Suppr超能文献

共病失眠与抑郁中的数字认知行为疗法失眠治疗:一项实用随机对照试验的临床结果

Digital CBT-I in Comorbid Insomnia and Depression: Clinical Outcomes From a Pragmatic Randomized Controlled Trial.

作者信息

Schuffelen Jennifer, Maurer Leonie F, Gieselmann Annika

机构信息

Department of Clinical Psychology, Institute of Experimental Psychology, Heinrich Heine University, Universitätsstraße 1, Düsseldorf 40225, Germany.

Mementor DE GmbH, Karl-Heine-Straße 15, Leipzig 04229, Germany.

出版信息

Depress Anxiety. 2025 May 26;2025:2171041. doi: 10.1155/da/2171041. eCollection 2025.

Abstract

Depression affects 8.1% of the German population annually, yet many patients remain resistant to conventional treatments. Given that 85% of individuals with depression also experience chronic insomnia, sleep may represent both a contributing and modifiable treatment factor. This study examines whether adding a fully automated digital cognitive behavioral therapy for insomnia (dCBT-I) to care-as-usual (CAU) improves depressive symptoms. Participants with comorbid depression and insomnia were randomized to either the intervention group (dCBT-I) or the waiting group (WLC). The intervention was delivered via a mobile app or web platform, consisting of 10 sequential core modules based on evidence-based CBT-I techniques. Assessments took place at baseline, 12- and 24-weeks post randomization. The primary outcome was the severity of depressive symptoms (Patient Health Questionnaire-9; PHQ-9). Secondary outcomes included insomnia severity, daytime sleepiness, fatigue, well-being and mechanistic effect measures. Linear mixed models were calculated to determine between-group effects. A total of 140 participants (120 women, mean age:  = 39.76 ± 11.65 years) were randomized to dCBT-I (=70) or WLC (=70). Large treatment effects at 12- and 24 weeks showed significant reductions in depressive symptoms (-3.34 and -2.83; s <0.001; s = 0.66-0.78) in the dCBT-I group. Treatment effects in favor of dCBT-I were also found for insomnia severity (s = 1.46-1.94) and most secondary outcomes (s = 0.33-1.14). This study demonstrates that digital dCBT-I can be effective not only for individuals with primary insomnia but also for those with depression. These findings align with previous research, highlighting the crucial role of sleep disturbances in depression management. Moreover, the effects remained stable even in the heterogeneous sample investigated in this study, reinforcing the robustness of dCBT-I across diverse patient groups. Thus, dCBT-I emerges as a promising adjunctive treatment. Considering these findings, it is essential to explore the integration of sleep-focused interventions into standard depression treatment. German Clinical Trial Registry identifier: DRKS00030919.

摘要

抑郁症每年影响8.1%的德国人口,但许多患者对传统治疗仍有抗药性。鉴于85%的抑郁症患者也患有慢性失眠症,睡眠可能既是一个促成因素,也是一个可调整的治疗因素。本研究探讨在常规护理(CAU)基础上增加全自动数字认知行为疗法治疗失眠症(dCBT-I)是否能改善抑郁症状。患有抑郁症和失眠症的参与者被随机分为干预组(dCBT-I)或等待组(WLC)。干预通过移动应用程序或网络平台进行,包括基于循证认知行为疗法治疗失眠症技术的10个连续核心模块。在随机分组后的基线、12周和24周进行评估。主要结果是抑郁症状的严重程度(患者健康问卷-9;PHQ-9)。次要结果包括失眠严重程度、日间嗜睡、疲劳、幸福感和机制效应指标。计算线性混合模型以确定组间效应。共有140名参与者(120名女性,平均年龄:=39.76±11.65岁)被随机分为dCBT-I组(=70)或WLC组(=70)。在12周和24周时,dCBT-I组的治疗效果显著,抑郁症状显著减轻(-3.34和-2.83;s<0.001;s= 0.66-0.78)。在失眠严重程度(s= 1.46-1.94)和大多数次要结果(s= 0.33-1.14)方面也发现了有利于dCBT-I的治疗效果。本研究表明,数字dCBT-I不仅对原发性失眠症患者有效,对抑郁症患者也有效。这些发现与先前的研究一致,突出了睡眠障碍在抑郁症管理中的关键作用。此外,即使在本研究调查的异质样本中,效果也保持稳定,加强了dCBT-I在不同患者群体中的稳健性。因此,dCBT-I成为一种有前景的辅助治疗方法。考虑到这些发现,探索将以睡眠为重点的干预措施纳入标准抑郁症治疗至关重要。德国临床试验注册标识符:DRKS00030919。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b15d/12129620/caf759d57536/DA2025-2171041.001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验