Personalized Depression Treatment Supported by Mobile Sensor Analytics

NCT ID: NCT06292221

Last Updated: 2025-07-31

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

22 participants

Study Classification

INTERVENTIONAL

Study Start Date

2024-04-04

Study Completion Date

2025-06-08

Brief Summary

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The current best practice guidelines for treating depression call for close monitoring of patients, and periodically adjusting treatment as needed. This present study seeks to develop and investigate an innovative digital system, DepWatch, that leverages mobile health technologies and machine learning tools to provide clinicians objective, accurate, and timely assessment of depression symptoms to assist with their clinical decision making process. Specifically, DepWatch collects sensory data passively from smartphones and wristbands, without any user interaction, and uses simple user-friendly interfaces to collect ecological momentary assessments (EMA), medication adherence and safety related data from patients. The collected data will be fed to machine learning models to be developed in the project to provide weekly assessment of patient symptom levels and predict the trajectory of treatment response over time. The assessment and prediction results are then presented using a graphic interface to clinicians to help them make critical treatment decisions. The main question the present clinical trial aims to answer are as follows:

1. Feasibility of the digital tool, DepWatch, to assist clinicians in depression treatment and inform their clinical decision process
2. Effectiveness of the digital tool, DepWatch, to improve depression treatment outcomes All study participants will carry the DepWatch app on their smartphones and wear a Fitbit provided by the study team during the study period. They will also complete brief questionnaires via the app at specific time intervals throughout the study period.

Detailed Description

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Conditions

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Depression

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Two groups of participants (64 per group) will be enrolled and will participate in the study over a 3 month period . Both will receive standard of care depression treatment with their respective providers in the clinic. Both groups will undergo standard depression assessment using depression questionnaires as well as behavioral assessments using a mobile health (mHealth) tool 'DepWatch' developed by the study team in the phase I of the study. Study clinicians will receive weekly behavioral assessment reports for participants enrolled in the first 'experimental' group and will not receive such reports for the second 'control' group
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

There is no masking

Study Groups

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Experimental

For this group of participants: The study clinicians will receive the weekly depression and behavioral assessment reports generated by the mHealth tool 'DepWatch' via a secure clinician portal

Group Type EXPERIMENTAL

A mobile Health (mHealth) tool called 'DepWatch'

Intervention Type OTHER

The mobile Health (mHealth) tool 'DepWatch' developed by the study team consists of the DepWatch app that is uploaded on participant's smart phones with their consent and a Fitbit provided to the participants

Control

For this group of participants: The study clinicians will NOT receive the weekly depression and behavioral assessment reports generated by the mHealth tool 'DepWatch'

Group Type OTHER

A mobile Health (mHealth) tool called 'DepWatch'

Intervention Type OTHER

The mobile Health (mHealth) tool 'DepWatch' developed by the study team consists of the DepWatch app that is uploaded on participant's smart phones with their consent and a Fitbit provided to the participants

Interventions

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A mobile Health (mHealth) tool called 'DepWatch'

The mobile Health (mHealth) tool 'DepWatch' developed by the study team consists of the DepWatch app that is uploaded on participant's smart phones with their consent and a Fitbit provided to the participants

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Age 18 year or older
* Moderate level of depression as defined by a score of ≥ 11 on the 16 item Quick Inventory of Depressive Symptomatology (QIDS) self-report questionnaire
* Initiating a pharmacological treatment for depression as monotherapy or adjunctive treatment or reporting a dose increase with their existing depression treatment.

Exclusion Criteria

* Diagnosis of a primary psychotic disorder such as schizophrenia or schizoaffective disorder
* Currently active substance use disorder (within 1 month of enrollment) dominating clinical scenario
* Other clinically significant medical of psychiatric conditions that may adversely affect participants' study participation and/or affect their adherence to study protocol (as determined by study clinician) e.g., significant cognitive deficits
Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Institute of Mental Health (NIMH)

NIH

Sponsor Role collaborator

UConn Health

OTHER

Sponsor Role lead

Responsible Party

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Bing Wang

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Jayesh Kamath, MD PhD

Role: PRINCIPAL_INVESTIGATOR

UConn Health

Locations

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University of Connecticut Health Center

Farmington, Connecticut, United States

Site Status

Countries

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United States

References

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Kamath J, Bi J, Russell A, Wang B. Grant Report on SCH: Personalized Depression Treatment Supported by Mobile Sensor Analytics. J Psychiatr Brain Sci. 2020;5:e200010. doi: 10.20900/jpbs.20200010. Epub 2020 Apr 29.

Reference Type BACKGROUND
PMID: 32529036 (View on PubMed)

Other Identifiers

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R01MH119678

Identifier Type: NIH

Identifier Source: secondary_id

View Link

H19-078

Identifier Type: -

Identifier Source: org_study_id

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