Does Simulation-Based Medical Education With Deliberate Practice Yield Better Results Than Traditional Clinical Education? A Meta-Analytic Comparative Review of the Evidence
TL;DR: Although the number of reports analyzed in this meta-analysis is small, these results show that SBME with DP is superior to traditional clinical medical education in achieving specific clinical skill acquisition goals.
Abstract: Purpose This article presents a comparison of the effectiveness of traditional clinical education toward skill acquisition goals versus simulation-based medical education (SBME) with deliberate practice (DP). Method This is a quantitative meta-analysis that spans 20 years, 1990 to 2010. A search strategy involving three literature databases, 12 search terms, and four inclusion criteria was used. Four authors independently retrieved and reviewed articles. Main outcome measures were extracted to calculate effect sizes.
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Boston Children's Hospital1, Harvard University2, King's College London3, Lund University4, Massachusetts Eye and Ear Infirmary5, University of São Paulo6, University of California, San Diego7, Imperial College London8, Partners In Health9, Brigham and Women's Hospital10, Royal North Shore Hospital11, Medical College of Wisconsin12, Monash University13, Nanyang Technological University14, University of Sierra Leone15, University of Oxford16, Mongolian National University17, University of Malawi18, Flinders University19, Beth Israel Deaconess Medical Center20, Bhabha Atomic Research Centre21, Royal Australasian College of Surgeons22, Stanford University23, University of California, San Francisco24
TL;DR: The need for surgical services in low- and middleincome countries will continue to rise substantially from now until 2030, with a large projected increase in the incidence of cancer, road traffic injuries, and cardiovascular and metabolic diseases in LMICs.
2,209 citations
TL;DR: In comparison with no intervention, technology-enhanced simulation training in health professions education is consistently associated with large effects for outcomes of knowledge, skills, and behaviors and moderate effects for patient-related outcomes.
Abstract: Context Although technology-enhanced simulation has widespread appeal, its effectiveness remains uncertain. A comprehensive synthesis of evidence may inform the use of simulation in health professions education. Objective To summarize the outcomes of technology-enhanced simulation training for health professions learners in comparison with no intervention. Data Source Systematic search of MEDLINE, EMBASE, CINAHL, ERIC, PsychINFO, Scopus, key journals, and previous review bibliographies through May 2011. Study Selection Original research in any language evaluating simulation compared with no intervention for training practicing and student physicians, nurses, dentists, and other health care professionals. Data Extraction Reviewers working in duplicate evaluated quality and abstracted information on learners, instructional design (curricular integration, distributing training over multiple days, feedback, mastery learning, and repetitive practice), and outcomes. We coded skills (performance in a test setting) separately for time, process, and product measures, and similarly classified patient care behaviors. Data Synthesis From a pool of 10 903 articles, we identified 609 eligible studies enrolling 35 226 trainees. Of these, 137 were randomized studies, 67 were nonrandomized studies with 2 or more groups, and 405 used a single-group pretest-posttest design. We pooled effect sizes using random effects. Heterogeneity was large (I2>50%) in all main analyses. In comparison with no intervention, pooled effect sizes were 1.20 (95% CI, 1.04-1.35) for knowledge outcomes (n = 118 studies), 1.14 (95% CI, 1.03-1.25) for time skills (n = 210), 1.09 (95% CI, 1.03-1.16) for process skills (n = 426), 1.18 (95% CI, 0.98-1.37) for product skills (n = 54), 0.79 (95% CI, 0.47-1.10) for time behaviors (n = 20), 0.81 (95% CI, 0.66-0.96) for other behaviors (n = 50), and 0.50 (95% CI, 0.34-0.66) for direct effects on patients (n = 32). Subgroup analyses revealed no consistent statistically significant interactions between simulation training and instructional design features or study quality. Conclusion In comparison with no intervention, technology-enhanced simulation training in health professions education is consistently associated with large effects for outcomes of knowledge, skills, and behaviors and moderate effects for patient-related outcomes.
1,420 citations
TL;DR: In this article, the authors review the scientific knowledge on expertise and expert performance and how experts may differ from non-experts in terms of their development, training, reasoning, knowledge, social support, and innate talent.
