Effectiveness of unguided digital cognitive behavioral therapy for insomnia on depressive symptoms: a systematic review and meta-analysis of randomized controlled trials

Objective This study aims to assess the intervention effects of unguided digital cognitive behavioral therapy for insomnia (dCBT-I) on patients with comorbid depression and insomnia through a systematic review and meta-analysis, in order to determine its effectiveness as a treatment strategy for comorbid depression and insomnia. Methods We conducted a systematic search across PubMed, Cochrane, Embase, ClinicalTrials.gov, and PsycINFO.databases to identify randomized controlled trials (RCTs) focusing on adults with comorbid insomnia and depressive symptoms, excluding those with severe physical illnesses or psychiatric disorders. Following the removal of duplicates, 1842 articles were screened, resulting in the inclusion of 16 RCTs in the final meta-analysis. Results Post-treatment evaluations revealed that digital cognitive behavioral therapy for insomnia (dCBT-I) demonstrated a significant impact on insomnia (SMD = -0.94; 95% CI: -1.40 to -0.48; p < 0.001; k = 16), though substantial heterogeneity was observed (I² = 98.63%; Q = 1250.89, df = 15, p < 0.05). For depressive symptoms, dCBT-I demonstrated a moderate effect (SMD = -0.63; 95% CI: -0.81 to -0.46; p < 0.05; k = 16), with high heterogeneity (I² = 81%; Q = 78.31, df = 15, p < 0.05).Strong outcomes were observed in both the Web and APP cohorts when analyzing program carriers, with notable findings in the moderately depressed subgroup. Conclusions This meta-analysis evaluated the efficacy of therapist-unguided digital cognitive behavioral therapy (dCBT-I) for insomnia and depression, dCBT-I demonstrated significant reductions in insomnia severity and depressive symptoms within the studied population, despite substantial heterogeneity. It also demonstrated moderate to large effects for moderate-to-severe depression, further supporting the effectiveness of unguided dCBT-I. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/view/CRD420251044042 , identifier CRD420251044042.