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
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
Citation Information
Choi, S., Hong, J. Y., Kim, Y. J., & Park, H. (2020). Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S. International journal of environmental research and public health, 17(17), 6057. https://doi.org/10.3390/ijerph17176057