Digital cognitive behavioural therapy platform with artificialintelligence for depression management and nursing follow-up:A comprehensive review

Abstract

Major depressive disorder remains a leading global cause of disability, exacerbated by severe psychiatric workforce shortages and high attrition rates in traditional, unguided digital therapies. This review evaluates the clinical effectiveness, architectural integration, and ethical dimensions of artificial intelligence (AI)-enabled digital Cognitive Behavioural Therapy (dCBT) platforms, with a specific focus on the collaborative role of structured nursing follow-up frameworks. By synthesising evidence from recent randomised controlled trials, systematic reviews, and international healthcare guidelines, the review demonstrates that combining advanced computational algorithms—such as natural language processing, predictive analytics, and digital phenotyping—with the holistic, empathetic oversight of nursing professionals creates a highly scalable and safe therapeutic ecosystem. While fully automated platforms frequently suffer from low engagement, the integration of structured telenursing follow-up significantly reduces patient attrition, ensures continuous risk triage, and enhances treatment adherence. Ultimately, AIintegrated dCBT platforms do not replace clinical staff; rather, they serve as cognitive force multipliers that enable psychiatric and community nurses to manage digital caseloads more efficiently, intervene before clinical crises occur, and lead the deployment of evidence-based digital therapeutics in modern healthcare systems