{"title":"从沟通到行动:运用有序网络分析来模拟临床模拟中的团队绩效。","authors":"Vitaliy Popov, Lauryn R Rochlen","doi":"10.1186/s12909-025-07062-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Effective team communication is crucial for managing medical emergencies like malignant hyperthermia (MH), but current assessment methods fail to capture the dynamic and temporal nature of teamwork processes. The lack of reliable measures to inform feedback to teams is likely limiting the overall effectiveness of simulation training. This study demonstrates the application of ordered network analysis (ONA) to model communication sequences during the simulated MH scenario.</p><p><strong>Methods: </strong>Twenty-two anesthesiologists participated in video-recorded MH simulations. Each scenario involved one participant as the primary anesthesiologist with confederates in supporting roles. Team communication was coded using the Team Reflection Behavioral Observation (TuRBO) framework, capturing behaviors related to information gathering, evaluation, planning, and implementation. ONA modeled the sequences of these coded behaviors as dynamic networks. Teams were classified as high- or low-performing based on timely dantrolene administration and appropriate MH treatment actions. Network visualizations and statistical tests compared communication patterns between groups.</p><p><strong>Results: </strong>Five of 22 teams (23%) were high-performing. ONA revealed high-performers transitioned more effectively from situation assessment (information seeking/evaluation) to planning and implementation, while low-performers cycled between assessment behaviors without progressing (p = 0.04, Cohen's d = 1.72). High-performers demonstrated stronger associations between invited input, explicitly assessing the situation, stating plans, and implementation.</p><p><strong>Conclusions: </strong>Integrating video coding with ONA provides an innovative approach for examining team behaviors. Leveraging ONA can uncover patterns in communication timing and sequences, guiding targeted interventions to improve team coordination in various real-world clinical and simulated settings (e.g., operating room, EMS, ICU).</p>","PeriodicalId":51234,"journal":{"name":"BMC Medical Education","volume":"25 1","pages":"479"},"PeriodicalIF":2.7000,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11967124/pdf/","citationCount":"0","resultStr":"{\"title\":\"From communication to action: using ordered network analysis to model team performance in clinical simulation.\",\"authors\":\"Vitaliy Popov, Lauryn R Rochlen\",\"doi\":\"10.1186/s12909-025-07062-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Effective team communication is crucial for managing medical emergencies like malignant hyperthermia (MH), but current assessment methods fail to capture the dynamic and temporal nature of teamwork processes. The lack of reliable measures to inform feedback to teams is likely limiting the overall effectiveness of simulation training. This study demonstrates the application of ordered network analysis (ONA) to model communication sequences during the simulated MH scenario.</p><p><strong>Methods: </strong>Twenty-two anesthesiologists participated in video-recorded MH simulations. Each scenario involved one participant as the primary anesthesiologist with confederates in supporting roles. Team communication was coded using the Team Reflection Behavioral Observation (TuRBO) framework, capturing behaviors related to information gathering, evaluation, planning, and implementation. ONA modeled the sequences of these coded behaviors as dynamic networks. Teams were classified as high- or low-performing based on timely dantrolene administration and appropriate MH treatment actions. Network visualizations and statistical tests compared communication patterns between groups.</p><p><strong>Results: </strong>Five of 22 teams (23%) were high-performing. ONA revealed high-performers transitioned more effectively from situation assessment (information seeking/evaluation) to planning and implementation, while low-performers cycled between assessment behaviors without progressing (p = 0.04, Cohen's d = 1.72). High-performers demonstrated stronger associations between invited input, explicitly assessing the situation, stating plans, and implementation.</p><p><strong>Conclusions: </strong>Integrating video coding with ONA provides an innovative approach for examining team behaviors. 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引用次数: 0
摘要
背景:有效的团队沟通对于管理诸如恶性热疗(MH)等医疗紧急情况至关重要,但目前的评估方法未能捕捉团队合作过程的动态性和时效性。缺乏向团队提供反馈的可靠措施可能会限制模拟训练的整体有效性。本研究演示了有序网络分析(ONA)在模拟MH场景中对通信序列建模的应用。方法:22名麻醉医师参与视频模拟MH。每个场景中都有一名参与者担任主要麻醉师,其他参与者担任辅助角色。使用团队反思行为观察(TuRBO)框架对团队沟通进行编码,捕获与信息收集、评估、计划和实施相关的行为。ONA将这些编码行为的序列建模为动态网络。根据及时给予丹曲林和适当的MH治疗行动,将小组分为高绩效或低绩效。网络可视化和统计测试比较了各组之间的通信模式。结果:22个团队中有5个(23%)表现良好。ONA显示,高绩效者更有效地从情况评估(信息寻求/评估)过渡到计划和实施,而低绩效者在评估行为之间循环而没有进展(p = 0.04, Cohen’s d = 1.72)。高绩效人员在邀请输入、明确评估情况、陈述计划和实施之间表现出更强的联系。结论:将视频编码与ONA集成为检验团队行为提供了一种创新的方法。利用ONA可以揭示沟通时间和顺序的模式,指导有针对性的干预措施,以改善各种现实世界临床和模拟环境(如手术室、EMS、ICU)中的团队协调。
From communication to action: using ordered network analysis to model team performance in clinical simulation.
Background: Effective team communication is crucial for managing medical emergencies like malignant hyperthermia (MH), but current assessment methods fail to capture the dynamic and temporal nature of teamwork processes. The lack of reliable measures to inform feedback to teams is likely limiting the overall effectiveness of simulation training. This study demonstrates the application of ordered network analysis (ONA) to model communication sequences during the simulated MH scenario.
Methods: Twenty-two anesthesiologists participated in video-recorded MH simulations. Each scenario involved one participant as the primary anesthesiologist with confederates in supporting roles. Team communication was coded using the Team Reflection Behavioral Observation (TuRBO) framework, capturing behaviors related to information gathering, evaluation, planning, and implementation. ONA modeled the sequences of these coded behaviors as dynamic networks. Teams were classified as high- or low-performing based on timely dantrolene administration and appropriate MH treatment actions. Network visualizations and statistical tests compared communication patterns between groups.
Results: Five of 22 teams (23%) were high-performing. ONA revealed high-performers transitioned more effectively from situation assessment (information seeking/evaluation) to planning and implementation, while low-performers cycled between assessment behaviors without progressing (p = 0.04, Cohen's d = 1.72). High-performers demonstrated stronger associations between invited input, explicitly assessing the situation, stating plans, and implementation.
Conclusions: Integrating video coding with ONA provides an innovative approach for examining team behaviors. Leveraging ONA can uncover patterns in communication timing and sequences, guiding targeted interventions to improve team coordination in various real-world clinical and simulated settings (e.g., operating room, EMS, ICU).
期刊介绍:
BMC Medical Education is an open access journal publishing original peer-reviewed research articles in relation to the training of healthcare professionals, including undergraduate, postgraduate, and continuing education. The journal has a special focus on curriculum development, evaluations of performance, assessment of training needs and evidence-based medicine.