Self-Focused and Other-Focused Health Concerns as Predictors of the Uptake of Corona Contact Tracing Apps: Empirical Study

Abstract

Background Corona contact tracing apps are a novel and promising measure to reduce the spread of COVID-19. They can help to balance the need to maintain normal life and economic activities as much as possible while still avoiding exponentially growing case numbers. However, a majority of citizens need to be willing to install such an app for it to be effective. Hence, knowledge about drivers for app uptake is crucial. Objective This study aimed to add to our understanding of underlying psychological factors motivating app uptake. More specifically, we investigated the role of concern for one’s own health and concern to unknowingly infect others. Methods A two-wave survey with 346 German-speaking participants from Switzerland and Germany was conducted. We measured the uptake of two decentralized contact tracing apps officially launched by governments (Corona-Warn-App, Germany; SwissCovid, Switzerland), as well as concerns regarding COVID-19 and control variables. Results Controlling for demographic variables and general attitudes toward the government and the pandemic, logistic regression analysis showed a significant effect of self-focused concerns (odds ratio [OR] 1.64, P=.002). Meanwhile, concern of unknowingly infecting others did not contribute significantly to the prediction of app uptake over and above concern for one’s own health (OR 1.01, P=.92). Longitudinal analyses replicated this pattern and showed no support for the possibility that app uptake provokes changes in levels of concern. Testing for a curvilinear relationship, there was no evidence that “too much” concern leads to defensive reactions and reduces app uptake. Conclusions As one of the first studies to assess the installation of already launched corona tracing apps, this study extends our knowledge of the motivational landscape of app uptake. Based on this, practical implications for communication strategies and app design are discussed.

Predicting the use of a COVID‐19 contact tracing application: A study across two points of measurements

“…The intention, in turn, is assumed to predict actual behavior (Maddux & Rogers, 1983). Empirical results from studies conducted in the context of COVID‐19 for explaining contact tracing mobile app use partly support these assumptions: For instance, higher risk perceptions were related to higher intentions to use the app (Große Deters et al, 2021; Kostka & Habich‐Sobiegalla, 2020). Similarly, believing that one has already had COVID‐19 was related to lower app use intentions.…”

Thematic Analysis of User Experience of Contact Tracing Applications for COVID-19 Using Twitter Data

“…Psychological factors also play a part. Deters et al (2021) explored motivations for adopting contact tracing apps in Germany and Switzerland. They found that personal health concerns played a role in adoption, while the possibility of unknowingly infecting others did not.…”

“…The research offers significant and novel findings based on a fine-grained exploration of users' experiences of contact-tracing apps and mobile government in Kuwait using social media sources. Most research on contact tracing focuses on the design of the technology (Bente et al, 2021;Chuenyindee et al, 2022), privacy and cybersecurity (Azad et al, 2021;Bengio et al, 2020), and concern about the operability of the technology (Deters et al, 2021;Osmanlliu et al, 2021;Parker et al, 2020). Few studies have explored system and service quality simultaneously within an information system model, and most studies overlook cultural and social factors in favor of a focus on technical aspects.…”