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Group-level human values estimated with web search data and archival data explain the geographic variation in COVID-19 severity in the United States
Psychology & Health ( IF 3.358 ) Pub Date : 2021-07-21 , DOI: 10.1080/08870446.2021.1952582
Mac Zewei Ma 1
Affiliation  

Abstract

Objectives

Personal Focus values (PF = Openness to change values + Self-enhancement values) motivate self-centred behaviours, and Social Focus values (SF = Conservation values + Self-transcendence values) promote self-sacrificial counterparts. This research investigated how a state-level PF-SF value-continuum would explain the geographic variation in COVID-19 severity in the United States.

Design

This research estimated state-level values by Google search data (from 2004 to 2019) on value-related words (e.g. family for conservation values) (Study 1a) and archival indicators (e.g. gun ownership rate for security values) (Study 1b). COVID-19 severity was measured by shorter time delay of first documented cases, shorter overall doubling times, higher reproductive ratio and higher case fatality ratio. Hierarchical and multilevel analyses examined how state-level values would predict COVID-19 severity across U.S. states (Studies 1a and 1b) and 3,135 counties (Study 2).

Results

State-level analyses accounting for spatial autocorrelation and covariates (e.g. COVID-19 testing rate, airport traffic, personality, etc.) revealed that the PF-SF value-continuums measured with different methods positively and significantly predicted COVID-19 severity, and the effects of state-level values on county-level COVID-19 severity were significant when county- and state-level covariates were controlled.

Conclusion

Social focus values may mitigate the devastating effect of COVID-19 in the United States.



中文翻译:

用网络搜索数据和档案数据估计的群体层面的人类价值解释了美国 COVID-19 严重程度的地理差异

摘要

目标

个人焦点价值观(PF = 开放改变价值观 + 自我提升价值观)激发以自我为中心的行为,而社会焦点价值观(SF = 保守价值观 + 自我超越价值观)促进自我牺牲的行为。这项研究调查了州级 PF-SF 值连续体将如何解释美国 COVID-19 严重程度的地理差异。

设计

本研究通过谷歌搜索数据(从 2004 年到 2019 年)对价值相关词(例如保护价值的家庭)(研究 1a)和档案指标(例如安全价值的枪支拥有率)(研究 1b)估计州级价值。COVID-19 的严重程度是通过首次记录病例的较短时间延迟、较短的总体倍增时间、较高的繁殖率和较高的病死率来衡量的。分层和多级分析检查了州级值如何预测美国各州(研究 1a 和 1b)和 3,135 个县(研究 2)的 COVID-19 严重程度。

结果

考虑到空间自相关和协变量(例如 COVID-19 检测率、机场交通量、个性等)的州级分析表明,用不同方法测量的 PF-SF 值连续体积极且显着地预测了 COVID-19 的严重程度,并且当控制县级和州级协变量时,州级值对县级 COVID-19 严重程度的影响显着。

结论

社会焦点价值观可能会减轻 COVID-19 在美国的破坏性影响。

更新日期:2021-07-21
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