Latent class patterns of work-life balance changes among Korean SME workers during COVID-19 based on organizational support and psychosocial health
Year: 2025
Type: article
Study design: Observational Study
Abstract: The COVID-19 pandemic disrupted work-life balance (WLB), particularly among workers in small and medium-sized enterprises (SMEs). This study aimed to classify patterns of WLB changes and identify associated factors using the Job Demands-Resources model as a theoretical framework. A cross-sectional survey was conducted among 503 SME employees in South Korea between July and September 2020. Latent class analysis identified WLB change patterns, and multinomial logistic regression compared factors across classes. Three latent classes were identified: stable (Class 1, 81.0%), worsened (Class 2, 11.4%), and improved (Class 3, 7.6%). Compared to Class 1, Class 2 was more likely to include individuals with higher economic status (OR = 2.163) and less likely to perceive strong organizational support (OR = 0.466). Compared to Class 1, Class 3 included more individuals with better psychosocial health and higher adherence to personal infection prevention (OR = 3.499). Compared to Class 3, individuals in Class 2 were more likely to have poorer psychosocial health (OR = 32.827), and less likely to report a supportive organizational environment (OR = 0.443). Workplace-level infection control scores were significantly higher in Class 3 than in other classes (p < .001). Distinct WLB patterns were observed among SME workers during COVID-19. Psychosocial health, economic status, infection prevention, and organizational support significantly influenced class membership. Identifying and supporting vulnerable groups during future public health crises is essential through targeted, workplace-level interventions.
Source: Scientific Reports
Authors: Sung-Sook Lee, Su-mi Cho, Eun-Hi Choi
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,690
Award: G1178436721
OpenAlex ID: W4417092217
