The architecture of psychological well-being: A network analysis study of the Ryff Psychological Well-Being Scale

The proliferation of mental health research is orienting its efforts towards the exploration of psychological well-being. One of the main burdens is the measurement challenges reported by the widely used Psychological Well-Being Scale (PWBS), which has often been criticized for inconsistencies between the theoretical and the empirical model. A potential alternative to understand the structure of psychological well-being is network models, which conceptualizes psychological phenomena as emerging systems of mutually connected variables. Employing exploratory graph analysis, we examined the network structure of the Spanish 29-item PWBS in a random sample of 1,404 adults. We estimated a regularized partial correlation network using the graphical LASSO algorithm in the item and dimension level. We tested the stability of both networks and identified the most important variables of the network. The PWBS network model revealed four dimensions, with self-acceptance, life purpose and environmental mastery clustering together. Node strength centrality suggested that self-acceptance is the most central dimension in the psychological well-being structure as measured by the PWBS. Despite the network model of psychological well-being did not replicate the theoretical structure of Ryff's model, it provides a novel conceptualization of psychological well-being and proposes target indicators for mental health interventions.