Catastrophic health expenditure refers to measure the level of the economic burden of households due to medical expenses. The purpose of this study was to examine the proportion of households that experienced catastrophic health expenditure between 2006 and 2018 using available data from the National Survey of Tax and Benefit (NaSTaB), Korea Health Panel (KHP), and Households Income and Expenditure Survey (HIES). Trend test was used to analyze the proportion of household with catastrophic healthcare expenditure. The households experienced the catastrophic health expenditure 2.08% in 2018 using the NaSTaB data. Trend analysis was significant with the decreasing trend (Annual Percentage Change [APC], -4.88; p<0.0001) in the proportion of households with the catastrophic health expenditure. On the other hand, the results of the HIES showed 2.92%, and KHP showed 2.48% of households experienced the catastrophic health expenditure in 2016. The trend was significantly increased in HIES (APC, 1.43; p<0.0001) and KHP (APC, 6.68; p<0.0001). Therefore, this suggests that further interventions to alleviate the burden of catastrophic health expenditure to the low-income group are needed.

Catastrophic health expenditure refers to measure the level of the economic burden of households due to medical expenses. The purpose of this study was to examine the proportion of households that experienced catastrophic health expenditure between 2006 and 2019 using available data from the National Survey of Tax and Benefit (NaSTaB), Korea Health Panel (KHP), and Households Income and Expenditure Survey (HIES). Trend test was used to analyze the proportion of households with catastrophic healthcare expenditure. The households experienced a catastrophic health expenditure of 2.44% in 2019 using the NaSTaB data. Trend analysis was significant with the decreasing trend (annual percentage change [APC], -4.49; p<0.0001) in the proportion of households with catastrophic health expenditure. Also, the results of the 2017 KHP and the 2016 HIES showed 2.20% and 2.92%. The trend was significantly increased in the KHP (APC, 1.79; p<0.0001) and the HIES (APC, 1.43; p<0.0001). Therefore, this study suggests that further public healthcare interventions to alleviate the burden of catastrophic health expenditure, especially for low-income households, are needed.

Catastrophic health expenditure refers to measure the level of the economic burden of households due to medical expenses. The purpose of this study was to examine the proportion of households that experienced catastrophic health expenditure between 2006 and 2019 using available data from the National Survey of Tax and Benefit (NaSTaB), Korea Health Panel (KHP), and Households Income and Expenditure Survey (HIES). Trend test was used to analyze the proportion of households with catastrophic healthcare expenditure. The households experienced a catastrophic health expenditure of 2.44% in 2019 using the NaSTaB data. Trend analysis was significant with the decreasing trend (annual percentage change [APC], -4.49; p<0.0001) in the proportion of households with catastrophic health expenditure. Also, the results of the 2017 KHP and the 2016 HIES showed 2.20% and 2.92%. The trend was significantly increased in the KHP (APC, 1.79; p<0.0001) and the HIES (APC, 1.43; p<0.0001). Therefore, this study suggests that further public healthcare interventions to alleviate the burden of catastrophic health expenditure, especially for low-income households, are needed.

Objectives: With the growing importance of monitoring cancer patients’ internet usage, there is an increasing need for technology that expands access to relevant information through text mining. This study analyzed internet articles from portal sites in 2023 to identify trends in the information available to cancer patients and to derive meaningful insights. Methods: This study analyzed 19,578 news articles published on Naver, a major Korean portal site, from January 1, 2023, to December 31, 2023. Natural language processing, text mining, network analysis, and word cloud analysis were employed. The search term “am” (Korean for “cancer”) was used to identify keywords related to cancer. Results: In 2023, an average of 1,631 cancer-related articles were published monthly, with a peak of 1,946 in September and a low of 1,371 in February. A total of 132,456 keywords were extracted, with “cure” (2,218 occurrences), “lung cancer” (1,652), and “breast cancer” (1,235) being the most frequent. Term frequency-inverse document frequency analysis ranked “struggle” (1064.172) as the most significant keyword, followed by “lung cancer” (839.988) and “breast cancer” (744.840). Network analysis revealed four distinct clusters focusing on treatment, celebrity-related issues, major cancer types, and cancer-causing factors. Conclusions The analysis of cancer-related keywords in 2023 indicates that news articles often prioritize gossip over essential information. These findings provide foundational data for future policy directions and strategies to address misinformation. This study underscores the importance of understanding the nature of cancer-related information consumed by the public and offers insights to guide official policies and healthcare practices.

Objectives: With the growing importance of monitoring cancer patients’ internet usage, there is an increasing need for technology that expands access to relevant information through text mining. This study analyzed internet articles from portal sites in 2023 to identify trends in the information available to cancer patients and to derive meaningful insights. Methods: This study analyzed 19,578 news articles published on Naver, a major Korean portal site, from January 1, 2023, to December 31, 2023. Natural language processing, text mining, network analysis, and word cloud analysis were employed. The search term “am” (Korean for “cancer”) was used to identify keywords related to cancer. Results: In 2023, an average of 1,631 cancer-related articles were published monthly, with a peak of 1,946 in September and a low of 1,371 in February. A total of 132,456 keywords were extracted, with “cure” (2,218 occurrences), “lung cancer” (1,652), and “breast cancer” (1,235) being the most frequent. Term frequency-inverse document frequency analysis ranked “struggle” (1064.172) as the most significant keyword, followed by “lung cancer” (839.988) and “breast cancer” (744.840). Network analysis revealed four distinct clusters focusing on treatment, celebrity-related issues, major cancer types, and cancer-causing factors. Conclusions The analysis of cancer-related keywords in 2023 indicates that news articles often prioritize gossip over essential information. These findings provide foundational data for future policy directions and strategies to address misinformation. This study underscores the importance of understanding the nature of cancer-related information consumed by the public and offers insights to guide official policies and healthcare practices.

