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Clingan CA, Dittakavi M, Rozwadowski M, Gilley KN, Cislo CR, Barabas J, Sandford E, Olesnavich M, Flora C, Tyler J, Mayer C, Stoneman E, Braun T, Forger DB, Tewari M, Choi SW. Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study. JMIR Res Protoc 2021; 10:e29562. [PMID: 33945497 PMCID: PMC8117956 DOI: 10.2196/29562] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/03/2021] [Accepted: 05/03/2021] [Indexed: 12/22/2022] Open
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://clinicaltrials.gov/ct2/show/NCT04756869. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/29562.
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Affiliation(s)
- Caroline A Clingan
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
| | - Manasa Dittakavi
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
| | - Michelle Rozwadowski
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
| | - Kristen N Gilley
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
| | - Christine R Cislo
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
| | - Jenny Barabas
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Erin Sandford
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Mary Olesnavich
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Christopher Flora
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Jonathan Tyler
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
- Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Caleb Mayer
- Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Emily Stoneman
- Department of Internal Medicine, Division of Infectious Diseases, University of Michigan, Ann Arbor, MI, United States
| | - Thomas Braun
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Daniel B Forger
- Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States
| | - Muneesh Tewari
- Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States
| | - Sung Won Choi
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States
- Rogel Cancer Center, University of Michigan, Ann Arbor, MI, United States
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