Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: May 8, 2020
Date Accepted: Jul 26, 2020
Date Submitted to PubMed: Sep 2, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Using smartphones and wearable devices to monitor behavioural changes during COVID-19
ABSTRACT
Background:
In the absence of a vaccine or effective treatment for COVID-19, countries have adopted Non-Pharmaceutical Interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of monitoring the impact and response of these interventions at a local level is urgently required.
Objective:
We aimed to explore the utility of the recently developed open-source mobile health platform RADAR-base as a toolbox to test the effect and response to NPIs aimed at limiting the spread of COVID-19.
Methods:
We included 1062 participants recruited in Italy, Spain, Denmark, the UK, and the Netherlands. We derived features from the phone and wearable device for length of time spent at home, distance travelled from home, heart rate, sleep, and patterns of phone use. We visualised data using time series plots and performed statistical tests to assess differences in behaviour during baseline, pre-, and post-lockdown periods.
Results:
We found significant changes in behaviours between baseline/pre-lockdown and post-lockdown for all features except total sleep duration. In general, participants spent more time at home (P < .001 for all five countries), travelled much less (P < .001 for all five countries), and were more active on their phones (P < .001 for Italy and Spain, P = 0.006 for the UK, P = .02 for the Netherlands), interacting with others by using social apps (P < .001 for Italy, Spain, and the Netherlands; P = .02 for the UK). Nevertheless, the response across nations differed with Denmark showing attenuated changes in behaviour.
Conclusions:
Differences in the extracted features by country may reflect variations in communication and implementation of different NPIs as well as cultural differences. We have demonstrated that generalised open-source mobile health monitoring platforms such as RADAR-base which leverages data from wearables and mobile technologies are valuable tools for helping understand the behavioural impact of public health interventions implemented in response to infectious outbreaks such as COVID-19.
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