Objective: Adult attachment style is linked to how an individual responds to threats or stress and is known to be related to the onset of psychiatric symptoms such as depression. However, as the current assessment of attachment type mainly relies on self-report questionnaires and can be prone to bias, there is a need to incorporate physiological factors along with psychological symptoms and history in this process. We aimed to predict the measurement of two important types of adult attachment with heart rate variability (HRV), early life stress experience, and subjective psychiatric symptoms. Methods: Five hundred eighty-two subjects with depressive disorder were recruited retrospectively from January 2015 to June 2021. The experience of early life stress and psychiatric symptoms were collected, and HRV measures were obtained as input for an ensembled Voting Regressor model of machine learning-based regression models, including linear regression, ElasticNet, Support Vector Machine (SVM), Random Forest, and Extreme Gradient Boosting (XGBoost). Results: Model performances evaluated with R-squared score averaged across 30 seeds were 0.377 and 0.188 for anxious- and avoidant-attachment, respectively. Mean absolute error averaged to 13.251 and 12.083, respectively. Shapley value importance analysis indicated that for both attachment types, the most important feature was the trait-anxiety, followed by emotional abuse, state-anxiety or self-reported depressive symptoms, and fear or helplessness felt in the moment of an early life stressor. Conclusion Our results provide the evidence base that may be utilized in clinical settings to predict the degree of attachment type using bio-psychological factors.

Objective: Despite lower depression rates in men than in women, men’s suicide rates are significantly higher, suggesting potential gaps in depression screening. Rutz et al. developed the Gotland Male Depression Scale (GMDS), which includes symptoms commonly associated with male depression. This study was conducted to validate the Korean version of the GMDS (K-GMDS). Methods: The K-GMDS, Patient Health Questionnaire-9 (PHQ-9), and outpatient records of 233 new patients at the outpatient psychiatry department of Catholic University Hospital in Daegu from February and May 2022 were retrospectively reviewed. Internal consistency was measured using Cronbach’s α, and external validity was tested by analyzing the scale’s correlation with the PHQ-9. The screening capacity of the K-GMDS was tested based on the receiver operating characteristic (ROC) curve, sensitivity, specificity, and overall accuracy. Results: Of 233 patients, 42.6% (n=98) were classified to the depression group. Cronbach’s α was 0.92, and external validity was established with a Pearson’s correlation coefficient of 0.83 between the total score of the K-GMDS and the PHQ-9. While there were no significant differences in the area under the ROC curve between the K-GMDS and the PHQ-9, the K-GMDS had better sensitivity, specificity, and overall accuracy in screening depressive symptoms among men compared to the PHQ-9. Conclusion The K-GMDS exhibits satisfactory reliability and validity in psychiatric outpatient settings and outperforms the PHQ-9 in screening for depression among men. This study will be useful in developing male depression scales that are currently unavailable in South Korea.

Objective: This study aims to understand the structure of meaning in life among patients with cancer through the validation of the Meaning in Life Scale among Korean patients (K-MiLS) with cancer. Methods: From August 2021 to November 2022, participants were recruited from multiple sites in South Korea. Participants completed related questionnaires, including the MiLS, on the web or mobile. Test-retest reliability was assessed between 2 and 4 weeks after the initial assessment. Exploratory and confirmatory factor analyses and Pearson’s correlations were used to evaluate the reliability and validity of the MiLS. A multiple regression analysis was conducted to examine the sociodemographic and disease-related variables correlated with the MiLS. Regarding concurrent validity, a hierarchical regression analysis was performed. Results: The results (n=345) indicated that the K-MiLS has a four-factor structure: Harmony and Peace; Life Perspective, Purpose, and Goals; Confusion and Lessened Meaning; and Benefits of Spirituality. Regarding convergent and discriminant validity, K-MiLS was negatively correlated with Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and Fear of Cancer Recurrence Inventory while showing a significantly positive correlation with the Posttraumatic Growth Inventory, Self-Compassion Scale, Functional Assessment of Cancer Therapy-General, and Functional Social Support Questionnaire. Hierarchical regression analysis revealed that the demographic variable influencing MiLS was religious affiliation. Conclusion The K-MiLS had a multidimensional four-factor structure similar to that of the original version. It is also a reliable and valid measure for assessing cancer survivors’ meaning in life after a cancer diagnosis.

