Objective

In the context of anesthesiology, we investigated whether the salience effort expectancy value (SEEV) model fit is associated with situation awareness and perception scores.

Background

The distribution of visual attention is important for situation awareness—that is, understanding what is going on—in safety-critical domains. Although the SEEV model has been suggested as a process situation awareness measure, the validity of the model as a predictor of situation awareness has not been tested.

Method

In a medical simulation, 31 senior and 30 junior anesthesiologists wore a mobile eye tracker and induced general anesthesia into a simulated patient. When inserting a breathing tube into the mannequin’s trachea (endotracheal intubation), the scenario included several clinically relevant events for situation awareness and general events in the environment. Both were assessed using direct awareness measures.

Results

The overall SEEV model fit was good with no difference between junior and senior anesthesiologists. Overall, the situation awareness scores were low. As expected, the SEEV model fits showed significant positive correlations with situation awareness level 1 scores.

Conclusion

The SEEV model seems to be suitable as a process situation awareness measure to predict and investigate the perception of changes in the environment (situation awareness level 1). The situation awareness scores indicated that anesthesiologists seem not to perceive the environment well during endotracheal intubation.

Application

The SEEV model fit can be used to capture and assess situation awareness level 1. During endotracheal intubation, anesthesiologists should be supported by technology or staff to notice changes in the environment.

中文翻译：

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SEEV 模型作为态势感知过程测量的有效性：模拟气管插管的示例

客观的

在麻醉学的背景下，我们调查了突出努力期望值 (SEEV) 模型拟合是否与情境意识和感知分数相关。

背景

视觉注意力的分布对于态势感知很重要，即了解安全关键领域中正在发生的事情。尽管 SEEV 模型已被建议作为过程态势感知测量，但该模型作为态势感知预测器的有效性尚未经过测试。

方法

在医学模拟中，31 名高级麻醉师和 30 名初级麻醉师佩戴移动眼动仪，对模拟患者进行全身麻醉。当将呼吸管插入人体模型的气管（气管插管）时，该场景包括几个临床相关事件，以了解情况和环境中的一般事件。两者均使用直接意识措施进行评估。

结果

整体 SEEV 模型拟合良好，初级和高级麻醉师之间没有差异。总体而言，态势感知得分较低。正如预期的那样，SEEV 模型拟合显示与情境意识级别 1 分数显着正相关。

结论

SEEV 模型似乎适合作为过程态势感知度量来预测和调查对环境变化的感知（态势感知级别 1）。情境意识评分表明，麻醉师在气管插管期间似乎无法很好地感知环境。

应用

SEEV 模型拟合可用于捕获和评估情境意识水平 1。在气管插管期间，麻醉师应在技术或工作人员的支持下注意到环境的变化。