Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S.
Int J Environ Res Public Health
; 17(17)2020 08 20.
Article
in English
| MEDLINE | ID: covidwho-724202
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Stress, Psychological
/
Adaptation, Psychological
/
Coronavirus Infections
/
Emigrants and Immigrants
/
Machine Learning
/
Betacoronavirus
Type of study:
Observational study
/
Prognostic study
/
Qualitative research
Limits:
Adult
/
Female
/
Humans
/
Male
/
Middle aged
Country/Region as subject:
North America
/
Asia
Language:
English
Year:
2020
Document Type:
Article
Affiliation country:
Ijerph17176057
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