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- Big Data Analysis of Mental Health Trends from the COVID-19 Pandemic into the Endemic Phase
- Seo Yeon Lee, Kuem Sun Han, Soo Yeon Lee, Ji Hye Shin, Moon Ju Song
- STRESS. 2025;33(3):117-126. Published online September 30, 2025
- DOI: https://doi.org/10.17547/kjsr.2025.33.3.117
- 342 View
- 12 Download
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Abstract
PDF - Background
This study aimed to examine temporal trends in mental health issues in South Korea from the onset of the coronavirus disease (COVID-19) pandemic through to the post-pandemic endemic phase. Using large-scale online data, this study sought to identify key mental health concerns at different stages and offer foundational evidence for future public health policy development.
Methods
A total of 13,797 textual data entries, —comprising 8,664 Naver blog posts and 5,133 news articles, —were collected between January 20, 2020, and April 17, 2024. The data were segmented into five distinct periods based on critical milestones in South Korea’s pandemic response. Text mining and network analysis were employed to extract and examine the following mental health-related keywords: depression, anxiety, and stress.
Results
During the early phase of the pandemic, negative psychological states, such as anxiety, stress, and depression, were highly prevalent, reflecting widespread fear and uncertainty among the public. Although the frequency of these keywords gradually declined, they remained significant even after the transition to the endemic phase. In contrast, the later stages showed an increased frequency of keywords related to recovery and adaptation, such as education, environment, and support, indicating ongoing societal adjustment.
Conclusions
These findings underscore the prolonged psychological effects of COVID-19, with mental health concerns persisting into the endemic phase. Continuous mental health support and adaptive public health strategies are essential to mitigate the enduring impact of global health emergencies.
- Mobile Health (m-health) on Mental Health
- Jae Soon Jang, Seung Hun Cho
- Korean J Str Res. 2016;24(4):231-236. Published online December 31, 2016
- DOI: https://doi.org/10.17547/kjsr.2016.24.4.231
- 5,325 View
- 141 Download
- 8 Citations
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Abstract
PDF
Recently, the demand for mental health services using information and communication technology (ICT) such as mobile communication and social network service (SNS) is increasing. Mobile health (m-Health) and health big data are expected to play a major role in driving the future healthcare paradigm. In particular, the value of applications utilizing smart devices including smartphone and wearable devices is increasing day by day. Mobile applications that can be applied to the patient to restore disease in the neuropsychiatric area can be easily provided, and clinicians can also use the clinic in patient diagnosis, evaluation, and treatment. In practical use, it is still a step in the process, so it is necessary to check the stability of the system that operates the data and prevent infringement and leakage of personal information that may occur later. In addition, it is necessary to establish the effectiveness and credibility based on the basis of practical use of mobile health (m-Health) and health big data. With technological advances being made day by day, mental health care workers should be aware of this trend and have an active interest.
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Citations
Citations to this article as recorded by
- Strategies in Ecological Momentary Interventions for Mental Health Care in Adults: A Scoping Review
Gi Wook Ryu
Journal of Digital Contents Society.2024; 25(4): 961. CrossRef - Effects of Mobile-Based Forest-Therapy Programs Using Urban Forests for Symptoms of Depressed Patients
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Journal of Physics: Conference Series.2021; 1852(3): 032030. CrossRef - Development and Assessment of a Social Network Service-Based Lifestyle-Modification Program for Workers at High Risk of Developing Cardiovascular Disease
Soo Hee Woo, Eui Geum Oh, Kyung-SOO Kim, Sang Hui Chu, Gwang Suk Kim, Chung Mo Nam
Workplace Health & Safety.2020; 68(3): 109. CrossRef - Analysis of Health Insurance Big Data for Early Detection of Disabilities: Algorithm Development and Validation
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Soontae An, Hannah Lee
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- Strategies in Ecological Momentary Interventions for Mental Health Care in Adults: A Scoping Review
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