Internet-based cognitive behavior therapy for major depressive disorder: A randomized controlled trial

基于互联网的认知行为疗法治疗重度抑郁症:一项随机对照试验

阅读:1

Abstract

BACKGROUND: Prior research has shown that the Sadness Program, a technician-assisted Internet-based cognitive behavioral therapy (iCBT) intervention developed in Australia, is effective for treating major depressive disorder (MDD). The current study aimed to expand this work by adapting the protocol for an American population and testing the Sadness Program with an attention control group. METHODS: In this parallel-group, randomized controlled trial, adult MDD participants (18-45 years) were randomized to a 10-week period of iCBT (n = 37) or monitored attention control (MAC; n = 40). Participants in the iCBT group completed six online therapy lessons, which included access to content summaries and homework assignments. During the 10-week trial, iCBT and MAC participants logged into the web-based system six times to complete self-report symptom scales, and a nonclinician technician contacted participants weekly to provide encouragement and support. The primary outcome was the Hamilton Rating Scale for Depression (HRSD), and the secondary outcomes were the Patient Health Questionnaire-9 and Kessler-10. RESULTS: Intent-to-treat analyses revealed significantly greater reductions in depressive symptoms in iCBT compared with MAC participants, using both the self-report measures and the clinician-rated HRSD (d = -0.80). Importantly, iCBT participants also showed significantly higher rates of clinical response and remission. Exploratory analyses did not support illness severity as a moderator of treatment outcome. CONCLUSIONS: The Sadness Program led to significant reductions in depression and distress symptoms. With its potential to be delivered in a scalable, cost-efficient manner, iCBT is a promising strategy to enhance access to effective care.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。