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Trajectories of Self-Esteem Development for Adolescence Based on China Family Panel Studies: A Piecewise Growth Mixture Model Analysis

Author

Listed:
  • Jiaqin Huang
  • Xin Xie
  • Yuxi Pan
  • Guangming Li
  • Fadi Zhang
  • Ningjing Cui

Abstract

Self-esteem has always been a hot research object in the field of adolescent mental health. But in longitudinal research, using a single slope to describe the trajectory of adolescent self-esteem is unrealistic. The piecewise growth mixture model (PGMM) was used to fit the data in this study. Selecting from China Family Panel Studies database, a total of 1,759 individuals were selected and their self-esteem (RSES) scores over the years were used as the tracking index. Based on the characteristics of the development trajectories of three latent classes, class 1 was referred to as “stable low level group,†class 2 was named “rapidly rising group,†and class 3 was referred to as “rapidly decrease group.†And there were two stages in the development process of self-esteem in the adolescent group. The slope of the stable low level group showed a significant downward trend in the first stage and a significant upward trend in the second stage, with a relatively flat development trajectory and relatively low self-esteem on the whole. The slope of the rapidly rising group showed an insignificant upward trend in the first stage and a significant rapid upward trend in the second stage. The rapidly decrease group showed a significant and rapid downward trend in the first stage and a significant and rapid upward trend in the second stage. In the development of self-esteem in adolescence, there were three latent classes in which the characteristics of development trajectories were different. Age of 14 is the turning point between the two stages of development.

Suggested Citation

  • Jiaqin Huang & Xin Xie & Yuxi Pan & Guangming Li & Fadi Zhang & Ningjing Cui, 2022. "Trajectories of Self-Esteem Development for Adolescence Based on China Family Panel Studies: A Piecewise Growth Mixture Model Analysis," SAGE Open, , vol. 12(2), pages 21582440221, April.
    • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221086611
    DOI: 10.1177/21582440221086611
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