Ong Anthony D, Wang Lijuan, Fang Yuan, Zhang Guangjian, Joiner Raquael J, Wilcox Kenneth T, Bergeman C S
Department of Psychology, Cornell University.
Department of Psychology, University of Notre Dame.
Emotion. 2025 Jun;25(4):1060-1064. doi: 10.1037/emo0001465. Epub 2024 Dec 5.
The inertia-instability paradox poses an intriguing question in depression research: How can the affective experiences of depressed individuals demonstrate both resistance to change and fluctuation? Prior studies examining this paradox have faced limitations, including small sample sizes, analytic approaches prone to biased parameter estimates, and inconsistent results. Using data from 842 adults ( = 54.31, = 13.25, age range: 18-88; 58.2% female) collected over 56 consecutive days, we applied dynamic structural equation modeling to quantify individualized indices of mean levels, variability, instability, and inertia of negative affect. When adjusting for shared variances among affect dynamic measures, depressive symptoms were uniquely associated with both higher mean levels and inertia of negative affect. However, neither variability nor instability demonstrated unique links to depressive symptoms after accounting for the mean and inertia. Findings indicate that greater predictability in day-to-day negative affect is an important dynamic feature of depression. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
惯性-不稳定性悖论在抑郁症研究中提出了一个有趣的问题:抑郁症患者的情感体验如何既表现出对变化的抵抗又表现出波动?此前研究这一悖论的研究存在局限性,包括样本量小、分析方法容易产生有偏差的参数估计以及结果不一致。我们使用连续56天收集的842名成年人(年龄范围:18-88岁;58.2%为女性)的数据,应用动态结构方程模型来量化消极情绪的平均水平、变异性、不稳定性和惯性的个体指标。在调整情感动态测量之间的共享方差后,抑郁症状与消极情绪的较高平均水平和惯性均存在独特关联。然而,在考虑了平均水平和惯性之后,变异性和不稳定性均未显示出与抑郁症状的独特联系。研究结果表明,日常消极情绪中更高的可预测性是抑郁症的一个重要动态特征。(PsycInfo数据库记录(c)2025美国心理学会,保留所有权利)