Impact of Adherence to Digital Cognitive Behavioral Therapy for Insomnia Effectiveness

数字认知行为疗法依从性对失眠疗效的影响

阅读:1

Abstract

PURPOSE: Although digital cognitive behavioral therapy for insomnia (dCBT-I) offers a promising solution to the accessibility limitations of traditional face-to-face CBT-I, few studies have examined dCBT-I against a sham app and adherence issues remain. This study assessed the efficacy of dCBT-I compared with a sham app and investigated whether adherence predicts sleep outcomes. MATERIALS AND METHODS: In this combined analysis of two multicenter, double-blind, sham-controlled randomized controlled trials, 120 patients with insomnia were randomized to use the dCBT-I app (n=60) or a sham app (n=60). The primary outcome was the change in sleep efficiency (SE) from baseline after the 6-week intervention. The relationship between adherence to sleep restriction therapy (SRT) and sleep outcomes post-intervention was assessed. RESULTS: After adjusting for age, sex, sleep medication use, and baseline levels of each outcome variable, the dCBT-I group demonstrated better treatment outcomes than the sham app group, with significant improvements of 7.69% in SE [95% confidence interval (CI), 3.09% to 12.30%; p=0.001], -16.77 minutes in sleep onset latency (95% CI, -31.48 to -2.06 minutes; p=0.026), and -0.97 in dysfunctional beliefs about sleep (95% CI, -1.46 to -0.48; p<0.001) from baseline. Poorer adherence to SRT was associated with reduced SE (p=0.006) and increased nighttime wakefulness (p=0.002) after controlling for age, sex, years of education, and the baseline value of each outcome variable. CONCLUSION: This combined analysis demonstrates the efficacy of dCBT-I in improving sleep outcomes compared with a sham app and highlights the role of adherence to SRT in enhancing treatment efficacy. The two studies were registered with ClinicalTrials.gov (NCT05822999, NCT05809544).

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。