Latent Classes of Social Exclusion Experienced By Migrant Workers in South Korea and Their Impact on Loneliness

Background/purpose: Due to the COVID-19 pandemic, South Korea, which already had negative perceptions of migrant workers, has become even more exclusionary towards them. In particular, H2 visa workers are a socially excluded population compared to Korean workers. They experience various interconnected issues, not just limited to poverty while staying in Korea. H2 visa workers’ loneliness is a significant issue as many of them leave behind friends and family in their home country to work in Korea. Thus, the concept ‘social exclusion’ can help examine the harsh reality that H2visa workers face. However, previous studies on social exclusion did not fully examine the relationship between dimensions of social exclusion and its impact on H2 visa workers’ loneliness. To address this gap, the researchers used Latent Class Analysis(LCA) and Logistic Regression Analysis(LRA) to focus on this relationship.

Methods: For the analysis, researchers used data of 2,124 H2 visa workers who participated in the 2020 Survey on Immigrants’ living conditions and labor force. First, LCA was conducted to identify latent classes of social exclusion experiences based on the interrelationships among the ten indicators representing various types of exclusion: employment status, employment insurance coverage, occupational health and safety insurance coverage, financial difficulties, housing instability, bad health condition, unmet medical needs, discrimination, internet usage, and leisure dissatisfaction.

Second, LRA was used to examine whether the identified classes affect the dependent variable loneliness while controlling socio-demographic factors (gender, age, level of education, marital status, child status, proficiency in Korean, religion, years living in Korea, and cohabitation status). Loneliness was coded as a dichotomous variable (‘1’ for the presence and ‘0’ for the absence of loneliness) and used for the analysis.

Results: The LCA model generated four latent classes based on the evaluation of model fit indices: ‘Low Exclusion Group (G1, 46.8%)’. ‘Economic Exclusion Group (G2, 19.9%)’. ‘Multiple Exclusion Group (G3, 8.8%)’, and ‘Social protection exclusion group (G4, 24.5%)’.

The LRA results revealed that members of G2(OR=2.83, p<.001) and G3(OR=2.86, p<.001) had a higher probability of experiencing loneliness compared to those in G1. However, no specific relationship was found for G4.

Conclusions/Implications: The results indicated that members of G2 and G3 were more likely to feel lonely than those in G1. Since the most significant difference between G1 and G2/G3 was the presence of economic exclusion, the researchers confirmed the urgent need for interventions regarding economic exclusion. A lack of economic resources can make interacting with others and participating in external activities challenging, ultimately resulting in presence of loneliness. Although this study focused on foreign workers with H2 visas in Korea, it has high applicability to other nations with a predicted increase in migrant workers in the near future. Additionally, migrant workers are likely to experience social exclusion due to their status as immigrants and foreigners, the importance of this study is high because their loneliness seems unavoidable. Based on the research results, intervention measures can be suggested to address the economic difficulties and loneliness experienced by migrant workers.