Schmidt Iony D, Forand Nicholas R, Strunk Daniel R
Department of Psychology, The Ohio State University, 1835 Neil Avenue, Columbus, OH 43210, United States.
The Barbara and Donald Zucker School of Medicine at Hofstra/Northwell, 500 Hofstra Blvd, Hempstead, NY 11549, United States.
Cognit Ther Res. 2019 Jun;43(3):620-630. doi: 10.1007/s10608-018-9979-5. Epub 2018 Nov 16.
Internet-based cognitive behavioral therapy (iCBT), provided with guidance, has been shown to outperform wait-list control conditions and appears to perform on par with face-to-face psychotherapy. However, dropout remains an important problem. Dropout rates for iCBT programs for depression have ranged from 0% to 75%, with a mean of 32%. Drawing from a recent study in which 117 people participated in iCBT with support, we examined participant characteristics, participants' use of iCBT skills, and their experience of technical difficulties with iCBT as predictors of dropout risk. Educational level, extraversion, and participant skill use predicted lower risk of dropout; technical difficulties and openness predicted higher dropout risk. We encourage future research on predictors of dropout in the hope that greater understanding of dropout risk will inform efforts to promote program engagement and retention.
有指导的基于互联网的认知行为疗法（iCBT）已被证明比等待名单控制组更有效，并且似乎与面对面心理治疗效果相当。然而，退出治疗仍然是一个重要问题。iCBT抑郁症治疗项目的退出率在0%至75%之间，平均为32%。基于最近一项有117人参与有支持的iCBT的研究，我们考察了参与者特征、参与者对iCBT技能的使用以及他们在iCBT中遇到的技术困难经历，将其作为退出风险的预测因素。教育水平、外向性和参与者技能使用可预测较低的退出风险；技术困难和开放性则预测较高的退出风险。我们鼓励未来对退出预测因素进行研究，希望对退出风险有更深入的了解能为促进项目参与和留存的努力提供信息。
