An overview of realist evaluation for simulation-based education.

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ID: 34709
2018
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Abstract
This article describes the key features of realist (realistic) evaluation and illustrates their application using, as an example, a simulation-based course for final year medical students. The use of simulation-based education (SBE) is increasing and so too is the evidence supporting its value as a powerful technique which can lead to substantial educational benefits. Accompanying these changes is a call for research into its use to be more theory-driven and to investigate both 'Did it work?' and as importantly 'Why did it work (or not)?' An evaluation methodology that is capable of answering both questions is realist evaluation. Realist evaluation is an emerging methodology that is suited to evaluating complex interventions such as SBE. The realist philosophy positions itself between positivist and constructivist paradigms and seeks to answer the question 'What works for whom, in what circumstances and why?' In seeking to answer this question, realist evaluation sets out to identify three fundamental components of an intervention, namely context, mechanism and outcome. Educational programmes work (successful outcomes) when theory-driven interventions (mechanisms) are applied to groups under appropriate conditions (context). Realist research uses a mixed methods (qualitative and quantitative) approach to gathering data in order to test the proposed context-mechanism-outcome (CMO) configurations of the intervention under investigation. Realist evaluation offers a valuable methodology for researchers investigating interventions utilising simulation-based education. By investigating and understanding the context, mechanisms and outcomes of SBE interventions, realist evaluation can provide the deeper level of understanding being called for.
Reference Key
graham2018anadvances Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Graham, Alastair C;McAleer, Sean;
Journal advances in simulation (london, england)
Year 2018
DOI
10.1186/s41077-018-0073-6
URL
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