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This study aimed to identify factors significantly associated with recent depressive mood with respect to health-related behavioral patterns at the individual level, perceived safety in the school environment, and willingness to share concerns with family and social networks. Self-reported responses to questions regarding recent feelings of depression, health-related behaviors in physical, psychological, and spiritual subdomains, school refusal and perceived safety at school, and perceived social support were obtained from 1,991 in-school adolescents (mean [SD] age = 15.3 [1.7] years; male/female = 936/1055). Multivariate logistic regression analyses were used to identify explanatory factors significantly associated with recent depression, defined as feelings of sadness or hopelessness for more than 2 weeks (during the last 12 months) that interfered with everyday functioning. Of the 1,991 students, 271 (13.6%) reported recent depression. Multivariate logistic regression analyses revealed higher odds of recent depression in adolescents with frequent thoughts of school refusal (odds ratio [95% confidence interval] = 3.25 [2.44-4.32]) and those who engaged in regular physical exercise (1.57 [1.19-2.07]), whereas a positive mindset (0.65 [0.49-0.86]), perceived safety at school (0.62 [0.47-0.82]), and perceived social support from one's mother (0.54 [0.40-0.72]) were associated with lower odds of recent depression. Taken together, our findings suggest that parents and teachers should talk regularly with adolescents about recent life (dis)satisfaction and stressors, particularly when they report frequent thoughts of school refusal. Perceived social support would increase perceived safety on school grounds and make it easier for teenagers to share their concerns with parents, thereby reducing the risk for depressive symptoms. School-based programs that promote a positive mindset would be helpful in preparing students for the challenges of adulthood.

This study aimed to investigate the general South Korean public attitudes toward the legalization of euthanasia or physician-assisted suicide (EAS) and examine the reasons underpinning these attitudes. From March–April 2021, we conducted a cross-sectional survey of a representative national sample of 1000 South Koreans aged 19 years or older. Three in four participants (76.4%) expressed positive attitudes toward the legalization of EAS. Participants who agreed with this legalization reported “meaninglessness of the rest of life” and “right to a good death” as their main reasons. Participants who disagreed with the legalization of EAS reported “respect for life”, “violation of the right to self-determination”, “risk of abuse or overuse”, and “violation of human rights” as theirs. In the multivariate logistic regression analyses, participants with poor physical status (adjusted odds ratio [aOR]: 1.41, 95%; confidence interval [CI]: 1.02–1.93) or comorbidity (aOR: 1.84, 95%; CI: 1.19–2.83) showed positive attitudes toward the legalization of EAS. In summary, most of the general South Korean population regards the legalization of EAS positively, especially participants with poor physical status or comorbidity.

The primary goal of this study was to evaluate the major roles of health-related quality of life (HRQOL) in a 5-year lung cancer survival prediction model using machine learning techniques (MLTs). The predictive performances of the models were compared with data from 809 survivors who underwent lung cancer surgery. Each of the modeling technique was applied to two feature sets: feature set 1 included clinical and sociodemographic variables, and feature set 2 added HRQOL factors to the variables from feature set 1. One of each developed prediction model was trained with the decision tree (DT), logistic regression (LR), bagging, random forest (RF), and adaptive boosting (AdaBoost) methods, and then, the best algorithm for modeling was determined. The models’ performances were compared using fivefold cross-validation. For feature set 1, there were no significant differences in model accuracies (ranging from 0.647 to 0.713). Among the models in feature set 2, the AdaBoost and RF models outperformed the other prognostic models [area under the curve (AUC) = 0.850, 0.898, 0.981, 0.966, and 0.949 for the DT, LR, bagging, RF and AdaBoost models, respectively] in the test set. Overall, 5-year disease-free lung cancer survival prediction models with MLTs that included HRQOL as well as clinical variables improved predictive performance.

