Bosley Hannah G, Soyster Peter D, Fisher Aaron J
University of California, Berkeley.
J Pers Oriented Res. 2019 Dec 30;5(2):101-113. doi: 10.17505/jpor.2019.09. eCollection 2019.
Studies of affect dynamics in psychopathology often focus on the prediction of broad constructs like subjective well-being and psychological health. Less is known about how fluctuation in affect over time relates to specific symptom measures (e.g., anxiety or depression), or how these domains change in treatment. A clinical sample of 32 adults with mood and anxiety disorders (13 generalized anxiety, 5 major depression, 14 comorbid) completed four daily assessments of positive (PA) and negative affect (NA) for 30 days prior to receiving cognitive behavioral treatment. Anxiety and depression symptom severity were assessed pre- and post-treatment. We calculated three metrics of affect dynamics for each person's PA and NA time series: (1) (experiencing emotional extremes, the standard deviation of a person's PA or NA vector); (2) (magnitude of point-to-point change in emotion, the vector's mean squared successive difference); and (3) (the extent to which emotions self-perpetuate over time, the lag-1 autocorrelation of the vector). Multiple regression models were run to test dynamics of positive and negative affect as between-subjects predictors of symptom severity and pre-to-posttreatment change in symptoms. Findings suggest NA dynamics are unrelated to depression symptom severity or treatment response, but we observed a specific effect of NA instability (MSSD) on both severity and response of anxiety symptoms. All PA dynamics were unrelated to anxiety or depression symptom severity. However, variability, instability, and inertia of PA were all found to relate to treatment response for both anxiety and depression symptoms. Taken together, our results suggest that affect dynamics have some specificity in their relationship to clinically relevant phenomena such as symptom severity and treatment outcomes at the between-subjects level of analysis.
精神病理学中情感动态的研究通常侧重于预测诸如主观幸福感和心理健康等宽泛的概念。对于情感随时间的波动如何与特定症状指标（如焦虑或抑郁）相关，或者这些领域在治疗中如何变化，我们了解得较少。一个由32名患有情绪和焦虑障碍的成年人组成的临床样本（13名广泛性焦虑症患者、5名重度抑郁症患者、14名共病患者）在接受认知行为治疗前30天，每天完成四次积极情感（PA）和消极情感（NA）评估。在治疗前后评估焦虑和抑郁症状的严重程度。我们为每个人的PA和NA时间序列计算了三个情感动态指标：（1）情感极端体验（一个人的PA或NA向量的标准差）；（2）情感逐点变化幅度（向量的均方连续差）；（3）情感随时间自我延续的程度（向量的滞后1自相关）。运行多元回归模型，以测试积极和消极情感动态作为症状严重程度和治疗前后症状变化的组间预测因素。研究结果表明，消极情感动态与抑郁症状严重程度或治疗反应无关，但我们观察到消极情感不稳定性（MSSD）对焦虑症状的严重程度和反应都有特定影响。所有积极情感动态与焦虑或抑郁症状严重程度均无关。然而，积极情感的变异性、不稳定性和惯性都与焦虑和抑郁症状的治疗反应有关。综上所述，我们的结果表明，在组间分析层面，情感动态与诸如症状严重程度和治疗结果等临床相关现象之间的关系具有一定的特异性。
