• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.31-48
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• 2021

The purpose of this study was to provide an understanding of the trajectories of multidimensional health among older adults, including depression, chronic diseases, and cognitive function. Data were drawn from the 1-6 waves of the Korean Longitudinal Study of Ageing(KLoSA), and a sample of 2,059 respondents aged 65 and older at baseline was used for the analyses. Latent growth curve models and growth mixture models were used to explore the changes in depression, chronic diseases, cognitive function, and heterogeneous trajectories among them. One-way ANOVAs with Scheffé post-hoc analysis and chi-square tests were used to find differences in sociodemographic characteristics, health behaviors, and life satisfaction across the latent trajectory classes. Latent growth curve models revealed that depressive symptoms and the number of chronic diseases increased over time, while cognitive function showed gradual decreases. Three heterogeneous patterns of multidimensional health trajectories were identified: normal aging, increase in chronic diseases, and chronic deterioration. Significant differences were observed in sociodemographic characteristics, health behaviors, and life satisfaction across the three latent classes. In particular, low educational attainment, household income, and life satisfaction were associated with the chronic deterioration class. Based on the findings, we discussed suggestions for health promotion education targeting older adults. This study also emphasizes the importance of home economics education in promoting health literacy across the life course.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.4
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• pp.1-11
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• 2016

Recently numerous studies are conducted to estimate the human personality from the online social activities. This paper develops a comprehensive model for political attitude estimation leveraging the Facebook Like information of the users. We designed a Facebook Crawler that efficiently collects data overcoming the difficulties in crawling Ajax enabled Facebook pages. We show that the category level selection can reduce the data analysis complexity utilizing the sparsity of the huge like-attitude matrix. In the Korean Facebook users' context, only 28 criteria (3% of the total) can estimate the political polarity of the user with high accuracy (AUC of 0.82).

• The Mathematical Education
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• v.57 no.4
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• pp.393-412
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• 2018

Teacher quality is a key factor that determines quality of education. Being aware of this, the Korean government and teachers have been striving to improve teachers' professionalism. Research about the impacts of efforts to enhance teacher professionalism on students' academic achievement and course satisfaction, however, is extremely limited. This study sought to advance our understanding of the relationship between these factors by analyzing what teacher characteristics impact students' achievement and satisfaction. To this end, the study drew on the middle and high school data from 3rd to 6th year survey of the Seoul Educational Longitudinal Study. Structural equational modeling were used as the main approach. Latent profile analysis, a kind of mixture modeling analysis, were used as needed. This study found that teachers' participation in instruction enhancement activity and professional development impact students' attitude toward mathematics lessons and their perception on class atmosphere, and ultimately impact their academic achievement as well as their overall satisfaction in the course. In addition, teachers' use of EBS textbooks and videos impact 3rd grade high schoolers' academic achievement. These findings suggest that effort to improve teacher professionalism positively impact students' academic achievement and course satisfaction, although there is a difference according to the year grade. This study provides implications for education policy makers and teacher educators.

• Journal of Korean Society of Forest Science
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• v.112 no.2
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• pp.248-257
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• 2023

Because of various societal changes, such as the recent improvement in income levels and extension of the flexible work system, the demand for forest recreation activities and their use patterns are undergoing a change. Accordingly, it is necessary to identify the characteristics of each type through the segmentation of the overall forest recreation and welfare markets and to plan differentiated policies for each market type. This study classifies the forest recreation and welfare activities according to four types of users (i.e., passive usage type, ordinary type, active lover type, and indifferent type) using the Latent Class Analysis and examines their demographic and socioeconomic characteristics to explain the differences between the groups. Three policy implications were derived from the results obtained: 1) the group experiencing forest recreation welfare is subdivided; 2) the socioeconomic characteristics that distinguish the groups undertaking forest recreation activities were identified; and 3) the policy targets and characteristics that can increase the experience of forest recreation welfare were identified. This study is insightful as it suggests differentiated policies for each group and proposes policy measures to move to the desirable group.

• 한국노년학
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• v.39 no.2
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• pp.305-323
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• 2019

In recognition of the increasing social attention paid to the notion of how to die well, this study explored what it is that middle-aged and older Koreans think of as "dying well." Specifically, it was aimed at classifying the perceptions people middle-aged and older have regarding dying well. To this end, we used data from the National Survey on Well-Dying, which was conducted in 2018 by the Korea Institute for Health and Social Affairs, and employed Latent Class Analysis. The demographic characteristics of each of the classified subgroups were identified through technical statistics. The types identified were multilayered depending on the imminence of death, perspectives of the last stages before dying, and the meaning of death in the context of social relationships. These types differed according to gender and subjective health conditions. Based on our findings in this study, we put forward policy suggestions about awareness improvement of personal and social levels, promoting on comprehensive death preparation, providing a system to reduce the cost of medical and nursing expense at the end of one's life, promoting of the right to self-determination regarding death, raising social attention to groups that are least prepared for dying well.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.193-203
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• 2019

The study participants are nurses who work at three general hospitals in M City, who used structured questionnaires to list 214 people from July 17 to August 7, 2017. Analysis of the collected data was carried out using SPSS WIN 21.0. and M plus 7.00 to analyze latent classes depending on the type of nursing managers' leadership. This study showed that the type of nursing managers' leadership has in analyzing latent classes influences nurses' job performance and turnover intention. Because there is a strong influence on the job performance and the turnover intention so that nurses can be highly aware of transformation-transaction-emotion leadership, the managers of the nursing organization need to foster effective leadership. Training programs are needed to improve nurses' job performance through transformational, transactional, and emotional leadership, and to foster nursing manager's leadership skills to better reflect the turnover intention.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.739-754
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• 2022

Usually, text data consists of many variables, and some of them are closely correlated. Such multi-collinearity often results in inefficient or inaccurate statistical analysis. For supervised learning, one can select features by examining the relationship between target variables and explanatory variables. On the other hand, for unsupervised learning, since target variables are absent, one cannot use such a feature selection procedure as in supervised learning. In this study, we propose a word selection procedure that employs topic models to find latent topics. We substitute topics for the target variables and select terms which show high relevance for each topic. Applying the procedure to real data, we found that the proposed word selection procedure can give clear topic interpretation by removing high-frequency words prevalent in various topics. In addition, we observed that, by applying the selected variables to the classifiers such as naïve Bayes classifiers and support vector machines, the proposed feature selection procedure gives results comparable to those obtained by using class label information.

• Journal of the Korea Convergence Society
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• v.12 no.8
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• pp.267-277
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• 2021

This study was done with collected and analyzed data using the convenient sampling method on 349 middle school students located in the metropolitan area in order to verify the effect of instructors verbal and nonverbal communications on instructor trust and class commitment in middle school sports clubs. As a result of analyzing the collected data, First, as a result of correlation analysis using the total number of items between sub-factors of latent variables, all correlation coefficients showed a positive (+) significant relationship. Second, as a result of the effect of verbal and nonverbal communications on instructor trust, it was found that the influence of spatial language, appearance language, body language, and linguistic factors were significantly explained in order. Third, as a result of the effect of verbal and nonverbal communications on class flow, it was found that class commitment was significantly explained in the order of appearance language, spatial language, and linguistic factors. Fourth, as a result of the influence of instructor's trust on class commitment, it was found that only the exercise capacity factor significantly explained class commitment. This study provides basic academic data to plan and create interactions with school sports club instructors and students.

• The Mathematical Education
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• v.60 no.4
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• pp.493-508
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• 2021

This study aims to examine the effects of learner-centered mathematical instruction perceived by middle school students such as discussion learning, self-directed learning, and cooperative learning on their math self-efficacy and engagement in mathematics class. Moreover, it attempts to verify if there are differences in the mean of latent variables and effect among groups divided based on achievement level. Research results are as follows. First, discussion learning did not have a direct effect on students' engagement in mathematics class, but still created an indirect effect on it through math self-efficacy. Self-directed learning and cooperative learning created a direct effect on engagement in mathematics class as well as an indirect effect through self-efficacy on mathematics. Second, high-achievement group had a higher perception of discussion learning, self-directed learning, and cooperative learning than a low-achievement group, and showed a higher level of math self-efficacy and engagement in mathematics class. Third, there were significant differences among groups, in the effect of discussion learning on self-efficacy in mathematics, effect of self-directed learning on self-efficacy in mathematics, and effect of math self-efficacy on engagement in mathematics class. Thus, this study offers meaningful implications for the role of math teachers as assistants in learning for learner-centered math classes.

• Clinical and Experimental Pediatrics
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• v.62 no.9
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• pp.325-333
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• 2019

Allergic diseases, including allergic rhinitis, asthma, and atopic dermatitis, are common heterogeneous diseases that encompass diverse phenotypes and different pathogeneses. Phenotype studies of allergic diseases can facilitate the identification of risk factors and their underlying pathophysiology, resulting in the application of more effective treatment, selection of better treatment responses, and prediction of prognosis for each phenotype. In the early phase of phenotype studies in allergic diseases, artificial classifications were usually performed based on clinical features, such as triggering factors or the presence of atopy, which can result in the biased classification of phenotypes and limit the characterization of heterogeneous allergic diseases. Subsequent phenotype studies have suggested more diverse phenotypes for each allergic disease using relatively unbiased statistical methods, such as cluster analysis or latent class analysis. The classifications of phenotypes in allergic diseases may overlap or be unstable over time due to their complex interactions with genetic and encountered environmental factors during the illness, which may affect the disease course and pathophysiology. In this review, diverse phenotype classifications of allergic diseases, including atopic dermatitis, asthma, and wheezing in children, allergic rhinitis, and atopy, are described. The review also discusses the applications of the results obtained from phenotype studies performed in other countries to Korean children. Consideration of changes in the characteristics of each phenotype over time in an individual's lifespan is needed in future studies.