How Does COVID-19 Differ from the Flu/Cold? A Study of Multilevel Information Seeking among Korean Immigrant Women in the U.S.

Objectives: The purpose of this study was to understand COVID-19 information seeking among Korean immigrant women in comparison to their flu/cold information seeking. In particular, the study aimed to examine: (1) the levels of information sought regarding both COVID-19 and the flu/cold, and (2) the content of information discussed at each level. Methods: We analyzed the posts on Missy USA--one of the largest Korean online communities for married Korean immigrant women. Two sets of data, one for COVID-19 (n=726) and the other for the flu/cold (n=50), were analyzed with codes at different levels, which were adapted from the social-ecological model. Results: Applying the social-ecological model, we found that about 80% of information regarding the flu/cold and about 60% of COVID-19 information was concentrated at individual, interpersonal, and organizational levels. Information seeking at the community level was more frequent for COVID-19 than for the flu/cold. Conclusions: Our finding that Korean immigrant women primarily sought information regarding COVID-19 serves as a theoretical contribution at the transnational level, which might be relevant for immigrant women during the unprecedented COVID-19 pandemic.

Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S.

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.