Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia: A Meta-Analysis of Randomized Controlled Trials
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Abstract
Abstract
Objective: This study aimed to evaluate the effectiveness of fully automated Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) interventions in reducing insomnia severity through a systematic review and meta-analysis of randomized controlled trials (RCTs).
Method: A systematic search was conducted across multiple databases, including PubMed, PsycINFO, Web of Science, Scopus, and Google Scholar, to identify RCTs evaluating fully automated dCBT-I. Eligible studies were included those assessing adults diagnosed with insomnia using validated criteria or scales, utilizing digital delivery platforms, and reporting quantitative insomnia severity outcomes. A meta-analysis was performed using a random-effects model, with standardized mean differences (SMDs) and 95% confidence intervals (CIs) as the primary effect measures. Subgroup and sensitivity analyses were conducted to explore sources of heterogeneity.
Results: A total of 49 RCTs involving 20,118 participants were included. Fully automated dCBT-I significantly reduced insomnia severity compared to control conditions (WMD: -3.42; 95% CI: -4.35 to -2.48; P < 0.001). Subgroup analyses revealed greater effectiveness in studies using rigorous diagnostic criteria, as well as among U.S.-based populations. Despite substantial heterogeneity (I² > 98%), sensitivity analyses confirmed the robustness of findings. Funnel plot asymmetry suggested minor potential publication bias, though Egger’s test did not confirm significant bias (P = 0.494).
Conclusion: Fully automated dCBT-I programs effectively reduce insomnia severity, offering a scalable, accessible solution to overcome barriers in traditional CBT-I delivery. However, variability in study methodologies and the predominance of studies from high-income countries highlight the need for further research. Future directions include incorporating objective sleep measures, assessing long-term outcomes, and adapting interventions to diverse cultural and economic contexts. Fully automated dCBT-I holds transformative potential for addressing insomnia on a global scale.
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3. Mukherjee U, Sehar U, Brownell M, Reddy PH. Mechanisms, consequences and role of interventions for sleep deprivation: Focus on mild cognitive impairment and Alzheimer's disease in elderly. Ageing Res Rev. 2024;100:102457.
4. Chalet FX, Albanese E, Egea Santaolalla C, Ellis JG, Ferini-Strambi L, Heidbreder A, et al. Epidemiology and burden of chronic insomnia disorder in Europe: an analysis of the 2020 National Health and Wellness Survey. J Med Econ. 2024;27(1):1308-19.
5. Bouchou Y, Giffard-Quillon L, Fontana L, Roche F, Pélissier C, Berger M. Sleep Habits and Disturbances in Healthcare Workers: A Cross-Sectional Survey in French Public Hospitals. Nat Sci Sleep. 2024;16:1687-98.
6. Kutana S, Mao JJ, Garland SN. Acupuncture as an Adjunct Treatment to Cognitive-Behavioral Therapy for Insomnia. Sleep Med Clin. 2023;18(1):113-22.
7. Doos Ali Vand H, Gharraee B, Asgharnejad Farid AA, Ghaleh Bandi MF, Habibi M. The Effectiveness of Transdiagnostic Cognitive Behavioral Therapy for Comorbid Insomnia: A Case Report. Iran J Psychiatry. 2018;13(2):154-9.
8. Furukawa Y, Sakata M, Yamamoto R, Nakajima S, Kikuchi S, Inoue M, et al. Components and Delivery Formats of Cognitive Behavioral Therapy for Chronic Insomnia in Adults: A Systematic Review and Component Network Meta-Analysis. JAMA Psychiatry. 2024;81(4):357-65.
9. Hertenstein E, Trinca E, Schneider CL, Fehér KD, Johann AF, Nissen C. Acceptance and Commitment Therapy, Combined with Bedtime Restriction, versus Cognitive Behavioral Therapy for Insomnia: A Randomized Controlled Pilot Trial. Psychother Psychosom. 2024;93(2):114-28.
10. Babiano-Espinosa L, Skarphedinsson G, Weidle B, Wolters LH, Compton S, Ivarsson T, et al. eCBT Versus Standard Individual CBT for Paediatric Obsessive-Compulsive Disorder. Child Psychiatry Hum Dev. 2023;54(6):1567-76.
11. Otorkpa OJ, Alao JO, Olaiya AP. Enhancing monitoring and evaluation of digital health interventions in sub-Saharan Africa: big data, mHealth, and dashboards. J Glob Health. 2025;15:03013.
12. Hwang JW, Lee GE, Woo JH, Kim SM, Kwon JY. Systematic review and meta-analysis on fully automated digital cognitive behavioral therapy for insomnia. NPJ Digit Med. 2025;8(1):157.
