Identifying Predictors of Psychological Distress During COVID-19: A Machine Learning Approach.
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ABSTRACT:
SUBMITTER: Prout TA
PROVIDER: S-EPMC7682196 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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Identifying Predictors of Psychological Distress During COVID-19: A Machine Learning Approach.
Prout Tracy A TA Zilcha-Mano Sigal S Aafjes-van Doorn Katie K Békés Vera V Christman-Cohen Isabelle I Whistler Kathryn K Kui Thomas T Di Giuseppe Mariagrazia M
Frontiers in psychology 20201105
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 (<i>N</i> = 2,787) provided demographics ...[more]
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