Work

The heterogeneity of insomnia symptoms for emerging workers in the digital economy: Latent profile and network analysis

Year: 2024

Type: article

Abstract: Although insomnia symptoms is a common public health issue, few studies pay attention to insomnia symptoms among emerging workers in the digital economy. In this study, a total of 1093 emerging workers were recruited. Latent profile analysis was used to investigate the heterogeneity profiles and the relationship between job characteristics and these profiles. Additionally, core symptoms of insomnia were explored through network analysis. Latent profile analysis identified four insomnia profiles: severe insomnia without daytime dysfunction (8.8%), good sleepers (39.6%), mild insomnia (41.7%), and moderate to severe insomnia (9.9%). Job characteristics (e.g. daily working duration, intensity, and performance measurement system) significantly affected the profiles. Network analysis revealed that four profiles had similar network structures, but the edge and strength were varied. The implication for preventing and intervening insomnia symptoms for emerging workers in the digital economy has been discussed.

Source: Journal of Health Psychology

DOI: 10.1177/13591053241274472

Authors: Ying Huang, Ruobing Zheng, Xiaxin Xiong, Yanping Chen, Wanqing Zheng, Rongmao Lin

Institutions: Fujian Normal University, Fujian Polytechnic Normal University, University of Groningen

Language: English

Topic: Sleep and related disorders

Subfield: Experimental and Cognitive Psychology

Field: Psychology

Domain: Social Sciences

SDGs: Decent work and economic growth, Good health and well-being

Open Access status: bronze

OpenAlex ID: W4402680706