주요 논문
3
*2026년 기준 최근 6년 이내 논문에 한해 Impact Factor가 표기됩니다.
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인용수 0·
2025Intolerance of uncertainty and COVID-19-related post-traumatic stress disorder symptoms in US and Korean college students: serial mediation by COVID-19 concerns and loneliness
Ji Geun Kim, Hyunjung Yang, Deachul Seo, Gayeon Lee, Mijeong Park, Larkin S. McReynolds, Lawrence Amsel, Soo Hyun Park, Juyoen Hur, Young-Hoon Kim, Sang Hoon Han
BMC Psychology
This study provides comprehensive insights into the mechanisms underlying COVID-19-related PTSD symptoms in college students from the US and Korea, emphasizing the roles of intolerance of uncertainty, COVID-19 concerns, and loneliness, which have implications for designing effective interventions and support strategies during the pandemic.
https://doi.org/10.1186/s40359-025-03027-x
Coronavirus disease 2019 (COVID-19)
Psychology
Loneliness
Mediation
2019-20 coronavirus outbreak
Clinical psychology
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Stress (linguistics)
Psychiatry
Medicine
2
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인용수 3·
2024Investigation of factors regarding the effects of COVID-19 pandemic on college students’ depression by quantum annealer
Junggu Choi, Kion Kim, Soo Hyun Park, Juyoen Hur, Hyunjung Yang, Young-Hoon Kim, Hakbae Lee, Sanghoon Han
IF 3.9 (2024)
Scientific Reports
Diverse cases regarding the impact, with its related factors, of the COVID-19 pandemic on mental health have been reported in previous studies. In this study, multivariable datasets were collected from 751 college students who could be easily affected by pandemics based on the complex relationships between various mental health factors. We utilized quantum annealing (QA)-based feature selection algorithms that were executed by commercial D-Wave quantum computers to determine the changes in the relative importance of the associated factors before and after the pandemic. Multivariable linear regression (MLR) and XGBoost models were also applied to validate the QA-based algorithms. Based on the experimental results, we confirm that QA-based algorithms have comparable capabilities in factor analysis research to the MLR models that have been widely used in previous studies. Furthermore, the performance of the QA-based algorithms was validated through the important factor results from the algorithms. Pandemic-related factors (e.g., confidence in the social system) and psychological factors (e.g. decision-making in uncertain situations) were more important in post-pandemic conditions. Although the results should be validated using other mental health variables or national datasets, this study will serve as a reference for researchers regarding the use of the quantum annealing approach in factor analysis with validation through real-world survey dataset analysis.
https://doi.org/10.1038/s41598-024-54533-8
Pandemic
Mental health
Computer science
Coronavirus disease 2019 (COVID-19)
Regression analysis
Linear regression
Multivariable calculus
Feature selection
Psychology
Machine learning
3
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인용수 3·
2023Identification and comparison of pandemic-to-symptom networks of South Korea and the United States
Mijeong Park, Deachul Seo, Ji Geun Kim, Gayeon Lee, Larkin S. McReynolds, Lawrence Amsel, Hyunjung Yang, Young-Hoon Kim, Sang Hoon Han, Soo Hyun Park, Juyoen Hur
IF 3.2 (2023)
Frontiers in Psychiatry
The similar network structures and patterns observed in both countries imply that there may exist a stable relationship between the pandemic and internalizing symptoms above and beyond the sociocultural differences. The current findings provide new insights into the common potential pathway between the pandemic and internalizing symptoms in South Korea and in the U.S. and inform policymakers and mental health professionals of potential intervention targets to alleviate internalizing symptoms.
https://doi.org/10.3389/fpsyt.2023.1161200
Worry
Anxiety
Pandemic
Mental health
Psychiatry
Psychology
Depression (economics)
Distress
Medicine
Clinical psychology