Abstract: This is the first handbook where the world’s foremost “experts on expertise” review our scientific knowledge on expertise and expert performance and how experts may differ from non-experts in terms of their development, training, reasoning, knowledge, social support, and innate talent. Methods are described for the study of experts’ knowledge and their performance of representative tasks from their domain of expertise. The development of expertise is also studied by retrospective interviews and the daily lives of experts are studied with diaries. In 15 major domains of expertise, the leading researchers summarize our knowledge of the structure and acquisition of expert skill and knowledge and discuss future prospects. General issues that cut across most domains are reviewed in chapters on various aspects of expertise, such as general and practical intelligence, differences in brain activity, self-regulated learning, deliberate practice, aging, knowledge management, and creativity.
1,268 citations
TL;DR: This Guide provides practical guidance to aid educators in effectively using simulation for training, and will focus on the educational principles that lead to effective learning, and include topics such as feedback and debriefing, deliberate practice, and curriculum integration – all central to simulation efficacy.
Abstract: Over the past two decades, there has been an exponential and enthusiastic adoption of simulation in healthcare education internationally. Medicine has learned much from professions that have established programs in simulation for training, such as aviation, the military and space exploration. Increased demands on training hours, limited patient encounters, and a focus on patient safety have led to a new paradigm of education in healthcare that increasingly involves technology and innovative ways to provide a standardized curriculum. A robust body of literature is growing, seeking to answer the question of how best to use simulation in healthcare education. Building on the groundwork of the Best Evidence in Medical Education (BEME) Guide on the features of simulators that lead to effective learning, this current Guide provides practical guidance to aid educators in effectively using simulation for training. It is a selective review to describe best practices and illustrative case studies. This Guide is the second part of a two-part AMEE Guide on simulation in healthcare education. The first Guide focuses on building a simulation program, and discusses more operational topics such as types of simulators, simulation center structure and set-up, fidelity management, and scenario engineering, as well as faculty preparation. This Guide will focus on the educational principles that lead to effective learning, and include topics such as feedback and debriefing, deliberate practice, and curriculum integration – all central to simulation efficacy. The important subjects of mastery learning, range of difficulty, capturing clinical variation, and individualized learning are also examined. Finally, we discuss approaches to team training and suggest future directions. Each section follows a framework of background and definition, its importance to effective use of simulation, practical points with examples, and challenges generally encountered. Simulation-based healthcare education has great potential for use throughout the healthcare education continuum, from undergraduate to continuing education. It can also be used to train a variety of healthcare providers in different disciplines from novices to experts. This Guide aims to equip healthcare educators with the tools to use this learning modality to its full capability.
715 citations
TL;DR: The PEARLS framework and debriefing script fill a need for many health care educators learning to facilitate debriefings in simulation-based education and offers a structured framework adaptable fordebriefing simulations with a variety in goals.
Abstract: Summary StatementWe describe an integrated conceptual framework for a blended approach to debriefing called PEARLS [Promoting Excellence And Reflective Learning in Simulation]. We provide a rationale for scripted debriefing and introduce a PEARLS debriefing tool designed to facilitate implementation
604 citations
References
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Book•
01 Dec 1969TL;DR: The concepts of power analysis are discussed in this paper, where Chi-square Tests for Goodness of Fit and Contingency Tables, t-Test for Means, and Sign Test are used.
Abstract: Contents: Prefaces. The Concepts of Power Analysis. The t-Test for Means. The Significance of a Product Moment rs (subscript s). Differences Between Correlation Coefficients. The Test That a Proportion is .50 and the Sign Test. Differences Between Proportions. Chi-Square Tests for Goodness of Fit and Contingency Tables. The Analysis of Variance and Covariance. Multiple Regression and Correlation Analysis. Set Correlation and Multivariate Methods. Some Issues in Power Analysis. Computational Procedures.
115,069 citations
TL;DR: A checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion should improve the usefulness ofMeta-an analyses for authors, reviewers, editors, readers, and decision makers.
