Digital and AI-Enhanced Cognitive Behavioral Therapy for Insomnia: Neurocognitive Mechanisms and Clinical Outcomes
Abstract
Background/Objectives: This systematic review explores the integration of digital and AI-enhanced cognitive behavioral therapy (CBT) for insomnia, focusing on underlying neurocognitive mechanisms and associated clinical outcomes. Insomnia significantly impairs cognitive functioning, overall health, and quality of life. Although traditional CBT has demonstrated efficacy, its scalability and ability to deliver individualized care remain limited. Emerging AI-driven interventions-including chatbots, mobile applications, and web-based platforms-present innovative avenues for delivering more accessible and personalized insomnia treatments. Methods: Following PRISMA guidelines, this review synthesized findings from 78 studies published between 2004 and 2024. A systematic search was conducted across PubMed, Scopus, Web of Science, and PsycINFO. Studies were included based on predefined criteria prioritizing randomized controlled trials (RCTs) and high-quality empirical research that evaluated AI-augmented CBT interventions targeting sleep disorders, particularly insomnia. Results: The findings suggest that digital and AI-enhanced CBT significantly improves sleep parameters, patient adherence, satisfaction, and the personalization of therapy in alignment with individual neurocognitive profiles. Moreover, these technologies address critical limitations of conventional CBT, notably those related to access and scalability. AI-based tools appear especially promising in optimizing…
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