Lessons Learned From an Evaluation of Serious Gaming as an Alternative to Mannequin-Based Simulation Technology: Randomized Controlled Trial

从严肃游戏作为基于模型模拟技术的替代方案的评估中汲取的经验教训:随机对照试验

阅读:1

Abstract

BACKGROUND: The use of new technology like virtual reality, e-learning, and serious gaming can offer novel, more accessible options that have been demonstrated to improve learning outcomes. OBJECTIVE: The aim of this study was to compare the educational effectiveness of serious game-based simulation training to traditional mannequin-based simulation training and to determine the perceptions of physicians and nurses. We used an obstetric use case, namely electronic fetal monitoring interpretation and decision making, for our assessment. METHODS: This study utilized a mixed methods approach to evaluate the effectiveness of the new, serious game-based training method and assess participants' perceptions of the training. Participants were randomized to traditional simulation training in a center with mannequins or serious game training. They then participated in an obstetrical in-situ simulation scenario to assess their learning. Participants also completed a posttraining perceptions questionnaire. RESULTS: The primary outcome measure for this study was the participants' performance in an in-situ mannequin-based simulation scenario, which occurred posttraining following a washout period. No significant statistical differences were detected between the mannequin-based and serious game-based groups in overall performance, although the study was not sufficiently powered to conclude noninferiority. The survey questions were tested for significant differences in participant perceptions of the educational method, but none were found. Qualitative participant feedback revealed important areas for improvement, with a focus on game realism. CONCLUSIONS: The serious game training tool developed has potential utility in providing education to those without access to large simulation centers; however, further validation is needed to demonstrate if this tool is as effective as mannequin-based simulation.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。