• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.45-51
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• 2018

The purpose of the study was to examine the effects of family related factors (mothers' self-esteem, mothers' parenting stress, mothers' marital satisfaction, fathers' parenting involvement, and social support) on mothers' postpartum depression. The subjects were 797 households that were extracted from the $1^{st}$ wave of the Panel Study of Korean Children (PSKC). The study variables were measured using the survey questionnaires, and analyses of Pearson's correlation and multiple regression were conducted. Results showed that family related factors significantly predicted mothers' postpartum depression. Moreover, the most significant predictor was mothers' parenting stress, followed by marital satisfaction, self-esteem, fathers' parenting involvement, and social support. Study findings indicate that mothers' postpartum depression is attributed to not only personal but also family related factors. Our results suggest importance of parent education and family support along with social support.

• Journal of Genetic Medicine
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• v.18 no.1
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• pp.1-7
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• 2021

The oocyte quality is of great importance in infertility as it reflects the follicle developmental potential and further affects the embryo development, clinical pregnancy outcomes. The analysis of gene expression in somatic cells is an important study to better clinical in vitro fertilization (IVF) outcomes in embryo selection reflecting the appropriate communication between the oocyte and somatic cells. Specifically, somatic cell transcriptomic technology can help assess biomarkers of oocyte and embryo ability. The present article aims to overview the basic aspect of folliculogenesis and review studies involving changes in candidate gene expression of cumulus or granulosa cell related to clinical outcomes in human IVF.

• Asian Journal for Public Opinion Research
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• v.10 no.3
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• pp.230-253
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• 2022

Based on Goffman's dramaturgical theory and self-objectification framework, this study examined: 1) Chinese female's WeChat self-presentation, 2) the impact of WeChat usage on female self-objectification, and 3) the impact of self-objectification on WeChat self-presentation tactics. An online survey was conducted. The main findings include: 1) most of the participants chose to beautify their pictures and videos before they posted them, 2) the respondents attached higher importance to appearance-based body attributes than competence-based ones, 3) the most frequently applied self-presentation tactic was ingratiation, 4) WeChat usage was not a predictor of Chinese women's self-objectification, and, 5) along with extroversion, self-objectification had an impact on ingratiation, supplication, self-promotion, and exemplification. Meanwhile, use of the electronic curtain and audience sifting to control who can see a post and for how long demonstrated the empowerment of the users when they conduct self-presentation.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.101-130
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• 2023

The increasing cost, and demand for, household energy has increased attention to the phenomena of energy burdens. Despite this increased attention, a lack of consensus remains in pinpointing the strongest predictors, and geographic differences, that exist within the energy ecosystem. This study addresses this gap by utilizing a series of dummy variable regressions across cities, suburbs, and rural areas within Erie County, New York-a county noted to have particularly high energy burdens. Specifically, three types of predictor sets were incorporated into the methodology: a set of socioeconomic variables, physical variables, and a combination of both variable sets. The results of this study suggest that cities tend to have the highest electricity burdens. Despite the aging infrastructure in Erie County, high energy burdens were driven primarily by socioeconomic factors such as housing cost burden and poverty status. Lastly, this study explores various planning and policy implications Erie County can utilize to reduce energy burdens. In turn, this study highlights the importance of focusing policy efforts on existing social service programs to provide support to the region's neediest households.

• Journal of Hospice and Palliative Care
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• v.24 no.3
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• pp.174-183
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• 2021

