Adoption of a Contact Tracing App for Containing COVID-19: A Health Belief Model Approach

JMIR Public Health Surveill. 2020 Sep 1;6(3):e20572. doi: 10.2196/20572.

Abstract

Background: To track and reduce the spread of COVID-19, apps have been developed to identify contact with individuals infected with SARS-CoV-2 and warn those who are at risk of having contracted the virus. However, the effectiveness of these apps depends highly on their uptake by the general population.

Objective: The present study investigated factors influencing app use intention, based on the health belief model. In addition, associations with respondents' level of news consumption and their health condition were investigated.

Methods: A survey was administered in Flanders, Belgium, to 1500 respondents, aged 18 to 64 years. Structural equation modeling was used to investigate relationships across the model's constructs.

Results: In total, 48.70% (n=730) of respondents indicated that they intend to use a COVID-19 tracing app. The most important predictor was the perceived benefits of the app, followed by self-efficacy and perceived barriers. Perceived severity and perceived susceptibility were not related to app uptake intention. Moreover, cues to action (ie, individuals' exposure to [digital] media content) were positively associated with app use intention. As the respondents' age increased, their perceived benefits and self-efficacy for app usage decreased.

Conclusions: Initiatives to stimulate the uptake of contact tracing apps should enhance perceived benefits and self-efficacy. A perceived barrier for some potential users is privacy concerns. Therefore, when developing and launching an app, clarification on how individuals' privacy will be protected is needed. To sustain perceived benefits in the long run, supplementary options could be integrated to inform and assist users.

Keywords: COVID-19; SARS-CoV-2; contact tracing; health belief model; privacy; proximity tracing.

Publication types

  • Comment

MeSH terms

  • Adolescent
  • Adult
  • Belgium
  • Betacoronavirus
  • COVID-19
  • Contact Tracing
  • Coronavirus Infections*
  • Humans
  • Middle Aged
  • Mobile Applications*
  • Pandemics*
  • Pneumonia, Viral*
  • Privacy
  • SARS-CoV-2
  • Smartphone*
  • Young Adult