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An App-Based Intervention to Support First Responders and Essential Workers During the COVID-19 Pandemic: Needs Assessment and Mixed Methods Implementation Study.
Vilendrer, Stacie; Amano, Alexis; Brown Johnson, Cati G; Favet, Marissa; Safaeinili, Nadia; Villasenor, Jacqueline; Shaw, Jonathan G; Hertelendy, Attila J; Asch, Steven M; Mahoney, Megan.
  • Vilendrer S; Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.
  • Amano A; Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.
  • Brown Johnson CG; Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.
  • Favet M; College of Liberal Arts and Sciences, University of Iowa, Iowa City, IA, United States.
  • Safaeinili N; Health Policy and Management, University of California, Berkeley, Berkeley, CA, United States.
  • Villasenor J; John Muir College, University of California, San Diego, La Jolla, CA, United States.
  • Shaw JG; Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.
  • Hertelendy AJ; Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, United States.
  • Asch SM; Disaster Medicine Fellowship, Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States.
  • Mahoney M; Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, CA, United States.
J Med Internet Res ; 23(5): e26573, 2021 05 20.
Article in English | MEDLINE | ID: covidwho-1236646
ABSTRACT

BACKGROUND:

The COVID-19 pandemic has created unprecedented challenges for first responders (eg, police, fire, and emergency medical services) and nonmedical essential workers (eg, workers in food, transportation, and other industries). Health systems may be uniquely suited to support these workers given their medical expertise, and mobile apps can reach local communities despite social distancing requirements. Formal evaluation of real-world mobile app-based interventions is lacking.

OBJECTIVE:

We aimed to evaluate the adoption, acceptability, and appropriateness of an academic medical center-sponsored app-based intervention (COVID-19 Guide App) designed to support access of first responders and essential workers to COVID-19 information and testing services. We also sought to better understand the COVID-19-related needs of these workers early in the pandemic.

METHODS:

To understand overall community adoption, views and download data of the COVID-19 Guide App were described. To understand the adoption, appropriateness, and acceptability of the app and the unmet needs of workers, semistructured qualitative interviews were conducted by telephone, by video, and in person with first responders and essential workers in the San Francisco Bay Area who were recruited through purposive, convenience, and snowball sampling. Interview transcripts and field notes were qualitatively analyzed and presented using an implementation outcomes framework.

RESULTS:

From its launch in April 2020 to September 2020, the app received 8262 views from unique devices and 6640 downloads (80.4% conversion rate, 0.61% adoption rate across the Bay Area). App acceptability was mixed among the 17 first responders interviewed and high among the 10 essential workers interviewed. Select themes included the need for personalized and accurate information, access to testing, and securing personal safety. First responders faced additional challenges related to interprofessional coordination and a "culture of heroism" that could both protect against and exacerbate health vulnerability.

CONCLUSIONS:

First responders and essential workers both reported challenges related to obtaining accurate information, testing services, and other resources. A mobile app intervention has the potential to combat these challenges through the provision of disease-specific information and access to testing services but may be most effective if delivered as part of a larger ecosystem of support. Differentiated interventions that acknowledge and address the divergent needs between first responders and non-first responder essential workers may optimize acceptance and adoption.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Emergency Responders / Mobile Applications / COVID-19 Type of study: Experimental Studies / Observational study / Qualitative research Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26573

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Emergency Responders / Mobile Applications / COVID-19 Type of study: Experimental Studies / Observational study / Qualitative research Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: 26573