A Mixed Model to Disentangle Variance and Serial Autocorrelation in Affective Instability Using Ecological Momentary Assessment Data
A Mixed Model to Disentangle Variance and Serial Autocorrelation in Affective Instability Using Ecological Momentary Assessment Data
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DOI：
10.1080/00273171.2016.1159177
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发表时间：
2016-01-01
影响因子：
3.8
通讯作者：
Verbeke, Geert
中科院分区：
文献类型：
--
作者：
Vansteelandt, Kristof;Verbeke, Geert
情感不稳定性，即随着时间的推移经历频繁和强烈波动的情绪的倾向，是包括边缘型人格障碍在内的几种精神障碍的核心特征。目前，影响往往是衡量与生态瞬时评估协议，产生的可能性，以量化的影响随着时间的推移不稳定。提出了一些线性混合模型来检查（诊断）组的情感不稳定的差异。该模型有助于现有的文献，同时估计方差和串行依赖组件的情感不稳定时，观察是不均匀的时间间隔与串行自相关（或情绪惯性）下降作为观察之间的时间间隔的函数。此外，该模型可以消除系统的趋势，考虑到受试者之间的差异和测试（诊断）组的差异，在串行自相关，短期以及长期的情感变异。该模型的实用性说明在饮食失调领域的情感不稳定的诊断组差异的研究。该模型的局限性在于它们涉及群体（而不是个体）差异，并且没有明确关注影响的昼夜节律或周期。
Affective instability, the tendency to experience emotions that fluctuate frequently and intensively over time, is a core feature of several mental disorders including borderline personality disorder. Currently, affect is often measured with Ecological Momentary Assessment protocols, which yield the possibility to quantify the instability of affect over time. A number of linear mixed models are proposed to examine (diagnostic) group differences in affective instability. The models contribute to the existing literature by estimating simultaneously both the variance and serial dependency component of affective instability when observations are unequally spaced in time with the serial autocorrelation (or emotional inertia) declining as a function of the time interval between observations. In addition, the models can eliminate systematic trends, take between subject differences into account and test for (diagnostic) group differences in serial autocorrelation, short-term as well as long-term affective variability. The usefulness of the models is illustrated in a study on diagnostic group differences in affective instability in the domain of eating disorders. Limitations of the model are that they pertain to group (and not individual) differences and do not focus explicitly on circadian rhythms or cycles in affect.