Your browser doesn't support javascript.
Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study.
Clingan, Caroline A; Dittakavi, Manasa; Rozwadowski, Michelle; Gilley, Kristen N; Cislo, Christine R; Barabas, Jenny; Sandford, Erin; Olesnavich, Mary; Flora, Christopher; Tyler, Jonathan; Mayer, Caleb; Stoneman, Emily; Braun, Thomas; Forger, Daniel B; Tewari, Muneesh; Choi, Sung Won.
  • Clingan CA; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Dittakavi M; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Rozwadowski M; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Gilley KN; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Cislo CR; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Barabas J; Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Sandford E; Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Olesnavich M; Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Flora C; Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
  • Tyler J; Division of Pediatric Hematology/Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI, United States.
  • Mayer C; Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States.
  • Stoneman E; Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States.
  • Braun T; Department of Internal Medicine, Division of Infectious Diseases, University of Michigan, Ann Arbor, MI, United States.
  • Forger DB; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States.
  • Tewari M; Department of Mathematics, College of Literature, Arts, and Sciences, University of Michigan, Ann Arbor, MI, United States.
  • Choi SW; Division of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States.
JMIR Res Protoc ; 10(5): e29562, 2021 May 12.
Article in English | MEDLINE | ID: covidwho-1304555
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.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Qualitative research / Randomized controlled trials Language: English Journal: JMIR Res Protoc Year: 2021 Document Type: Article Affiliation country: 29562

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Observational study / Prognostic study / Qualitative research / Randomized controlled trials Language: English Journal: JMIR Res Protoc Year: 2021 Document Type: Article Affiliation country: 29562