Title

Predicting psychological distress amid the COVID-19 pandemic by machine learning: Discrimination and coping mechanisms of Korean immigrants in the U.S.

Document Type

Article

Publication Date

9-1-2020

Subject Area

ARRAY(0x55c826457b50)

Abstract

The current study examined the predictive ability of discrimination-related variables, coping mechanisms, and sociodemographic factors on the psychological distress level of Korean immigrants in the U.S. amid the COVID-19 pandemic. Korean immigrants (both foreign-born and U.S.-born) in the U.S. above the age of 18 were invited to participate in an online survey through purposive sampling. In order to verify the variables predicting the level of psychological distress on the final sample from 42 states (n = 790), the Artificial Neural Network (ANN) analysis, which is able to examine complex non-linear interactions among variables, was conducted. The most critical predicting variables in the neural network were a person’s resilience, experiences of everyday discrimination, and perception that racial discrimination toward Asians has increased in the U.S. since the beginning of the COVID-19 pandemic.

Publication Title

International Journal of Environmental Research and Public Health

Volume

17

Issue

17

First Page

1

Last Page

14

Digital Object Identifier (DOI)

10.3390/ijerph17176057

PubMed ID

32825349

ISSN

16617827

E-ISSN

16604601

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