Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens. (Preprint)

BACKGROUND eHealth applications have been recognized as a valuable tool to reduce COVID-19's effective reproduction number. The factors that determine acceptance of COVID-19 apps are unknown. The exception here is privacy. OBJECTIVE The aim of this article was to identify antecedents of acceptance of 1) a mobile application for COVID-19 symptom recognition and monitoring, and 2) a mobile application for contact tracing, both by means of an online survey among Dutch citizens. METHODS Next to the demographics, the online survey contained questions focusing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of the model for acceptance of the two mobile applications we conducted multiple linear regression analyses. RESULTS In total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD±17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an r2 of 0.141. The final model for the tracing app included the same predictors and had an r2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications. CONCLUSIONS Age, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance. CLINICALTRIAL