• Korean Journal of Health Education and Promotion
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• v.19 no.2
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• pp.73-98
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• 2002

This study was carried out to investigate the relationship between social support, social network and health behaviors as surveyed by cross-sectional study in 744 rural people aged above 30 of a community dwelling sample of one county for 6 days of July in 2000. Objectives of this study was in order to establish an effective health promotion. The sample was accrued by face to face interview of direct visiting from clustered sampling method. Interview was conducted by trained medical students with the questionnaire consisted of socio-demographic data, health behavior, social support and social network based on previous literature. The summarized results were as follows: 1. There were significant difference in the level of social support and social network by general characteristic variables except occupation and residency type(p〈0.05). 2. There were significant difference in knowledge about hypertension, smoking status, status of physical exercise, diet patterns by social support and social network in spite of variation of social support and social network subconcept(p〈0.05). And there were significant difference in alcohol drinking status, body weight control and diet pattern according to level of social network(p〈0.05). But smoking status by social support and network results opposite direction(p〈0.05). 3. There were no regular or consistent result in the relationship between social support, social network and health behavior. 4. Major predictors for health behavior on the multiple logistic regression that included general characteristic, social support and social network were age, instrumental social support and worry about health. Significant variables of multiple logistic regression for health behavior that included social support(instrumental and emotional) and social network were instrumental social support and social network. These results suggest that only a instrumental element and social network may be associated with health behavior. Inconsistent with prior research in these some item, a positive consistent relationship was not found between social support, social network and health behavior. So the study should be replicated to determined the reliability of our findings.

• Korean Journal of Health Education and Promotion
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• v.28 no.4
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• pp.39-49
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• 2011

Objectives: This study was to examine the association between structural and functional characteristics of social network and self-rated health in middle-aged Korea population. We also explored gender difference in the relationship between social network and health. Methods: Data were collected from individuals aged 40-69 years old participating in the 2005 survey for the Korean Genome & Epidemiology Study. We examined the association between social network, social support, social conflict and self-rated health using multiple logistic regression analysis stratified by gender. Results: The extent and contact frequency of close people, and social participations were associated by not only the positive function but also the negative function of social network. Both the positive and negative functions of social network affected self-rated health. The relationship between the function of social network and health showed a gender difference: only positive function was significantly associated with health in men while only negative function had significant relationship with health in women. Conclusions: Social support and social conflict affected the health in both genders through different ways. The ambivalent effect of social network on health should be explored further.

• Annals of Geriatric Medicine and Research
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• v.20 no.3
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• pp.149-159
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• 2016

Background: Since the mid-20th century, the ways in which social networks and older adults' health are related have been widely studied. However, few studies investigate the relationship between self-rated health and position in a complete social network of one entire Korean rural village. This study highlights use of a complete network in health studies. Methods: Using the Korean Social Life and Health Project, the population-based data of adults aged 60 or older and their spouses in one myeon in Ganghwa island (Ganghwa-gun, Incheon, Korea), Incheon, Korea (with a 95% response rate), this study built a $1,012{\times}1,012$ complete social network matrix of the village. The data were collected from 2011 to 2012, and 731 older adults were analyzed. The ordered logistic models to predict self-rated health allowed us to examine social factors from socio-demographic to individual community activities, ego-centered network characteristics, and positions in a complete network. Results: From the network data, 5 network components were identified. Even after controlling for all other factors, if a respondent belonged to a segregated component, the probability that he or she reported good health dropped substantially. Additionally, high in-degree centrality was connected to greater self-rated health. Conclusion: This finding highlights the importance of social position not only from the respondents' point of view but also from the entire village's perspective. Even if a respondent maintained a large social network, when all of those social ties belonged to a segregated group in the village, the respondent's health suffered from this segregation.

• Health Policy and Management
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• v.21 no.4
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• pp.493-510
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• 2011

Objectives : This study aims to explore how social support and social network are related with health behavior. Methods : The target population was 12,449 people in Chungcheongbuk-do. The sample was accrued for the period of 3 months in 2008 by face to face interview of direct visiting from systematic sampling method. The instruments used in this study were social support, social network and health behavior. Results : There was significant difference in the level of social support and social network by sex, age, educational level, occupation, and monthly income(p<0.05). There was significant difference in the level of social support by alcohol drinking, physical exercise. There was significant difference in the level of social network by smoking, alcohol drinking, physical exercise, obesity(p<0.05). Multivarite analysis shows significant difference in the level of social instrumental support by smoking, physical exercise. It shows significant difference in the level of social emotional support by smoking. It also shows significant difference in the level of social network by smoking, physical exercise. Conclusion : These results suggest that social support and social network may be associated with health behavior. Because this study was cross sectional research, the order was not found between social support, social network and health behavior. Through a study on monitoring, we will obtain more information for relationship.

• Journal of Korean Academy of Nursing
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• v.40 no.1
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• pp.88-98
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• 2010

Purpose: The purpose of this study was to identify the social network types of elders and to identify differences among latent classes by social network. Methods: The data of 312 elders used in this study were collected from health, welfare, and other facilities and from elders living in the community. The interviews were conducted from July 16 to September 30, 2007 using a standard, structured questionnaire. Descriptive statistics, one way ANOVA with the SPSS 15.0 program and latent class analysis using Maximum Likelihood Latent Structure Analysis (MLLSA) program were used to analyze the data. Results: Using latent class analysis, social network types among older adults were identified as diverse for 58.0% of the sample, as family for 34.0%, and as isolated for 8.0%. The health status of respondents differed significantly by network type. Elders in diverse networks had significantly higher health status and elders in isolated networks had significantly lower physical health status on average than those in all other networks. Conclusion: The results of this study suggest that these network types have important practical implications for health status of elders. Social service programs should focus on different groups based on social network type and promote social support and social integration.

