Predicting Dropouts of the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders: Joint Modelling of Survival and Longitudinal Data

IF 2.9 3区心理学 Q1 PSYCHOLOGY, CLINICAL

Clinical psychology & psychotherapy Pub Date : 2026-08-05 DOI:10.1002/cpp.70313

Ângela Ferreira, Inês Sousa, Eugénia Ribeiro

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引用次数: 0

Abstract

Understanding when and who is at greater risk of dropping out can help therapists and mental health professionals develop strategies to keep clients engaged, thereby improving the overall effectiveness of therapy. In the present study, we aimed to explore the hazard of dropout, both early and late in treatment, and evaluate the predictive power of both static (i.e., baseline client characteristics) and dynamic predictors (i.e., treatment process variables), in a sample of 97 clients treated with the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders. Thirty-one clients (31.96%) discontinued treatment, with the highest dropout rate observed at the end of Session 4. Stratified Cox modelling showed a significant effect of younger age $(β_{1} = - 1.706, p = 0.031)$ , non-student status $(β_{2} = - 1.715, p = 0.031)$ and higher baseline anxiety severity $(β_{3} = 1.806, p = 0.022)$ , on the risk of dropping out until Session 4 (i.e., the early phase of treatment). Beyond Session 4, only lower depressive severity measured at intake began to significantly affect the risk of dropout $(β_{8} = - 1.007, p = 0.034)$ . Additionally, joint modelling (JM) of survival and longitudinal data for the early phase of treatment provided evidence of the predictive power of lower distress levels $(γ_{01} = - 0.181, p = 0.093)$ and lower therapeutic alliance quality $(γ_{02} = - 0.137, p = 0.05)$ on the clients' decision to discontinue treatment prematurely. After Session 4, no factor showed a significant association with dropout risk within the JM approach. The results suggest that early sessions are critical for the client's retention, and the JM approach is indispensable for studying psychotherapy dropout, especially in the context of endogenous time-varying predictors. Implications for clinical and research contexts are discussed.

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预测情绪障碍跨诊断治疗统一方案的退出：生存和纵向数据的联合建模。

了解什么时候以及谁有更大的辍学风险，可以帮助治疗师和心理健康专业人员制定策略，让客户保持参与，从而提高治疗的整体效果。在本研究中，我们旨在探讨治疗早期和晚期的辍学风险，并评估静态（即基线客户特征）和动态预测因子（即治疗过程变量）的预测能力，样本为97名接受情绪障碍跨诊断治疗统一方案治疗的客户。31名患者（31.96%）停止治疗，在第4期结束时观察到最高的辍学率。分层Cox模型显示，较年轻的年龄β 1 = - 1.706, p = 0.031，非学生身份β 2 = - 1.715, p = 0.031，较高的基线焦虑严重程度β 3 = 1.806, p = 0.022，对直到第4阶段（即治疗早期阶段）的退学风险有显著影响。在第4阶段之后，只有在摄入时测量的较低抑郁严重程度开始显著影响辍学的风险β 8 = - 1.007, p = 0.034。此外，治疗早期阶段的生存和纵向数据联合建模（JM）提供了较低痛苦水平（01 = - 0.181,p = 0.093）和较低治疗联盟质量（02 = - 0.137,p = 0.05）对客户过早停止治疗决定的预测能力的证据。在第4阶段之后，在JM方法中没有任何因素显示出与辍学风险的显著关联。结果表明，早期治疗对来访者的保留至关重要，JM方法对于研究心理治疗退出是不可或缺的，特别是在内源性时变预测因素的背景下。对临床和研究背景的影响进行了讨论。

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来源期刊

Clinical psychology & psychotherapy PSYCHOLOGY, CLINICAL-

CiteScore

6.30

自引率

5.60%

发文量

106

期刊介绍： Clinical Psychology & Psychotherapy aims to keep clinical psychologists and psychotherapists up to date with new developments in their fields. The Journal will provide an integrative impetus both between theory and practice and between different orientations within clinical psychology and psychotherapy. Clinical Psychology & Psychotherapy will be a forum in which practitioners can present their wealth of expertise and innovations in order to make these available to a wider audience. Equally, the Journal will contain reports from researchers who want to address a larger clinical audience with clinically relevant issues and clinically valid research.