• Human Ecology Research
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• v.59 no.1
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• pp.45-58
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• 2021

The present study examined whether enjoyable couple activity and common dyadic coping as daily positive couple interactions have direct or indirect effects on marital satisfaction through the mediation of sexual intimacy among urban Chinese women in the early years of marriage. The subjects were 182 urban women born under the one-child policy, who live in Heilongjiang, Anhui and Beijing provinces of China, and have been married up to six years. Data were collected using a self-administered questionnaire. We conducted a hierarchical multiple regression analysis in SPSS software and tested the significance of the mediation effects using bootstrapping method in Mplus software. The results of the study are as follows. First, both enjoyable couple activity and common dyadic coping had positive direct impacts on urban Chinese women's marital satisfaction and positive indirect impacts on marital satisfaction via sexual intimacy. Second, enjoyable couple activity was the strongest predictor of marital satisfaction, followed by common dyadic coping and sexual intimacy. The path model explained 48% of the variance in marital satisfaction. The results suggest that enjoyable couple activity, common dyadic coping, and sexual intimacy should be considered in the design of interventions to enhance urban Chinese women's marital satisfaction in the early years of marriage.

• Health Policy and Management
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• v.31 no.2
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• pp.158-172
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• 2021

Background: Metabolic syndrome has been known as a risk of cardiovascular disease. Meanwhile, high sensitivity C-reactive protein (hs-CRP) is used as a predictor of cardiovascular disease. In this paper, we aimed to investigate the association between hs-CRP and metabolic syndrome. Method: A total of 7,633 were chosen as the study population from the 7th Korea National Health and Nutrition Examination Survey dataset (2016-2017). Our dependent variable was whether an individual had metabolic syndrome or not, and the independent variable of interest was hs-CRP which was categorized into three groups. The chi-square tests and hierarchical logistic regression analyses reflecting survey characteristics were conducted. All analyses were stratified by gender. Results: According to the adjusted model with all covariates, compared to individuals having the low risk of hs-CRP, those having its average risk were more likely to have metabolic syndrome in men (odds ratio [OR], 1.41; 95% confidence interval [CI], 1.12-1.76) and women (OR, 1.69; 95% CI, 1.33-2.16). Individuals having the high risk was not significantly different in men; however, they were more likely to have metabolic syndrome in women (OR, 2.03; 95% CI, 1.28-3.23). Conclusion: In an upcoming aging society, it is important to reduce the risk of metabolic syndrome to improve population health. This study suggests that hs-CRP may be used as a marker of the risk of metabolic syndrome in a gender-specific way, thereby contributing to enhancing awareness of the risk of metabolic syndrome among the general public.

• The Korean Journal of Pain
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• v.35 no.4
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• pp.447-457
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• 2022

Background: Ultrasound-guided genicular nerve radiofrequency (RF) procedures are of interest in the management of chronic knee pain. A wide variety of demographic, clinical, and procedural characteristics can affect treatment success. This study aimed to determine predictive factors to provide superior treatment outcomes. Methods: The demographic, clinical, and technical data of patients who received genicular nerve RF for knee pain between September 2016 and September 2021 were evaluated. A positive outcome was defined as at least 50% pain relief on a pain score for at least 6 months. Logistic regression analysis was performed to determine the factors associated with a successful response to genicular RF. Results: Among 206 patients who underwent genicular RF, 62% of the patients reported successful outcomes at 6 months. In the multivariate model, targeting 5 nerves (odds ratio [OR], 6.184; 95% confidence interval [CI], 2.291-16.690; P < 0.001) was the most significant predictor of successful outcomes. Multivariable logistic regression analysis showed that prognostic genicular nerve block with a 50% cut-off value (OR, 2.109; 95% CI, 1.038-4.287; P = 0.039), no opioid use (OR, 2.753; 95% CI, 1.405-5.393; P = 0.003), and depression (OR, 0.297; 95% CI, 0.124-0.713; P = 0.007) were the predictive factors significantly associated with response to genicular RF. Conclusions: Clinical and technical factors associated with better treatment outcomes were ultimately targeting more nerves, performing prognostic block, no opioid use, and no depression. These results are expected to be considered when selecting patients for genicular RF.

