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在大流行期间对公民对联合接触者追踪应用程序功能偏好的调查:联合分析。

Survey of Citizens' Preferences for Combined Contact Tracing App Features During a Pandemic: Conjoint Analysis.

机构信息

National Hospital Organization Tokyo Medical Center, Tokyo, Japan.

Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.

出版信息

JMIR Public Health Surveill. 2024 Nov 14;10:e53340. doi: 10.2196/53340.

Abstract

BACKGROUND

During the COVID-19 pandemic, an increased need for novel solutions such as digital contact tracing apps to mitigate virus spread became apparent. These apps have the potential to enhance public health initiatives through timely contact tracing and infection rate reduction. However, public and academic scrutiny has emerged around the adoption and use of these apps due to privacy concerns.

OBJECTIVE

This study aims to investigate public attitudes and preferences for contact tracing apps, specifically in Japan, using conjoint analysis to examine what specifications the public values most in such apps. By offering a nuanced understanding of the values that citizens prioritize, this study can help balance public health benefits and data privacy standards when designing contact tracing apps and serve as reference data for discussions on legal development and social consensus formation in the future.

METHODS

A cross-sectional, web-based questionnaire survey was conducted to determine how various factors related to the development and integration of infectious disease apps affect the public's intention to use such apps. Individuals were recruited anonymously by a survey company. All respondents were asked to indicate their preferences for a combination of basic attributes and infectious disease app features for conjoint analysis. The respondents were randomly divided into 2 groups: one responded to a scenario where the government was assumed to be the entity dealing with infectious disease apps (ie, the government cluster), and the other responded to a scenario where a commercial company was assumed to be this entity (ie, the business cluster). Samples of 500 respondents from each randomly selected group were used as target data.

RESULTS

For the government cluster, the most important attribute in scenario A was distributor rights (42.557), followed by public benefits (29.458), personal health benefits (22.725), and profit sharing (5.260). For the business cluster, the most important attribute was distributor rights (45.870), followed by public benefits (32.896), personal health benefits (13.994), and profit sharing (7.240). Hence, personal health benefits tend to be more important in encouraging active app use than personal financial benefits. However, the factor that increased motivation for app use the most was the public health benefits of cutting infections by half. Further, concern about the use of personal data collected by the app for any secondary purpose was a negative incentive, which was more significant toward app use compared to the other 3 factors.

CONCLUSIONS

The findings suggest that potential app users are positively motivated not only by personal health benefits but also by contributing to public health. Thus, a combined approach can be taken to increase app use.

摘要

背景

在 COVID-19 大流行期间,对新型解决方案的需求增加,例如数字接触者追踪应用程序,以减轻病毒传播。这些应用程序有可能通过及时的接触者追踪和降低感染率来增强公共卫生计划。然而,由于隐私问题,公众和学术界对这些应用程序的采用和使用提出了质疑。

目的

本研究旨在使用联合分析调查公众对接触者追踪应用程序的态度和偏好,特别是在日本。通过提供对公民优先考虑的价值观的细致理解,本研究可以帮助在设计接触者追踪应用程序时平衡公共卫生利益和数据隐私标准,并为未来的法律发展和社会共识形成提供参考数据。

方法

通过调查公司进行了一项横断面、基于网络的问卷调查,以确定与传染病应用程序的开发和集成相关的各种因素如何影响公众使用此类应用程序的意愿。个人匿名招募。所有受访者都被要求对基本属性和传染病应用程序功能的组合进行偏好选择,以进行联合分析。受访者被随机分为两组:一组对政府被假设为处理传染病应用程序的实体的情况做出反应(即政府集群),另一组对商业公司被假设为该实体的情况做出反应(即商业集群)。每组随机选择 500 名受访者的样本作为目标数据。

结果

对于政府集群,情景 A 中最重要的属性是分销商权利(42.557),其次是公共利益(29.458)、个人健康利益(22.725)和利润分享(5.260)。对于商业集群,最重要的属性是分销商权利(45.870),其次是公共利益(32.896)、个人健康利益(13.994)和利润分享(7.240)。因此,与个人财务利益相比,个人健康利益更能促使人们积极使用应用程序。然而,最能增加应用程序使用动机的因素是将感染减少一半的公共卫生效益。此外,对应用程序收集的个人数据用于任何次要目的的担忧是一个消极的激励因素,与其他 3 个因素相比,该因素对应用程序使用的影响更为显著。

结论

研究结果表明,潜在的应用程序用户不仅受到个人健康利益的积极激励,还受到为公共卫生做出贡献的激励。因此,可以采取综合方法来增加应用程序的使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba2b/11605258/b3a3b013fe4b/publichealth_v10i1e53340_fig1.jpg

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