• Journal of Korean Society of Rural Planning
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• v.14 no.3
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• pp.63-73
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• 2008

The purpose of this study is to analyze the determinants of the digital divide at individual level and regional level in Korea, considering interaction between individual and the regional variables. Following results are obtained. First, individual level digital devide in the 16 different regions has been found in terms of Internet use, implying the needs for further analysis on impact of the regional factor in individual Internet use. Second, the result finds the impact of level-l individual variables, "gender, age, education, income and jobs" on digital divide, significantly at level 10% level. Third, the regional variables influencing the individual digital divide were not found at state level. However, regional factors might affect digital devide at county level. Study suggest some plans to reduce digital divide. First, the digital devide at individual level should be remedied by focusing on neglected class of people. Second, we need to approach the digital divide by analyzing in more detail, reflecting interactions of the regional variables and individual variables. Third, we should come up with a policy for mending the digital divide at regional level.

• Journal of Korean Academy of Nursing
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• v.38 no.2
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• pp.287-297
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• 2008

Purpose: The purpose of this study was to identify factors related to nurses' organizational citizenship behavior using multilevel analysis which included both nurse characteristics at individual levels and nursing unit characteristics at group levels. Methods: The sample was composed of 1,996 nurses who were selected from 182 nursing units in 28 hospitals in six metropolitan cities and seven provinces using cluster sampling. Data were collected using self-reported questionnaires from February to March 2006. Results: The results of the study indicated that individual level variables related to organizational citizenship behavior were religion, job position, clinical career, self efficacy, positive affectivity, and supervisor support. The group level variables related to organizational citizenship behavior were collective efficacy, number of nurses in a nursing unit, and the average salary level of a nursing unit. 30.9% of individual level variances of organizational citizenship behavior were explained by the nurses' individual level variables. The explanatory power of group level variables, which is related to group level variances of organizational citizenship behavior, was 75.5%. Conclusion: This research showed that it was necessary to develop appropriate strategies related to not only individual factors, but also higher-level organizational factors such as collective efficacy, to improve individual performances in the hospital.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.65-75
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• 2015

This paper analyzes the determinants of wage for the college and university graduates utilizing both individual-level and industry-level variables. We note that wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and industry-level (level-2) variables. Then, the assumption that individual wage is independent in the classical regression is violated. Therefore, this paper utilizes the hierarchical linear model (HLM). The major results are the followings. First, the multiple correspondence analysis including level-1 and 2 variables reveals that both level 1 and level 2 variables affects individual wages judging from the fact that the values of level 1 and level 2 variables differ across the different level of individual wage groups. Second, the decision tree analysis including level-1 and 2 variables shows that the most influential variable in wage determination is industry-level wage and the next is industry-level working hour, ages and sex in the decling order in. This suggests that the utilization of the HLM is appropriate since the characteristics of industry is important in determining the individual wage. Third, it is shown that the HLM model is the best compared to the other models which do not take level-1 and level-2 variables simultaneously into account.

• Korean Journal of Social Welfare
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• v.61 no.4
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• pp.137-161
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• 2009

In an effort to identify predictors of job performance, research studies in social work administration has been so far on the individual practitioners' levels of knowledge and skills, which could be used in a workplace. As the theoretical concept of organizational environment was fully introduced into social work administration research, however, studies on practitioners' job performance began to have interest in the team or the organizational level variables as well as individual level variables. Along the course of this tendency, this study attempted to test the effect of individual, team, and organizational level variables on the job performance of human service workers. The individual level variables consisted of knowledge, skills, job satisfaction, personality, and counter-productive work behaviors of workers. The team or the organizational level variables included situational constraint, organizational justice, job characteristics, government-dependency, and inter-organizational cooperation. Multi-level complex survey data collected by cluster sampling method from 314 practitioners in 23 organizations were analyzed using Hierarchial Linear Model. Results showed that both task and contextual performance were affected by individual, team, and organizational level variables in various ways.

• Health Policy and Management
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• v.32 no.1
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• pp.63-72
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• 2022

Background: Depression is a common disease around the world. Many studies are showing that mental health can be improved through physical activity, and daily regular exercise can reduce the negative effects of depression or depressive symptoms. In order to promote individual physical activity, a physical activity-friendly environment must precede. Therefore, this study attempted to confirm whether the number of sports facilities for all affects individual depression. Methods: Among the respondents to the 2018 Community Health Survey, data from 181,086 people excluding missing value were used. Descriptive and chi-square tests were performed to understanding the general characteristics of individual level variables. A multilevel logistic regression was conducted to confirm the effect of individual and regional level variables on depressive symptoms. Results: As a result of confirming the effect of individual characteristics on depressive symptoms, it was confirmed that both socioeconomic and health behavior factors had an effect. Similar results were shown in a model that considered regional level variables, and in the case of the number of sports facilities per population, people who belongs to smaller areas were more likely to have depressive symptoms (odds ratio, 0.98; 95% confidence interval, 0.97-0.99). Conclusion: As a result of the analysis, it was confirmed that both individual level and regional level variables had a significant effect on depressive symptoms. This suggests that not only individual level approaches but also regional level approaches are needed to improve individual depressive symptoms In particular, it may be possible to consider to increase the number of sports facilities in areas where the prevalence of depressive symptoms is high and the number of sports facilities is insufficient.