• Journal of Trauma and Injury
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• v.35 no.1
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• pp.25-33
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• 2022

Purpose: The scoring system for traumatic liver injury (SSTLI) was developed in 2015 to predict mortality in patients with polytraumatic liver injury. This study aimed to validate the SSTLI as a prognostic factor in patients with polytrauma and liver injury through a generalized estimating equation analysis. Methods: The medical records of 521 patients with traumatic liver injury from January 2015 to December 2019 were reviewed. The primary outcome variable was in-hospital mortality. All the risk factors were analyzed using multivariate logistic regression analysis. The SSTLI has five clinical measures (age, Injury Severity Score, serum total bilirubin level, prothrombin time, and creatinine level) chosen based on their predictive power. Each measure is scored as 0-1 (age and Injury Severity Score) or 0-3 (serum total bilirubin level, prothrombin time, and creatinine level). The SSTLI score corresponds to the total points for each item (0-11 points). Results: The areas under the curve of the SSTLI to predict mortality on post-traumatic days 0, 1, 3, and 5 were 0.736, 0.783, 0.830, and 0.824, respectively. A very good to excellent positive correlation was observed between the probability of mortality and the SSTLI score (γ=0.997, P<0.001). A value of 5 points was used as the threshold to distinguish low-risk (<5) from high-risk (≥5) patients. Multivariate analysis using the generalized estimating equation in the logistic regression model indicated that the SSTLI score was an independent predictor of mortality (odds ratio, 1.027; 95% confidence interval, 1.018-1.036; P<0.001). Conclusions: The SSTLI was verified to predict mortality in patients with polytrauma and liver injury. A score of ≥5 on the SSTLI indicated a high-risk of post-traumatic mortality.

• Korean Journal of Culture and Social Issue
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• v.21 no.2
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• pp.159-176
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• 2015

This study was conducted to revalidate CQS and to examine the factors influencing cultural intelligence among Korean students studying abroad. 143 Korean students in USA and Canada were participated in the survey. Confirmatory factor analysis identified a model with four factors and CQS has negative correlation with acculturation stress and academic stress but positive correlation with subjective wellbeing. This findings suggest that CQS is a reliable and valid scale. Hierarchical regression analyses confirmed that personality is more significant predictor than cultural experiences for CQS. Discussion focuses on the importance of the findings, limitations and future directions.

• Journal of Yeungnam Medical Science
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• v.40 no.1
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• pp.65-77
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• 2023

Background: This study aimed to compare clinical outcomes between surveillance and adjuvant therapy (AT) groups after R0 resection for cholangiocarcinoma (CCA). Methods: A total of 154 patients who underwent R0 resection for CCA at the Daegu Catholic University Medical Center between January 2010 and December 2019 were included. Overall survival (OS) and progression-free survival (PFS) were analyzed. Results: The median follow-up duration was 899 days. There were 109 patients in the AT group and 45 patients in the surveillance group. The patients in the AT group were younger (67 years vs. 74 years, p<0.001) and included more males (64.2% vs. 46.7%, p=0.044). The proportion of patients with stage III CCA was larger in the AT group than in the surveillance group (13.8% vs. 2.2%, p=0.005). In addition, AT did not improve OS (5-year OS rate, 69.3% in the AT group vs. 64.2% in the surveillance group, p=0.806) or PFS (5-year PFS rate, 42.6% in the AT group vs. 48.9% in the surveillance group, p=0.113). In multivariate analysis using the Cox proportional hazards model, stage III CCA (hazard ratio [HR], 10.81; 95% confidence interval [CI], 2.92-40.00; p<0.001) was a significant predictor of OS. American Society of Anesthesiologists classification II (HR, 0.50; 95% CI, 0.31-0.81; p=0.005), and American Joint Committee on Cancer stages II (HR, 3.14; 95% CI, 1.25-7.89; p=0.015) and III (HR, 8.08; 95% CI, 2.80-23.32; p<0.001) were independent predictors of PFS. Conclusion: AT after R0 resection for CCA did not improve OS or PFS.

• Journal of Preventive Medicine and Public Health
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• v.56 no.3
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• pp.255-263
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• 2023

Objectives: The study investigated the association between indoor air pollution (IAP) and risk factors for acute respiratory infection (ARI) symptoms in children under 5 years of age. Methods: A cross-sectional study was conducted using data derived from Indonesia Demographic and Health Survey in 2017. Binary logistic regression modeling was employed to examine each predictor variable associated with ARI among children under 5 years of age in Indonesia. Results: The study included a total of 4936 households with children. Among children under 5 years old, 7.2% reported ARI symptoms. The presence of ARI symptoms was significantly associated with the type of residence, wealth index, and father's smoking frequency, which were considered the sample's socio-demographic characteristics. In the final model, living in rural areas, having a high wealth index, the father's smoking frequency, and a low education level were all linked to ARI symptoms. Conclusions: The results revealed that households in rural areas had a substantially higher level of reported ARI symptoms among children under 5 years old. Furthermore, the father's smoking frequency and low education level were associated with ARI symptoms.

