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Wound Care Nursing Education in the Acute Care Setting

2023· article· en· W4372238165 on OpenAlex

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

VenueAdvances in Skin & Wound Care · 2023
Typearticle
Languageen
FieldPsychology
TopicLearning Styles and Cognitive Differences
Canadian institutionsRoyal Victoria Regional Health Centre
Fundersnot available
KeywordsMedicineWound careNursingAcute careMEDLINEIntensive care medicineMedical emergencyHealth care

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the feasibility of a survey study exploring how nurses in acute care prefer to be educated, particularly regarding wound management in the acute care setting. METHODS: This pilot study utilized a cross-sectional survey design that included both open-ended and close-ended questions. Participants (N = 47) completed the Index of Learning Styles Questionnaire and provided information regarding their educational preferences related to wound management through use of an online survey. RESULTS: Participants described the importance of varying educational techniques by topic, ensuring an appropriate time of day for education, and preferring smaller educational sessions over time. Most participants preferred one-on-one bedside education, and the most commonly reported learning styles were active, sensing, visual, and a balanced approach to sequential and global learning. There were few correlations between learning styles and choice of education method, only one of which was expected. CONCLUSIONS: It would be beneficial to conduct this study on a larger scale to confirm results, improve understanding of the correlations, and determine further potential correlations between study variables.

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)0.000
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: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.376
Teacher spread0.366 · 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