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

被引:0
|
作者
Huang, Ying [1 ,2 ]
Zheng, Ruobing [1 ]
Xiong, Xiaxin [1 ,2 ]
Chen, Yanping [3 ]
Zheng, Wanqing [1 ]
Lin, Rongmao [1 ]
机构
[1] Fujian Normal Univ, Sch Psychol, Qishan Campus, Fuzhou 350117, Fujian, Peoples R China
[2] Fujian Polytech Normal Univ, Fuzhou, Peoples R China
[3] Univ Groningen, Groningen, Netherlands
关键词
insomnia symptoms; latent profile analysis; network analysis; emerging workers in the digital economy; job characteristics; SEVERITY INDEX;
D O I
10.1177/13591053241274472
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
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.
引用
收藏
页码:976 / 988
页数:13
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