The drivers of work engagement: A meta-analytic review of longitudinal evidence

ABSTRACT

Work engagement is currently one of the most popular outcomes in occupational health psychology. According to the motivational process within the job demands-resources (JD-R) framework, job resources stimulate work engagement, which in turn fosters job performance. While the general positive impact of job resources on work engagement is well established, it remains unclear how different types of job resources differentially predict work engagement over time. In our meta-analytic review, we identified 55 longitudinal studies that investigate the impact of various job resources on work engagement. To uncover the drivers of work engagement, we examined the differential impact of job resources on work engagement at group level, leader level, and organisational level via meta-analytic structural equation modelling. The findings suggest that job resources at each of the three levels predict work engagement over time. However, organisational-level resources (reflecting how the work is organised, designed and managed) contribute much more strongly to work engagement than group-level, and leader-level resources. All three levels of job resources and work engagement are highly stable. We advocate for interventions at any of the three levels. However, interventions at the organisational-level are most promising for enhancing work engagement and we thus strongly recommend strengthening those job resources.     

The job demands-resources model: A meta-analytic review of longitudinal studies

The job demands-resources (JD-R) model is an influential framework to understand how job characteristics foster employee well-being. Differing from the cross-sectional focus of most JD-R model reviews, this meta-analytic review uses longitudinal evidence to validate the essential assumptions within the JD-R model. We highlight two aspects: (1) The assessment of the methodological quality of the available longitudinal studies, and (2) the examination of the essential assumptions – the impact of job characteristics on well-being, and vice-versa – with meta-analytic structural equation modelling (metaSEM). We included 74 studies and evaluated their quality. Eighteen studies suffered from serious methodological shortcomings, whereas 29 studies (39%) were considered high-quality studies. Our meta-analytic structural equation models confirmed the essential assumptions simultaneously. The quality of the studies also had an influence on the goodness-of-fit indices. The models with reciprocal assumptions between job characteristics and well-being fitted the data best. The findings of this meta-analytic review suggest that the JD-R model is an excellent theoretical basis to assess employee well-being for a broad range of organisations. However, more research is needed to clarify the reciprocal relationships between job characteristics and employee well-being, as well as the different influences of challenging and hindering job demands on work engagement.