论文标题

有糟糕的一天?使用可穿戴传感器检测非典型生活事件的影响

Having a Bad Day? Detecting the Impact of Atypical Life Events Using Wearable Sensors

论文作者

Burghardt, Keith, Tavabi, Nazgol, Ferrara, Emilio, Narayanan, Shrikanth, Lerman, Kristina

论文摘要

生活事件会极大地影响我们的心理状态和工作表现。例如,压力与专业的不满,焦虑增加和工作场所倦怠有关。我们通过对医院和航空航天工人进行的多个月纵向研究来探索积极和负面的生活事件对许多心理结构的影响。通过因果推断,我们证明了积极的生命事件会增加积极的影响,而负面事件会增加压力,焦虑和负面影响。尽管大多数事件对心理状态都有短暂的影响,但主要的负面事件(例如疾病或参加葬礼)可以减少多天的积极影响。接下来,我们评估是否可以通过可穿戴传感器检测到这些事件,这些传感器可以廉价且不明显地监测与健康相关的因素。我们表明,这些传感器与基于嵌入的学习模型配对,可以使用``在野外''来捕获两个数据集中数百名工人的非典型生活事件。总体而言,我们的结果表明,基于生理感知的自动干预措施可能是可行的,可以帮助工人调节生活事件的负面影响。

Life events can dramatically affect our psychological state and work performance. Stress, for example, has been linked to professional dissatisfaction, increased anxiety, and workplace burnout. We explore the impact of positive and negative life events on a number of psychological constructs through a multi-month longitudinal study of hospital and aerospace workers. Through causal inference, we demonstrate that positive life events increase positive affect, while negative events increase stress, anxiety and negative affect. While most events have a transient effect on psychological states, major negative events, like illness or attending a funeral, can reduce positive affect for multiple days. Next, we assess whether these events can be detected through wearable sensors, which can cheaply and unobtrusively monitor health-related factors. We show that these sensors paired with embedding-based learning models can be used ``in the wild'' to capture atypical life events in hundreds of workers across both datasets. Overall our results suggest that automated interventions based on physiological sensing may be feasible to help workers regulate the negative effects of life events.

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