Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

September 25, 2023


Pages


DOI

Article

Does Work Engagement Effectively Predict Subjective Well-Being? : A Meta-Analysis Using R Statistical Software


Authors

Hui Ding Affiliation:
School of Marxism, Anhui Vocational College of Defense Technology, Lu’an, Anhui, China
and Shoujing Si Affiliation:
School of economic and trade management, Anhui Vocational College of Defense Technology, Lu’an, Anhui, China


Abstract

Does work engagement effectively predict subjective well-being? In this paper, we investigated the relationship between work engagement and subjective well-being by synthesizing 176 effects from 59 studies involving 21927 subjects. The results showed that work engagement were positively correlated with subjective well-being, while job burnout were negatively correlated with subjective well-being. Literature sources significantly adjusted the relationship among work engagement, job burnout and subjective well-being. The paper proved that work engagement and subjective well-being are closely related, and literature sources may play a moderating role.


Keywords

Meta-analysis, work engagement, subjective well-being, R Statistical Software, 91E99


Citation

Ding, H. & Si, S. (2023). Does work engagement effectively predict subjective well-being? : A meta-analysis using r statistical software. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.01128

Published by: Engineering Journals

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