Open AccessPredictors to Use Mobile Apps for Monitoring COVID-19 Symptoms and Contact Tracing: Survey Among Dutch Citizens
Author(s) -
Stephanie Jansen-Kosterink,
Marian Z.M. Hurmuz,
Marjolein E.M. den Ouden,
Lex van Velsen
Publication year - 2021
Publication title -
jmir formative research
Language(s) - English
Resource type - Journals
ISSN - 2561-326X
DOI - 10.2196/28416
Subject(s) - snowball sampling , covid-19 , contact tracing , internet privacy , psychology , mhealth , demographics , social media , mobile apps , smartphone app , social distance , computer assisted web interviewing , applied psychology , medicine , computer science , demography , business , world wide web , psychological intervention , psychiatry , sociology , disease , pathology , marketing , infectious disease (medical specialty)
Background eHealth apps have been recognized as a valuable tool to reduce COVID-19’s effective reproduction number. The factors that determine the acceptance of COVID-19 apps remain unknown. The exception here is privacy. Objective The aim of this article was to identify antecedents of acceptance of (1) a mobile app for COVID-19 symptom recognition and monitoring and (2) a mobile app 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 2 mobile apps, we conducted multiple linear regression analyses. Results In total, 238 Dutch adults completed the survey; 59.2% (n=141) of the responders were female and the average age was 45.6 years (SD 17.4 years). For the symptom app, the final model included the predictors age, attitude toward 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 apps was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason to not use the mobile apps. Conclusions Age, attitude toward technology, and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile apps for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile apps to secure acceptance.