All the authors were supported by a Coordinated Research Grant ("BParent") from the French Community of Belgium (ARC Grant 19/24-100). M. Annelise Blanchard (as FRS-FNRS research follow) and Alexandre Heeren (as FRS-FNRS research associate) are also supported by the FRS-FNRS Belgian National Science Foundation. These funds did not exert any influence or censorship of any kind on the present work.

The notion of climate change anxiety has gained traction in the last years. Clayton & Karazsia ( 2020 ) recently developed the 22-item Climate Change Anxiety Scale (CAS), which assesses climate change anxiety via a four-factor structure. Yet other research has cast doubts on the very structure of the CAS by calling either for a shorter (i.e. 13 items) two-factor structure or for a shorter single-factor structure (i.e. 13 items). So far, these three different models have not yet been compared in one study. Moreover, uncertainty remains regarding the associations between the CAS and other psychological constructs, especially anxiety and depression. This project was designed to overcome these limitations. In a first preregistered study ( n = 305), we translated the scale into French and tested, via confirmatory factor analyses (CFA), whether the French version would better fit with a four-, two-, or single-factor structure, as implied by previous works. We also examined how the CAS factors related to depression, anxiety, and environmental identity. In a second preregistered study, we aimed at replicating our comparison between the three CFA models in a larger sample ( n = 905). Both studies pointed to a 13-item version of the scale with a two-factor structure as the best fitting model, with one factor reflecting cognitive and emotional features of climate change anxiety and the other reflecting the related functional impairments. Each factor exhibited a positive association with depression and environmental identity but not with general anxiety. We discuss how this two-factor structure impacts the conceptualization of climate change anxiety.

Background: The use of network analyses in psychology has increasingly gained traction in the last few years. A network perspective views psychological constructs as dynamic systems of interacting elements. Objective: We present the first study to apply network analyses to examine how the hallmark features of parental burnout — i.e., exhaustion related to the parental role, emotional distancing from children, and a sense of ineffectiveness in the parental role — interact with one another and with maladaptive behaviors related to the partner and the child(ren), when these variables are conceptualized as a network system. Participants and setting: In a preregistered fashion, we reanalyzed the data from a French-speaking sample (n = 1551; previously published in Mikolajczak, Brianda, Avalosse, & Roskam, 2018), focusing on seven specific variables: the three hallmark parental burnout features, partner conflict, partner estrangement, neglectful behavior toward children, and violent behavior toward children. Methods: We computed two types of network models, a graphical Gaussian model to examine network structure, potential communities, and influential nodes, and a directed acyclic graph to examine the probabilistic dependencies among the different variables. Results: Both network models pointed to emotional distance as an especially potent mechanism in activating all other nodes. Conclusions: These results suggest emotional distance as critical to the maintenance of the parental burnout network and a prime candidate for future interventions, while affirming that network analysis can successfully expose the structure and relationship of variables related to parental burnout and its consequences related to the partner and the child(ren).

This is a preprint (version January 19, 2022) of a manuscript that is undergoing peer-review for publication in a scientific journal. Analysis code, data, and supplementary materials can be found in the accompanying Open Science Framework project: https://osf.io/8647n/ TEMPORAL NETWORK APPROACH: A SCOPING REVIEW 2 Author Note