Objective: The clinical presentation of depressive disorders might be influenced by age, and its diagnosis and treatment can be affected by ageism-related bias. A network analysis can reveal symptom patterns unrecognized by the reductionistic approach. Therefore, this study explores the network structure of depression and anxiety symptoms in older Asian patients with depressive disorders and examines age-related differences in the context of ageism. Methods: We used data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants, Phase 3 study and included 2,785 psychiatric patients from 11 Asian countries. Depression and anxiety symptoms were assessed using the Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7. Network analyses were conducted to identify symptom interconnections and centrality among older (>65 years), middle-aged (35–64 years), and young (18–34 years) adult groups. The network structures were also compared using a network comparison test. Results: Depressed mood was the most central symptom across all age groups. Network comparisons revealed no significant structural differences among the three age groups, despite several variations in terms of global strength. The network structure of the older group was characterized by strong interconnections between somatic symptoms (insomnia-energy) and core depressive symptoms (little interest or pleasure-feelings of hopelessness). Conclusion This study reveals that the network structures of depression and anxiety symptoms have relatively consistent interconnections across age groups, despite subtle age-based differences. Specifically, older adults tend to present anxiety and depression symptoms as physical complaints. These findings challenge ageist stereotypes and advocate for inclusive, age-neutral approaches to treatment.

Purpose: This study aimed to leverage Shapley additive explanation (SHAP)-based feature engineering to predict appendix cancer. Traditional models often lack transparency, hindering clinical adoption. We propose a framework that integrates SHAP for feature selection, construction, and weighting to enhance accuracy and clinical relevance. Methods: Data from the Kaggle Appendix Cancer Prediction dataset (260,000 samples, 21 features) were used in this prediction study conducted from January through March 2025, in accordance with TRIPOD-AI guidelines. Preprocessing involved label encoding, SMOTE (synthetic minority over-sampling technique) to address class imbalance, and an 80:20 train-test split. Baseline models (random forest, XGBoost, LightGBM) were compared; LightGBM was selected for its superior performance (accuracy=0.8794). SHAP analysis identified key features and guided 3 engineering steps: selection of the top 15 features, construction of interaction-based features (e.g., chronic severity), and feature weighting based on SHAP values. Performance was evaluated using accuracy, precision, recall, and F1-score. Results: Four LightGBM model configurations were evaluated: baseline (accuracy=0.8794, F1-score=0.8691), feature selection (accuracy=0.8968, F1-score=0.8860), feature construction (accuracy=0.8980, F1-score=0.8872), and feature weighting (accuracy=0.8986, F1-score=0.8877). SHAP-based engineering yielded performance improvements, with feature weighting achieving the highest precision (0.9940). Key features (e.g., red blood cell count and chronic severity) contributed to predictions while maintaining interpretability. Conclusion The SHAP-based framework substantially improved the accuracy and transparency of appendix cancer predictions using LightGBM (F1-score=0.8877). This approach bridges the gap between predictive power and clinical interpretability, offering a scalable model for rare disease prediction. Future validation with real-world data is recommended to ensure generalizability.

This study explores the development, roles, and key initiatives of the Regional Environmental Health Centers in Korea, detailing their evolution through four distinct phases and their impact on environmental health policy and local governance. It chronicles the establishment and transformation of these centers from their inception in May 2007, through four developmental stages. Originally named Environmental Disease Research Centers, they were subsequently renamed Environmental Health Centers following legislative changes. The analysis includes the expansion in the number of centers, the transfer of responsibilities to local governments, and the launch of significant projects such as the Korean Children’s Environmental Health Study (Ko-CHENS ). During the initial phase (May 2007–February 2009), the 10 centers concentrated on research-driven activities, shifting from a media-centered to a receptor-centered approach. In the second phase, prompted by the enactment of the Environmental Health Act, six additional centers were established, broadening their scope to address national environmental health issues. The third phase introduced Ko-CHENS, a 20-year national cohort project designed to influence environmental health policy by integrating research findings into policy frameworks. The fourth phase marked a decentralization of authority, empowering local governments and redefining the centers' roles to focus on regional environmental health challenges. The Regional Environmental Health Centers have significantly evolved and now play a crucial role in addressing local environmental health issues and supporting local government policies. Their capacity to adapt and respond to region-specific challenges is essential for the effective implementation of environmental health policies, reflecting geographical, socioeconomic, and demographic differences.

