protocolSection identificationModule nctId: NCT06292221, orgStudyIdInfo id: H19-078, secondaryIdInfos id: R01MH119678, type: NIH, link: https://reporter.nih.gov/quickSearch/R01MH119678, briefTitle: Personalized Depression Treatment Supported by Mobile Sensor Analytics, acronym: DepWatch, statusModule overallStatus: NOT_YET_RECRUITING, startDateStruct date: 2024-03, primaryCompletionDateStruct date: 2025-04, completionDateStruct date: 2025-06, studyFirstPostDateStruct date: 2024-03-05, lastUpdatePostDateStruct date: 2024-03-05, sponsorCollaboratorsModule leadSponsor name: UConn Health, class: OTHER, collaborators name: National Institute of Mental Health (NIMH), descriptionModule briefSummary: 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 process2. 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., conditionsModule conditions: Depression, designModule studyType: INTERVENTIONAL, phases: NA, designInfo allocation: RANDOMIZED, interventionModel: PARALLEL, interventionModelDescription: 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, primaryPurpose: DIAGNOSTIC, maskingInfo masking: NONE, maskingDescription: There is no masking, enrollmentInfo count: 128, type: ESTIMATED, armsInterventionsModule interventions name: A mobile Health (mHealth) tool called 'DepWatch', outcomesModule primaryOutcomes measure: Feasibility and Usability, secondaryOutcomes measure: Depression outcomes, eligibilityModule sex: ALL, stdAges: CHILD, stdAges: ADULT, stdAges: OLDER_ADULT, contactsLocationsModule, hasResults: False