1. Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S
- Author
-
Shinwoo Choi, Yong Je Kim, Hyejoon Park, and Joo Young Hong
- Subjects
Adult ,Male ,Artificial Neural Network ,Health, Toxicology and Mutagenesis ,media_common.quotation_subject ,Pneumonia, Viral ,Immigration ,Emigrants and Immigrants ,lcsh:Medicine ,Sample (statistics) ,Racism ,Article ,Machine Learning ,Nonprobability sampling ,Betacoronavirus ,03 medical and health sciences ,0302 clinical medicine ,Perception ,Adaptation, Psychological ,Republic of Korea ,Pandemic ,Humans ,0501 psychology and cognitive sciences ,030212 general & internal medicine ,Pandemics ,racism ,media_common ,SARS-CoV-2 ,lcsh:R ,05 social sciences ,Public Health, Environmental and Occupational Health ,COVID-19 ,Middle Aged ,Korean immigrants ,Mental health ,United States ,Female ,Psychological resilience ,Coronavirus Infections ,Psychology ,Stress, Psychological ,mental health ,050104 developmental & child psychology ,Clinical psychology - 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.
- Published
- 2020