Sociodemographic characteristics determine download and use of a Corona contact tracing app in Germany-Results of the COSMO surveys

Grill, Eva; Eitze, Sarah; Bock, Freia de; Dragano, Nico; Huebl, Lena; Schmich, Patrick; Wieler, Lothar H. und Betsch, Cornelia (2021): Sociodemographic characteristics determine download and use of a Corona contact tracing app in Germany-Results of the COSMO surveys.
In: PloS one 16(9), e0256660

Abstract

During the SARS-CoV-2 pandemic mobile health applications indicating risks emerging from close contacts to infected persons have a large potential to interrupt transmission chains by automating contact tracing. Since its dispatch in Germany in June 2020 the Corona Warn App has been downloaded on 25.7 Mio smartphones by February 2021. To understand barriers to download and user fidelity in different sociodemographic groups we analysed data from five consecutive cross-sectional waves of the COVID-19 Snapshot Monitoring survey from June to August 2020. Questions on the Corona Warn App included information on download, use, functionality, usability, and consequences of the app. Of the 4,960 participants (mean age 45.9 years, standard deviation 16.0, 50.4% female), 36.5% had downloaded the Corona Warn App. Adjusted analysis found that those who had downloaded the app were less likely to be female (Adjusted Odds Ratio for men 1.16 95% Confidence Interval 1.02;1.33), less likely to be younger (Adjusted Odds Ratio for age 18 to 39 0.47 0.32;0.59 Adjusted Odds Ratio for age 40 to 64 0.57 0.46;0.69), less likely to have a lower household income (AOR 0.55 0.43;0.69), and more likely to live in one of the Western federal states including Berlin (AOR 2.31 1.90;2.82). Willingness to disclose a positive test result and trust in data protection compliance of the Corona Warn App was significantly higher in older adults. Willingness to disclose also increased with higher educational degrees and income. This study supports the hypothesis of a digital divide that separates users and non-users of the Corona Warn App along a well-known health gap of education, income, and region.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin > Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie > Epidemiologie für Schwindelerkrankungen
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• Sprache: Englisch