How do social networks, perception of social isolation, and loneliness affect depressive symptoms among Japanese adults?

Author:

Kushibiki NatsuhoORCID,Aiba Miyuki,Midorikawa HaruhikoORCID,Komura Kentaro,Sugawara Daichi,Shiratori Yuki,Kawakami Naoaki,Ogawa TakafumiORCID,Yaguchi Chie,Tachikawa HirokazuORCID

Abstract

Objective This study aims to elucidate the complex relationship among social isolation, loneliness, and perception of social isolation and its influence on depressive symptoms by evaluating a hypothetical model. This understanding is essential for the formulation of effective intervention strategies. Methods We conducted an online survey on Japanese adults (N = 3,315) and used the six-item Lubben Social Network Scale to assess the size of their social networks. We employed a single question to gauge their perception of social isolation. Loneliness was assessed using the three-item UCLA Loneliness Scale, and depressive symptoms were examined using the Patient Health Questionnaire-9. Structural equation modeling was employed to test the hypothesized model. Results The final model demonstrated satisfactory fit with data (χ2 (1) = 3.73; not significant; RMSEA = 0.03; CFI = 1.00; TLI = 1.00). The size of social network demonstrated a weak negative path to loneliness and depressive symptoms (β = −.13 to −.04). Notably, a strong positive association existed between perception of social isolation and loneliness (β = .66) and depressive symptoms (β = .27). Additionally, a significant positive relationship was found between loneliness and depressive symptoms (β = .40). Mediation analysis indicated that perception of social isolation and loneliness significantly intensified the relationships between social networks and depressive symptoms. Conclusions Results indicate that interventions of psychological approaches, such as cognitive–behavioral therapy, are effective in reducing the perception of social isolation and loneliness, which may lead to the prevention of depressive symptoms. Future longitudinal studies are expected to refine and strengthen the proposed model.

Funder

Research Institute of Science and Technology for Society

Publisher

Public Library of Science (PLoS)

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