Location-scale modeling as an integrative approach to symptom dynamics during psychotherapy: An illustration with depressive symptoms.

IF 4.5 1区心理学 Q1 PSYCHOLOGY, CLINICAL Journal of consulting and clinical psychology Pub Date : 2024-09-01 Epub Date: 2024-05-23 DOI:10.1037/ccp0000892

Annette Brose, Peter Koval, Manuel Heinrich, Pavle Zagorscak, Johannes Bohn, Christine Knaevelsrud

{"title":"Location-scale modeling as an integrative approach to symptom dynamics during psychotherapy: An illustration with depressive symptoms.","authors":"Annette Brose, Peter Koval, Manuel Heinrich, Pavle Zagorscak, Johannes Bohn, Christine Knaevelsrud","doi":"10.1037/ccp0000892","DOIUrl":null,"url":null,"abstract":"Objective: Depressive symptom dynamics, including change trajectories and symptom variability, have been related to therapy outcomes. However, such dynamics have often been examined separately and related to outcomes of interest using two-step analyses, which are characterized by several limitations. Here, we show how to overcome these limitations using location-scale models in a dynamic structural equation modeling framework.Method: We introduce location-scale modeling in an accessible manner to pave the way for its use in research integrating within-person dynamics and intervention-related change in psychopathology, and we illustrate this modeling approach in a large-scale internet-based intervention for depression (N = 1,656). Using eight data points sampled across about 8 weeks, we predicted improvement across the intervention (50% symptom reduction) as a function of early change and symptom variability.Results: Early symptom change was associated with a more likely improvement across therapy. Variability of symptoms beyond change trajectories during the intervention was associated with less likely improvement.Conclusions: Location-scale models, and dynamic structural equation modeling more generally, are well suited to modeling how patterns of symptom change during psychotherapy are related to important (e.g., therapy) outcomes. Our illustrative application of location-scale modeling showed that symptom variability was associated with less overall improvement in depressive symptoms. However, this finding requires replication with more intensive sampling of symptoms before final conclusions can be drawn on when and how to distinguish maladaptive from adaptive variability during psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).","PeriodicalId":15447,"journal":{"name":"Journal of consulting and clinical psychology","volume":" ","pages":"556-568"},"PeriodicalIF":4.5000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of consulting and clinical psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/ccp0000892","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}

引用次数: 0

Abstract

Objective: Depressive symptom dynamics, including change trajectories and symptom variability, have been related to therapy outcomes. However, such dynamics have often been examined separately and related to outcomes of interest using two-step analyses, which are characterized by several limitations. Here, we show how to overcome these limitations using location-scale models in a dynamic structural equation modeling framework.

Method: We introduce location-scale modeling in an accessible manner to pave the way for its use in research integrating within-person dynamics and intervention-related change in psychopathology, and we illustrate this modeling approach in a large-scale internet-based intervention for depression (N = 1,656). Using eight data points sampled across about 8 weeks, we predicted improvement across the intervention (50% symptom reduction) as a function of early change and symptom variability.

Results: Early symptom change was associated with a more likely improvement across therapy. Variability of symptoms beyond change trajectories during the intervention was associated with less likely improvement.

Conclusions: Location-scale models, and dynamic structural equation modeling more generally, are well suited to modeling how patterns of symptom change during psychotherapy are related to important (e.g., therapy) outcomes. Our illustrative application of location-scale modeling showed that symptom variability was associated with less overall improvement in depressive symptoms. However, this finding requires replication with more intensive sampling of symptoms before final conclusions can be drawn on when and how to distinguish maladaptive from adaptive variability during psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

位置尺度建模作为心理治疗过程中症状动态的综合方法：以抑郁症状为例

目的：抑郁症状的动态变化（包括变化轨迹和症状变异性）与治疗效果有关。然而，这些动态变化通常都是通过两步分析法进行单独研究，并将其与相关结果联系起来，而两步分析法存在一些局限性。在此，我们将展示如何在动态结构方程建模框架中使用位置尺度模型来克服这些局限性：方法：我们以通俗易懂的方式介绍了位置尺度模型，为其在研究中的应用铺平了道路，该模型综合了人内动态和心理病理学中与干预相关的变化，我们还在一项大规模的基于互联网的抑郁症干预中（N = 1,656）说明了这种建模方法。我们使用 8 个数据点（取样时间约为 8 周），根据早期症状变化和症状变异性，预测了整个干预过程中的改善情况（症状减轻 50%）：结果：早期症状变化与更有可能在整个治疗过程中得到改善有关。结果：早期症状变化与整个治疗过程中症状改善的可能性较高相关，而干预期间超出变化轨迹的症状变异与症状改善的可能性较低相关：结论：位置尺度模型，以及更广泛的动态结构方程模型，非常适合用于模拟心理治疗期间症状变化模式与重要结果（如治疗）之间的关系。我们对位置尺度模型的说明性应用表明，症状变化与抑郁症状总体改善程度较低有关。然而，这一发现需要通过对症状进行更密集的取样来进行复制，然后才能就何时以及如何区分心理治疗过程中的适应性变异与适应性变异得出最终结论。(PsycInfo Database Record (c) 2024 APA，保留所有权利）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of consulting and clinical psychology PSYCHOLOGY, CLINICAL-

CiteScore

9.00

自引率

3.40%

发文量

期刊介绍： The Journal of Consulting and Clinical Psychology® (JCCP) publishes original contributions on the following topics: the development, validity, and use of techniques of diagnosis and treatment of disordered behaviorstudies of a variety of populations that have clinical interest, including but not limited to medical patients, ethnic minorities, persons with serious mental illness, and community samplesstudies that have a cross-cultural or demographic focus and are of interest for treating behavior disordersstudies of personality and of its assessment and development where these have a clear bearing on problems of clinical dysfunction and treatmentstudies of gender, ethnicity, or sexual orientation that have a clear bearing on diagnosis, assessment, and treatmentstudies of psychosocial aspects of health behaviors. Studies that focus on populations that fall anywhere within the lifespan are considered. JCCP welcomes submissions on treatment and prevention in all areas of clinical and clinical–health psychology and especially on topics that appeal to a broad clinical–scientist and practitioner audience. JCCP encourages the submission of theory–based interventions, studies that investigate mechanisms of change, and studies of the effectiveness of treatments in real-world settings. JCCP recommends that authors of clinical trials pre-register their studies with an appropriate clinical trial registry (e.g., ClinicalTrials.gov, ClinicalTrialsRegister.eu) though both registered and unregistered trials will continue to be considered at this time.