Checklist inter-rater reliability and trainee discrimination were more favourable than suggested in earlier work, but each task requires a separate checklist. Compared with the checklist, the GRS has higher average inter-item and inter-station reliability, can be used across multiple tasks, and may better capture nuanced elements of expertise.
Objectives: Technology-enhanced simulation is used frequently in emergency medicine (EM) training programs. Evidence for its effectiveness, however, remains unclear. The objective of this study was to evaluate the effectiveness of technology-enhanced simulation for training in EM and identify instructional design features associated with improved outcomes by conducting a systematic review. Methods:The authors systematically searched MEDLINE, EMBASE, CINAHL, ERIC, PsychINFO, Scopus, key journals, and previous review bibliographies through May 2011. Original research articles in any language were selected if they compared simulation to no intervention or another educational activity for the purposes of training EM health professionals (including student and practicing physicians, midlevel providers, nurses, and prehospital providers). Reviewers evaluated study quality and abstracted information on learners, instructional design (curricular integration, feedback, repetitive practice, mastery learning), and outcomes.Results: From a collection of 10,903 articles, 85 eligible studies enrolling 6,099 EM learners were identified. Of these, 56 studies compared simulation to no intervention, 12 compared simulation with another form of instruction, and 19 compared two forms of simulation. Effect sizes were pooled using a random-effects model. Heterogeneity among these studies was large (I 2 ! 50%). Among studies comparing simulation to no intervention, pooled effect sizes were large (range = 1.13 to 1.48) for knowledge, time, and skills and small to moderate for behaviors with patients (0.62) and patient effects (0.43; all p < 0.02 except patient effects p = 0.12). Among comparisons between simulation and other forms of instruction, the pooled effect sizes were small ( 0.33) for knowledge, time, and process skills (all p > 0.1). Qualitative comparisons of different simulation curricula are limited, although feedback, mastery learning, and higher fidelity were associated with improved learning outcomes.Conclusions: Technology-enhanced simulation for EM learners is associated with moderate or large favorable effects in comparison with no intervention and generally small and nonsignificant benefits in comparison with other instruction. Future research should investigate the features that lead to effective simulation-based instructional design.ACADEMIC EMERGENCY MEDICINE 2013; 20:117-127 © 2013 T echnology-enhanced simulation has emerged as a cornerstone of many emergency medicine (EM) training programs. 1-3 Simulation allows complex tasks to be deconstructed into more manageable learning objectives and fosters repeated practice on specific tasks that occur infrequently or expose patients to risk when performed by novice learners. 4 Computer-based virtual reality simulators, robotic and static mannequins, artificial models, live animals, inert animal products, and human cadavers have all been employed as educational tools for these purposes.1 At the 2008 Academic Emergency Medicine (AEM) consensus conference entitled...
Contemporary theories of clinical reasoning espouse a dual processing model, which consists of a rapid, intuitive component (Type 1) and a slower, logical and analytical component (Type 2). Although the general consensus is that this dual processing model is a valid representation of clinical reasoning, the causes of diagnostic errors remain unclear. Cognitive theories about human memory propose that such errors may arise from both Type 1 and Type 2 reasoning. Errors in Type 1 reasoning may be a consequence of the associative nature of memory, which can lead to cognitive biases. However, the literature indicates that, with increasing expertise (and knowledge), the likelihood of errors decreases. Errors in Type 2 reasoning may result from the limited capacity of working memory, which constrains computational processes. In this article, the authors review the medical literature to answer two substantial questions that arise from this work: (1) To what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes? (2) To what extent are errors a consequence of cognitive biases versus a consequence of knowledge deficits?The literature suggests that both Type 1 and Type 2 processes contribute to errors. Although it is possible to experimentally induce cognitive biases, particularly availability bias, the extent to which these biases actually contribute to diagnostic errors is not well established. Educational strategies directed at the recognition of biases are ineffective in reducing errors; conversely, strategies focused on the reorganization of knowledge to reduce errors have small but consistent benefits.
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