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

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  • van der Waal, Nadine Elisa
  • de Wit, Jan
  • Bol, Nadine
  • Ebbers, Wolfgang
  • Hooft, Lotty
  • Metting, Esther
  • van der Laan, Laura Nynke

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.

Suggested Citation

  • van der Waal, Nadine Elisa & de Wit, Jan & Bol, Nadine & Ebbers, Wolfgang & Hooft, Lotty & Metting, Esther & van der Laan, Laura Nynke, 2022. "Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors," Technology in Society, Elsevier, vol. 71(C).
    • Handle: RePEc:eee:teinso:v:71:y:2022:i:c:s0160791x22002421
    DOI: 10.1016/j.techsoc.2022.102101
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    1. Maras, Marie-Helen & Miranda, Michelle D., 2023. "Augmented body surveillance: Human microchip implantations and the omnipresent threat of function creep," Technology in Society, Elsevier, vol. 74(C).

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