Multiple Trajectories and Predictors of Self-Esteem Change in Later Life: A Latent Growth Mixture Modeling Approach.

Abstract

Applying latent growth mixture modeling (GMM), this study delves into the examination of self-esteem trajectories in a sample of 5,597 older adults over a nine-year period. Four distinct patterns of self-esteem changes have emerged: low, decreasing, increasing, and high. Additionally, the study explores the relationships between each trajectory and various predictors encompassing demographic factors, socioeconomic status, health, and interpersonal relationships. The findings highlight the significance of these factors in predicting the likelihood of an individual following a specific self-esteem trajectory. Notably, maintaining employment, fostering satisfactory social relationships, and being free of frequent depressive feelings emerged as strong predictors for the stability and increase of high self-esteem. Intriguingly, an average or above-average income was unexpectedly associated with lower levels of self-esteem. The study emphasizes the contribution of GMM to advancing aging research.