Predicting adherence to fully-automated, chatbot-delivered digital cognitive behavioral therapy for insomnia (dCBT-I) using machine learning: A pilot real-world study
Digital cognitive behavioral therapy for insomnia (dCBT-I) is effective in treating insomnia, but adherence remains a major challenge in real-world applications. Machine learning (ML) offers potential in predicting healthcare utilization. This study applied ML techniques to predict adherence to dCBT-I based on participant baseline characteristics. This pilot real-world study included 75 individuals (69% female; 41% aged 35–44 years) with insomnia symptoms (Insomnia Severity Index, ISI ≥ 8) who p...