PURPOSE: The goal of this study was to examine the association between perceived racial discrimination and substance use and the potential moderating effect of perceived parental affection between the two variables. METHODS: A total of 101 Korean American adolescents participated in this cross-sectional study utilized an online survey. Descriptive statistics were used to describe for means and frequencies and the patterns of substance use. Logistic regression analysis was also used to examine the association between perceived discrimination and substance use. RESULTS: Ninety percent of the participants reported perceiving racial discrimination, and 21% had used at least one kind of substance in the month prior to taking the survey. The most frequently used substance was alcohol, followed by marijuana and tobacco products. Logistic regression analysis revealed a link between perceived racial discrimination and substance use (OR = 1.74, 95% CI = 1.01, 3.00). However, parental affection did not moderate between racial discrimination and substance use. CONCLUSION: These findings suggest that perceived racial discrimination is positively associated with substance use among Korean American adolescents, and health care providers, counselors, and school nurses should screen for discrimination-related stress and substance use in this population.
Adolescent* ; Asian Americans* ; Cannabis ; Counseling ; Cross-Sectional Studies ; Discrimination (Psychology) ; Health Personnel ; Humans ; Logistic Models ; Parents ; Racism* ; Tobacco Products

Objectives: This study aimed to examine the correlations between the regional characteristics of counties in Gangwon Province, Republic of Korea and the ratio of intracounty to extracounty sources of coronavirus disease 2019 (COVID-19) infection. Methods: The region of the infectious contact was analysed for each COVID-19 case reported in Gangwon Province between February 22, 2020 and February 7, 2022. The population, population density, area, the proportion of urban residents, the proportion of older adults (>65 years), financial independence, and the number of adjacent counties were assessed for each of the 18 counties in Gangwon Province. Correlation coefficients between regional characteristics and the ratio of intracounty to extracounty infections were calculated. Results: In total, 19,645 cases were included in this study. The population, population density, proportion of older adults, and proportion of urban residents were significantly correlated with the ratio of intracounty to extracounty infections. A stratified analysis with an age cut-point of 65 years showed that the proportion of older adults had a significant negative correlation with the ratio of intracounty to extracounty infections. In other words, the proportions of extracounty infections were higher in countries with higher proportions of older adults. Conclusion Regions with ageing populations should carefully observe trends in infectious disease outbreaks in other regions to prevent possible transmission.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.

This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first hackathon of Genomics & Informatics Annotation Hackathon (GIAH) event. Extracting text from multi-column biomedical documents such as Genomics & Informatics is known to be notoriously difficult. The hackathon was piloted as part of a coding competition of the ELTEC College of Engineering at Ewha Womans University in order to enable researchers and students to create or annotate their own versions of the Genomics & Informatics corpus, to gain and create knowledge about corpus linguistics, and simultaneously to acquire tangible and transferable skills. The proposed projects during the hackathon harness an internal database containing different versions of the corpus and annotations.