Objective The COVID-19 pandemic has changed peoples’ routine of daily living and posed major risks to global health and economy. Few studies have examined differential impacts of economic factors on health during pandemic compared to pre-pandemic. We aimed to compare the strength of associations between perceived health and socioeconomic position (household income, educational attainment, and employment) estimated before and during the pandemic. Methods Two waves of nationwide survey [on 2018(T1; n  = 1200) and 2021(T2; n  = 1000)] were done for 2200 community adults. A balanced distribution of confounders (demographics and socioeconomic position) were achieved across the T2 and T1 by use of the inverse probability of treatment weighting. Distributions of perceived health [= (excellent or very good)/(bad, fair, or good)] for physical-mental-social-spiritual subdomains were compared between T1 and T2. Odds of bad/fair/good health for demographics and socioeconomic position were obtained by univariate logistic regression. Adjusted odds (aOR) of bad/fair/good health in lower household income(< 3000 U.S. dollars/month) were retrieved using the multiple hierarchical logistic regression models of T1 and T2. Results Perceived health of excellent/very good at T2 was higher than T1 for physical(T1 = 36.05%, T2 = 39.13%; P  = 0.04), but were lower for mental(T1 = 38.71%, T2 = 35.17%; P  = 0.01) and social(T1 = 42.48%, T2 = 35.17%; P  < 0.001) subdomains. Odds of bad/fair/good health were significantly increased at T2 than T1 for household income (physical-mental-social; all Ps < 0.001) and educational attainment (social; P  = 0.04) but not for employment (all Ps > 0.05). AORs of bad/fair/good health in lower household income were stronger in T2 than T1, for mental [aOR (95% CI) = 2.15(1.68–2.77) in T2, 1.33(1.06–1.68) in T1; aOR difference = 0.82( P  < 0.001)], physical [aOR (95% CI) = 2.64(2.05–3.41) in T2, 1.50(1.18–1.90) in T1; aOR difference = 1.14( P  < 0.001)] and social [aOR (95% CI) = 2.15(1.68–2.77) in T2, 1.33(1.06–1.68) in T1; aOR difference = 0.35( P  = 0.049)] subdomains. Conclusions Risks of perceived health worsening for mental and social subdomains in people with lower monthly household income or lower educational attainment became stronger during the COVID-19 pandemic compared to pre-pandemic era. In consideration of the prolonged pandemic as of mid-2022, policies aiming not only to sustain the monthly household income and compulsory education but also to actively enhance the perceived mental-social health status have to be executed and maintained .

This study aims to evaluate the psychometric properties of the Satisfaction with Life Scale (SWLS) and the Subjective Well-Being Inventory (SWBI) in a nationally representative sample in Korea. A total of 1200 people completed the semi-structured, self-reported questionnaire, which included five items from the SWLS and 14 items from the SWBI. All items and the total score of both the SWLS and the SWBI showed high internal consistency (with Cronbach’s alphas of 0.886 and 0.946, respectively). The item-total correlation values for both measures were in the ranges of 0.71–0.75 and 0.65–0.80, respectively. There were positive correlations between the SWLS and SWBI (r = 0.59, p = 0.01). The SWLS, SWBI and global well-being (GWB) scores were positively correlated with the McGill Quality of Life subscales (p = 0.01) but negatively correlated with the Patient Health Questionnaire-9 (p = 0.01). Participants under 50 years old (adjusted odds ratio [aOR] = 1.30, 95% confidence interval [CI] = 1.00–1.69) and those in rural areas (aOR = 1.63, 95% CI = 1.28–2.07) had higher scores on the SWLS than other participant groups. Participants who were under 50 years old (aOR = 1.47, 95% CI = 1.12–1.92), were male (aOR = 1.33, 95% CI = 1.04–1.71), were married (aOR = 1.51, 95% CI = 1.13–2.01), lived in rural areas (aOR = 2.30, 95% CI = 1.35–3.91), or had higher incomes (aOR = 1.30, 95% CI = 1.02–1.65) showed higher SWBI scores. This study showed that the SLWS and SWBI have good psychometric properties and could be applicable to Korea.

