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Property Damage and Exposure to Other People in Distress Differentially Predict Prosocial Behavior After a Natural Disaster.财产损失和对他人困境的暴露程度对自然灾害后的亲社会行为有不同的预测作用。
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生态威胁与文化体系:流行病和自然灾害无法预测集体主义。

Ecological Threats and Cultural Systems : Epidemics and Natural Disasters Do Not Predict Collectivism.

作者信息

Shapouri Soheil, Rafiee Yasaman

机构信息

Department of Psychology, Lehigh University, 17 Memorial Dr. E, Bethlehem, PA, 18015, USA.

Department of Psychological Sciences & Health, University of Strathclyde, Glasgow, UK.

出版信息

Hum Nat. 2024 Dec;35(4):382-396. doi: 10.1007/s12110-024-09480-8. Epub 2024 Nov 28.

DOI:10.1007/s12110-024-09480-8
PMID:39607607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11835910/
Abstract

Considering the role of human interactions in infectious disease outbreaks and cooperation in mitigating natural disasters consequences, ecological threats to human survival have been among proposed drivers of collectivism. Utilizing established and novel measures of parasite stress and natural disasters, we investigated their association with collectivism in a large sample of countries (N = 188). Linear mixed-effect models indicated that after controlling for national wealth, neither natural disasters nor infectious disease can predict collectivism scores. Null results were consistent across different measures of threats, suggesting that previous findings can be attributed to small, non-representative samples of cultures. When universal patterns are a major concern, drawing conclusions based on small, nonrepresentative subsets of cultures risks promoting unreliable findings. Future cross-cultural research will benefit from data-driven exploratory methods to uncover factors previously unexamined in the theory-driven studies of collectivism.

摘要

考虑到人际互动在传染病爆发中的作用以及在减轻自然灾害后果方面的合作,对人类生存的生态威胁一直是集体主义的潜在驱动因素之一。我们利用已有的和新的寄生虫压力及自然灾害衡量指标,在大量国家样本(N = 188)中研究了它们与集体主义的关联。线性混合效应模型表明,在控制国家财富因素后,自然灾害和传染病都无法预测集体主义得分。在不同的威胁衡量指标中均得到了零结果,这表明先前的研究结果可能归因于规模小且缺乏代表性的文化样本。当普遍模式成为主要关注点时,基于规模小且缺乏代表性的文化子集得出结论,可能会导致不可靠的研究结果。未来的跨文化研究将受益于数据驱动的探索性方法,以揭示在集体主义的理论驱动研究中以前未被考察的因素。