Mütze Kaline, Witthöft Michael, Lutz Wolfgang, Bräscher Anne-Kathrin
Department of Clinical Psychology, Psychotherapy, and Experimental Psychopathology, University of Mainz, Germany.
Department of Clinical Psychology and Psychotherapy, University of Trier, Germany.
Psychother Res. 2022 Mar;32(3):358-371. doi: 10.1080/10503307.2021.1930244. Epub 2021 May 21.
Despite evidence showing that systematic outcome monitoring can prevent treatment failure, the practical conditions that allow for implementation are seldom met in naturalistic psychological services. In the context of limited time and resources, session-by-session evaluation is rare in most clinical settings. This study aimed to validate innovative prediction methods for individual treatment progress and dropout risk based on basic outcome monitoring.
Routine data of a naturalistic psychotherapy outpatient sample were analyzed ( = 3902). Patients were treated with cognitive behavioral therapy with up to 95 sessions ( = 39.19, = 16.99) and assessment intervals of 5-15 sessions. Treatment progress and dropout risk were predicted in two independent analyses using the nearest neighbor method and least absolute shrinkage and selection operator regression, respectively.
The correlation between observed and predicted patient progress was = .46. Intrinsic treatment motivation, previous inpatient treatment, university-entrance qualification, baseline impairment, diagnosed personality disorder, and diagnosed eating disorder were identified as significant predictors of dropout, explaining 11% of variance.
Innovative outcome prediction in naturalistic psychotherapy is not limited to elaborated progress monitoring. This study demonstrates a reasonable approach for tracking patient progress as long as session-by-session assessment is not a valid standard.
尽管有证据表明系统的结果监测可以预防治疗失败，但在自然主义心理治疗服务中，很少能满足实施所需的实际条件。在时间和资源有限的情况下，在大多数临床环境中，逐节评估很少见。本研究旨在验证基于基本结果监测的个体治疗进展和脱落风险的创新预测方法。
分析了自然主义心理治疗门诊样本的常规数据（n = 3902）。患者接受认知行为治疗，最多95节（M = 39.19，SD = 16.99），评估间隔为5 - 15节。分别使用最近邻法和最小绝对收缩和选择算子回归在两项独立分析中预测治疗进展和脱落风险。
观察到的与预测的患者进展之间的相关性为r = 0.46。内在治疗动机、既往住院治疗、大学入学资格、基线损伤、诊断出的人格障碍和诊断出的饮食失调被确定为脱落的显著预测因素，解释了11%的方差。
自然主义心理治疗中的创新结果预测不限于详尽的进展监测。本研究展示了一种合理的方法来跟踪患者进展，只要逐节评估不是有效的标准。
