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Record W1978551686 · doi:10.1016/j.aorn.2009.11.068

Redefining the Future of Perioperative Nursing Education: A Conceptual Framework

2010· article· en· W1978551686 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

VenueAORN Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsPerioperativePerioperative nursingEconomic shortageSAFERNursing shortageConceptual frameworkCurriculumConstructivism (international relations)Quality (philosophy)Medical educationNursingMedicineNurse educationPsychologyComputer scienceSociologyPedagogyPolitical scienceAnesthesia

Abstract

fetched live from OpenAlex

Perioperative nursing is practiced in a technologically advanced, fast-paced environment, and there is a continuing shortage of qualified and competent perioperative nurses. The expansion of nursing education programs into web-based environments has the potential to address this shortage. Online learning is both effective and efficient and particularly appropriate for adult learners compared with traditional, lecture-style programs. This article proposes a conceptual framework that combines social constructivism, Benner's Novice to Expert theory, and the principles of adult learning to provide a basis for the design and implementation of future perioperative curricula. Although the proposed framework needs to be questioned and empirically tested through research, the application of this framework could potentially shift the quality of perioperative education to a higher level and result in safer, more highly reliable patient care.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score0.999

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.386
Teacher spread0.361 · 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