIntensive care medicinePolitical scienceHealth care

Abstract

fetched live from OpenAlex

This research study investigated the profound physical, social, and psychological effects of pressure injuries on individuals. Despite ongoing efforts, hospital-acquired pressure injuries remain prevalent, with up to seventy percent deemed preventable. The study, which involved 40 nurses, employed the Pressure Ulcer Knowledge Assessment Tool (PUKAT) 2.0 to assess the impact of an educational workshop on nurses' knowledge. Statistical analysis revealed a statistically significant improvement in PUKAT 2.0 scores post-education (p < .001, r = .61), aligning with existing literature emphasizing the positive effect of education on nurses' knowledge of pressure injuries.

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)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.070
GPT teacher head0.585
Teacher spread0.514 · 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 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

Citations0
Published2024
Admission routes3
Has abstractyes

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