• Korean Journal of Health Education and Promotion
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• v.33 no.3
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• pp.1-11
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• 2016

Objectives: The challenging issue of public health program is to strengthen partnership and network between health resources. This study identified the structure and characteristics of school health program network. Methods: In this paper we collected data from schools and organizations in 4 local communities in 2014 that participated to school health program. Using social network analysis techniques we measured the number of component, diameter, density, average degree, node centralization for each network. Results: We determined that networks shared some common organizational structure such as less density, low average degree, and short diameter. Networks were dominated by the health center, and directions of collaborations between nodes were mostly one-way. Conclusions: These findings can help to depict the network of school health program. The further research is necessary to define causal relationship between network effectiveness and public health outcomes.

• Journal of Preventive Medicine and Public Health
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• v.46 no.1
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• pp.28-38
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• 2013

Objectives: This study aimed to collect information that will help enhance the social networks and improve the quality of life among elderly people by observing the relationship between their social network and health-related quality of life (HRQoL) and by analyzing social network factors affecting HRQoL. Methods: This study was based on the 2008 Community Health Survey in Yeoncheon County. Three hundred elders were included in the study population. We compared the revised Lubben Social Network Scale (LSNS-R) score and Euro quality of life-5 dimensions health status index by demographic characteristics and chronic disease prevalence. We analyzed the data using multiple regression and tobit regression by setting the HRQoL as the dependent variable and social network and other characteristics as the independent variables. We analyzed social network factors by using factor analysis. Results: The LSNS-R score differed significantly according to age and existence of a spouse. According to the results from the hierarchical multiple regression analysis, the LSNS-R explained 0.10 of the variance and LSNS-R friends factor explained 0.10 of the variance. The tobit regression indicated that the contribution of the LSNS-R family size factor to the regression coefficient of the independent variable that affected the HRQoL was $B_T$=2.96, that of the LSNS-R family frequency factor was $B_T$=3.60, and that of LSNS-R friends factor was $B_T$=5.41. Conclusions: Social networks among elderly people had a significant effect on HRQoL and their networks of friends had a relatively higher effect than those of family members.

• The Journal of Information Systems
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• v.32 no.3
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• pp.41-61
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• 2023

Purpose This study aims to categorize the types of health, analyze the effects among health types based on network analysis find the most important type of health, and explain whether the results between health types vary depending on demographic characteristics. Design/methodology/approach This study investigated individual physical, clinical, mental, and social health(social capital and social support) levels through a survey of 100 people. Network analysis was applied to the survey data to confirm the degree centrality of nodes. Furthemore, we investigated the differences in core nodes according to gender and age groups. Findings According to the analysis result, social support was the most important health type in the entire group. Furthermore, the importance of health type was different depending on the characteristics of the groups. In the case of men, clinical health was the most important health type, and social support was analyzed to be the most important for women. In the case of young people, clinical health was the most important health type, and mental health was the most important health type in the middle-aged.

• The Korean Journal of Health Service Management
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• v.7 no.3
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• pp.177-192
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• 2013

The present study investigated the effect of area-specific social networks on urban workers life satisfaction. For this, 356 adults over age 20 were interviewed from June 17th 2013 to June 29th 2013. The findings are as follows: First, the closeness of family network index demonstrates that participants with higher affective support have higher life satisfaction. In addition, stronger extended family network brings more life satisfaction and so does a bigger friendship network. Secondly, the extended family network explains 17.6% of the variance in social networks follows by family network, other network, and friendship network, respectively. The closeness variable of social networks yields statistical significance on all categories of networks. The affective support level in the closeness variable of social networks shows differences as well; family network positively associates with life satisfaction. The purposes of this research are to investigate the actual conditions of urban workers' life satisfaction and the influence of family, extended family, friendship, and other variables on life satisfaction. If social networks have an influence on life satisfaction, to find the domain of social networks that holds the most influences on life satisfaction is an important ground in the process of implementing regional welfare.

• Korean Journal of Health Education and Promotion
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• v.29 no.1
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• pp.1-11
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• 2012

Objectives: The nurse visiting health service named Customized Visiting Health Care Program(CVHCP) requires the service innovations incorporating community support into a local service network. The purpose of this study was to assess the community network in CVHCP and inform improvement in this network. Methods: We used Social Network Analysis(SNA) in one CVHCP at H city. Network links were generated by self-administered questionnaires by the 14 community resource centers who quantified their links to all other 25 agents on the list. Links were analyzed by a dichotomous scale for any experience of collaboration and a scored scale of 0 to 3 for level of collaboration using UCINET v6. Results: A list of 14 agents was generated, and local network was dominated by the Public Health Center and a local welfare center named Unlimited Care Center(UCC). According to centrality score, UCC was the most prominent agent, and Public Health Center was the most influential agent, being a link in the pathway flow between other agents for 9.5% of contribution. CVHCP scored lower rank of prominent with 30.8% of other agents reported referring to it. Conclusions: Social network analysis provides a useful network description for informing and evaluation service network improvement in maximizing its service for the CVHCP.