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

Primary Purpose

Major Depressive Disorder, Bipolar 1 Disorder, Bipolar II Disorder

Status

Recruiting

Phase

Not Applicable

Locations

Korea, Republic of

Study Type

Interventional

Intervention

Circadian Rhythms for Mood (CRM) application - Active

Circadian Rhythms for Mood (CRM) application - Sham

About this trial

This is an interventional prevention trial for Major Depressive Disorder

Eligibility Criteria

19 Years - 70 Years (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

Male and female patients, 19-70 years old
Diagnosis with Bipolar I disorder, Bipolar II disorder, Major depressive disorder based on DSM-5 criteria, in euthymic state for more than two weeks at the time of the recruitment
Android smartphone users, capable of installing and executing the CRM application
Consent to wear wearable device (Fitbit) continuously and synchronize and backup data regularly

Exclusion Criteria:

Patients who have not experienced major depressive, manic, or hypomanic episode in the last two years
Patients who are difficult to specify mood episode or evaluate symptoms of mood episode independently due to personality traits (borderline personality trait, cyclothymic temperament, etc.)
Patients with degenerative neurological disorders (Parkinson's disease, dementia, Huntington's disease, etc.), neurodevelopmental disorders (intellectual disorder, autism spectrum disorder, down syndrome, etc.), epilepsy, severe traumatic brain damage, stroke, and other brain neurological disorders
Inmates or patients who are forced into custody for the treatment of mental or physical illness (non-voluntary isolation or hospitalization)
Patients with difficulties in understanding the objectives and process of the study and the potential benefits and risks of participating in the study

Sites / Locations

Korea University Anam HospitalRecruiting

Arms of the Study

Arm 1

Arm 2

Arm Type

Active Comparator

Sham Comparator

Arm Label

Active CRM

Sham CRM

Arm Description

Outcomes

Primary Outcome Measures

Comparison of total number of recurrent mood episodes between the active and sham groups

We aim to evaluate the efficacy of reducing recurrence rate of mood episodes through the CRM mobile application.

Comparison of duration of mood episodes between the active and sham groups

We aim to evaluate the efficacy of reducing duration of mood episodes through the CRM mobile application.

Secondary Outcome Measures

Full Information

NCT ID

NCT05400785

First Posted

May 27, 2022

Last Updated

December 20, 2022

Sponsor

Hucircadian

Collaborators

Korea University Guro Hospital, Korea University Ansan Hospital, Pusan National University Hospital, Inje University Ilsan Paik Hospital

1. Study Identification

Unique Protocol Identification Number

NCT05400785

Brief Title

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

Official Title

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

Study Type

Interventional

2. Study Status

Record Verification Date

December 2022

Overall Recruitment Status

Recruiting

Study Start Date

May 27, 2022 (Actual)

Primary Completion Date

July 31, 2023 (Anticipated)

Study Completion Date

October 31, 2023 (Anticipated)

3. Sponsor/Collaborators

Responsible Party, by Official Title

Sponsor

Name of the Sponsor

Hucircadian

Collaborators

Korea University Guro Hospital, Korea University Ansan Hospital, Pusan National University Hospital, Inje University Ilsan Paik Hospital

4. Oversight

Studies a U.S. FDA-regulated Drug Product

Studies a U.S. FDA-regulated Device Product

5. Study Description

Brief 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study

Major Depressive Disorder, Bipolar 1 Disorder, Bipolar II Disorder

7. Study Design

Primary Purpose

Prevention

Study Phase

Not Applicable

Interventional Study Model

Parallel Assignment

Masking

ParticipantCare ProviderInvestigator

Allocation

Randomized

Enrollment

96 (Anticipated)

8. Arms, Groups, and Interventions

Arm Title

Active CRM

Arm Type

Active Comparator

Arm Title

Sham CRM

Arm Type

Sham Comparator

Intervention Type

Other

Intervention Name(s)

Circadian Rhythms for Mood (CRM) application - Active

Intervention Description

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.

Intervention Type

Other

Intervention Name(s)

Circadian Rhythms for Mood (CRM) application - Sham

Intervention Description

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.

Primary Outcome Measure Information:

Title

Comparison of total number of recurrent mood episodes between the active and sham groups

Description

We aim to evaluate the efficacy of reducing recurrence rate of mood episodes through the CRM mobile application.

Time Frame

12 months

Title

Comparison of duration of mood episodes between the active and sham groups

Description

We aim to evaluate the efficacy of reducing duration of mood episodes through the CRM mobile application.

Time Frame

12 months

10. Eligibility

Sex

All

Minimum Age & Unit of Time

19 Years

Maximum Age & Unit of Time

70 Years

Accepts Healthy Volunteers

Eligibility Criteria

Inclusion Criteria: Male and female patients, 19-70 years old Diagnosis with Bipolar I disorder, Bipolar II disorder, Major depressive disorder based on DSM-5 criteria, in euthymic state for more than two weeks at the time of the recruitment Android smartphone users, capable of installing and executing the CRM application Consent to wear wearable device (Fitbit) continuously and synchronize and backup data regularly Exclusion Criteria: Patients who have not experienced major depressive, manic, or hypomanic episode in the last two years Patients who are difficult to specify mood episode or evaluate symptoms of mood episode independently due to personality traits (borderline personality trait, cyclothymic temperament, etc.) Patients with degenerative neurological disorders (Parkinson's disease, dementia, Huntington's disease, etc.), neurodevelopmental disorders (intellectual disorder, autism spectrum disorder, down syndrome, etc.), epilepsy, severe traumatic brain damage, stroke, and other brain neurological disorders Inmates or patients who are forced into custody for the treatment of mental or physical illness (non-voluntary isolation or hospitalization) Patients with difficulties in understanding the objectives and process of the study and the potential benefits and risks of participating in the study

Central Contact Person:

First Name & Middle Initial & Last Name or Official Title & Degree

Heon-Jeong Lee, MD, PhD

Phone

+82 10 4529 5653

leehjeong@korea.ac.kr

Facility Information:

Facility Name

Korea University Anam Hospital

City

Seoul

Country

Korea, Republic of

Individual Site Status

Recruiting

Facility Contact:

First Name & Middle Initial & Last Name & Degree

Heon-Jeong Lee, MD, PhD

Phone

+82 10 4529 5653

leehjeong@korea.ac.kr

First Name & Middle Initial & Last Name & Degree

Heon-Jeong Lee, MD, PhD

12. IPD Sharing Statement

Learn more about this trial

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

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