Assessing patient-reported outcomes (PROs) through interviews or conversations during clinical encounters provides insightful information about survivorship. This study aims to test the validity of natural language processing (NLP) and machine learning (ML) algorithms in identifying different attributes of pain interference and fatigue symptoms experienced by child and adolescent survivors of cancer versus the judgment by PRO content experts as the gold standard to validate NLP/ML algorithms. This cross-sectional study focused on child and adolescent survivors of cancer, aged 8 to 17 years, and caregivers, from whom 391 meaning units in the pain interference domain and 423 in the fatigue domain were generated for analyses. Data were collected from the After Completion of Therapy Clinic at St. Jude Children's Research Hospital. Experienced pain interference and fatigue symptoms were reported through in-depth interviews. After verbatim transcription, analyzable sentences (ie, meaning units) were semantically labeled by 2 content experts for each attribute (physical, cognitive, social, or unclassified). Two NLP/ML methods were used to extract and validate the semantic features: bidirectional encoder representations from transformers (BERT) and Word2vec plus one of the ML methods, the support vector machine or extreme gradient boosting. Receiver operating characteristic and precision-recall curves were used to evaluate the accuracy and validity of the NLP/ML methods. Compared with Word2vec/support vector machine and Word2vec/extreme gradient boosting, BERT demonstrated higher accuracy in both symptom domains, with 0.931 (95% CI 0.905-0.957) and 0.916 (95% CI 0.887-0.941) for problems with cognitive and social attributes on pain interference, respectively, and 0.929 (95% CI 0.903-0.953) and 0.917 (95% CI 0.891-0.943) for problems with cognitive and social attributes on fatigue, respectively. In addition, BERT yielded superior areas under the receiver operating characteristic curve for cognitive attributes on pain interference and fatigue domains (0.923, 95% CI 0.879-0.997; 0.948, 95% CI 0.922-0.979) and superior areas under the precision-recall curve for cognitive attributes on pain interference and fatigue domains (0.818, 95% CI 0.735-0.917; 0.855, 95% CI 0.791-0.930). The BERT method performed better than the other methods. As an alternative to using standard PRO surveys, collecting unstructured PROs via interviews or conversations during clinical encounters and applying NLP/ML methods can facilitate PRO assessment in child and adolescent cancer survivors.

PurposeTo evaluate the impact of co-morbidities on financial hardship in adult cancer survivors and the role of health insurance and a usual source of care (i.e., a particular doctor’s office/health center/other place that the person usually goes if he/she is sick or needs advice) in relieving this impact.MethodsUsing the Medical Expenditure Panel Survey, we estimated prevalence of two financial hardships, out-of-pocket (OOP) burden and financial worry, among 1196 adult cancer survivors. A modified Charlson co-morbidity index (CCI) assessed co-morbidities, which represent a medical event (e.g., a doctor’s appointment) associated with co-morbid conditions within the past 1 year. Multivariable logistic regression tested the influence of health insurance and a usual source of care on associations of co-morbidities with financial hardship by middle/high vs. low-income families and by working vs. retirement-age individuals.ResultsYears since cancer diagnosis ranged from 0 to 76 years (mean: 10.3, SD: 9.8), 10 and 25% of survivors experienced OOP burden and financial worry. For OOP burden, increased CCI was a risk factor among survivors of low-income families, ORs: 1.91 (95% CI: 1.06, 3.46) for a CCI 1–2 and 3.37 (95% CI: 1.72, 6.61) for a CCI ≥ 3 vs. CCI of 0. For financial worry, increased CCI was a risk factor among working-age survivors, ORs: 1.58 (95% CI: 1.02, 2.47) for a CCI 1–2 and 2.15 (95% CI: 1.19, 3.87) for a CCI ≥ 3 vs. CCI of 0. However, having health insurance and a usual source of care did not mitigate impact of co-morbidities on financial hardship (P values > 0.05).ConclusionsImpact of co-morbidities on OOP and financial worry burden was greatest in survivors of low-income families and working-age, respectively. Health insurance and a usual source of care did not relieve the impact of co-morbidities on financial hardship.ImplicationsEffective strategies are warranted to mitigate financial hardship for survivors.

Background Smoking is linked to an increased risk of infectious diseases, underscoring the importance of smoking prevention and cessation in improving public health. However, using smoking history as a surrogate marker of infection severity may have unintended consequences, potentially prompting clinicians to prescribe broad-spectrum antibiotics more readily for patients with a history of smoking. This study evaluated whether smoking history was independently associated with the increased prescription of broad-spectrum antibiotics to adult men in the general population of South Korea. Methods We analyzed data from two nationally representative cohorts of Korean adult men enrolled in the National Health Insurance Service (NHIS): the National Sample Cohort (NSC) and the Health Screening Cohort (HEALS). Smoking status was classified using data from self-reported questionnaires collected from 2009 to 2013. Participants were followed from 2013 to 2021 to assess broad-spectrum antibiotic use. The primary outcome was the receipt of at least one prescription of antipseudomonal penicillins, antipseudomonal cephalosporins, carbapenems, or glycopeptides for at least 3 consecutive days. We used a composite outcome to assess the use of antibiotics targeting resistant Gram-negative organisms. After accounting for confounders, the association between smoking status and antibiotic use was evaluated using multivariable regression models. Results The NHIS–NSC cohort included 50,134 adult men (17,300 never-smokers and 32,834 smokers), and the NHIS–HEALS cohort included 42,979 adult men (20,145 never-smokers and 22,834 smokers). In both cohorts, the rate of prescription of broad-spectrum antibiotics was low. For the composite outcome, the adjusted incidence rate ratios (IRR) for smokers compared to never-smokers were 1.55 (95% confidence interval [CI] = 0.67–3.52) in NHIS–NSC and 0.59 (95% CI = 0.24–1.46) in NHIS–HEALS. Smoking history was not significantly associated with the use of different antibiotic subclasses in these cohorts. For glycopeptides, the adjusted IRRs were 1.07 (95% CI = 0.23–5.10) in NHIS–NSC and 3.47 (95% CI = 0.70–17.13) in NHIS–HEALS, and neither association was statistically significant. Conclusion In these two cohorts, the prescription rates of broad-spectrum antibiotics were low, and we did not observe evidence of an independent association between smoking history and their use. These findings suggest that smoking history alone should not be regarded as sufficient justification for prescribing broad-spectrum agents and emphasize the importance of basing prescribing decisions on comprehensive clinical assessment.

