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

Jansen-Kosterink, S. M.; Hurmuz, M.; den Ouden, M.; van Velsen, L.

Introduction: eHealth applications have been recognized as a valuable tool to reduce COVID-19s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing. Methods: Next to the demographics, the online survey contained questions focussing 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 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. Discussion: 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.