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Journal of Happiness Studies

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08.11.2023 | Research Paper

Dualfactor Model of Mental Health in Chinese Employees: A Latent Profile Analysis

verfasst von: Yi Xu, Sicheng Xiong, Bin Zhang, Yun Chen

Erschienen in: Journal of Happiness Studies | Ausgabe 8/2023

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Abstract

The dual-factor model emphasizes the integration of negative and positive indicators in the conceptualization of mental health. Yet, no research to date has used this model to describe employees with varying mental health characteristics. The current study used latent profile analysis (LPA) to identify groups of employees who shared certain mental health characteristics (i.e., who had the same profile), and also examined whether these profiles differed on sociodemographic and work-related factors. Participants were 15,123 full-time employees (58.6% women, aged 18–64 years) from 14 cities in Hunan province, China, who completed questionnaires in their work setting. LPA identified a four-profile solution as the best fitting mode: complete mental health group (21.5%), symptomatic but content group (23.7%), vulnerable group (20.9%), and troubled group (33.9%). The results of multinomial logistic regression showed that these profiles differed on sociodemographic and work-related factors, namely age, marital status, gender, daily hours of work, annual income, and occupational position. The current study is the first to apply the dual-factor model as a framework for identifying mental health profiles and their associated factors in a large-scale sample of Chinese adults. The findings have implications for developing specific prevention strategies and intervention policies tailored to employees’ different mental health profiles.

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Titel: Dualfactor Model of Mental Health in Chinese Employees: A Latent Profile Analysis
verfasst von: Yi Xu
Sicheng Xiong
Bin Zhang
Yun Chen
Publikationsdatum: 08.11.2023
Verlag: Springer Netherlands
Erschienen in: Journal of Happiness Studies / Ausgabe 8/2023
Print ISSN: 1389-4978
Elektronische ISSN: 1573-7780
DOI: https://doi.org/10.1007/s10902-023-00695-7

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