论文标题

使用智能手机和可穿戴设备来监视Covid-19期间的行为改变

Using smartphones and wearable devices to monitor behavioural changes during COVID-19

论文作者

Sun, Shaoxiong, Folarin, Amos, Ranjan, Yatharth, Rashid, Zulqarnain, Conde, Pauline, Stewart, Callum, Cummins, Nicholas, Matcham, Faith, Costa, Gloria Dalla, Simblett, Sara, Leocani, Letizia, Sørensen, Per Soelberg, Buron, Mathias, Guerrero, Ana Isabel, Zabalza, Ana, Penninx, Brenda WJH, Lamers, Femke, Siddi, Sara, Haro, Josep Maria, Myin-Germeys, Inez, Rintala, Aki, Wykes, Til, Narayan, Vaibhav A., Comi, Giancarlo, Hotopf, Matthew, Dobson, Richard JB

论文摘要

我们旨在探索最近开发的开源移动健康平台雷达基碱基的实用性,以迅速测试旨在限制Covid-19的效果和对NPI的响应。我们分析了从智能手机和可穿戴设备中提取的数据,并由在意大利,西班牙,丹麦,英国和荷兰招募的1062名参与者的雷达基础管理。我们每天都会得出九个功能,包括在家中度过的时间,最大距离距离的设备(作为物理距离的代理),步骤计数,平均心率,睡眠持续时间,睡眠时间,手机解锁持续时间和社交应用程序用途。我们进行了Kruskal-Wallis测试,然后进行了事后DUNNS测试,以评估基线,前和锁定期间这些特征的差异。我们还按年龄,性别,体重指数(BMI)和教育背景研究了行为差异。我们能够量化预期在家中所花费的时间,距离旅行的时间以及锁定前和锁定期间蓝牙设备的附近设备的数量。我们看到通过流动性特征来衡量的社会性降低,并通过电话使用增加了虚拟社会性。人们在手机上更加活跃,使用社交媒体应用程序花费更多的时间,尤其是在重大新闻事件周围。此外,参与者的心率较低,后来上床睡觉,睡得更多。我们还发现,在锁定期间,年轻人的寄宿家庭比老年人更长,日常台阶较少。尽管在家中度过的高BMI组之间没有显着差异,但低BMI组的行走却更多。雷达碱可用于快速量化,并为响应于公共卫生干预措施的行为变化而整体视野,这是由于传染性暴发(例如Covid-19)。

We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to rapidly test the effect and response to NPIs aimed at limiting the spread of COVID-19. We analysed data extracted from smartphone and wearable devices and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, maximum number of Bluetooth-enabled nearby devices (as a proxy for physical distancing), step count, average heart rate, sleep duration, bedtime, phone unlock duration, and social app use duration. We performed Kruskal-Wallis tests followed by post-hoc Dunns tests to assess differences in these features among baseline, pre-, and during-lockdown periods. We also studied behavioural differences by age, gender, body mass index (BMI), and educational background. We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between pre- and during-lockdown periods. We saw reduced sociality as measured through mobility features, and increased virtual sociality through phone usage. People were more active on their phones, spending more time using social media apps, particularly around major news events. Furthermore, participants had lower heart rate, went to bed later, and slept more. We also found that young people had longer homestay than older people during lockdown and fewer daily steps. Although there was no significant difference between the high and low BMI groups in time spent at home, the low BMI group walked more. RADAR-base can be used to rapidly quantify and provide a holistic view of behavioural changes in response to public health interventions as a result of infectious outbreaks such as COVID-19.

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