4.7 Article

Using Smartphones and Wearable Devices to Monitor Behavioral Changes During COVID-19

Journal

JOURNAL OF MEDICAL INTERNET RESEARCH
Volume 22, Issue 9, Pages -

Publisher

JMIR PUBLICATIONS, INC
DOI: 10.2196/19992

Keywords

mobile health; COVID-19; behavioral monitoring; smartphones; wearable devices; mobility; phone use

Funding

  1. National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust, King's College London
  2. EU/European Federation of Pharmaceutical Industries and Associations (EFPIA) IMI Joint Undertaking 2 (RADAR-CNS) [115902]
  3. ZonMw-Memorabel [73305095003]
  4. Dutch Deltaplan Dementie
  5. Gieskes-Strijbis Foundation
  6. Alzheimer's Society in the Netherlands (Alzheimer Nederland)
  7. Brain Foundation Netherlands (Hersenstichting)
  8. Health Data Research UK
  9. UK Medical Research Council
  10. Engineering and Physical Sciences Research Council
  11. Economic and Social Research Council
  12. Department of Health and Social Care (England)
  13. Chief Scientist Office of the Scottish Government Health and Social Care Directorates
  14. Health and Social Care Research and Development Division (Welsh Government)
  15. Public Health Agency (Northern Ireland)
  16. British Heart Foundation
  17. Wellcome Trust
  18. NIHR University College London Hospitals Biomedical Research Centre
  19. MRC [MC_PC_17214, G0902393, MR/M501633/2] Funding Source: UKRI
  20. National Institute for Health Research [NF-SI-0507-10088, NF-SI-0515-10102] Funding Source: researchfish

Ask authors/readers for more resources

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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available