Using smartphone and wearable data plus AI-guided online CBT to personalize depression care

Integrating Digital Phenotypes and AI-Driven Cognitive-Behavioral Therapy: Advancing Precision Medicine in Depression Through Digital Medicine

Not applicable Interventional National Science and Technology Council, Taiwan · NCT07500714

This project will try combining real-time smartphone and wearable monitoring with AI-driven online cognitive-behavioral therapy to personalize treatment for adults (18–75) with major depressive disorder in Taiwan.

Quick facts

PhaseNot applicable
Study typeInterventional
Enrollment100 (estimated)
Ages18 Years to 75 Years
SexAll
SponsorNational Science and Technology Council, Taiwan Government
Locations1 site (Taichung, Taichung)
Trial IDNCT07500714 on ClinicalTrials.gov

What this trial studies

Participants will provide passive and active digital phenotyping data (behavioral and physiological signals) via smartphones and wearables while receiving either AI-driven internet cognitive-behavioral therapy or a sham internet intervention. The platform will link dynamic, real-time markers to symptom changes to refine diagnostic classifications and guide individualized therapeutic recommendations. Eligible participants are adults with DSM-5 major depressive disorder and a HAMD-21 score above 17 who have had no recent changes in psychiatric treatment. The study is conducted at the Mind Body Interface Research Center in Taichung and aims to integrate data-driven diagnostics with personalized digital treatment pathways.

Who should consider this trial

Good fit: Adults aged 18–75 with DSM-5 major depressive disorder, HAMD-21 > 17, stable psychiatric treatment for at least four weeks, capacity to consent, and ability to use a smartphone and attend the Taichung site are ideal candidates.

Not a fit: Patients with marked to extreme illness severity (high CGI-S), psychotic or bipolar disorders, recent substance use disorder, active suicidal ideation, or unstable medical illness are unlikely to benefit from participation.

Why it matters

Potential benefit: If successful, the approach could speed up matching patients to more effective, personalized treatments and reduce the need for frequent in-person visits.

How similar studies have performed: Previous work has shown promising results for internet CBT and for digital phenotyping separately, but combining real-time digital markers with AI-driven individualized CBT is relatively novel and less well tested.

Eligibility criteria

Show full inclusion / exclusion criteria
Inclusion Criteria:

* (1) Aged 18-75 years
* Diagnosis of major depressive disorder disorder (Based on Diagnostic Statistical Manual 5)
* 21-item Hamilton Depression Scale (HAMD21)\>17
* No changes in current psychiatric treatment for depression (e.g., no treatment, antidepressant medication, psychotherapy, or non-invasive brain stimulation) within the past four weeks, and
* Full competency to understand the study details and provide written informed consent

Exclusion Criteria:

* Scores of 5 ( Markedly ill), 6,(Severely ill), and 7 (Among the most extremely ill) according to the Clinical Global Impression Scale-Severity (CGI-S)
* Psychotic disorders, bipolar affective disorder, a substance use disorders in the past 6 months, active suicidal or homicidal ideation (per assessment or HAMD\>3)
* Unstable or active medical illness.

Where this trial is running

Taichung, Taichung

Study contacts

How to participate

  1. Review the eligibility criteria above with your treating physician.
  2. Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
  3. Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions Depression - Major Depressive Disorder
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.