Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19
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Abstract
Background: In the absence of a vaccine or effective treatment for COVID-19, countries have adopted nonpharmaceutical interventions (NPIs) such as social distancing and full lockdown. An objective and quantitative means of passively monitoring the impact and response of these interventions at a local level is needed. Objective: We aim to explore the utility of the recently developed open-source mobile health platform Remote Assessment of Disease and Relapse (RADAR)–base as a toolbox to rapidly test the effect and response to NPIs intended to limit the spread of COVID-19. Methods: We analyzed data extracted from smartphone and wearable devices, and managed by the RADAR-base from 1062 participants recruited in Italy, Spain, Denmark, the United Kingdom, and the Netherlands. We derived nine features on a daily basis including time spent at home, maximum distance travelled from home, the 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 Dunn tests to assess differences in these features among baseline, prelockdown, and during lockdown periods. We also studied behavioral differences by age, gender, BMI, and educational background. Results: We were able to quantify expected changes in time spent at home, distance travelled, and the number of nearby Bluetooth-enabled devices between prelockdown and during lockdown periods (P<.001 for all five countries). We saw reduced sociality as measured through mobility features and increased virtual sociality through phone use. People were more active on their phones (P<.001 for Italy, Spain, and the United Kingdom), spending more time using social media apps (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), particularly around major news events. Furthermore, participants had a lower heart rate (P<.001 for Italy and Spain; P=.02 for Denmark), went to bed later (P<.001 for Italy, Spain, the United Kingdom, and the Netherlands), and slept more (P<.001 for Italy, Spain, and the United Kingdom). We also found that young people had longer homestay than older people during the 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. Conclusions: RADAR-base, a freely deployable data collection platform leveraging data from wearables and mobile technologies, can be used to rapidly quantify and provide a holistic view of behavioral changes in response to public health interventions as a result of infectious outbreaks such as COVID-19. RADAR-base may be a viable approach to implementing an early warning system for passively assessing the local compliance to interventions in epidemics and pandemics, and could help countries ease out of lockdown.
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The COVID-19 pandemic and related lockdown policies greatly impacted the behaviors (particularly mobility, social interactions, and working environment [working from home]) of European people.
“However, according to our previous research, the COVID-19 pandemic and related lockdown policies greatly impacted the behaviors (particularly mobility, social interactions, and working environment [working from home]) of European people [25].”
From Predicting depressive symptom severity through individuals’ nearby Bluetooth device count data collected by mobile phones: preliminary longitudinal study (2021) · cites this paper as [25]
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“During the COVID-19 pandemic, many researchers used wearable devices for infection surveillance [48, 49], contract tracing [48] and monitoring behavioral changes [50].”
- Authors
- Sun, S., Folarin, A. A., Ranjan, Y., Rashid, Z., Conde, P., Stewart, C., Cummins, N., Matcham, F., Dalla Costa, G., Simblett, S., Leocani, L., Lamers, F., Sørensen, P. S., Buron, M., Zabalza, A., Guerrero Pérez, A. I., Penninx, B. W., Siddi, S., Haro, J. M., Myin-Germeys, I., Rintala, A., Wykes, T., Narayan, V. A., Comi, G., Hotopf, M., Dobson, R. J., & RADAR-CNS Consortium
- Affiliations
- King's College London (GB)
- University of Augsburg (DE)
- Vita-Salute San Raffaele University (IT)
- Amsterdam Neuroscience (NL)
- Copenhagen University Hospital (DK)
- Vall d'Hebron Hospital Universitari (ES)
- Centro de Investigación Biomédica en Red de Salud Mental (ES)
- KU Leuven (BE)
- Corresponding author
- Sun, Shaoxiong
- ORCID
- Sun, Shaoxiong
- Folarin, Amos A
- Ranjan, Yatharth
- Rashid, Zulqarnain
- Conde, Pauline
- Stewart, Callum
- Cummins, Nicholas
- Matcham, Faith
- Dalla Costa, Gloria
- Simblett, Sara
- Leocani, Letizia
- Lamers, Femke
- Sørensen, Per Soelberg
- Buron, Mathias
- Zabalza, Ana
- Guerrero Pérez, Ana Isabel
- Penninx, Brenda WJH
- Siddi, Sara
- Haro, Josep Maria
- Myin-Germeys, Inez
- Rintala, Aki
- Wykes, Til
- Narayan, Vaibhav A
- Comi, Giancarlo
- Hotopf, Matthew
- Dobson, Richard JB
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2020-09-25
- Volume
- 22
- Issue
- 9
- Pages
- e19992
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC7527031
- OpenAlex
- W3105534656
- Cited by
- 256
- References
- 21
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 41 · 2023: 37 · 2022: 77 · 2021: 66 · 2020: 12
- FWCI
- 42.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion, other-oa)
- arXiv (Cornell University) (submittedVersion)
- Lirias (submittedVersion, cc-by)
- Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- UCL Discovery (University College London) (submittedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- Research Portal (King's College London) (submittedVersion, cc-by)
- OPUS (Augsburg University) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- arXiv (Cornell University)
- Funders
- Wellcome Trust
- Scottish Government
- European Federation of Pharmaceutical Industries and Associations
- Alzheimer's Society
- National Institute for Health and Care Research (RP-PG-0407-10314, NIHR-INF-0684, NF-SI-0509-10023, NF-SI-0515-10102, NF-SI-0507-10088, CS-2018-18-ST2-014, 05/40/04, NF-SI-0616-10066)
- British Heart Foundation
- Department of Health and Social Care
- King's College London
- University College London
- European Commission (115902)
- Public Health Agency
- ZonMw (73305095003)
- Hersenstichting
- Alzheimer Nederland
- GIESKES-STRIJBIS FONDS
- Chief Scientist Office, Scottish Government Health and Social Care Directorate
- Medical Research Council (MR/K006584/1, MR/M501633/2, MC_PC_13041, MC_PC_17214)
- Engineering and Physical Sciences Research Council
- Economic and Social Research Council
- Health and Social Care Research and Development Division
- Health Data Research UK
- Topics
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- COVID-19 pandemic, lockdown, non-pharmaceutical interventions, behavior change, RADAR-base, mobile health, wearable devices, smartphone data, social distancing, social media use, sleep, heart rate, step count, mobility, age differences, body mass index
- MeSH terms
- Smartphone, Wearable Electronic Devices, COVID-19, Adolescent, Adult, Aged, Aged, 80 and over, Data Collection, Denmark, Female, United Kingdom, Humans, Italy, Male, Middle Aged, Monitoring, Physiologic, Netherlands, Pneumonia, Viral, Social Isolation, Spain, Body Mass Index, Telemedicine, Coronavirus Infections, Young Adult, Pandemics, Social Media, Mobile Applications
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