Purpose: This study aimed to investigate the effects of the nursing practice environment and self-leadership on person-centered care provided by oncology nurses. Methods: This cross-sectional study included 145 nurses who worked in oncology wards at eight university hospitals in Seoul, Daejeon, and Chungcheong Province with at least six months of experience. Data were collected using a self-administered survey and analyzed using descriptive statistics, Pearson correlation coefficients, the t-test, analysis of variance, and hierarchical multiple regression analysis in SPSS version 26.0. Results: Person-centered care was significantly correlated with the nursing practice environment (r=0.27, P<0.001) and self-leadership (r=0.40, P<0.001), and the nursing practice environment was correlated with self-leadership (r=0.380, P<0.001). Hierarchical multiple regression analysis showed that the nursing practice environment was a significant predictor of person-centered care (β=0.31, P<0.001), after adjusting for covariates including monthly salary, total clinical career, and the position of oncology nurses. Self-leadership was a significant predictor of person-centered care (β=0.34, P<0.001) after controlling for the nursing practice environment, along with covariates. The final model explained 18.7% of the variance in personcentered care. Conclusion: Our findings emphasize the importance of the nursing practice environment and nurses' self-leadership for providing person-centered care in oncology care units. Educational programs to reinforce nurses' self-leadership and administrative support for nursing practice are necessary to improve oncology nurses' capability to provide person-centered care.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.3
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• pp.67-76
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• 2013

In this study we surveyed service satisfaction for the start-up support program and measured the relative importance of the factors that influence service satisfaction. The five service factors(physical facilities, finance and accounting, human resources, marketing, product development) were used to measure service satisfaction. Typically, the relative importance of predictors is assessed by simply comparing their standardized regression coefficients. However, when the predictors are correlated, regression coefficients cannot be used to explain variance shared by two or more predictors. The dominance analysis used by many researchers in recent years to measure the relative importance of predictor variables. In this article, we applied it in satisfaction research for the start-up support program. The results obtained by the dominance analysis are compared with the results obtained by multiple regression analysis. And satisfaction and relative importance of the five factors are analyzed by entrepreneurship motivation. These findings will contribute to the marketing research field relating to service satisfaction. Service satisfaction for the start-up support program can improve based on this study.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Journal of the Korean Home Economics Association
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• v.42 no.12 s.202
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• pp.161-174
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• 2004

The primary objective of this study was to employ Darden's store patronage model in order to investigate the role that shopping orientation and store attributes play in store patronage. The study sample consisted of 340 female university students residing in Seoul. The data was analyzed by using path analysis and factor analysis. The recreational shopping orientation played a greater role in influencing the importance of store attributes than did the convenience shopping orientation. Recreational shoppers want a variety of brands and convenience shoppers can be attracted by a convenient location and availability of parking. Six important store attributes(variety of products and price level, proximity, variety of trendy brands, store decor, sales promotion, sales personnel) have a differential influence on store patronage. Shopping orientation was a direct predictor of patronage behavior and mediated the relationship between shopping orientation and store attribute importance. The finding indicated that both the recreational shopping orientation and convenience shopping orientation can be used effectively to position store patronage in such a way as to provide a strong means for shoppers to satisfy their needs. The findings of this study demonstrated that South Korean female shoppers with different shopping orientation have different store attribute preference and store patronage. The results provide a basis for building a successful strategy to attract shoppers and generate sales. The study focused on a specific product category, i.e., women's apparel. To meet the needs of female apparel shoppers, further research is needed to learn more about the distinctive characteristics of Korean consumers that could be applied to a variety of jobs, ages and living areas.

• 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.

• The Journal of Korean Academic Society of Nursing Education
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• v.21 no.2
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• pp.168-181
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• 2015

Purpose: This study was conducted to determine the factors affecting the prevention of needle stick injury. Methods: Data collection was conducted during the period July 15-31, 2013 by a self-administered questionnaire involving 220 nurses working in 7 hospitals. The data was analyzed by SPSS v18 and AMOS v18. Results: Actions by nurses to prevent needle stick injury were directly and indirectly influenced by perceived benefits, attitude toward the behavior, perceived behavioral control, and intention underlying the behavior. Specially, perceived behavioral control is verified to have not only direct influence but also indirect influence on the performance of preventive action through the intention underlying the behavior. Also, perceived benefits indirectly influence the intention toward the behavior and performance of preventive action through attitude toward the behavior and perceived behavioral control. The predictor variables in this model are 52% explicable in terms of intention of prevention action against needle stick injury, and 66% explicable in terms of performance of preventive action. Conclusion: To ensure high performance of preventive action against needle stick injury, constructing not only the solution that inspires the intention toward behavior but also a system that can positively solve and improve obstructive factors in behavioral performance is of primary importance.