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Explaining citizens' resistance to use digital contact tracing apps: A mixed-methods study.

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Public distrust, privacy concerns, and usability issues hinder adoption of digital contact tracing (DCT) apps. Understanding these barriers is crucial for effective public health strategies during pandemics.

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Area of Science:

  • Public Health
  • Information Systems
  • Behavioral Science

Background:

  • Digital contact tracing (DCT) apps are key for pandemic exit strategies.
  • Low public acceptance of DCT apps indicates significant user resistance.
  • Understanding resistance determinants is vital for DCT app success.

Purpose of the Study:

  • To explore factors influencing citizens' resistance to using DCT apps.
  • To examine the consequences of resistance on DCT app adoption.
  • To identify strategies for improving DCT app implementation.

Main Methods:

  • Sequential mixed-methods approach: qualitative interviews followed by quantitative surveys.
  • Qualitative stage: 24 Indian smartphone users who opted out of DCT apps.
  • Quantitative stage: Survey of 194 non-adopters using an integrated model of innovation resistance and distrust theories.

Main Results:

  • Distrust, value barrier, information privacy concerns, and usage barrier significantly predicted resistance to DCT apps.
  • Resistance to DCT apps negatively impacted intention to use.
  • Distrust acted as a key mediator between innovation barriers and user resistance.

Conclusions:

  • Addressing distrust and specific barriers is essential for increasing DCT app adoption.
  • Insights can inform policymakers and developers in designing effective public health interventions.
  • Strategies are needed to overcome user resistance for future disease outbreaks.