影响COVID-19接触者追踪app下载意愿的因素:说服性设计和智能手机使用体验的调节作用

Kiemute Oyibo, Plinio Pelegrini Morita
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引用次数: 3

摘要

COVID-19大流行的高潮是全球推出接触者追踪应用程序,也称为暴露通知应用程序(ENAs),以遏制病毒的传播。ENAs会通知用户可能发生感染,并建议用户采取自我隔离和COVID-19检测等健康措施。虽然已经有一些关于影响ENA采用的因素的研究,但很少有人关注劝导式设计和智能手机使用体验的调节作用。本文旨在利用加拿大政府的官方应用程序“COVID Alert”和加拿大非收养人口(n = 133)作为案例研究来弥合这一差距。在我们调查的七个因素中,感知信任(β = 0.29, p < 0.01)和感知享受(β = 0.21, p < 0.05)被证明是整个模型中非采纳者下载应用意愿的唯一显著预测因素。劝导式设计和智能手机使用体验都缓和了模型中的一些关系。例如,虽然感知享受在说服设计子模型(β = 0.34, p < 0.01)和低经验子模型(β = 0.36, p < 0.001)中显著,但在控制设计和高经验子模型中却不显著。此外,感知享受(β = 0.36, p < 0.001)和隐私关注(β = -0.46, p < 0.05)分别是低体验和高体验子模型中最强的预测因子。这些结果表明,为了提高ENAs的下载量,赞助商应该在营销活动和应用商店描述中实施和突出能够培养信任的应用功能。尤其要突出高经验群体的隐私保护特征和低经验群体的享乐属性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Factors Influencing the Willingness to Download COVID-19 Contact Tracing Apps: The Moderating Effect of Persuasive Design and Smartphone Usage Experience
The COVID-19 pandemic culminated in the global roll-out of contact tracing apps, also known as exposure notification apps (ENAs), to contain the spread of the virus. ENAs notify users about a possible infection and advises them to take certain health measures such as self-isolation and COVID-19 test. While some work has been done on the factors that influence ENA adoption, little attention has been paid to the moderating effect of persuasive design and smartphone usage experience. This paper sets out to bridge this gap using the Government of Canada’s official app “COVID Alert” and Canadian non-adopter population (n = 133) as a case study. Of the seven factors we investigated, perceived trust (β = 0.29, p < 0.01) and perceived enjoyment (β = 0.21, p < 0.05) turned out to be the only significant predictors of non-adopters’ willingness to download the app in the overall model. Both persuasive design and smartphone usage experience moderated some of the relationships in the model. For example, while perceived enjoyment is significant in the persuasive design submodel (β = 0.34, p < 0.01) and low-experience submodel (β = 0.36, p < 0.001), it is not in the control design and high-experience submodels. Moreover, perceived enjoyment (β = 0.36, p < 0.001) and privacy concern (β = -0.46, p < 0.05) turned out to be the strongest predictors in the low-experience and high-experience submodels, respectively. These results indicate that, to improve the download of ENAs, sponsors should implement and highlight app features that foster trust in marketing campaigns and app-store descriptions. Particularly, they should highlight their privacy-protection feature and hedonic attribute among the high-experience and low-experience groups, respectively.
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