Abstract: ObjectiveBecause of the pressure for timely, informed decisions in public health
and clinical practice and the explosion of information in the scientific literature,
research results must be synthesized. Meta-analyses are increasingly used
to address this problem, and they often evaluate observational studies. A
workshop was held in Atlanta, Ga, in April 1997, to examine the reporting
of meta-analyses of observational studies and to make recommendations to aid
authors, reviewers, editors, and readers.ParticipantsTwenty-seven participants were selected by a steering committee, based
on expertise in clinical practice, trials, statistics, epidemiology, social
sciences, and biomedical editing. Deliberations of the workshop were open
to other interested scientists. Funding for this activity was provided by
the Centers for Disease Control and Prevention.EvidenceWe conducted a systematic review of the published literature on the
conduct and reporting of meta-analyses in observational studies using MEDLINE,
Educational Research Information Center (ERIC), PsycLIT, and the Current Index
to Statistics. We also examined reference lists of the 32 studies retrieved
and contacted experts in the field. Participants were assigned to small-group
discussions on the subjects of bias, searching and abstracting, heterogeneity,
study categorization, and statistical methods.Consensus ProcessFrom the material presented at the workshop, the authors developed a
checklist summarizing recommendations for reporting meta-analyses of observational
studies. The checklist and supporting evidence were circulated to all conference
attendees and additional experts. All suggestions for revisions were addressed.ConclusionsThe proposed checklist contains specifications for reporting of meta-analyses
of observational studies in epidemiology, including background, search strategy,
methods, results, discussion, and conclusion. Use of the checklist should
improve the usefulness of meta-analyses for authors, reviewers, editors, readers,
and decision makers. An evaluation plan is suggested and research areas are
explored.
17,663 citations
Book•
27 Apr 200910,518 citations
TL;DR: While research in this field needs improvement in terms of rigor and quality, high-fidelity medical simulations are educationally effective and simulation-based education complements medical education in patient care settings.
Abstract: SUMMARY Review date: 1969 to 2003, 34 years. Background and context: Simulations are now in widespread use in medical education and medical personnel evaluation. Outcomes research on the use and effectiveness of simulation technology in medical education is scattered, inconsistent and varies widely in methodological rigor and substantive focus. Objectives: Review and synthesize existing evidence in educational science that addresses the question, ‘What are the features and uses of high-fidelity medical simulations that lead to most effective learning?’. Search strategy: The search covered five literature databases (ERIC, MEDLINE, PsycINFO, Web of Science and Timelit) and employed 91 single search terms and concepts and their Boolean combinations. Hand searching, Internet searches and attention to the ‘grey literature’ were also used. The aim was to perform the most thorough literature search possible of peer-reviewed publications and reports in the unpublished literature that have been judged for academic quality. Inclusion and exclusion criteria: Four screening criteria were used to reduce the initial pool of 670 journal articles to a focused set of 109 studies: (a) elimination of review articles in favor of empirical studies; (b) use of a simulator as an educational assessment or intervention with learner outcomes measured quantitatively; (c) comparative research, either experimental or quasi-experimental; and (d) research that involves simulation as an educational intervention. Data extraction: Data were extracted systematically from the 109 eligible journal articles by independent coders. Each coder used a standardized data extraction protocol. Data synthesis: Qualitative data synthesis and tabular presentation of research methods and outcomes were used. Heterogeneity of research designs, educational interventions, outcome measures and timeframe precluded data synthesis using meta-analysis. Headline results: Coding accuracy for features of the journal articles is high. The extant quality of the published research is generally weak. The weight of the best available evidence suggests that high-fidelity medical simulations facilitate learning under the right conditions. These include the following:
3,176 citations
TL;DR: In this article, the use of VR surgical simulation to train skills and reduce error risk in the operating room (OR) has been demonstrated in a prospective, randomized, blinded stud.
Abstract: ObjectiveTo demonstrate that virtual reality (VR) training transfers technical skills to the operating room (OR) environment.Summary Background DataThe use of VR surgical simulation to train skills and reduce error risk in the OR has never been demonstrated in a prospective, randomized, blinded stud
2,597 citations