This paper is in the following e-collection/theme issue:

Non-randomized Protocols and Methods (ehealth) (596) JMIR Theme Issue: COVID-19 Special Issue (2481) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1526) Outbreak and Pandemic Preparedness and Management (1775) Infectious Diseases (non-STD/STI) (1641) mHealth for Wellness, Behavior Change and Prevention (3048) Wearable Devices and Sensors (963) Fitness Trackers and Smart Pedometers/Accelerometers (600) Theme Issue: Apps for COVID-19 (#Apps4Covid) (137) JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions (401) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1524) Crowdsourcing, Big Data, Quantified Self-based Research Data (10)

Published on in Vol 10, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32587, first published .
Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

Investigating the Use of Digital Health Technology to Monitor COVID-19 and Its Effects: Protocol for an Observational Study (Covid Collab Study)

Authors of this article:

Callum Stewart1 Author Orcid Image ;   Yatharth Ranjan1 Author Orcid Image ;   Pauline Conde1 Author Orcid Image ;   Zulqarnain Rashid1 Author Orcid Image ;   Heet Sankesara1 Author Orcid Image ;   Xi Bai2 Author Orcid Image ;   Richard J B Dobson1, 2, 3, 4, 5 Author Orcid Image ;   Amos A Folarin1, 2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Chan H. Wearable Devices for Long COVID: Prospects, Challenges and Options. Asian Bioethics Review 2024;16(4):757 View
  2. Ranjan Y, Chang J, Sankesara H, Conde P, Rashid Z, Dobson R, Folarin A. RADAR-IoT: An Open-Source, Interoperable, and Extensible IoT Gateway Framework for Health Research. Sensors 2024;24(14):4614 View
  3. Stewart C, Ranjan Y, Conde P, Sun S, Zhang Y, Rashid Z, Sankesara H, Cummins N, Laiou P, Bai X, Dobson R, Folarin A. Physiological presentation and risk factors of long COVID in the UK using smartphones and wearable devices: a longitudinal, citizen science, case–control study. The Lancet Digital Health 2024;6(9):e640 View
  4. Zhang Y, Stewart C, Ranjan Y, Conde P, Sankesara H, Rashid Z, Sun S, Dobson R, Folarin A. Large-scale digital phenotyping: Identifying depression and anxiety indicators in a general UK population with over 10,000 participants. Journal of Affective Disorders 2025;375:412 View