Personalized Depression Treatment Supported by Mobile Sensor Analytics
NCT ID: NCT06292221
Last Updated: 2025-07-31
Study Results
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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COMPLETED
NA
22 participants
INTERVENTIONAL
2024-04-04
2025-06-08
Brief Summary
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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.
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
NONE
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
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
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'
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
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
Eligibility Criteria
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Inclusion Criteria
* 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
* 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
ALL
No
Sponsors
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National Institute of Mental Health (NIMH)
NIH
UConn Health
OTHER
Responsible Party
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Bing Wang
Professor
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
Countries
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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.
Other Identifiers
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H19-078
Identifier Type: -
Identifier Source: org_study_id
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