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Cited by 943

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Low‐ to high‐fidelity simulation – a continuum of medical education?

Maran, N J, Glavin, R J·2003·Medical Education

Abstract

Context Changes in medical training and culture have reduced the acceptability of the traditional apprenticeship style training in medicine and influenced the growth of clinical skills training. Simulation is an educational technique that allows interactive, and at times immersive, activity by recreating all or part of a clinical experience without exposing patients to the associated risks. The number and range of commercially available technologies used in simulation for education of health care professionals is growing exponentially. These range from simple part‐task training models to highly sophisticated computer driven models. Aim This paper will review the range of currently available simulators and the educational processes that underpin simulation training. The use of different levels of simulation in a continuum of training will be discussed. Although simulation is relatively new to medicine, simulators have been used extensively for training and assessment in many other domains, most notably the aviation industry. Some parallels and differences will be highlighted.

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Metadata

Authors
Maran, N. J., & Glavin, R. J.
Venue
Medical Education
Publisher
Wiley
Published
2003-10-27
Volume
37
Issue
s1
Pages
22-28
ISSN
  • 0308-0110 (ISSN-L)
  • 1365-2923
OpenAlex
W2020138070
Cited by
943
References
2
FWCI
4.34
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Low‐ to high‐fidelity simulation – a continuum of medical education? https://app.cochat.ai/papers/10.1046/j.1365-2923.37.s1.9.x
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Maran, N. J., & Glavin, R. J. (2003). Low‐ to high‐fidelity simulation – a continuum of medical education? Medical Education. https://doi.org/10.1046/j.1365-2923.37.s1.9.x

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.