With the increasing emphasis on diversity, equity, and inclusion (DEI) in organizations and institutions, academic societies in gastroenterology and hepatology are beginning to take actionable steps toward achieving DEI. The successful implementation of DEI initiatives leads to excellence in the field, improved patient outcomes, particularly in areas where health disparities are prevalent, and advances in the gastrointestinal discipline. Such implementation also results in a workforce that better reflects the growing diversity of the population. This review defines DEI and introduces the DEI policies and strategies adopted by the academic societies of gastroenterology in other countries. This paper proposes strategies to integrate DEI better into the Korean Society of Gastroenterology, emphasizing the importance of embedding DEI into the culture and strategic framework. The key strategies include establishing a DEI committee, setting clear targets, and conducting formal assessments to measure DEI progress. This study focused on enhancing workforce diversity, particularly among women and young doctors, and advocates for the need to support their academic development through male allyship and the promotion of equitable and inclusive academic cultures.

Objectives: The success of Helicobacter pylori eradication using clarithromycin-based triple therapy relies on the bacteria being sensitive to clarithromycin. This study evaluated the diagnostic performance of two frequently used polymerase chain reaction (PCR) methods (AllplexTM H. pylori & ClariR Assay [Seegene] and Ezplex® HP-CLA Real-time PCR [SML Genetree]) to detect H. pylori infection and identify point mutations associated with clarithromycin resistance. Methods: Patients who underwent esophagogastroduodenoscopy between August 2023 and April 2024 at Incheon St. Mary’s Hospital were enrolled in this study. The diagnostic performance of the Allplex method was evaluated against the rapid urease test (RUT), culture, and Ezplex HP-CLA methods. Point mutation detection using the Allplex and Ezplex methods was compared with the results of gene sequencing. The rates of H. pylori eradication following Ezplex-based tailored therapy were also analyzed. Results: Eighty-seven gastric biopsy specimens were analyzed. For diagnosing H. pylori infections, Allplex demonstrated kappa values of 0.670 compared with RUT, 0.468 compared with culture, and 0.880 compared with Ezplex. Among the 87 bacterial isolates subjected to gene sequencing to detect clarithromycin resistance-associated point mutations, the Allplex and Ezplex methods demonstrated 74 and 76 concordant results, respectively. The H. pylori eradication rate using Ezplex-based tailored therapy was 90.7%. Conclusions This study demonstrated that both the Allplex and Ezplex methods are helpful for diagnosing H. pylori infections and detecting clarithromycin resistance. Furthermore, the Ezplex method was clinically effective for guiding tailored therapy to yield successful H. pylori eradication.

Background/Aims: Elevated troponin levels predict in-hospital mortality and influence decisions regarding thrombolytic therapy in patients with acute pulmonary embolism (PE). However, the usefulness of high-sensitivity troponin T (hsTnT) regarding PE remains uncertain. We aimed to establish the optimal cut-off level and compare its performance for precise risk stratification. Methods: 374 patients diagnosed with acute PE were reviewed. PE-related adverse outcomes, a composite of PE-related deaths, cardiopulmonary resuscitation incidents, systolic blood pressure < 90 mmHg, and all-cause mortality within 30 days were evaluated. The optimal hsTnT cut-off for all-cause mortality, and the net reclassification index (NRI) was used to assess the incremental value in risk stratification. Results: Among 343 normotensive patients, 17 (5.0%) experienced all-cause mortality, while 40 (10.7%) had PE-related adverse outcomes. An optimal hsTnT cut-off value of 60 ng/L for all-cause mortality (AUC 0.74, 95% CI 0.61–0.85, p < 0.001) was identified, which was significantly associated with PE-related adverse outcomes (OR 4.07, 95% CI 2.06–8.06, p < 0.001). Patients with hsTnT ≥ 60 ng/L were older, hypotensive, had higher creatinine levels, and right ventricular dysfunction signs. Combining hsTnT ≥ 60 ng/L with simplified pulmonary embolism severity index ≥1 provided additional prognostic information. Reclassification analysis showed a significant shift in risk categories, with an NRI of 1.016 ± 0.201 (p < 0.001). Conclusions We refined troponin’s predictive value in patients with acute PE, proposing a new cut-off value of hsTnT ≥ 60 ng/L. Validation through large-scale studies is essential to offer clinically useful guidance for managing patient population.