Digital Therapeutic for Insomnia: Feasibility of Circadian Rhythm-Based Intervention

Overview

This study introduces the Circadian Rhythm for Sleep (CRS) app, a digital therapeutic designed to improve insomnia by targeting circadian misalignment through personalized, wearable-driven feedback. The single-arm feasibility study demonstrated promising user engagement and potential improvements in sleep parameters by promoting consistent wake times and optimized light exposure.

Background

Insomnia affects 10–30% of adults and is linked to significant health risks including depression and cardiovascular disease. While Cognitive Behavioral Therapy for Insomnia (CBT-I) is the first-line treatment, it does not directly address circadian misalignment, a key factor in many insomnia cases. Circadian rhythm disruption, often due to modern lifestyle factors like artificial lighting and irregular schedules, contributes to sleep difficulties. Chronotherapy, which realigns biological rhythms through behavioral and environmental strategies, is an emerging complementary approach but remains underutilized in clinical practice. Digital therapeutics offer scalable solutions to deliver such interventions.

Data Highlights

The CRS app integrates wearable data to provide adaptive recommendations on wake-up times, morning light exposure, and activity. It uses a machine-learning model to predict insomnia-like sleep disruptions based on multiday patterns of sleep, activity, heart rate, and light exposure. The app’s closed-loop system dynamically adjusts behavioral guidance daily to promote circadian realignment. Feasibility outcomes include measures of user engagement, subjective sleep improvements, and objective sleep metrics derived from wearables.

Key Findings

• CRS targets circadian misalignment by promoting consistent wake times and morning light exposure, addressing a key insomnia etiology not directly targeted by CBT-I.
• The app employs passive data collection from wearables and smartphones to minimize user burden and maximize adherence.
• A supervised machine-learning algorithm predicts daily insomnia-like sleep disruption, enabling personalized, adaptive recommendations.
• Behavior-change techniques such as self-monitoring, feedback, and goal setting are integrated to support sustained user engagement.
• The closed-loop design allows real-time adjustment of interventions based on recent sleep–wake and light exposure data.
• Preliminary feasibility data suggest good user engagement and potential improvements in sleep outcomes through circadian realignment strategies.

Clinical Implications

The CRS app represents a novel digital chronotherapy approach that can complement existing insomnia treatments by directly targeting circadian misalignment. Its use of wearable data and adaptive feedback may enhance personalization and adherence, potentially improving sleep quality in patients with circadian-related insomnia. Clinicians might consider integrating such digital therapeutics to address biological timing factors alongside cognitive-behavioral strategies.

Conclusion

This feasibility study supports the potential of a wearable-driven, circadian rhythm–focused digital therapeutic to improve insomnia by realigning biological clocks. Further controlled trials are warranted to establish efficacy and optimize integration into clinical practice.

References

1. American College of Physicians Guideline -- Management of Chronic Insomnia
2. Circadian Neuroscience and Behavioral Psychology Literature -- Foundations of CRS App
3. Social Cognitive Theory and Behavior Change Techniques -- Supporting Sustained Adherence
4. Digital Therapeutics Best Practices -- Design and Implementation