13. Bai N, Cao J, Zhang H, Liu X, Yin M. Digital cognitive behavioural therapy for patients with insomnia and depression: A systematic review and meta-analysis. J Psychiatr Ment Health Nurs. 2024;31(4):654-67.
14. Zachariae R, Lyby MS, Ritterband LM, O'Toole MS. Efficacy of internet-delivered cognitive-behavioral therapy for insomnia - A systematic review and meta-analysis of randomized controlled trials. Sleep Med Rev. 2016;30:1-10.
15. Seyffert M, Lagisetty P, Landgraf J, Chopra V, Pfeiffer PN, Conte ML, et al. Internet-Delivered Cognitive Behavioral Therapy to Treat Insomnia: A Systematic Review and Meta-Analysis. PLoS One. 2016;11(2):e0149139.
16. Hwang JW, Lee GE, Woo JH, Kim SM, Kwon JY. Systematic review and meta-analysis on fully automated digital cognitive behavioral therapy for insomnia. NPJ Digit Med. 2025;8(1):157.
17. Forma F, Pratiwadi R, El-Moustaid F, Smith N, Thorndike F, Velez F. Network meta-analysis comparing the effectiveness of a prescription digital therapeutic for chronic insomnia to medications and face-to-face cognitive behavioral therapy in adults. Curr Med Res Opin. 2022;38(10):1727-38.
18. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med. 2009;151(4):264-9, w64.
19. Higgins JP, Savović J, Page MJ, Elbers RG, Sterne JA. Assessing risk of bias in a randomized trial. Cochrane handbook for systematic reviews of interventions. 2019:205-28.
20. Verhagen AP, de Vet HC, de Bie RA, Kessels AG, Boers M, Bouter LM, et al. The Delphi list: a criteria list for quality assessment of randomized clinical trials for conducting systematic reviews developed by Delphi consensus. J Clin Epidemiol. 1998;51(12):1235-41.
21. Borenstein M, Cooper H, Hedges L, Valentine J. Effect sizes for continuous data. The handbook of research synthesis and meta-analysis. 2009;2:221-35.
22. Sun T, Wang Y, Hui D, Jing X, Feng W. Vertical distributions of soil microbial biomass carbon: a global dataset. Data Brief. 2020;32:106147.
23. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. Bmj. 2003;327(7414):557-60.
24. Sweetman A, Reynolds C, Richardson C. Digital cognitive behavioural therapy for insomnia versus digital sleep education control in an Australian community-based sample: a randomised controlled trial. Intern Med J. 2024;54(11):1838-48.
25. Shin J, Kim S, Lee J, Gu H, Ahn J, Park C, et al. Efficacy of Mobile App-Based Cognitive Behavioral Therapy for Insomnia: Multicenter, Single-Blind Randomized Clinical Trial. J Med Internet Res. 2024;26:e50555.
26. Hinterberger A, Eigl ES, Schwemlein RN, Topalidis P, Schabus M. Investigating the subjective and objective efficacy of a cognitive behavioural therapy for insomnia (CBT-I)-based smartphone app on sleep: A randomised controlled trial. J Sleep Res. 2024;33(4):e14136.
27. Maurer LF, Bauermann P, Karner L, Müller C, Lorenz N, Gieselmann A. Investigating the efficacy of digital cognitive behavioural therapy in comparison to a sleep-monitoring application via integrated diary and actigraphy: A randomised-controlled trial. J Sleep Res. 2025;34(1):e14255.
28. Rötger A, Schuffelen J, Maurer LF, Lorenz N, Pollok B, Gieselmann A. The clinical effect of digital cognitive behavioural therapy for insomnia in subgroups with depressive and anxiety symptoms: A secondary analysis of a randomized-controlled trial. J Sleep Res. 2024;33(5):e14173.
29. Fleming MK, Smejka T, Macey E, Luengo-Fernandez R, Henry AL, Robinson B, et al. Improving sleep after stroke: A randomised controlled trial of digital cognitive behavioural therapy for insomnia. J Sleep Res. 2024;33(2):e13971.
30. Chan WS, Cheng WY, Lok SHC, Cheah AKM, Lee AKW, Ng ASY, et al. Assessing the Short-Term Efficacy of Digital Cognitive Behavioral Therapy for Insomnia With Different Types of Coaching: Randomized Controlled Comparative Trial. JMIR Ment Health. 2024;11:e51716.
31. Wu Y, Li J, Liu H, Luo J, He W, Li H. The effects of digital CBT intervention on attentional bias and sleep quality of poor sleepers with insomnia symptoms. BMC Psychol. 2024;12(1):676.
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1.
Nazari A, Mirzakhani A, Garmaroudi G, Amani M. Effectiveness of Digital Cognitive Behavioral Therapy for Insomnia: A Meta-Analysis of Randomized Controlled Trials. Iran J Psychiatry. 2025;:1-22.
