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Record W2050584073 · doi:10.1097/sih.0b013e318053e066

Millennium Conference 2005 on Medical Simulation: A Summary Report

2007· article· en· W2050584073 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2007
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceMedical physicsMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Medical simulation takes advantage of contextual and experiential learning by allowing trainees to practice in realistic environments prior to actual patient care. Although proponents argue that patient simulation can fundamentally enhance both medical education and patient safety, large-scale experience with advanced simulation technologies is limited. To explore expert opinion on the topic, we convened a conference of educational leaders and simulation experts to provide recommendations for how this field should be directed on a broad scale to improve the training of future health professionals. This document summarizes the proceedings of that conference. METHODS: We issued a request for applications to all U.S. and Canadian medical schools within the Association of American Medical Colleges (AAMC), seeking a diverse group of institutional teams committed to an in-depth exploration of the topic. Of 33 applications, nine medical schools were selected to participate. Once on site, eight working groups were formed, each comprised of representatives across sites and roles, including deans, clerkship and program directors, content experts, and trainees. We addressed four key topics, which are subsequently summarized for presentation in this report: 1) education (How can medical simulation contribute to the education of trainees?), 2) assessment (What is the role of simulation in evaluating trainees in the context of general competencies?), 3) research (How should we develop a research agenda to evaluate simulation?), and 4) implementation (How should simulation technologies be developed and managed within and across institutions?). RESULTS: Participants in the conference generally agreed that simulation offers a conducive environment for focused reflection and critical thought. Although there was consensus that medical simulation can provide a robust platform for performance assessment, most participants thought that the research basis for high-stakes assessment was still too immature for widespread implementation. Participants generally agreed that sufficiently powered research will require interinstitutional collaboration on uniform curricula and meaningful outcome tools, and that both biomedical and social science research paradigms will need to be applied to the questions at hand. Common barriers to medical simulation include both real and perceived lack of resources, poor understanding among faculty regarding the nature of the tools and techniques, and the inherent complexity of multidisciplinary collaboration. CONCLUSIONS: Medical simulation can and should be used to complement current methods of medical education. Educators should make thoughtful choices among simulation modalities to help trainees most effectively achieve learning objectives. Simulation researchers should prioritize the development and validation of clinical performance tools and other defined outcome measures on which meaningful large-scale research can be anchored. Finally, national collaboration should be encouraged and fostered by institutions and funding agencies.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.072
GPT teacher head0.434
Teacher spread0.362 · 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