论文标题

Dymand的开发,部署和评估 - 一种开源智能手表和智能手机系统,用于捕获夫妻在日常生活中慢性疾病管理中的二元相互作用

Development, Deployment, and Evaluation of DyMand -- An Open-Source Smartwatch and Smartphone System for Capturing Couples' Dyadic Interactions in Chronic Disease Management in Daily Life

论文作者

Boateng, George, Santhanam, Prabhakaran, Fleisch, Elgar, Lüscher, Janina, Pauly, Theresa, Scholz, Urte, Kowatsch, Tobias

论文摘要

夫妻的二元相互作用引起了人们的关注,因为它们可以洞悉关系质量和慢性病管理。当前,对夫妻互动的门诊评估需要在随机或计划的时间内收集数据,这可能会错过重要的夫妻的互动/对话时刻。在这项工作中,我们开发了,部署和评估Dymand,这是一种新颖的开源智能手表和智能手机系统,可根据合作伙伴的互动时刻从夫妇那里收集自我报告和传感器数据。我们的基于智能手表的算法使用一个合作伙伴佩戴的两个智能手表之间的蓝牙信号强度,以及一个语音活动检测机器学习算法来推断合作伙伴正在交互,然后触发数据收集。我们在7天的现场研究中部署了DYMAND系统,并收集了有关13(n = 26)基于瑞士的异性恋夫妇管理糖尿病的糖尿病2型伴侣的13(n = 26)的社会支持,情感健康和健康行为的数据。我们的系统触发了该应用程序运行时的99.1%的传感器和自我报告数据数量的99.1%,而算法触发的录音中有77.6%包含合作伙伴的对话矩,而计划触发器则为43.8%。可用性评估表明,Dymand易于使用。 Dymand可以由社会,临床或健康心理学研究人员使用,以了解日常生活中夫妻的社会动态,并为管理慢性疾病的夫妇开发和提供行为干预措施。

Dyadic interactions of couples are of interest as they provide insight into relationship quality and chronic disease management. Currently, ambulatory assessment of couples' interactions entails collecting data at random or scheduled times which could miss significant couples' interaction/conversation moments. In this work, we developed, deployed and evaluated DyMand, a novel open-source smartwatch and smartphone system for collecting self-report and sensor data from couples based on partners' interaction moments. Our smartwatch-based algorithm uses the Bluetooth signal strength between two smartwatches each worn by one partner, and a voice activity detection machine-learning algorithm to infer that the partners are interacting, and then to trigger data collection. We deployed the DyMand system in a 7-day field study and collected data about social support, emotional well-being, and health behavior from 13 (N=26) Swiss-based heterosexual couples managing diabetes mellitus type 2 of one partner. Our system triggered 99.1% of the expected number of sensor and self-report data when the app was running, and 77.6% of algorithm-triggered recordings contained partners' conversation moments compared to 43.8% for scheduled triggers. The usability evaluation showed that DyMand was easy to use. DyMand can be used by social, clinical, or health psychology researchers to understand the social dynamics of couples in everyday life, and for developing and delivering behavioral interventions for couples who are managing chronic diseases.

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