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Self‐esteem Is Mostly Stable Across Young Adulthood: Evidence from Latent STARTS Models
Author(s) -
Wagner Jenny,
Lüdtke Oliver,
Trautwein Ulrich
Publication year - 2016
Publication title -
journal of personality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.082
H-Index - 144
eISSN - 1467-6494
pISSN - 0022-3506
DOI - 10.1111/jopy.12178
Subject(s) - trait , psychology , self esteem , autoregressive model , variance (accounting) , longitudinal study , analysis of variance , longitudinal data , depressive symptoms , developmental psychology , stability (learning theory) , demography , statistics , mathematics , cognition , psychiatry , accounting , machine learning , sociology , computer science , business , programming language
How stable is self‐esteem? This long‐standing debate has led to different conclusions across different areas of psychology. Longitudinal data and up‐to‐date statistical models have recently indicated that self‐esteem has stable and autoregressive trait‐like components and state‐like components. We applied latent STARTS models with the goal of replicating previous findings in a longitudinal sample of young adults ( N = 4,532; M age = 19.60, SD = 0.85; 55% female). In addition, we applied multigroup models to extend previous findings on different patterns of stability for men versus women and for people with high versus low levels of depressive symptoms. We found evidence for the general pattern of a major proportion of stable and autoregressive trait variance and a smaller yet substantial amount of state variance in self‐esteem across 10 years. Furthermore, multigroup models suggested substantial differences in the variance components: Females showed more state variability than males. Individuals with higher levels of depressive symptoms showed more state and less autoregressive trait variance in self‐esteem. Results are discussed with respect to the ongoing trait–state debate and possible implications of the group differences that we found in the stability of self‐esteem.