Effectiveness of patient simulation in nursing education: Meta-analysis

Sujin Shin, Jin Hwa Park, Jung Hee Kim

Research output: Contribution to journalReview articlepeer-review

342 Scopus citations

Abstract

Background: The use of simulation as an educational tool is becoming increasingly prevalent in nursing education, and a variety of simulators are utilized. Based on the results of these studies, nursing facilitators must find ways to promote effective learning among students in clinical practice and classrooms. Objective: To identify the best available evidence about the effects of patient simulation in nursing education through a meta-analysis. Methods: This study explores quantitative evidence published in the electronic databases: EBSCO, Medline, ScienceDirect, and ERIC. Using a search strategy, we identified 2503 potentially relevant articles. Twenty studies were included in the final analysis. Results: We found significant post-intervention improvements in various domains for participants who received simulation education compared to the control groups, with a pooled random-effects standardized mean difference of 0.71, which is a medium-to-large effect size. In the subgroup analysis, we found that simulation education in nursing had benefits, in terms of effect sizes, when the effects were evaluated through performance, the evaluation outcome was psychomotor skills, the subject of learning was clinical, learners were clinical nurses and senior undergraduate nursing students, and simulators were high fidelity. Conclusions: These results indicate that simulation education demonstrated medium to large effect sizes and could guide nurse educators with regard to the conditions under which patient simulation is more effective than traditional learning methods.

Original languageEnglish
Pages (from-to)176-182
Number of pages7
JournalNurse Education Today
Volume35
Issue number1
DOIs
StatePublished - 1 Jan 2015

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Ltd.

Keywords

  • Education
  • Meta-analysis
  • Nursing
  • Simulation

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