Bremer-Hoeve Susanne, van Vliet Noortje I, van Bronswijk Suzanne C, Huntjens Rafaele J C, de Jongh Ad, van Dijk Maarten K
Dimence Mental Health Group, Deventer, Netherlands.
Department of Psychiatry and Neuropsychology, School for Mental health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands.
Front Psychiatry. 2023 Aug 4;14:1194669. doi: 10.3389/fpsyt.2023.1194669. eCollection 2023.
Knowledge about patient characteristics predicting treatment dropout for post-traumatic stress disorder (PTSD) is scarce, whereas more understanding about this topic may give direction to address this important issue.
Data were obtained from a randomized controlled trial in which a phase-based treatment condition (Eye Movement Desensitization and Reprocessing [EMDR] therapy preceded by Skills Training in Affect and Interpersonal Regulation [STAIR]; = 57) was compared with a direct trauma-focused treatment (EMDR therapy only; = 64) in people with a PTSD due to childhood abuse. All pre-treatment variables included in the trial were examined as possible predictors for dropout using machine learning techniques.
For the dropout prediction, a model was developed using Elastic Net Regularization. The ENR model correctly predicted dropout in 81.6% of all individuals. Males, with a low education level, suicidal thoughts, problems in emotion regulation, high levels of general psychopathology and not using benzodiazepine medication at screening proved to have higher scores on dropout.
Our results provide directions for the development of future programs in addition to PTSD treatment or for the adaptation of current treatments, aiming to reduce treatment dropout among patients with PTSD due to childhood abuse.
关于预测创伤后应激障碍（PTSD）治疗中断的患者特征的知识匮乏，而对这一主题的更多了解可能为解决这一重要问题指明方向。
数据来自一项随机对照试验，该试验将基于阶段的治疗方案（先进行情感与人际调节技能训练[STAIR]，随后进行眼动脱敏再处理[EMDR]治疗；n = 57）与针对童年期受虐所致PTSD患者的直接创伤聚焦治疗（仅EMDR治疗；n = 64）进行比较。使用机器学习技术将试验中纳入的所有预处理变量作为治疗中断的可能预测因素进行检验。
为了预测治疗中断情况，使用弹性网正则化开发了一个模型。该弹性网正则化（ENR）模型正确预测了所有个体中81.6%的治疗中断情况。结果表明，男性、教育水平低、有自杀念头、情绪调节存在问题、一般精神病理学水平高以及在筛查时未使用苯二氮䓬类药物的患者在治疗中断方面得分较高。
我们的结果为未来除PTSD治疗之外的项目开发或当前治疗方法的调整提供了方向，旨在减少童年期受虐所致PTSD患者的治疗中断情况。