Objectives: With the growing importance of monitoring cancer patients’ internet usage, there is an increasing need for technology that expands access to relevant information through text mining. This study analyzed internet articles from portal sites in 2023 to identify trends in the information available to cancer patients and to derive meaningful insights. Methods: This study analyzed 19,578 news articles published on Naver, a major Korean portal site, from January 1, 2023, to December 31, 2023. Natural language processing, text mining, network analysis, and word cloud analysis were employed. The search term “am” (Korean for “cancer”) was used to identify keywords related to cancer. Results: In 2023, an average of 1,631 cancer-related articles were published monthly, with a peak of 1,946 in September and a low of 1,371 in February. A total of 132,456 keywords were extracted, with “cure” (2,218 occurrences), “lung cancer” (1,652), and “breast cancer” (1,235) being the most frequent. Term frequency-inverse document frequency analysis ranked “struggle” (1064.172) as the most significant keyword, followed by “lung cancer” (839.988) and “breast cancer” (744.840). Network analysis revealed four distinct clusters focusing on treatment, celebrity-related issues, major cancer types, and cancer-causing factors. Conclusions The analysis of cancer-related keywords in 2023 indicates that news articles often prioritize gossip over essential information. These findings provide foundational data for future policy directions and strategies to address misinformation. This study underscores the importance of understanding the nature of cancer-related information consumed by the public and offers insights to guide official policies and healthcare practices.

Objectives: With the growing importance of monitoring cancer patients’ internet usage, there is an increasing need for technology that expands access to relevant information through text mining. This study analyzed internet articles from portal sites in 2023 to identify trends in the information available to cancer patients and to derive meaningful insights. Methods: This study analyzed 19,578 news articles published on Naver, a major Korean portal site, from January 1, 2023, to December 31, 2023. Natural language processing, text mining, network analysis, and word cloud analysis were employed. The search term “am” (Korean for “cancer”) was used to identify keywords related to cancer. Results: In 2023, an average of 1,631 cancer-related articles were published monthly, with a peak of 1,946 in September and a low of 1,371 in February. A total of 132,456 keywords were extracted, with “cure” (2,218 occurrences), “lung cancer” (1,652), and “breast cancer” (1,235) being the most frequent. Term frequency-inverse document frequency analysis ranked “struggle” (1064.172) as the most significant keyword, followed by “lung cancer” (839.988) and “breast cancer” (744.840). Network analysis revealed four distinct clusters focusing on treatment, celebrity-related issues, major cancer types, and cancer-causing factors. Conclusions The analysis of cancer-related keywords in 2023 indicates that news articles often prioritize gossip over essential information. These findings provide foundational data for future policy directions and strategies to address misinformation. This study underscores the importance of understanding the nature of cancer-related information consumed by the public and offers insights to guide official policies and healthcare practices.

Background: Many studies have reported noticeable increases in the proportion of employees working either relatively short or relatively long hours. Such trends have been accompanied by an increasing concern regarding work hour mismatches defined as a discrepancy between actual and preferred work hours. The aim of this study was to investigate association between work hour mismatch and depression. Methods: Data regarding work hour mismatches for 47,551 adults were extracted from the 2017 Korean Working Conditions Survey. The World Health Organization-Five Well-Being Index was used to measure depression. Multiple logistic regression analyses were performed to examine the association between work hour mismatch and depression. Results: Men and women workers with work hour mismatch were more likely to have depression [underemployed males: odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.14–1.49, overemployed males: OR = 1.28, 95% CI = 1.18–1.40; underemployed females: OR = 1.37, 95% CI = 1.20–1.56, overemployed females: OR = 1.12, 95% CI = 1.02–1.23]. Underemployed workers, workers who worked more than 52 hours per week, and workers with a high income level, all had higher ORs for depression. The greater the discrepancy between actual and preferred work hours, the higher OR for depression among both underemployed and overemployed workers. Conclusions A difference between actual and preferred work hours was associated with depression. Underemployed workers had a higher risk of depression than that of overemployed workers. As a work hour mismatch negatively affected workers' mental health, it is important to reduce work hours mismatches as well as shorten the absolute number of work hours.

Background: Many studies have reported noticeable increases in the proportion of employees working either relatively short or relatively long hours. Such trends have been accompanied by an increasing concern regarding work hour mismatches defined as a discrepancy between actual and preferred work hours. The aim of this study was to investigate association between work hour mismatch and depression. Methods: Data regarding work hour mismatches for 47,551 adults were extracted from the 2017 Korean Working Conditions Survey. The World Health Organization-Five Well-Being Index was used to measure depression. Multiple logistic regression analyses were performed to examine the association between work hour mismatch and depression. Results: Men and women workers with work hour mismatch were more likely to have depression [underemployed males: odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.14–1.49, overemployed males: OR = 1.28, 95% CI = 1.18–1.40; underemployed females: OR = 1.37, 95% CI = 1.20–1.56, overemployed females: OR = 1.12, 95% CI = 1.02–1.23]. Underemployed workers, workers who worked more than 52 hours per week, and workers with a high income level, all had higher ORs for depression. The greater the discrepancy between actual and preferred work hours, the higher OR for depression among both underemployed and overemployed workers. Conclusions A difference between actual and preferred work hours was associated with depression. Underemployed workers had a higher risk of depression than that of overemployed workers. As a work hour mismatch negatively affected workers' mental health, it is important to reduce work hours mismatches as well as shorten the absolute number of work hours.