Deconstructing trait anxiety: a network perspective. Issue 3 (4th May 2018)

• Record Type: Journal Article
• Authors: Heeren, Alexandre; Bernstein, Emily E.; McNally, Richard J.
• Is Part Of: Anxiety, stress, and coping. Volume 31:Issue 3(2018)
• Page Start: 262
• Page End: 276
• Publication Date: 2018-05-04
• Subjects: Trait anxiety -- network analysis -- graph theory -- graphical gaussian model -- anxiety -- network theory of personality; Anxiety -- Periodicals; Anxiety -- Research -- Periodicals; Anxiety -- periodicals; Stress -- periodicals; Adaptation, Psychological -- periodicals; 616.8522
• DOI: 10.1080/10615806.2018.1439263
• Languages: English
• ISSNs: 1061-5806

Abstract

ABSTRACT: Background and objectives: For decades, the dominant paradigm in trait anxiety research has regarded the construct as signifying the underlying cause of the thoughts, feelings, and behaviors that supposedly reflect its presence. Recently, a network theory of personality has appeared. According to this perspective, trait anxiety is a formative construct emerging from interactions among its constitutive features (e.g., thought, feelings, behaviors); it is not a latent cause of these features. Design : In this study, we characterized trait anxiety as a network system of interacting elements. Methods : To do so, we estimated a graphical gaussian model via the computation of a regularized partial correlation network in an unselected sample ( N = 611). We also implemented modularity-based community detection analysis to test whether the features of trait anxiety cohere as a single network system. Results : We find that trait anxiety can indeed be conceptualized as a single, coherent network system of interacting elements. Conclusions : This radically new approach to visualizing trait anxiety may offer an especially informative view of the interplay between its constitutive features. As prior research has implicated trait anxiety as a risk factor for the development of anxiety-related psychopathology, our findings also set the scene for novel research directions.