Jansen-Kosterink Stephanie, Hurmuz Marian, den Ouden Marjolein, van Velsen Lex
eHealth Department, Roessingh Research and Development, Enschede, Netherlands.
Biomedical Signals and Systems Group, University of Twente, Enschede, Netherlands.
JMIR Form Res. 2021 Dec 20;5(12):e28416. doi: 10.2196/28416.
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.
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.
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.
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.
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.
电子健康应用程序已被视为降低新冠病毒有效繁殖数的宝贵工具。决定新冠病毒应用程序接受度的因素尚不清楚。隐私问题是个例外。
本文旨在通过对荷兰公民进行在线调查，确定（1）一款用于新冠病毒症状识别和监测的移动应用程序以及（2）一款用于接触者追踪的移动应用程序的接受度的前因。
除了人口统计学信息外，在线调查还包含了关注感知健康、对新冠病毒的恐惧以及使用意愿的问题。我们通过社交媒体帖子和个人关系进行滚雪球抽样。为了确定这两款移动应用程序接受度模型的前因，我们进行了多元线性回归分析。
共有238名荷兰成年人完成了调查；59.2%（n = 141）的受访者为女性，平均年龄为45.6岁（标准差17.4岁）。对于症状应用程序，最终模型包括预测因素年龄、对技术的态度以及对新冠病毒的恐惧。该模型的r2为0.141。追踪应用程序的最终模型包括相同的预测因素，r2为0.156。使用这两款移动应用程序的主要原因是控制新冠病毒的传播。对隐私的担忧被提及为不使用移动应用程序的主要原因。
年龄、对技术的态度以及对新冠病毒的恐惧是接受用于症状识别和监测以及接触者追踪的新冠病毒移动应用程序的重要预测因素。在开发和实施这些移动应用程序时应考虑这些预测因素，以确保获得接受度。
