Intolerance of Uncertainty and Climate Change Experience as Driving Forces of Climate Anxiety: Insights from a Network Perspective

A plethora of studies have pointed to startling worldwide rates of people reporting anxiety related to climate change. However, uncertainties persist regarding the psychological processes that contribute to climate anxiety and how this anxiety can lead to adaptive behaviors (i.e., pro-environmental behaviors) and maladaptive consequences (i.e., impairments in daily functioning). In this study, we took inspiration from decades of basic research on anxiety that emphasizes that the way individuals cope with the unknown and do not tolerate uncertainty can hinder adaptive behaviors and lead to functional impairments. Therefore, we investigated the relationships among intolerance of uncertainty, the experience of climate change, as well as climate anxiety and it (mal)adaptive outcomes. To achieve this, we constructed two network models: a graphical Gaussian model (GGM) to explore the network's structure, potential cluster of variables, and influential nodes; and a directed acyclic graph (DAG) to examine the probabilistic dependencies among variables from data from an international unselected sample (n = 728). Our results indicate that both intolerance of uncertainty and the experience of climate change appear as driving forces of the entire network structure. We position this study within innovative computational network approaches to create data-driven models of climate anxiety.