Transfer of clinical decision-making-related learning outcomes following simulation-based education in nursing and medicine : a scoping review

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Purpose : Simulation is often depicted as an effective tool for clinical decision-making education. Yet, there is a paucity of data regarding transfer of learning related to clinical decision-making following simulation-based education. The authors conducted a scoping review to map the literature regarding transfer of clinical decision-making learning outcomes following simulation-based education in nursing or medicine. Method Based on the Joanna Briggs Institute methodology, the authors searched 5 databases (CINAHL, ERIC, MEDLINE, PsycINFO, and Web of Science) in May 2020 for quantitative studies in which the clinical decision-making performance of nursing and medical students or professionals was assessed following simulation-based education. Data items were extracted and coded. Codes were organized and hierarchized into patterns to describe conceptualizations and conditions of transfer, as well as learning outcomes related to clinical decision-making and assessment methods. Results : From 5,969 unique records, 61 articles were included. Only 7 studies (11%) assessed transfer to clinical practice. In the remaining 54 studies (89%), transfer was exclusively assessed in simulations that often included one or more variations in simulation features (e.g., scenarios, modalities, duration, and learner roles; 50, 82%). Learners’ clinical decision-making, including data gathering, cue recognition, diagnoses, and/or management of clinical issues, was assessed using checklists, rubrics, and/or nontechnical skills ratings. Conclusions : Research on simulation-based education has focused disproportionately on the transfer of learning from one simulation to another, and little evidence exists regarding transfer to clinical practice. The heterogeneity in conditions of transfer observed represents a substantial challenge in evaluating the effect of simulation-based education. The findings suggest that 3 dimensions of clinical decision-making performance are amenable to assessment—execution, accuracy, and speed—and that simulation-based learning related to clinical decision-making is predominantly understood as a gain in generalizable skills that can be easily applied from one context to another.