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

verifiedthin profile · Applied Mathematics and Nonlinear Sciences · 2023

Ding, Hui; Si, Shoujing

10.2478/amns.2023.2.01128 · CrossRef: verified

How this was studied

paradigm: positivistpurpose: explanatory causaldesign: meta analytic synthesisidentification: nonetime: cross sectionaldata: quantitative survey

A meta-analytic synthesis — it pools many primary studies rather than running a single design, so there is no single-study diagram.

analysis: meta analysis · validity (validity): internal unclear · external addressed · construct addressed · statistical addressed · classifier confidence 0.85

What this article reports

The findings we extracted from this work, normalized into Principia’s relationship form (X → Y). Each feeds the synthesized models below.

employee well beingwork engagement

r = 0.45 · k=59 · grade C · unverified

Models this article informs

The meta-analytic priors this article contributes evidence to — its place in the broader synthesis.

In the authors’ words

The article’s own abstract.

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.

What the literature says about it

Attributed, open-access quotes from other works that cite this article, plus the citation-graph verdict tally. Corroborations and disputes, in one place — the honest-broker view.

0 supporting

No open-access quotations have been captured yet.

Assembled from Principia’s registry — bibliographic record, extracted effect sizes, the models they inform, and open-access citing literature.