Perceived Quality of Social Network and the Risk of Depression Among Low-Income Workers in South Korea

BACKGROUND: Nonregular workers in South Korea are exposed to lower income and adverse job environment.  Under this stressful occupational environment, coping resources are protective factors against the risk of depression. Particularly, having access to a social network is an important asset during stressful situations. Social networks provide tangible resources needed to cope with immediate problems and emotional support to shorten stressful responses, possibly resulting in reduced psychological consequences. In addition to having a social network, the quality of the network also matters for adequate resource mobilization. Four concepts to measure the quality of a social network were proposed: 1) frequency of regular contact, 2) trustful members, 3) possible social support mobilization, and 4) influential figures within network. The four attributes appear to affect a social network’s utility when coping resources are needed. However, it is not clear whether these attributes are significantly associated with variance of depression risk when the network’s size is controlled. This study examined the association between these attributes and the risk of depression, controlled for demographic and clinical confounders and network size.

METHODS: A cross-sectional survey method was used for data collection from three corporations that hired nonregular workers, including cashiers, janitors, and building security personnel in Seoul, South Korea. In total, 333 workers participated in a self-administered survey after verbal informed consent. To measure the attributes of a social network, as proposed by Chen et al (2009), the Personal Social Capital Scale’s subdomain, “bonding capital,” was used. To measure depression risk, the Hopkins Symptom Checklist (HSCL)’s depression section was used. Multivariate regression and logistic regression were conducted to examine the association among the four attributes for quality of network and depression risk when controlled for network size and confounders. To avoid multicollinearity among the attributes, only one attribute of network quality was examined in a model.

RESULTS: In results from the multivariate regression models, frequency of interaction (p < .01), trustful members (p < .001), and possible social support mobilization (p < .001) were significantly associated with depression severity. Having influential members within the network did not show a significant correlation (p > .05). Interestingly, the effect size of a network’s size on depression severity was largely decreased when the attributes of the network were included in the analytic models. In logistic regression models, workers with one unit increase in trustful member and possible social support mobilization were .52 and .62 times less likely to have clinical depression (p< .01). Reduction in the effect size of a network’s size were observed, as well.

IMPLICATIONS: Having a network that can provide social support, that consists of trustful members, and that maintains frequent interaction seems to be an important resource for coping with toward reducing depression risk. The benefits of a larger social network seem largely explained by its quality. Therefore, social workers are recommended to provide skills and education to strengthen the quality of social networks so that nonregular workers can rely on the social network during stressful events.