背景:在COVID-19大流行期间,接触追踪应用程序(CTA)的采用有限.弱势群体的收养率特别低(例如,社会经济地位低或年龄较大的人),而这部分人群往往较少获得信息和通信技术,更容易受到COVID-19病毒的攻击。
目的:本研究旨在了解CTA采用滞后的原因,以促进采用并找到使公共卫生应用程序更易于访问并减少健康差异的适应症。
方法:因为发现一些心理社会变量可以预测CTA的采用,来自荷兰CTACoronaMelder(CM)的数据使用聚类分析进行分析。我们研究了是否可以基于6种心理社会感知形成亚组(即,信任政府,关于个人数据的信念,社会规范,感知到的个人和社会效益,风险认知,和自我效能感)有关CM的(非)用户,以检查这些聚类之间的差异以及哪些因素可以预测使用CTA的意图和CTA的采用。基于由2020年10月/11月(N=1900)和2020年12月(N=1594)的2个时间框架组成的纵向数据,检查了使用和采用CM的意图。这些集群是由人口统计学描述的,意图,并据此采用。此外,我们检查了发现的聚类和变量是否会影响CTA的采用,比如健康素养,预测CM应用程序的使用意图和采用。
结果:基于第1波数据的最终5簇解决方案包含显着不同的簇。在第一波中,集群中具有积极看法的受访者(即,采用CTA的有益心理社会变量)关于CM应用程序的年龄较大(P<.001),具有较高的教育水平(P<.001),并且具有更高的意向(P<.001)和采用率(P<.001)比具有负面认知的集群。在第二波中,集群预测了使用和采用的意图。在第2波中使用CM的意图也是使用第1波中测量的采用率预测的(P<.001,β=-2.904)。第2波中的收养是按年龄预测的(P=0.022,exp(B)=1.171),在第1波中使用的意图(P<.001,exp(B)=1.770),并在波1中采用(P<.001,exp(B)=0.043)。
结论:5个集群,以及年龄和以前的行为,预测CM应用程序的使用意图和采用。通过可区分的簇,深入了解CM(非)意图者和(非)采用者的概况。
背景:OSF注册中心osf.io/cq742;https://osf.io/cq742。
BACKGROUND: During the COVID-19 pandemic, there was limited adoption of contact-tracing apps (CTAs). Adoption was particularly low among vulnerable people (eg, people with a low socioeconomic position or of older age), while this part of the population tends to have lesser access to information and communication technology and is more vulnerable to the COVID-19 virus.
OBJECTIVE: This study aims to understand the cause of this lagged adoption of CTAs in order to facilitate adoption and find indications to make public health apps more accessible and reduce health disparities.
METHODS: Because several psychosocial variables were found to be predictive of CTA adoption, data from the Dutch CTA CoronaMelder (CM) were analyzed using cluster analysis. We examined whether subgroups could be formed based on 6 psychosocial perceptions (ie, trust in the government, beliefs about personal data, social norms, perceived personal and societal benefits, risk perceptions, and self-efficacy) of (non)users concerning CM in order to examine how these clusters differ from each other and what factors are predictive of the intention to use a CTA and the adoption of a CTA. The intention to use and the adoption of CM were examined based on longitudinal data consisting of 2 time frames in October/November 2020 (N=1900) and December 2020 (N=1594). The clusters were described by demographics, intention, and adoption accordingly. Moreover, we examined whether the clusters and the variables that were found to influence the adoption of CTAs, such as health literacy, were predictive of the intention to use and the adoption of the CM app.
RESULTS: The final 5-cluster solution based on the data of wave 1 contained significantly different clusters. In wave 1, respondents in the clusters with positive perceptions (ie, beneficial psychosocial variables for adoption of a CTA) about the CM app were older (P<.001), had a higher education level (P<.001), and had higher intention (P<.001) and adoption (P<.001) rates than those in the clusters with negative perceptions. In wave 2, the intention to use and adoption were predicted by the clusters. The intention to use CM in wave 2 was also predicted using the adoption measured in wave 1 (P<.001, β=-2.904). Adoption in wave 2 was predicted by age (P=.022, exp(B)=1.171), the intention to use in wave 1 (P<.001, exp(B)=1.770), and adoption in wave 1 (P<.001, exp(B)=0.043).
CONCLUSIONS: The 5 clusters, as well as age and previous behavior, were predictive of the intention to use and the adoption of the CM app. Through the distinguishable clusters, insight was gained into the profiles of CM (non)intenders and (non)adopters.
BACKGROUND: OSF Registries osf.io/cq742; https://osf.io/cq742.