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Description
Self-esteem, a fundamental aspect of an individual's perception of their own worth, has been extensively examined in psychological research. Based on a large and representative sample of 47,974 participants (mean age: 26.59 years; SD: 12.3; 61% female), and using the Rosenberg Self-Esteem Scale, one of the most widely used measures of self-esteem in psychological research, this study takes a novel approach to examine the structure of self-esteem. Utilizing network analysis techniques, our study focuses on the complex interactions among specific components of self-esteem, while also exploring differences in self-esteem across gender, age groups, and sociocultural contexts. Diverging from traditional methods, we employ Exploratory Graph Analysis (EGA) to uncover the underlying structure of self-esteem without presupposing the existence of latent constructs. Moreover, we utilize the Network Comparison Test (NCT), a resampling-based permutation testing method, to identify variations in the network structures across diverse populations. Our findings shed light on the subtle dynamics of self-esteem and its expressions within different groups, offering valuable insights for understanding this complex psychological construct.