• Steel and Composite Structures
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• v.45 no.2
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• pp.205-218
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• 2022

Proper calculation of splitting tensile strength (STS) of concrete has been a crucial task, due to the wide use of concrete in the construction sector. Following many recent studies that have proposed various predictive models for this aim, this study suggests and tests the functionality of three hybrid models in predicting the STS from the characteristics of the mixture components including cement compressive strength, cement tensile strength, curing age, the maximum size of the crushed stone, stone powder content, sand fine modulus, water to binder ratio, and the ratio of sand. A multi-layer perceptron (MLP) neural network incorporates invasive weed optimization (IWO), cuttlefish optimization algorithm (CFOA), and electrostatic discharge algorithm (ESDA) which are among the newest optimization techniques. A dataset from the earlier literature is used for exploring and extrapolating the STS behavior. The results acquired from several accuracy criteria demonstrated a nice learning capability for all three hybrid models viz. IWO-MLP, CFOA-MLP, and ESDA-MLP. Also in the prediction phase, the prediction products were in a promising agreement (above 88%) with experimental results. However, a comparative look revealed the ESDA-MLP as the most accurate predictor. Considering mean absolute percentage error (MAPE) index, the error of ESDA-MLP was 9.05%, while the corresponding value for IWO-MLP and CFOA-MLP was 9.17 and 13.97%, respectively. Since the combination of MLP and ESDA can be an effective tool for optimizing the concrete mixture toward a desirable STS, the last part of this study is dedicated to extracting a predictive formula from this model.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.155-166
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• 2024

Purpose : This study aims to identify key factors for predicting dropout risk at the university level and to provide a foundation for policy development aimed at dropout prevention. This study explores the optimal machine learning algorithm by comparing the performance of various algorithms using data on college students' dropout risks. Methods : We collected data on factors influencing dropout risk and propensity were collected from N University. The collected data were applied to several machine learning algorithms, including random forest, decision tree, artificial neural network, logistic regression, support vector machine (SVM), k-nearest neighbor (k-NN) classification, and Naive Bayes. The performance of these models was compared and evaluated, with a focus on predictive validity and the identification of significant dropout factors through the information gain index of machine learning. Results : The binary logistic regression analysis showed that the year of the program, department, grades, and year of entry had a statistically significant effect on the dropout risk. The performance of each machine learning algorithm showed that random forest performed the best. The results showed that the relative importance of the predictor variables was highest for department, age, grade, and residence, in the order of whether or not they matched the school location. Conclusion : Machine learning-based prediction of dropout risk focuses on the early identification of students at risk. The types and causes of dropout crises vary significantly among students. It is important to identify the types and causes of dropout crises so that appropriate actions and support can be taken to remove risk factors and increase protective factors. The relative importance of the factors affecting dropout risk found in this study will help guide educational prescriptions for preventing college student dropout.

• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.28 no.2
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• pp.229-237
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• 2024

Backgrounds/Aims: While patients with borderline resectable pancreatic cancer (BRPC) are a target population for neoadjuvant chemotherapy (NAC), formal guidelines for neoadjuvant therapy are lacking. We assessed the perioperative and oncological outcomes in patients with BRPC undergoing NAC with FOLFIRINOX for patients undergoing upfront surgery (US). Methods: The AHPBA criteria for borderline resectability and/or a CA19-9 level > 100 µ/mL defined borderline resectable tumors retrieved from a prospectively populated institutional registry from 2007 to 2020. The primary outcome was overall survival (OS) at 1 and 3 years. A Cox Proportional Hazard model based on intention to treat was used. A receiver-operator characteristics (ROC) curve was constructed to assess the discriminatory capability of the use of CA19-9 > 100 µ/mL to predict resectability and mortality. Results: Forty BRPC patients underwent NAC, while 46 underwent US. The median OS with NAC was 19.8 months (interquartile range [IQR], 10.3-44.24) vs. 10.6 months (IQR, 6.37-17.6) with US. At 1 year, 70% of the NAC group and 41.3% of the US group survived (p = 0.008). At 3 years, 42.5 % of the NAC group and 10.9% of the US group survived (p = 0.001). NAC significantly reduced the hazard of death (adjusted hazard ratio, 0.20; 95% confidence interval, 0.07-0.54; p = 0.001). CA19-9 > 100 µ/mL showed poor discrimination in predicting mortality, but was a moderate predictor of resectability. Conclusions: We found a survival benefit of NAC with FOLFIRINOX for BRPC. Greater pre-treatment of CA19-9 and multivessel involvement on initial imaging were associated with progression of the disease following NAC.