Given rising numbers in sleep disorders and insufficient availability of treatment options, the need for well-validated digital interventions rises. This study aims at assessing the efficacy of an app-program which combines sleep-training based on core elements of Cognitive Behavioural Therapy for Insomnia (CBT-I) with reliable sleep-monitoring based on heart rate variability via an ECG-sensor. Data of 48 participants (26 female) aged 30-73 (M= 50.33±11.88) were included in the analyses. At the beginning of the baseline (T0), at start (T1) and end (T2) of the 6-week training phase as well as 4 weeks after the end of the program (T3; follow-up) several questionnaires assessing sleep quality, insomnia severity, general psychological symptom severity, depression, anxiety as well as quality of life were completed. Insomnia severity (p<. 001), sleep quality (p<. 001), general psychological symptom severity (p<. 001), depression (p=. 002) and anxiety (p<. 001) improved significantly during the training phase and persisted until one-month follow-up assessment, while in sleep quality a trend for further improvement during the follow-up period was found (p=. 097). Furthermore, quality of life [physical (p=. 014) and psychological health (p=. 049)] improved significantly during the follow-up-period. This study adds evidence on the potential of digital interventions and indicates that digital CBT-I can have substantial effects on relevant sleep-and health-related outcome measures.