ISSN 0439-755X
CN 11-1911/B

Acta Psychologica Sinica ›› 2021, Vol. 53 ›› Issue (11): 1215-1227.doi: 10.3724/SP.J.1041.2021.01215

• Reports of Empirical Studies • Previous Articles     Next Articles

Effects of family affective involvement on aging self-stereotypes: An analysis based on latent growth model

XU Ran, ZHANG Baoshan(), LIN Yao   

  1. School of Psychology, Shaanxi Normal University, 199 South Chang’an Road, Xi’an 710062, China
  • Received:2020-10-09 Published:2021-11-25 Online:2021-09-23
  • Contact: ZHANG Baoshan E-mail:zhangbs@snnu.edu.cn
  • Supported by:
    National Social Science Foundation of China(17BSH153)

Abstract:

In this study, a total of 257 older adults were followed up for one year, and the latent growth model and cross-lagged panel analysis were used to examine the developmental trajectories of family affective involvement and aging self-stereotypes in older adults and the causal relationship between the two. The results were as follows: (1) older adults’ perceptions of family affective involvement decreased linearly during the follow-up period while aging self-stereotypes increased linearly; (2) the initial level of family affective involvement negatively predicted the initial levels and increases in aging self-stereotypes; (3) the rate of decrease in family affective involvement predicted the increases of aging self-stereotypes over time; (4) cross-lagged panel analysis showed that family affective involvement negatively predicted aging self-stereotypes after six months. This study expands the existing research on family affective involvement and aging self-stereotypes. A better understanding of the causal effects of older adults’ affective involvement from family members on aging self-stereotypes can also help ameliorate intervention programs designed to reduce the internalization of aging stereotypes and improve negative aging self-stereotypes.

Key words: family affective involvement, aging self-stereotypes, developmental trajectories, latent growth modeling, cross-lagged panel analysis.