The use of multiple-criteria decision-making theory to measure students' perceptions of high-fidelity simulation

Maureen Jersby, Paul van Schaik, Steve Green, Lilyana Nacheva-Skopalik

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Abstract

Background High fidelity simulation (HFS) has great potential to improve decision-making in clinical practice. Previous studies have found HFS promotes self-confidence, but its effectiveness in clinical practice has not been established. The aim of this research is to establish if HFS facilitates learning that informs decision-making skills in clinical practice using Multiple-Criteria Decision Making Theory (MCDMT). Method The sample were 2nd year undergraduate pre-registration adult nursing students. MCDMT was used to measure the students’ experience of HFS and how it developed their clinical decision-making skills. MCDMT requires characteristic measurements which for the learning experience were based on five factors that underpin successful learning and for clinical decision making an analytical framework was used. The study utilised a repeated-measures design to take two measurements: the first one after the first simulation experience and the second one after clinical placement. Baseline measurements were obtained from academics. Data were analysed utilising the MCDMT tool. Results After their initial exposure to simulation learning students reported that HFS provides a high quality learning experience (87%) and supports all aspects of clinical decision-making (85%). Following clinical practice the level of support for clinical decision-making remained at 85% suggesting that students believe HFS promotes transferability of knowledge to the practice setting. Conclusion Overall, students report a high level of support for learning and developing clinical decision-making skills from HFS. However, there are no comparative data available from classroom teaching of similar content so it cannot be established if these results are due to HFS alone.
Original languageEnglish
Pages (from-to)88-93
JournalBMJ Simulation & Technology Enhanced Learning
Volume3
Issue number3
Early online date26 Apr 2017
DOIs
Publication statusPublished - 1 Jul 2017

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