Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors

Abstract

Contact tracing apps (CTAs) have been introduced as a means to identify and isolate possible cases infected with COVID-19. Since the adoption rate determines the effectiveness of CTAs, it is important to examine what factors contribute to a higher CTA uptake. This study aimed to use an integrative approach to explain early CTA adoption, whereby three perspectives are distinguished: technology-related (derived from the Unified Theory of Acceptance and Use of Technology [UTAUT]), health-related (derived from the Health Belief Model [HBM]), and context-related. A survey was administered among a representative sample of the Dutch population (N = 1865). A hierarchical logistic regression analysis was performed in which the models were compared. Results showed that an integrative model including all three perspectives (i.e., UTAUT, HBM, and context-related variables) resulted in better model fit than any of the other models. All UTAUT variables were associated with CTA adoption in the expected directions. Regarding the HBM, self-efficacy, perceived barriers and perceived benefits were associated with CTA adoption in the expected directions. Several context-related variables, such as fear, were associated with CTA adoption. Our findings demonstrate that extending the UTAUT with preventive health-behavioral factors and contextual factors contribute to better understanding of CTA adoption.