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AI-Enabled Smartwatch for Medication Adherence in Outpatient Psychiatry

NCT07455916 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 85

Last updated 2026-08-24

No results posted yet for this study

Summary

Medication nonadherence remains difficult to measure objectively in psychiatric care. This completed, single-center exploratory randomized trial evaluated whether four weeks of AI-enabled smartwatch medication monitoring improved clinician-rated medication adherence compared with waitlist usual care in psychiatric outpatients aged 12 years or older, predominantly adolescents and young adults with mood disorders.

Conditions

  • Mood Disorders
  • Medication Adherence
  • Mental Disorders

Interventions

DEVICE

AI-enabled smartwatch

The smartwatch was designed to detect medication-taking behavior using a built-in camera and electronic tags attached to medication containers. The camera remained inactive under ordinary conditions and captured a brief sequence only when container motion, ambient light, and close proximity between the watch and tag were detected concurrently. The captured sequence was processed by an artificial intelligence algorithm to classify whether a medication-taking event had occurred. Participants assigned to the intervention were instructed to wear the device for four weeks. The device provided monitoring only and delivered no reminders, alerts, counseling, or treatment recommendations.

Sponsors & Collaborators

  • Wonkwang University Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
12 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-12-31
Primary Completion
2025-08-31
Completion
2025-08-31

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 NCT07455916 on ClinicalTrials.gov