Fear and anxiety about COVID-19 have swept across the globe. Understanding the factors that contribute to increased emotional distress regarding the pandemic is paramount—especially as experts warn about rising cases. Despite large amounts of data, it remains unclear which variables are essential for predicting who will be most affected by the distress of future waves. We collected cross-sectional data on a multitude of socio-psychological variables from a sample of 948 United States participants during the early stages of the pandemic. Using a cross-validated hybrid stepwise procedure, we developed a descriptive model of COVID-19 emotional distress. Results reveal that trait anxiety, gender, and social (but not government) media consumption were the strongest predictors of increasing emotional distress. In contrast, commonly associated variables, such as age and political ideology, exhibited much less unique explanatory power. Together, these results can help public health officials identify which populations will be especially vulnerable to experiencing COVID-19-related emotional distress.

对 COVID-19 的恐惧和焦虑席卷全球。了解导致大流行情绪困扰加剧的因素至关重要——尤其是在专家警告病例不断增加的情况下。尽管有大量数据，但仍不清楚哪些变量对于预测哪些人将受未来浪潮困扰的影响最大。在大流行的早期阶段，我们从 948 名美国参与者的样本中收集了大量社会心理变量的横断面数据。使用交叉验证的混合逐步程序，我们开发了 COVID-19 情绪困扰的描述性模型。结果显示，特质焦虑、性别和社会（但不是政府）媒体消费是情绪困扰加剧的最强预测因素。相比之下，通常相关的变量，诸如年龄和政治意识形态等，表现出的独特解释力要小得多。总之，这些结果可以帮助公共卫生官员确定哪些人群特别容易遭受与 COVID-19 相关的情绪困扰。