CHS: Medium: Collaborative Research: Managing Stress in the Workplace: Unobtrusive Monitoring and Adaptive Interventions

CHS：媒介：协作研究：管理工作场所的压力：不显眼的监控和适应性干预

• 批准号: 1704889
• 负责人: Gloria Mark
• 金额: $ 42万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704889&HistoricalAwards=false
• 关键词: CHS; Medium; Collaborative; Research; Managing

Workplace stress is a serious problem that has a direct and negative impact on health, happiness, and productivity. Current approaches for both measuring stress and reducing it are limited; measurements typically rely on self-report or obtrusive sensors, while people often don't seek treatment until the stress has built to dangerous levels (or at all, if they are afraid of other people's judgments). This project's goal is to develop methods both to detect stress and provide personalized relaxation exercises, in real time and in the work context. To detect stress, the research team will study how well data from commonly available devices at work such as webcams, fitness trackers, and keyboards can predict individuals' stress levels. To reduce stress, the team will develop a suite of brief relaxation exercises and a system that uses predicted stress levels to recommend different exercises, learning over time which ones work best for a particular person. These predictive models and interventions will be tested in a long-term study in a real office environment, both validating the work and providing direct effects on experimental participants' well-being. The project will also have direct educational impacts for groups underrepresented in STEM fields and generate anonymized datasets that other researchers can use. The team will develop experimental methods to reliably extract stress cues from commodity devices, using a suite of cognitive tasks that represent knowledge work and typical workplace stressors (e.g., time pressure, noise, distractions). Participants will perform the tasks and experience stressors while the team collects behavioral data from the commodity devices and ground truth stress measurements using physiological signals derived from thermal imaging. The team will evaluate how well features derived from the sensed behavioral data, using different sets of devices, can predict the ground truth stress data and how it varies based on specific stressors. The team will also develop a framework to deliver brief stress-reduction exercises that promote deep breathing, a proven effective and learnable stress reduction technique. The team will use iterative prototyping to develop novel, engaging mobile apps that use biofeedback, games, and music to support breathing exercises; these will be delivered by a multi-arm bandit-based recommendation system that considers the current context (predicted stress and stressors, time of day, particular computer activities) along with historical exercise adherence and results to suggest effective exercises. The stress sensing models and intervention framework will be validated through a series of lab and field studies with information workers at a software company, collecting stress data in situ with ecological momentary assessment techniques, validated survey instruments for stress and affect, and interviews.

工作场所压力是一个严重的问题，对健康、幸福感和生产力产生直接的负面影响。 目前测量压力和减轻压力的方法是有限的；测量通常依赖于自我报告或侵入式传感器，而人们通常不会寻求治疗，直到压力达到危险水平（或者根本不寻求治疗，如果他们害怕别人的判断）。 该项目的目标是开发在工作环境中实时检测压力并提供个性化放松练习的方法。 为了检测压力，研究团队将研究来自网络摄像头、健身追踪器和键盘等常用工作设备的数据如何预测个人的压力水平。 为了减轻压力，该团队将开发一套简短的放松练习和一个系统，该系统使用预测的压力水平来推荐不同的练习，随着时间的推移了解哪些练习最适合特定的人。 这些预测模型和干预措施将在真实办公环境中的长期研究中进行测试，既验证工作，又对实验参与者的福祉产生直接影响。 该项目还将对 STEM 领域代表性不足的群体产生直接的教育影响，并生成其他研究人员可以使用的匿名数据集。该团队将开发实验方法，使用一套代表知识工作和典型工作场所压力源（例如时间压力、噪音、干扰）的认知任务，从商品设备中可靠地提取压力线索。 参与者将执行任务并经历压力源，同时团队从商品设备收集行为数据，并使用热成像产生的生理信号进行地面真实压力测量。 该团队将评估使用不同设备组从感测到的行为数据中得出的特征可以在多大程度上预测真实的压力数据以及它如何根据特定的压力源而变化。 该团队还将开发一个框架，提供简短的减压练习，促进深呼吸，这是一种行之有效且可学习的减压技术。 该团队将使用迭代原型开发新颖、引人入胜的移动应用程序，使用生物反馈、游戏和音乐来支持呼吸练习；这些将由基于多臂老虎机的推荐系统提供，该系统考虑当前环境（预测的压力和压力源、一天中的时间、特定的计算机活动）以及历史锻炼坚持和结果，以建议有效的锻炼。 压力感知模型和干预框架将通过与软件公司信息工作者进行的一系列实验室和现场研究进行验证，利用生态瞬时评估技术、经过验证的压力和情感调查工具以及访谈收集现场压力数据。

项目成果

Stress and productivity patterns of interrupted, synergistic, and antagonistic office activities

中断、协同和对抗办公室活动的压力和生产力模式

• DOI: 10.1038/s41597-019-0249-5
• 发表时间: 2019
• 期刊: Scientific Data
• 影响因子: 9.8
• 作者: Zaman, Shaila;Wesley, Amanveer;Silva, Dennis Rodrigo Da Cunha;Buddharaju, Pradeep;Akbar, Fatema;Gao, Ge;Mark, Gloria;Gutierrez-Osuna, Ricardo;Pavlidis, Ioannis
• 通讯作者: Pavlidis, Ioannis

An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work

• DOI: 10.3390/s19173766
• 发表时间: 2019-09-01
• 期刊: SENSORS
• 影响因子: 3.9
• 作者: Akbar, Fatema;Mark, Gloria;Gutierrez-Osuna, Ricardo
• 通讯作者: Gutierrez-Osuna, Ricardo