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

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: <i>severe insomnia without daytime dysfunction</i> (8.8%), <i>good sleepers</i> (39.6%), <i>mild insomnia</i> (41.7%), and <i>moderate to severe insomnia</i> (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.

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Publication Details

Journal
Journal of Health Psychology
Published
2024-09-20
DOI
https://doi.org/10.1177/13591053241274472
Citations
5
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
2.54
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article

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

Rongmao Lin, Ruobing Zheng, Xia-Xin Xiong, Yanping Chen et al.
5 citations
Journal of Health Psychology
Mental Health Research Topics
2.54
article

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

Rongmao Lin, Ruobing Zheng, Xia-Xin Xiong, Yanping Chen, Ying Huang, Wan-Qing Zheng
article en
5 citations

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: <i>severe insomnia without daytime dysfunction</i> (8.8%), <i>good sleepers</i> (39.6%), <i>mild insomnia</i> (41.7%), and <i>moderate to severe insomnia</i> (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.

Journal of Health PsychologyVol. 30(5)
Fujian Normal University (CN), University of Groningen (NL)
Decent work and economic growth
Openalex Percentile: Top 10%
Mental Health Research Topics
2.54
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The heterogeneity of insomnia symptoms for emerging workers in the digital economy: Latent profile and network analysis — Rongmao Lin, Ruobing Zheng, et al. · Journal of Health Psychology (2024) | TGRS Research Map | TGRS