One major topic in colorectal cancer (CRC) research is the role of immune cells against cancer cells. The association of single-nucleotide polymorphisms (SNPs) and polygenic risk scores (PRS) with CRC was examined and their functional properties were identified using a gene-gene interaction network. 960 CRC patients at Seoul National University Hospital (SNUH, discovery) and 6,627 CRC patients at Chonnam National University Hospital (CNNUH, validation) were enrolled. SNPs were genotyped using the Korean Biobank Array. 2,729 immune-related genes were selected from the Ensembl, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes, and 37,398 SNPs were mapped. PRS were categorized into tertiles. Cox proportional hazard models were fitted for overall survival (OS) and progression-free survival (PFS). A gene-gene interaction network was analyzed. Among CRC patients from SNUH, 154 (16.0%) died, while 245 (25.5%) had progression. In CNNUH, 3,537 (53.4%) died. For OS, the most significant association was observed for rs117322760 (8q23.1, PKHD1L1 , hazard ratio (HR) = 4.58, p -value = 1.40 × 10 − 6 ). For PFS, it was observed in rs143531681 (7q36.1, NOS3 , HR = 4.67, p -value = 9.72 × 10 − 8 ). For PRS, the highest tertile group showed an increased risk for OS (HR = 59.58, p -value = 9.20 × 10 –48 ) and PFS (HR = 9.81, p -value = 1.69 × 10 –23 ). Significant interactions were observed between PIK3R2 and PIK3CA for OS and ALOX5 and COTL1 for PFS. This study presented novel genetic variants associated with OS and PFS in CRC patients, and notable findings from the analysis of PRS and the gene-gene interaction.

Background Genome-wide association studies (GWAS) and subsequent functional interpretation have been used to identify susceptible genes and potential drug-repositioning candidates. This study aimed to identify genes associated with colorectal cancer (CRC) and potential drug-repositioning candidates. Methods Patients with CRC at Seoul National University Hospital (SNUH, discovery study) and Chonnam National University Hospital (CNUH, replication study) were included as case groups. The Korean Genome and Epidemiology Study (KoGES) participants were included as a control group. Single-nucleotide polymorphisms (SNPs) were extracted from blood-derived DNA (N = 409,063). A SNP-based logistic regression model was applied. Furthermore, post-GWAS analysis was conducted. Drug-repositioning candidates were identified using a pre-trained deep neural network and the druggability assessment tool. Results In the discovery study, we conducted a 1:3 age- and sex-matched case–control study that included 500 CRC cases (mean age 63.0 ± 7.15 years) and 1,500 healthy controls (mean age 62.9 ± 7.07 years), each group comprising 50% males and 50% females. The replication study enrolled 4,860 patients with CRC and 46,384 healthy controls. The two-stage GWAS revealed statistically significant associations among MKLN1 (rs75170436, 7q32.3, beta (log odds ratio) = − 0.90, P meta  = 5.90 × 10 –13 ), MMP14 (rs3751489, 14q11.2, beta (log odds ratio) = − 1.91, P meta  = 2.31 × 10 –12 ). Post-GWAS functional analysis revealed strong associations on two genes highlighting deleterious effects and increased gene expression. Drug-repositioning analysis identified GW0742 (PPARβ/δ agonist) with the highest binding score and druggability score for MMP14 with a reference allele (12.06, 0.85). Conclusions Using GWAS, MKLN1 and MMP14 were found to be associated with CRC development and we identified GW0742 (PPARβ/δ agonist) as a potential drug-repositioning candidate for CRC based on MKLN1 and MMP14. These findings improve the understanding of CRC development and provide insights into novel therapeutic targets and candidates for CRC treatment.