von Dincklage Falk, Helfrich Janna, Koch Susanne, Soehle Martin, Berger-Estilita Joana, Bublitz Viktor, Bonhomme Vincent, Sleigh Jamie, Schneider Gerhard, Kreuzer Matthias, Radtke Finn
Department of Anaesthesia, Intensive Care, Emergency and Pain Medicine, University Medicine Greifswald, Greifswald, Germany.
Department of Anaesthesiology, Yale School of Medicine, New Haven, United States.
BMC Anesthesiol. 2025 Sep 20;25(1):449. doi: 10.1186/s12871-025-03276-8.
Monitoring the brain under general anaesthesia using the electroencephalogram (EEG) can help to optimise anaesthetic levels and improve patient outcomes. Therefore, it has been recommended by several societies and organisations. Yet, many clinicians only consider the processed indices, even though they are prone to interference and their information value is limited in many situations. To use EEG monitoring systems to their full potential, clinicians need to be able to integrate all information provided. Here, we introduce a structured teaching course and evaluate its effect on the participants' knowledge and attitudes.
The course contents were derived from learning goals, that we considered as required to leverage the full potential of the EEG monitoring systems. The course structure was built using several didactic tools to facilitate learning, including a high level of algorithmisation as well as tools for knowledge repetition, activation, and transfer. To investigate the effects of the course, we compared the participants' self-ratings of their knowledge with regard to the learning goals as well as their attitudes towards using EEG monitoring before and after the course. For this purpose, we anonymously questioned the participants of one course conducted in Greifswald/Germany in December 2023.
The ratings of 36 participants before and after the course show that participation led to a significant improvement in knowledge throughout all learning goals (paired Wilcoxon signed-rank tests, p < 0.001 for each learning goal). Self-ratings of knowledge and competence increased across all learning goals from a mean of 1.9 before the course to 4.0 after the course, rated on Likert scales between 0 ('No knowledge/competency') and 5 ('Expert knowledge/competency'). Furthermore, the attitude towards applying EEG monitoring during general anaesthesia improved significantly (paired Wilcoxon signed-rank test, p = 0.019) from 3.0 ± 1.7 to 3.8 ± 1.2 (mean ± sd), rated on a Likert scale between 0 ('never') and 5 ('always').
We show that the course improves the participants' self-ratings of knowledge with and attitude towards EEG monitoring. By providing teaching methods and resources with standardized contents we aim to facilitate training of the highest quality and motivating clinicians to improve anaesthesia practice, and ultimately patient outcome.
使用脑电图(EEG)在全身麻醉下监测大脑有助于优化麻醉水平并改善患者预后。因此,多个协会和组织都推荐使用。然而,许多临床医生只考虑经过处理的指标,尽管这些指标容易受到干扰,并且在许多情况下其信息价值有限。为了充分发挥EEG监测系统的潜力,临床医生需要能够整合所提供的所有信息。在此,我们介绍一门结构化教学课程,并评估其对参与者知识和态度的影响。
课程内容源自学习目标,我们认为这些目标是充分发挥EEG监测系统潜力所必需的。课程结构采用多种教学工具构建,以促进学习,包括高度的算法化以及知识重复、激活和转移的工具。为了研究该课程的效果,我们比较了参与者在课程前后对学习目标的知识自我评估以及他们对使用EEG监测的态度。为此,我们对2023年12月在德国格赖夫斯瓦尔德举办的一期课程的参与者进行了匿名问卷调查。
36名参与者在课程前后的评分表明,参与该课程使所有学习目标的知识都有显著提高(配对Wilcoxon符号秩检验,每个学习目标的p < 0.001)。在从0(“无知识/能力”)到5(“专家知识/能力”)的李克特量表上,所有学习目标的知识和能力自我评分从课程前的平均1.9提高到课程后的4.0。此外,在全身麻醉期间应用EEG监测的态度从3.0±1.7显著改善(配对Wilcoxon符号秩检验,p = 0.019)到3.8±1.2(平均值±标准差),在从0(“从不”)到5(“总是”)的李克特量表上进行评分。
我们表明该课程提高了参与者对EEG监测的知识自我评估和态度。通过提供具有标准化内容的教学方法和资源,我们旨在促进高质量的培训,并激励临床医生改善麻醉实践,最终改善患者预后。