Effect of Cognitive Behavioral Therapy for Insomnia on Sleep Architecture: Systematic Review, Meta-Analysis, and Real-World Evidence

• Grant number: 24/14180-5
• Support Opportunities: Scholarships in Brazil - Master
• Start date: September 01, 2025
• End date: September 30, 2026
• Field of knowledge: Humanities - Psychology - Psychological Treatment and Prevention
• Principal Investigator: Gabriel Natan de Souza Pires
• Grantee: Ingrid Porto Araújo Leite
• Host Institution: Escola Paulista de Medicina (EPM). Universidade Federal de São Paulo (UNIFESP). Campus São Paulo. São Paulo , SP, Brazil

Abstract

Introduction: Current treatment guidelines for insomnia recognize Cognitive Behavioral Therapy for Insomnia (CBT-I) as the gold standard treatment, supported by numerous studies attesting to its efficacy on insomnia symptoms. However, there is still no consensus regarding its effects on sleep architecture. Objectives: To investigate the effect of CBT-I on sleep architecture parameters (time spent in stages N1, N2, N3, and REM, wake after sleep onset (WASO), number of awakenings, and arousal index). Methodology: This study will be structured in two phases, evaluating CBT-I as an intervention and sleep architecture parameters as outcomes. The first phase will consist of a systematic review with meta-analysis. After searching four databases (PubMed, Web of Science, Scopus, and PsychInfo), two reviewers will analyze all records in two phases (abstracts and full texts), and meta-analyses will be conducted whenever at least three studies on the same type of CBT-I and the same outcome can be grouped. The effect sizes of each study will be calculated using simple or standardized mean differences, and the meta-analyses will be calculated using the DerSimonian and Laird random-effects method via the RevMan Web software. The second phase will be a real-world evidence (RWE) study based on a convenience sample of users of a digital CBT-I service. Sleep architecture parameters will be assessed using a portable electroencephalogram band. Data will be analyzed using generalized estimating equations (GEE) models, with the JAMOVI 2.3.28 software, considering statistical significance at p<0.05.