%0 Journal Article
%@ 2561-326X
%I JMIR Publications
%V 5
%N 5
%P e23461
%T Digital Phenotypes for Understanding Individuals' Compliance With COVID-19 Policies and Personalized Nudges: Longitudinal Observational Study
%A Ibrahim,Ahmed
%A Zhang,Heng
%A Clinch,Sarah
%A Poliakoff,Ellen
%A Parsia,Bijan
%A Harper,Simon
%+ Department of Computer Science, The University of Manchester, LF7, Kilburn Building, Kilburn Buidling, Manchester, M13 9PL, United Kingdom, 44 7427630668, heng.zhang@manchester.ac.uk
%K behavior
%K compliance
%K COVID-19
%K digital phenotyping
%K nudges
%K personalization
%K policy
%K sensor
%K smartphone
%D 2021
%7 27.5.2021
%9 Original Paper
%J JMIR Form Res
%G English
%X Background: Governments promote behavioral policies such as social distancing and phased reopening to control the spread of COVID-19. Digital phenotyping helps promote the compliance with these policies through the personalized behavioral knowledge it produces. Objective: This study investigated the value of smartphone-derived digital phenotypes in (1) analyzing individuals’ compliance with COVID-19 policies through behavioral responses and (2) suggesting ways to personalize communication through those policies. Methods: We conducted longitudinal experiments that started before the outbreak of COVID-19 and continued during the pandemic. A total of 16 participants were recruited before the pandemic, and a smartphone sensing app was installed for each of them. We then assessed individual compliance with COVID-19 policies and their impact on habitual behaviors. Results: Our results show a significant change in people’s mobility (P<.001) as a result of COVID-19 regulations, from an average of 10 visited places every week to approximately 2 places a week. We also discussed our results within the context of nudges used by the National Health Service in the United Kingdom to promote COVID-19 regulations. Conclusions: Our findings show that digital phenotyping has substantial value in understanding people’s behavior during a pandemic. Behavioral features extracted from digital phenotypes can facilitate the personalization of and compliance with behavioral policies. A rule-based messaging system can be implemented to deliver nudges on the basis of digital phenotyping. 
%M 33999832
%R 10.2196/23461
%U https://formative.jmir.org/2021/5/e23461
%U https://doi.org/10.2196/23461
%U http://www.ncbi.nlm.nih.gov/pubmed/33999832