Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study.
COVID-19
app
digital health
frontline worker
health care worker
mHealth
mobile health
sensor
smartphone
wearable
Journal
JMIR research protocols
ISSN: 1929-0748
Titre abrégé: JMIR Res Protoc
Pays: Canada
ID NLM: 101599504
Informations de publication
Date de publication:
12 May 2021
12 May 2021
Historique:
received:
12
04
2021
accepted:
03
05
2021
revised:
03
05
2021
pubmed:
5
5
2021
medline:
5
5
2021
entrez:
4
5
2021
Statut:
epublish
Résumé
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. By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19. 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. 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. 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. ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869. DERR1-10.2196/29562.
Sections du résumé
BACKGROUND
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
OBJECTIVE
By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19.
METHODS
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
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
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
BACKGROUND
ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)
UNASSIGNED
DERR1-10.2196/29562.
Identifiants
pubmed: 33945497
pii: v10i5e29562
doi: 10.2196/29562
pmc: PMC8117956
doi:
Banques de données
ClinicalTrials.gov
['NCT04756869']
Types de publication
Journal Article
Langues
eng
Pagination
e29562Subventions
Organisme : NHLBI NIH HHS
ID : K24 HL156896
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL146354
Pays : United States
Organisme : NHLBI NIH HHS
ID : T32 HL007622
Pays : United States
Informations de copyright
©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.
Références
JMIR Ment Health. 2021 Jan 20;8(1):e23125
pubmed: 33341754
Healthcare (Basel). 2020 Jul 24;8(3):
pubmed: 32722042
Clin Nurs Res. 2022 Nov;31(8):1390-1398
pubmed: 36154716
N Engl J Med. 2020 Mar 5;382(10):929-936
pubmed: 32004427
JMIR Mhealth Uhealth. 2019 Oct 24;7(10):e15775
pubmed: 31651402
J Urban Health. 2021 Apr;98(2):183-186
pubmed: 33471281
PLoS One. 2020 Dec 10;15(12):e0243693
pubmed: 33301493
Ann Intern Med. 2020 May 05;172(9):577-582
pubmed: 32150748
Lancet. 2020 Mar 14;395(10227):912-920
pubmed: 32112714
JMIR Mhealth Uhealth. 2020 Sep 16;8(9):e19796
pubmed: 32609622
Clin Infect Dis. 2020 Dec 31;71(11):2920-2926
pubmed: 32548628
Infect Control Hosp Epidemiol. 2020 Sep;41(9):1075-1076
pubmed: 32456720
Community Ment Health J. 2020 Oct;56(7):1204-1205
pubmed: 32772205
Nat Biomed Eng. 2020 Dec;4(12):1208-1220
pubmed: 33208926
Curr Opin Syst Biol. 2020 Apr;20:17-25
pubmed: 32984661
JMIR Res Protoc. 2020 Sep 18;9(9):e19288
pubmed: 32945777
Gen Hosp Psychiatry. 2020 Sep - Oct;66:1-8
pubmed: 32590254
Blood Adv. 2019 Dec 10;3(23):3977-3981
pubmed: 31809535
Psychol Health Med. 2021 Jan;26(1):23-34
pubmed: 32286091
MMWR Morb Mortal Wkly Rep. 2020 May 29;69(21):651-655
pubmed: 32463809
JAMA. 2020 Aug 18;324(7):703-704
pubmed: 32663246
Nat Med. 2021 Jan;27(1):73-77
pubmed: 33122860
J Med Internet Res. 2020 Aug 25;22(8):e21366
pubmed: 32763891
J Med Internet Res. 2020 Dec 30;22(12):e21815
pubmed: 33351777
Lancet Public Health. 2020 Sep;5(9):e475-e483
pubmed: 32745512
JMIR Mhealth Uhealth. 2020 Oct 5;8(10):e21692
pubmed: 32936769
Telemed J E Health. 2021 Mar;27(3):269-275
pubmed: 32821025
JMIR Form Res. 2020 Jan 23;4(1):e17077
pubmed: 32012037
J Med Internet Res. 2021 Feb 22;23(2):e26107
pubmed: 33529156
Can J Psychiatry. 2009 May;54(5):302-11
pubmed: 19497162
Infect Control Hosp Epidemiol. 2020 Dec;41(12):1466-1467
pubmed: 32576336
Epidemiol Infect. 2008 Jul;136(7):997-1007
pubmed: 17662167
JMIR Ment Health. 2020 Sep 25;7(9):e22408
pubmed: 32915764