Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study

Caroline A Clingan, Manasa Dittakavi, Michelle Rozwadowski, Kristen N Gilley, Christine R Cislo, Jenny Barabas, Erin Sandford, Mary Olesnavich, Christopher Flora, Jonathan Tyler, Caleb Mayer, Emily Stoneman, Thomas Braun, Daniel B Forger, Muneesh Tewari, Sung Won Choi, Caroline A Clingan, Manasa Dittakavi, Michelle Rozwadowski, Kristen N Gilley, Christine R Cislo, Jenny Barabas, Erin Sandford, Mary Olesnavich, Christopher Flora, Jonathan Tyler, Caleb Mayer, Emily Stoneman, Thomas Braun, Daniel B Forger, Muneesh Tewari, Sung Won Choi

Abstract

Background: Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families.

Objective: By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19.

Methods: We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use.

Results: A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing.

Conclusions: Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population.

Trial registration: ClinicalTrials.gov NCT04756869; https://ichgcp.net/clinical-trials-registry/NCT04756869.

International registered report identifier (irrid): DERR1-10.2196/29562.

Keywords: COVID-19; app; digital health; frontline worker; health care worker; mHealth; mobile health; sensor; smartphone; wearable.

Conflict of interest statement

Conflicts of Interest: None declared.

©Caroline A Clingan, Manasa Dittakavi, Michelle Rozwadowski, Kristen N Gilley, Christine R Cislo, Jenny Barabas, Erin Sandford, Mary Olesnavich, Christopher Flora, Jonathan Tyler, Caleb Mayer, Emily Stoneman, Thomas Braun, Daniel B Forger, Muneesh Tewari, Sung Won Choi. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 12.05.2021.

Figures

Figure 1
Figure 1
Study schematic. HCW: health care worker.

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