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Digital Phenotypes for Predicting Depression

NCT07151846 · Status: ENROLLING_BY_INVITATION · Type: OBSERVATIONAL · Enrollment: 540

Last updated 2025-09-03

No results posted yet for this study

Summary

This longitudinal study aims to identify and validate digital phenotypes that can predict recurrence of major depressive episodes using passively collected, real-time sensing data from smartphones and wearable devices. Over a 12-month period, 540 participants-including patients with mood disorders and healthy or high-risk controls-will complete five clinical assessments at 3-month intervals, wear a Fitbit device daily, and log daily mood ratings via a mobile app. The study includes the development of AI-based predictive models and the construction of an anonymized wearable big-data repository for mood disorders.

Conditions

  • Depression - Major Depressive Disorder
  • Depression Bipolar
  • Bipolar Disorder (BD)
  • Mood Disorders

Sponsors & Collaborators

  • Korea University Medicine

    collaborator UNKNOWN

  • Hucircadian

    collaborator INDUSTRY

  • Korea University Anam Hospital

    lead OTHER

Principal Investigators

  • Heon-Jeong Lee, Professor · Korea University Anam Hospital

Eligibility

Min Age
19 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-02-27
Primary Completion
2026-08-31
Completion
2026-08-31

Countries

  • South Korea

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07151846 on ClinicalTrials.gov