第一印象很重要:治疗师对患者动机和帮助联盟的印象可预测心理治疗的放弃。

IF 2.6 1区 心理学 Q2 PSYCHOLOGY, CLINICAL
Kristin Jankowsky, Johannes Zimmermann, Ulrich Jaeger, Robert Mestel, Ulrich Schroeders
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引用次数: 0

摘要

目的:根据荟萃分析估计,心理疗法的辍学率约为 25%,这是个人、临床医生和整个医疗保健系统都十分关注的问题。为了应对心理治疗中的辍学问题,我们需要准确了解其预测因素:方法:我们比较了逻辑回归模型和两种机器学习算法(弹性网回归和梯度提升机)在两个大型住院病人样本(N = 1,691 和 N = 12,473)中对治疗辍学的预测,并使用了病人和治疗师报告的基线和初始过程变量:结果:两种机器学习算法的预测准确率相似,且高于逻辑回归:样本 1 和样本 2 预测治疗退出的 AUC 分别为 0.73 和 0.83。对患者治疗动机的初步评估和由相关治疗师评定的治疗联盟是最重要的辍治预测因素:结论:利用基线指标和治疗师的第一印象可以在很大程度上预测自然住院环境中的治疗退出。通过正则化进行特征选择可获得更高的预测性能,而非线性效应或交互效应则是可有可无的。减少治疗辍学最有希望的干预点似乎是病人的动机和治疗联盟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
First impressions count: Therapists' impression on patients' motivation and helping alliance predicts psychotherapy dropout.

Objective: With meta-analytically estimated rates of about 25%, dropout in psychotherapies is a major concern for individuals, clinicians, and the healthcare system at large. To be able to counteract dropout in psychotherapy, accurate insights about its predictors are needed.

Method: We compared logistic regression models with two machine learning algorithms (elastic net regressions and gradient boosting machines) in the prediction of therapy dropout in two large inpatient samples (N = 1,691 and N = 12,473) using baseline and initial process variables reported by patients and therapists.

Results: Predictive accuracies of the two machine learning algorithms were similar and higher than for logistic regressions: Therapy dropout could be predicted with an AUC of .73 and .83 for Sample 1 and 2, respectively. The initial evaluation of patients' motivation and the therapeutic alliance rated by the respective therapist were the most important predictors of dropout.

Conclusions: Therapy dropout in naturalistic inpatient settings can be predicted to a considerable degree by using baseline indicators and therapists' first impressions. Feature selection via regularization leads to higher predictive performances whereas non-linear or interaction effects are dispensable. The most promising point of intervention to reduce therapy dropouts seems to be patients' motivation and the therapeutic alliance.

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来源期刊
Psychotherapy Research
Psychotherapy Research PSYCHOLOGY, CLINICAL-
CiteScore
7.80
自引率
10.30%
发文量
68
期刊介绍: Psychotherapy Research seeks to enhance the development, scientific quality, and social relevance of psychotherapy research and to foster the use of research findings in practice, education, and policy formulation. The Journal publishes reports of original research on all aspects of psychotherapy, including its outcomes, its processes, education of practitioners, and delivery of services. It also publishes methodological, theoretical, and review articles of direct relevance to psychotherapy research. The Journal is addressed to an international, interdisciplinary audience and welcomes submissions dealing with diverse theoretical orientations, treatment modalities.
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