Oyibo Kiemute, Sahu Kirti Sundar, Oetomo Arlene, Morita Plinio Pelegrini
School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada.
Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada.
JMIR Res Protoc. 2021 Jun 1;10(6):e28961. doi: 10.2196/28961.
Following the onset of the COVID-19 pandemic, digital contact tracing apps have become prevalent worldwide in a coordinated effort to curb the spread of COVID-19. However, their uptake has been low and slow due to privacy concerns, the lack of trust and motivational affordances, and their minimalist design.
The objective of this article is to present a protocol for a systematic review of the main factors, including facilitators and barriers, that influence the adoption of contact tracing apps.
We searched seven databases, namely, Scopus, CINAHL, PubMed (MEDLINE), IEEE Xplore Digital Library, Association for Computing Machinery (ACM) Digital Library, Web of Science, and Google Scholar, for relevant publications between October 30, 2020, and January 31, 2021. Three authors were involved in removing duplicates, screening, and selection of relevant articles according to the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-analysis Protocols) guidelines.
Altogether, we retrieved 777 articles from the seven databases. As of May 14, 2021, we have completed the screening process and arrived at 13 eligible articles to be included in the systematic review. We hope to elicit, summarize, and report the main findings in the systematic review article by the end of August 2021. We expect to uncover facilitators and barriers related to app utility, data security, ease of use, and persuasive design that are deemed important to adoption of contact tracing apps.
The findings of the systematic review will help researchers to uncover the gaps in the adoption of contact tracing apps, and decision makers and designers to focus on the principal adoption factors necessary to create better and more effective contact tracing apps.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28961.
在新型冠状病毒肺炎疫情爆发后，数字接触者追踪应用程序在全球范围内广泛使用，以协同努力遏制新型冠状病毒肺炎的传播。然而，由于隐私担忧、缺乏信任和激励因素以及其极简设计，这些应用程序的采用率一直很低且进展缓慢。
本文的目的是提出一项系统评价方案，以探讨影响接触者追踪应用程序采用的主要因素，包括促进因素和障碍。
我们在七个数据库中进行了搜索，分别是Scopus、CINAHL、PubMed（MEDLINE）、IEEE Xplore数字图书馆、美国计算机协会（ACM）数字图书馆、科学引文索引和谷歌学术，以查找2020年10月30日至2021年1月31日期间的相关出版物。三位作者根据系统评价和Meta分析方案的首选报告项目（PRISMA-P）指南，参与了去除重复项、筛选和选择相关文章的工作。
我们从这七个数据库中总共检索到777篇文章。截至2021年5月14日，我们已经完成了筛选过程，确定了13篇符合条件的文章纳入系统评价。我们希望在2021年8月底之前，在系统评价文章中引出、总结并报告主要发现。我们期望发现与应用程序实用性、数据安全性、易用性和劝导性设计相关的促进因素和障碍，这些因素被认为对接触者追踪应用程序的采用很重要。
系统评价的结果将有助于研究人员发现接触者追踪应用程序采用方面的差距，并帮助决策者和设计师关注创建更好、更有效的接触者追踪应用程序所需的主要采用因素。
国际注册报告识别号（IRRID）：DERR1-10.2196/28961。
