Does Health Vulnerability Predict Voting for Right-Wing Populist Parties in Europe?

IF 1.7 4区 心理学 Q2 PSYCHOLOGY, MULTIDISCIPLINARY
Jan-Erik Lönnqvist, V. Ilmarinen
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引用次数: 1

Abstract

Abstract: Introduction: A recent article by Kavanagh et al. (2021) in American Political Science Review suggested that health vulnerability predicts voting patterns for the populist far-right. Aim: We sought to distinguish socioculturally conservative from antielite voting, expecting health vulnerability to predict only the former. Methods: We combined data from the European Social Survey (round 7) with the Chapel Hill Expert Survey (2014). We preregistered several other hypotheses regarding associations between health and voting and predetermined the smallest effect size of interest (SESOI: r = .05). Results: Health vulnerability did not predict socioculturally conservative voting, and the results for antielite voting were mixed. To investigate why our result differed from Kavanagh et al.’s, we reran their analysis employing covariate specification curve analyses. The statistical significance and the direction of the association between health vulnerability and voting depended on which covariates were included. Across 1,000 models with randomly drawn covariate specifications, 59.6% showed a positive, 29.8% a zero, and 10.6% a negative association between health vulnerability and voting for far-right populist parties. However, all effect sizes were more consistently smaller than our predetermined SESOI. Conclusions: Our study illustrates the necessity of causally justifying and preregistering all covariates and predetermining an SESOI.
健康脆弱性能否预测欧洲右翼民粹主义政党的投票?
摘要:导言:Kavanagh 等人(2021 年)最近在《美国政治科学评论》上发表的一篇文章指出,健康脆弱性可预测民粹主义极右翼的投票模式。目的:我们试图区分社会文化保守型投票和反精英型投票,期望健康脆弱性只预测前者。研究方法我们将欧洲社会调查(第 7 轮)数据与教堂山专家调查(2014 年)数据相结合。我们预先登记了有关健康与投票之间关联的其他几个假设,并预先确定了最小的相关效应大小(SESOI:r = .05)。结果健康脆弱性并不能预测社会文化保守型投票,而反精英型投票的结果则好坏参半。为了研究为什么我们的结果与 Kavanagh 等人的结果不同,我们采用协变量规格曲线分析重新进行了分析。健康脆弱性与投票之间关联的统计意义和方向取决于纳入哪些协变量。在随机抽取协变量规格的 1000 个模型中,59.6% 的模型显示健康脆弱性与极右民粹主义政党投票之间存在正相关,29.8% 的模型显示零相关,10.6% 的模型显示负相关。然而,所有效应大小均小于我们预先设定的 SESOI。结论:我们的研究表明,有必要对所有协变量进行因果论证和预先登记,并预先确定 SESOI。
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来源期刊
European Journal of Psychology Open
European Journal of Psychology Open PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
2.20
自引率
8.30%
发文量
9
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