Networks of happiness: applying a Network Approach to Well-Being in the General Population

Abstract

Even though well-being can be seen as a multidimensional construct, made up of a variety of interacting aspects, most studies examine total scores on well-being measures, treating well-being as a latent variable. This so-called common cause perspective assumes that aspects of well-being are mere effects of a common cause, namely well-being itself. The network approach moves away from this approach by suggesting that research should no longer focus only on the mean level of psychological constructs, but on the relations between the different aspects of a construct over time. Instead of a static, common cause approach to well-being, the network perspective views thoughts and feelings not as reflections but as constituents of well-being, treating them as agents in a causal system instead of passive indicators. In this paper, we applied the network approach to investigate how fluctuations in specific symptoms of well-being are associated with fluctuations in other symptoms of well-being. Based on a sample of 151 working adults with on average 32.66 data points collected over a five-day period, we found that in general, the low arousal emotion of feeling satisfied played a central role in the dynamics between various aspects of well-being in the momentary context of daily life. This means that feeling satisfied cannot just be seen as a passive indicator of well-being, but also as an active agent in a causal system that brings about other aspects of well-being. These results provide insight into daily dynamic processes related to the development of well-being over time and contribute to our understanding of well-being and how to improve it.