• Health Policy and Management
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• v.30 no.3
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• pp.355-365
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• 2020

Background: This study is aimed to verify individual and regional-level factors affecting the depression of Koreans and to develop social programs for improving the depressive status. Methods: This study used individual-level variables from the Korean Community Health Survey (2018) and used the e-regional index of the Korean Statistical Information Service as the regional-level variable. A multi-level logistic regression was executed to identify individual and regional-level variables that were expected to affect the extent of depressive symptoms and to draw the receiver operating characteristic curve to compare the volume of impact between variables from both levels. Results: The results of the multi-level logistic regression analysis in regards to individual-level factors showed that older age, female gender, a lower income level, a lower education level, not having a spouse, the practice of walking, the consumption of breakfast higher levels of stress, and having high blood pressure or diabetes were associated with a greater increase in depressive symptoms. In terms of regional factors, areas with fewer cultural facilities and fewer car registration had higher levels of depressive symptoms. The comparison of area under the curve showed that individual factors had a greater influence than regional factors. Conclusion: This study showed that while both, individual and regional-level factors affect depression, the influence of the latter was relatively weaker as compared to the first. In this sense, it is necessary to develop programs focused on the individual, such as social prescribing at the local or community-level, rather than the city and nation-level approach that are currently prevalent.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.935-946
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• 2016

In this paper, we analyzed wage determinants of the vocational high school graduates utilizing both individual-level and work region-level variables. We formulate the models in the way wage determination has multi-level structure in the sense that individual wage is influenced by individual-level variables (level-1) and work region-level (level-2) variables. To incorporate dependency between individual wages into the model, we utilize hierarchical linear model (HLM). The major results are as follows. First, it is shown that the HLM model is better than the OLS regression models which do not take level-1 and level-2 variables simultaneously into account. Second, random effects on sex, maester dummy and engineering dummy variables are statistically significant. Third, the fixed effects on business hours and mean wage of regular job for level-2 variables are statistically significant effect individual-level wages. Finally, parental education level, parental income, number of licenses and high school grade are statistically significant for higher individual-level wages.

• International Journal of Human Ecology
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• v.2 no.1
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• pp.135-152
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• 2001

The purpose of this study was to investigate the association of protective and risk factors with adolescent delinquency. Using nationally representative data from the National Longitudinal Study of Adolescent Health (Add Health) project, the delinquency level and the influence of individual characteristics, dyadic relationships in the family, school and peer variables on adolescent delinquency were examined by gender. Boys and girls differed in delinquency level with boys showing significantly higher delinquency than girls. The relative influence of protective and risk factors in individual, familial, peer, and school contexts differed by gender as well. More diverse variables influenced the delinquency level of girls than that of boys.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.512-520
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• 2021

Purpose: The purpose is to analyze a relationship between urban characteristics and individual characteristics on the health level of individuals. Method: This study analyzed the relationship between urban characteristics and individual characteristics on individual health level in 2016 for local governments in Korea using a hierarchical linear model. Results: It was found that urban characteristics, along with individual characteristics, have a significant effect on the health level of individuals. Although the degree of influence is very large, some variables are not statistically significant, so more detailed research is needed for future urban policy. Conclusion: Although urban characteristics affect an individual's health level, additional research is needed on the variables of individual urban policies.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.437-449
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• 2014

In this study, we analyzed an effect of area-environmental factor on breast cancer screening rates using multi-level analysis. It was intended for the KNHANES-IV. Total subjects were 14338. Among them, 4143 subjects met the inclusion criteria. When we applied only empty Model, a variance of breast cancer screening rates was 0.061 in each region. When we applied Model with individual level variables, the variance was 0.034. However, when we applied both Model with individual level variables and Model with area level variables, the variance was 0.023. We drew applied only individual level variables parallel applied 3 regional variances which could explain variance of inspection of breast cancer up to 18.04% compared with applied only individual level variables. Area level variables could reduce a variance of region. This means besides individual level variables. The group can share a same thing and can effect to breast cancer screening rates. We need to discover factors which area level variables and suggest that make a standard for inspection of breast cancer.