Identifying Predictors of Psychological Distress During COVID-19: A Machine Learning Approach.

ABSTRACT: Scientific understanding about the psychological impact of the COVID-19 global pandemic is in its nascent stage. Prior research suggests that demographic factors, such as gender and age, are associated with greater distress during a global health crisis. Less is known about how emotion regulation impacts levels of distress during a pandemic. The present study aimed to identify predictors of psychological distress during the COVID-19 pandemic. Participants (N = 2,787) provided demographics, history of adverse childhood experiences, current coping strategies (use of implicit and explicit emotion regulation), and current psychological distress. The overall prevalence of clinical levels of anxiety, depression, and post-traumatic stress was higher than the prevalence outside a pandemic a

SUBMITTER: Prout TA 

PROVIDER: S-EPMC7682196 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature