• Journal of Korean Academy of Nursing
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• v.49 no.6
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• pp.701-712
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• 2019

Purpose: Despite the high drinking rates and the complexity of drinking behaviors in adolescents, insufficient attention has been paid to their drinking patterns. Therefore, we aimed to identify patterns of adolescent drinking behaviors and factors predicting the distinct subgroups of adolescent drinking behaviors. Methods: We analyzed nationally representative secondary data obtained in 2017. Our final sample included 24,417 Korean adolescents who had consumed at least one glass of alcohol in their lifetime. To investigate patterns of drinking behaviors, we conducted a latent class analysis using nine alcohol-related characteristics, including alcohol consumption levels, solitary drinking, timing of drinking initiation, and negative consequences of drinking. Furthermore, we investigated differences in demographics, mental health status, and characteristics of substance use across the latent classes identified in our study. To do so, we used the PROC LCA with COVARIATES statement in the SAS software. Results: We identified three latent classes of drinking behaviors: current non-drinkers (CND), binge drinkers (BD), and problem drinkers (PD). Compared to the CND class, both BD and PD classes were strongly associated with higher academic year, lower academic performance, higher levels of stress, suicidal ideation, lifetime conventional or electronic cigarette use, and lifetime use of other drugs. Conclusion: Health professionals should develop and implement intervention strategies targeting individual subgroups of drinking behaviors to obtain better outcomes. In particular, health professionals should consider different characteristics across subgroups of adolescent drinking behaviors when developing the interventions, such as poor mental health status and other substance use among binge and problem drinkers.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.137-148
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• 2023

The purpose of this study is to classify the potential types of mental health of mothers of multicultural youth by applying Latent Profile Analysis, analyze the influence of predictors, and find out how differences in potential types affect parental efficacy. To this end, panel data for the 9th year (2019) of the Multicultural Youth Panel Survey (MAPS) were used. As a result of the analysis, first, the mental health types of mothers of multicultural adolescents were analyzed in the order of 'middle risk type of mental health'(class3) > 'high risk type of self-esteem'(class1) > 'high risk type of mental health'(class4) > 'cultural adaptation and daily life stress'(class2). Second, compared to the "class 1" group, the lower the family economy level of multicultural youth mothers, the lower the educational background of multicultural youth fathers (husbands) graduate from middle school, the lower the level of Korean, and the lower the level of communication with children, the higher the odds of belonging to the 'mental health medium risk' group (Ods). Third, compared to the 'middle risk type of mental health'(class3) and 'high risk type of mental health'(class4), the 'high risk type of self-esteem'(class1) group was found to have a significant positive (+) effect on parental efficacy.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.3
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• pp.237-254
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• 2021

Objectives: This study aims to classify the latent profiles in the exposure to hazard factors of salaried employees and test the determinants. Methods: Latent profile analysis(LPA) was conducted using data from the fifth Korean Working Conditions Survey(KWCS). 30,050 of salaried employees were the subjects of this study. After classifying the employees, multinomial logistic regression was used to test the determinants. Results: Salaried employees were classified with three latent profiles based on the exposure to the hazard factors. Employees included in class 1(32.8%) tend to experience low level of physical hazard factors, moderate level of psychological hazard factors, and high level of office work hazard factors. Employees included in class 2(61.8%) tend to be exposed to the moderate to high level of physical hazard factors, moderate to low level of psychological hazard factors, and low level of office work hazard factors. Employees included in class 3(5.4%) tend to experience high level of psychological and physical hazard factors, and moderate level of office work hazard factors. After classification, the demographic, health-, and employment-related variables were tested. Conclusions: This study clarified the features of each class, and proved that employees in class 3 are quite hazardous in that they are exposed to physical and psychological hazard factors much more frequently than other employees. Thus, this study can be used in predicting the high-risk employees and taking preemptive measures for preventing industrial accidents.

• Research in Community and Public Health Nursing
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• v.33 no.1
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• pp.74-83
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• 2022

Purpose: The purpose of this study was to identify latent classes of health-related quality of life trajectories in middle-aged women and investigate predictors for latent classes. Methods: This study utilized data from the 2^nd, the 4^th to the 7^th Korean Longitudinal Survey of Women & Families. The subjects included 1,351 women aged 40~45 years. The data was analyzed using latent class growth analysis and logistic regression. Results: Two trajectories were identified for health-related quality of life in middle-aged women; 'persistently good' and 'increasing' groups. Predictors for the 'increasing' group were lower economic status, higher depression, and lower perceived health status. Conclusion: This study showed that characteristics of the individual, symptom status, and health perceptions were associated with health-related quality of life in middle-aged women. It is necessary to provide effective intervention for latent classes of health-related quality of life trajectories based on physical, mental, and social factors.

• Journal of The Korean Association For Science Education
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• v.37 no.1
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• pp.113-123
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• 2017

The purpose of this study is to investigate engineering students' attitude toward convergence and relevance with engineering education accreditation, gender, and academic year and attitude toward convergence. To be specific, fist, we examined whether the instrument for measuring attitudes toward convergence were reliable and valid for engineering students. Second, we compared levels of attitudes toward convergence in terms of engineering education accreditation, gender and academic year. Third, latent classes, which were distinguished in terms of attitudes toward convergence, were identified. Participants were 2076 engineering students. By using factor analysis and Rasch analysis, validity and reliability of instrument measuring attitudes toward convergence were confirmed. The differences in attitude toward convergence in terms of engineering education accreditation experience, gender, and academic year were examined by independent t-test and ANOVA. There were significant differences in attitude towards convergence in terms of engineering education accreditation, gender, and academic year. Students who experience engineering education accreditation program and male and high academic year have higher levels of attitude toward convergence than others. Lastly latent class analysis (LCA) was conducted to identify subgroups underlying engineering students in terms of attitude toward convergence and five latent classes were identified. In addition, the chi-square results showed that there were significant relationships between identified latent classes and engineering education accreditation, gender, and academic year. Based on these results, engineering education considering students' characteristics and diversity in attitude toward convergence were discussed.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.17-39
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• 2020

The purpose of this study is to analyze the mathematical beliefs of students and teachers by Latent Class Analysis(LCA). This study surveyed 60 teachers about beliefs of 'nature of mathematics', 'mathematic teaching', 'mathematical ability' and also asked 1850 students about beliefs of 'school mathematics', 'mathematic problem solving', 'mathematic learning' and 'mathematical self-concept'. Also, this study classified each student and teacher into a class that are in a similar response, analyzed the belief systems and built a profile of the classes. As a result, teachers were classified into three types of belief classes about 'nature of mathematics' and two types of belief classes about 'teaching mathematics' and 'mathematical ability' respectively. Also, students were classfied into three types of belief classes about 'self concept' and two types of classes about 'School Mathematics', 'Mathematics Problem Solving' and 'Mathematics Learning' respectively. This study classified the mathematics belief systems in which students were categorized into 9 categories and teachers into 7 categories by LCA. The belief categories analyzed through these inductive observations were found to have statistical validity. The latent class analysis(LCA) used in this study is a new way of inductively categorizing the mathematical beliefs of teachers and students. The belief analysis method(LCA) used in this study may be the basis for statistically analyzing the relationship between teachers' and students' beliefs.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.335-346
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• 2015

The electronic commerce site (EC site) has become an important marketing channel where consumers can purchase many kinds of products; their access logs, including purchase records and browsing histories, are saved in the EC sites' databases. These log data can be utilized for the purpose of web marketing. The customers who purchase many product items are good customers, whereas the other customers, who do not purchase many items, must not be good customers even if they browse many items. If the attributes of good customers and those of other customers are clarified, such information is valuable as input for making a new marketing strategy. Regarding the product items, the characteristics of good items that are bought by many users are valuable information. It is necessary to construct a method to efficiently analyze such characteristics. This paper proposes a new latent class model to analyze both purchasing and browsing histories to make latent item and user clusters. By applying the proposal, an example of data analysis on an EC site is demonstrated. Through the clusters obtained by the proposed latent class model and the classification rule by the decision tree model, new findings are extracted from the data of purchasing and browsing histories.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.226-236
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• 2021

The purpose of this study is to analyze the type of latent profile for general high school students' subject selection criteria and to identify the characteristics of the latent class. The survey data of 1072 general high school students (male; 648, female; 424) in G city, Jeollabuk-do and the scale composed of 8 sub-factors: 'SAT orientation', 'academic achievement', 'ability orientation', 'pursuit of interest', 'teacher orientation', 'career development', 'others' recommendation', and 'subject availability' were used for latent profile analysis and cross-analysis between potential layers. As a result of the analysis, high school students' perceptions of subject selection were classified into four latent profiles. The four groups were named 'High Perception Type', 'Low Perception Type', 'Self-Directed Type', and 'Stability-Oriented Type' according to their types. It was found that there was a difference between the latent classes in the importance and performance level of the subject selection criteria. These results can help identify the subject selection tendencies of latent groups in the operation of the 2015 revised curriculum and the 2025 high school credit system that emphasizes the student-centered course selection curriculum and they can also provide customized course selection guidance considering individual differences.

• Research in Community and Public Health Nursing
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• v.31 no.2
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• pp.212-221
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• 2020

Purpose: This study aims to identify the types of health-related quality of life (QoL) based on the EuroQoL 5 Dimensions among community older people and predict the factors affecting these types. Methods: This study used data from the 2016 Korea Health Panel Survey, whose participants included 3,848 older people. The data were analyzed using the software jamovi 1.2.17 and Mplus 8.2 for latent class analysis. Results: The subgroups of the older people's health-related QoL were identified as three latent classes: General stable type (43.9%), pain-related low type (35.0%), and general low type (21.1%). The types and characteristics of health-related QoL among the latent classes differed. Comparing the difference between the general low type and general stable type, the subjects showed higher probability of belonging to the general stable type when they were men, younger, higher education level, employment, better subjective health, lower BMI and stress level, and no suicidal ideation. A comparison between the general low type and the pain-related low type showed that the subjects were more likely to be classified as the pain-related low type when they were younger, higher education, employment, and better subjective health. Conclusion: The results showed a significant heterogeneity in the types of health-related QoL among community older people, and the predictors for each type were not the same. These findings present basic data for cultivating nursing interventions that enhance health-related QoL.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.435-445
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• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.