Developmental Trajectories of Depression and Academic Achievement in Children: Based on Parallel Latent Growth Modeling

Abstract

Abstract: In order to explore the developmental trajectories of depression and academic achievement in China, self-reports and teacher ratings were used to collect three-year longitudinal data annually among 535 elementary school children in grade 3 and 4. The present study examined the predictive relations between depression and academic achievement through cross-lagged analysis and parallel latent growth modeling. The results indicated that: 1) Children’s depression and academic achievement were stable across three years. Depression negatively predicted academic achievement in the following year, but not vice versa. 2) The intercept of academic achievement negatively predicted the developmental slope of depression. These findings suggest that academic achievement might be a protective factor for depression among Chinese children, which enlightens future research on children’s emotional adjustment.

Key words: depression, academic achievement, cross-lagged analysis, latent growth modeling

摘要： 采用自我报告和教师评价对535名小学3～4年级儿童抑郁水平与学业成绩的发展状况进行了三次追踪，通过交叉滞后回归分析和平行潜变量增长模型，考察抑郁水平与学业成绩的发展轨迹及其之间的相互作用。结果发现：（1）儿童抑郁水平和学业成绩在三年中都较为稳定，三年中上一年抑郁水平可以负向预测下一年的学业成绩，反之则不能；（2）儿童学业成绩的初始水平可以负向预测抑郁水平的发展速度。研究表明：较高的学业成绩可能是抑郁水平发展过程中的保护因素，为儿童情绪健康的研究提供了新的实证依据。

关键词: 抑郁水平, 学业成绩, 交叉滞后模型, 潜变量增长模型

CLC Number:

B844

YAO Wenyu, ZHANG Wen, LIU Ying, ZHANG Simin, DING Xuechen, XU Gangmin. Developmental Trajectories of Depression and Academic Achievement in Children: Based on Parallel Latent Growth Modeling[J]. Studies of Psychology and Behavior, 2021, 19(2): 223-229.

姚文玉, 张雯, 刘影, 张思敏, 丁雪辰, 徐刚敏. 儿童抑郁水平与学业成绩的发展轨迹：基于平行潜变量增长模型[J]. 心理与行为研究, 2021, 19(2): 223-229.

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