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Record W4308371390 · doi:10.1002/nop2.1466

The simulation design in health and nursing: A scoping review

2022· review· en· W4308371390 on OpenAlex
George Oliveira Silva, Luciana Mara Monti Fonseca, Karina Machado Siqueira, Fernanda dos Santos Nogueira de Góes, Laiane Medeiros Ribeiro, Natália D. Aredes

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

VenueNursing Open · 2022
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsAlberta Medical Association
Fundersnot available
KeywordsScopusComputer scienceMEDLINEManagement scienceEngineering

Abstract

fetched live from OpenAlex

AIMS: The aims of this study were to map the components of the simulation design in health and nursing and to propose a classification based on their definitions to support the planning of simulation-based experiences. DESIGN: Scoping review. METHOD: Searches were performed in the databases LILACS, Embase, MEDLINE/PubMed, SCOPUS, Web of Science, Google Scholar and ProQuest Thesis and Dissertation were performed, without time limitation, to identify studies about simulation design. RESULTS: This study mapped 19 components of the simulation design found in 26 studies included, which can contribute to the development of simulation-based experiences, classified into structural, methodological and theoretical-pedagogical components. The simulation design can be described according to its fundamental components: structural-define the basic formulation of a simulation in terms of infrastructure and conceptual framework; methodological-define the participants, roles and the instruction format; and theoretical-pedagogical-define the educational references used to support the simulation strategy.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.916
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.437
GPT teacher head0.594
Teacher spread0.157 · 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