A complex systems approach to psychopathology proposes that general principles lie in the dynamic patterns of psychopathology, which are not restricted to specific psychological processes like symptoms or affect. Hence, it must be possible to find general change profiles in time series data of fully personalized questionnaires. In the current study, we examined general change profiles in personalized self-ratings and related these to four measures of treatment outcome (International Symptom Rating, 21-item Depression Anxiety and Stress Scale, daily symptom severity, and self-reflective capacity). We analyzed data of 404 patients with mood and/or anxiety disorders who completed daily self-ratings on personalized questionnaires during psychotherapy. For each patient, a principal component analysis was applied to the multivariate time series in order to retrieve an univariate person-specific time series. Then, using classification and regression methods, we examined these time series for the presence of general change profiles. The change profile classification yielded the following distribution of patients: no-shift (n = 55; 14%), gradual-change (n = 52; 13%), one-shift (n = 233; 58%), reversed-shift (n = 39; 10%) and multiple-shifts (n = 25; 6%). The multiple-shift group had better treatment outcome than the no-shift group on all outcome measures. The one-shift and gradual-change groups had better treatment outcome than the no-shift group on two and three outcome measures, respectively. Overall, this study illustrates that person-specific (idiographic) and general (nomothetic) aspects of psychopathology can be integrated in a complex systems approach to psychopathology, which may combine "the best of both worlds." (PsycInfo Database Record (c) 2023 APA, all rights reserved).

中文翻译：

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两全其美的？个性化评估中精神病理学的一般原则。

精神病理学的复杂系统方法提出，一般原则在于精神病理学的动态模式，这些模式并不局限于症状或情感等特定的心理过程。因此，必须能够在完全个性化的调查问卷的时间序列数据中找到一般的变化概况。在当前的研究中，我们检查了个性化自我评分的一般变化概况，并将其与治疗结果的四项指标相关联（国际症状评分、21 项抑郁焦虑和压力量表、每日症状严重程度和自我反思能力）。我们分析了 404 名患有情绪和/或焦虑障碍的患者的数据，这些患者在心理治疗期间完成了个性化问卷的每日自我评分。对于每位患者，对多变量时间序列应用主成分分析，以便检索单变量个人特定时间序列。然后，使用分类和回归方法，我们检查了这些时间序列是否存在一般变化概况。变化概况分类产生以下患者分布：无变化（n = 55；14%）、渐进变化（n = 52；13%）、一变化（n = 233；58%）、反向变化(n = 39; 10%) 和多班制 (n = 25; 6%)。在所有结果指标上，多次轮班组的治疗结果均优于不轮班组。在两项和三项结果指标上，一班组和渐进组的治疗结果分别优于不班组。总体而言，这项研究表明，精神病理学的具体（个体）和一般（规律）方面可以整合到精神病理学的复杂系统方法中，这可能会结合“两全其美”。（PsycInfo 数据库记录 (c) 2023 APA，保留所有权利）。