Harborth David, Pape Sebastian
Goethe University Frankfurt am Main, Theodor-W.-Adorno-Platz 4, 60326 Frankfurt am Main, Germany.
Comput Secur. 2023 Sep;132:103338. doi: 10.1016/j.cose.2023.103338. Epub 2023 Jun 14.
The SARS-CoV-2 pandemic is a pressing societal issue today. The German government promotes a contract tracing app named Corona-Warn-App (CWA), aiming to change citizens' health behaviors during the pandemic by raising awareness about potential infections and enable infection chain tracking. Technical implementations, citizens' perceptions, and public debates around apps differ between countries, e. g., in Germany there has been a huge discussion on potential privacy issues of the app. Thus, we analyze effects of privacy concerns regarding the CWA, perceived CWA benefits, and trust in the German healthcare system to answer why citizens use the CWA. In our initial conference publication at , we used a sample with 1752 actual users and non-users of the CWA and and support for the privacy calculus theory, i. e., individuals weigh privacy concerns and benefits in their use decision. Thus, citizens privacy perceptions about health technologies (e. g., shaped by public debates) are crucial as they can hinder adoption and negatively affect future fights against pandemics. In this special issue, we adapt our previous work by conducting a second survey 10 months after our initial study with the same pool of participants (830 participants from the first study participated in the second survey). The goal of this longitudinal study is to assess changes in the perceptions of users and non-users over time and to evaluate the influence of the significantly lower hospitalization and death rates on the use behavior which we could observe during the second survey. Our results show that the privacy calculus is relatively stable over time. The only relationship which significantly changes over time is the effect of privacy concerns on the use behavior which significantly decreases over time, i. e., privacy concerns have a lower negative effect one the CWA use indicating that it did not play such an important role in the use decision at a later point in time in the pandemic. We contribute to the literature by introducing one of the rare longitudinal analyses in the literature focusing on the privacy calculus and changes over time in the relevant constructs as well as the relationships between the calculus constructs and target variables (in our case use behavior of a contact tracing app). We can see that the explanatory power of the privacy calculus model is relatively stable over time even if strong externalities might affect individual perceptions related to the model.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）大流行是当今一个紧迫的社会问题。德国政府推广一款名为“新冠预警应用程序”（Corona-Warn-App，CWA）的接触者追踪应用程序，旨在通过提高对潜在感染的认识来改变公民在大流行期间的健康行为，并实现感染链追踪。不同国家在应用程序的技术实施、公民认知以及围绕应用程序的公众辩论方面存在差异，例如，在德国，围绕该应用程序潜在的隐私问题进行了大量讨论。因此，我们分析了对CWA的隐私担忧、感知到的CWA益处以及对德国医疗保健系统的信任所产生的影响，以回答公民使用CWA的原因。在我们最初在会议上发表的论文中，我们使用了一个包含1752名CWA实际用户和非用户的样本，并支持隐私计算理论，即个人在使用决策中权衡隐私担忧和益处。因此，公民对健康技术的隐私认知（例如，由公众辩论形成）至关重要，因为它们可能会阻碍采用，并对未来抗击大流行产生负面影响。在本期特刊中，我们对之前的研究进行了调整，在最初研究10个月后，对同一批参与者（来自第一项研究的830名参与者参与了第二项调查）进行了第二次调查。这项纵向研究的目的是评估用户和非用户的认知随时间的变化，并评估在第二次调查期间我们能够观察到的显著降低的住院率和死亡率对使用行为的影响。我们的结果表明，隐私计算随时间相对稳定。随着时间推移唯一显著变化的关系是隐私担忧对使用行为的影响，这种影响随着时间显著下降，即隐私担忧对CWA使用的负面影响较小，表明在大流行后期的使用决策中它没有起到如此重要的作用。我们通过引入文献中罕见的纵向分析来为该领域做出贡献，该分析聚焦于隐私计算以及相关构念随时间的变化，以及计算构念与目标变量（在我们的案例中是接触者追踪应用程序的使用行为）之间的关系。我们可以看到，即使强大的外部因素可能会影响与该模型相关的个人认知，但隐私计算模型的解释力随时间相对稳定。
