Background The expansion of the coronavirus pandemic and the extraordinary confinement measures imposed by governments have caused an unprecedented intense and rapid contraction of the global economy. In order to revive the economy, people must be able to move safely, which means that governments must be able to quickly detect positive cases and track their potential contacts. Different alternatives have been suggested for carrying out this tracking process, one of which uses a mobile APP which has already been shown to be an effective method in some countries. Objective Use an extended Technology Acceptance Model (TAM) model to investigate whether citizens would be willing to accept and adopt a mobile application that indicates if they have been in contact with people infected with COVID-19. Research Methodology: A survey method was used and the information from 482 of these questionnaires was analyzed using Partial Least Squares-Structural Equation Modelling. Results The results show that the Intention to Use this app would be determined by the Perceived Utility of the app and that any user apprehension about possible loss of privacy would not be a significant handicap. When having to choose between health and privacy, users choose health. Conclusions This study shows that the extended TAM model which was used has a high explanatory power. Users believe that the APP is useful (especially users who studied in higher education), that it is easy to use, and that it is not a cause of concern for privacy. The highest acceptance of the app is found in over 35 years old’s, which is the group that is most aware of the possibility of being affected by COVID-19. The information is unbelievably valuable for developers and governments as users would be willing to use the APP.

中文翻译：

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研究 COVID-19 追踪应用接受度：结合技术接受度模型中的理论

背景 冠状病毒大流行的扩大和各国政府实施的非同寻常的限制措施导致全球经济出现前所未有的剧烈和快速收缩。为了重振经济，人们必须能够安全出行，这意味着政府必须能够快速发现阳性病例并追踪他们的潜在接触者。已经提出了不同的替代方案来执行这个跟踪过程，其中一个使用移动应用程序，这在一些国家已经被证明是一种有效的方法。目标 使用扩展的技术接受模型 (TAM) 模型来调查公民是否愿意接受和采用表明他们是否曾与感染 COVID-19 的人接触过的移动应用程序。研究方法论：使用了一种调查方法，并使用偏最小二乘结构方程模型分析了其中 482 份问卷的信息。结果 结果表明，使用此应用程序的意图将由应用程序的感知效用决定，并且任何用户对可能失去隐私的担忧都不会是一个重大障碍。当不得不在健康和隐私之间做出选择时，用户会选择健康。结论 本研究表明，所使用的扩展 TAM 模型具有很高的解释力。用户认为该APP有用（尤其是接受过高等教育的用户），易于使用，无需担心隐私问题。35 岁以上的人对该应用程序的接受度最高，这是最清楚可能受到 COVID-19 影响的群体。