Jennifer Schuffelen, Leonie F. Maurer, Annika Gieselmann
{"title":"数字CBT-I在共病性失眠和抑郁症中的应用：一项实用的随机对照试验的临床结果","authors":"Jennifer Schuffelen, Leonie F. Maurer, Annika Gieselmann","doi":"10.1155/da/2171041","DOIUrl":null,"url":null,"abstract":"<div>\n <p>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: <i>M</i> = 39.76 ± 11.65 years) were randomized to dCBT-I (<i>n</i> = 70) or WLC (<i>n</i> = 70). Large treatment effects at 12- and 24 weeks showed significant reductions in depressive symptoms (−3.34 and −2.83; <i>p</i>s <0.001; <i>d</i>s = 0.66–0.78) in the dCBT-I group. Treatment effects in favor of dCBT-I were also found for insomnia severity (<i>d</i>s = 1.46–1.94) and most secondary outcomes (<i>d</i>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.</p>\n <p><b>Trial Registration:</b> German Clinical Trial Registry identifier: DRKS00030919</p>\n </div>","PeriodicalId":55179,"journal":{"name":"Depression and Anxiety","volume":"2025 1","pages":""},"PeriodicalIF":4.7000,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/da/2171041","citationCount":"0","resultStr":"{\"title\":\"Digital CBT-I in Comorbid Insomnia and Depression: Clinical Outcomes From a Pragmatic Randomized Controlled Trial\",\"authors\":\"Jennifer Schuffelen, Leonie F. Maurer, Annika Gieselmann\",\"doi\":\"10.1155/da/2171041\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n <p>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: <i>M</i> = 39.76 ± 11.65 years) were randomized to dCBT-I (<i>n</i> = 70) or WLC (<i>n</i> = 70). Large treatment effects at 12- and 24 weeks showed significant reductions in depressive symptoms (−3.34 and −2.83; <i>p</i>s <0.001; <i>d</i>s = 0.66–0.78) in the dCBT-I group. Treatment effects in favor of dCBT-I were also found for insomnia severity (<i>d</i>s = 1.46–1.94) and most secondary outcomes (<i>d</i>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. 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Digital CBT-I in Comorbid Insomnia and Depression: Clinical Outcomes From a Pragmatic Randomized Controlled Trial
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: M = 39.76 ± 11.65 years) were randomized to dCBT-I (n = 70) or WLC (n = 70). Large treatment effects at 12- and 24 weeks showed significant reductions in depressive symptoms (−3.34 and −2.83; ps <0.001; ds = 0.66–0.78) in the dCBT-I group. Treatment effects in favor of dCBT-I were also found for insomnia severity (ds = 1.46–1.94) and most secondary outcomes (ds = 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.
Trial Registration: German Clinical Trial Registry identifier: DRKS00030919
期刊介绍：
Depression and Anxiety is a scientific journal that focuses on the study of mood and anxiety disorders, as well as related phenomena in humans. The journal is dedicated to publishing high-quality research and review articles that contribute to the understanding and treatment of these conditions. The journal places a particular emphasis on articles that contribute to the clinical evaluation and care of individuals affected by mood and anxiety disorders. It prioritizes the publication of treatment-related research and review papers, as well as those that present novel findings that can directly impact clinical practice. The journal's goal is to advance the field by disseminating knowledge that can lead to better diagnosis, treatment, and management of these disorders, ultimately improving the quality of life for those who suffer from them.
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