NCT05400785

Efficacy of the Mobile Application for Prediction and Prevention of Mood Episode Recurrence Based on Machine Learning

Efficacy of the Mobile Phone Application (Circadian Rhythms for Mood) for Prediction and Prevention of Mood Episode Recurrence in Mood Disorders Based on Machine Learning of Daily Digital Phenotype Variables : A Sham-controlled Randomized Clinical Trial

• Status: Completed
• Phase: N/A
• Study type: Interventional
• Enrollment: 93 (actual)
• Sponsor: Hucircadian · Industry
• Sex: All
• Age: 19 Years – 70 Years
• Healthy volunteers: Not accepted

Summary

This study was designed to evaluate the efficacy of the mobile application named Circadian Rhythm for Mood (CRM), which was developed to prevent recurring episodes of mood disorders (major depressive disorders, bipolar disorders type 1 and 2) based on machine learning.

Conditions

• Major Depressive Disorder
• Bipolar 1 Disorder
• Bipolar II Disorder

Interventions

Type	Name	Description
OTHER	Circadian Rhythms for Mood (CRM) application - Active	The study subjects participating in this clinical trial wear wearable activity tracker 24 hours a day for a continuous period of time and run the CRM app once a day to check their conditions (feelings, vitality, sleep, etc.) in the Daily Symptom Assessment (eMoodChart). The active intervention group are provided with mood prediction results and instructions as feedback through the 'life report' and push notification in the application.
OTHER	Circadian Rhythms for Mood (CRM) application - Sham	The study subjects assigned to the sham intervention group are provided with feedbacks operated by dummy algorithm. The application is visually indistinguishable from active CRM, and it is designed to minimize behavioral change.

Timeline

• Start date: 2022-05-27
• Primary completion: 2023-12-21
• Completion: 2023-12-21
• First posted: 2022-06-02
• Last updated: 2025-03-17

Locations

1 site across 1 country: South Korea