Ignite Creation Date:
2026-03-26 @ 3:16 PM
Ignite Modification Date:
2026-03-29 @ 11:51 PM
Study NCT ID:
NCT07382804
Status:
ENROLLING_BY_INVITATION
Last Update Posted:
2026-02-03
First Post:
2026-01-25
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Mobile Behavioral Activation Program With Wearable Sensors and Secure Activity Verification
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2026-03-25'}, 'conditionBrowseModule': {'meshes': [{'id': 'D015438', 'term': 'Health Behavior'}, {'id': 'D057185', 'term': 'Sedentary Behavior'}], 'ancestors': [{'id': 'D001519', 'term': 'Behavior'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'OTHER', 'interventionModel': 'PARALLEL', 'interventionModelDescription': 'Participants are assigned to one of several intervention groups operating in parallel. Each group receives a distinct combination of behavioral activation tools:\n\nGroup A: Mobile app only\n\nGroup B: Mobile app + wearable activity sensor\n\nGroup C: Mobile app + wearable sensor + decentralized data verification layer\n\nThere is no crossover between groups. Each participant engages with their assigned intervention throughout the study period.\n\nThis design allows for comparative analysis of engagement, productivity, and behavioral outcomes across intervention tiers.'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 227000}}, 'statusModule': {'overallStatus': 'ENROLLING_BY_INVITATION', 'startDateStruct': {'date': '2026-01-25', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2026-01', 'completionDateStruct': {'date': '2099-01-25', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2026-01-30', 'studyFirstSubmitDate': '2026-01-25', 'studyFirstSubmitQcDate': '2026-01-30', 'lastUpdatePostDateStruct': {'date': '2026-02-03', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2026-02-03', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2099-01-25', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Change in Average Daily Active Minutes', 'timeFrame': '8 weeks from baseline enrollment', 'description': 'Average number of minutes per day spent in non-sedentary activity, as captured by the wearable activity sensor (for applicable arms) and inferred from app interaction logs (for all arms). Daily active minutes will be averaged over the assessment period and compared across intervention arms to evaluate whether adding a wearable sensor and decentralized verification layer increases real-world physical activation associated with behavioral tasks.'}, {'measure': 'Change in Daily Task Completion Rate', 'timeFrame': '8 Weeks from baseline enrollment', 'description': 'Proportion of assigned behavioral activation tasks completed per day, as recorded by the mobile app, averaged over the assessment period. Daily task completion rate will be compared across intervention arms (mobile app only; mobile app + wearable sensor; mobile app + wearable sensor + decentralized verification layer) to evaluate the effect of each intervention tier on real-world task follow-through and productivity.'}], 'secondaryOutcomes': [{'measure': 'Change in Self-Reported Daily Productivity', 'timeFrame': '8 weeks from baseline enrollment', 'description': "Change in participants' self-reported daily productivity, measured using a brief in-app rating scale (e.g., 0-10) completed at least once per week. Scores will be averaged over the assessment period and compared across intervention arms to assess whether the different intervention tiers (mobile app only; mobile app + wearable sensor; mobile app + wearable sensor + decentralized verification layer) are associated with greater perceived productivity and task effectiveness in daily life."}, {'measure': 'Change in Routine Stability Index', 'timeFrame': '8 weeks from baseline enrollment', 'description': 'Change in routine stability, defined as the consistency of daily task timing and completion patterns over the assessment period. Routine stability will be quantified using variability in task completion times and day-to-day fluctuations in task completion rate, derived from app logs (and sensor timestamps where applicable). Lower variability indicates more stable routines. Outcomes will be compared across intervention arms to assess whether adding a wearable sensor and decentralized verification layer supports more consistent daily routines.'}]}, 'oversightModule': {'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Daily productivity', 'Task engagement', 'Routine building', 'Motivation', 'Behavioral patterns', 'Activity monitoring', 'Wearable sensor data', 'Ecological momentary intervention', 'Digital behavioral tools', 'Circadian activity patterns', 'Behavioral reinforcement', 'Adaptive prompting', 'Digital phenotyping', 'Participant-controlled data', 'Decentralized verification'], 'conditions': ['Health Behavior', 'Behavioral Activation', 'Sedentary Behavior']}, 'descriptionModule': {'briefSummary': "This study evaluates a mobile-integrated behavioral activation program designed to help adults improve their daily productivity, motivation, and task engagement. The program combines a smartphone application, wearable sensor data, and a decentralized data-verification layer to support participants as they build healthier routines and increase consistent daily activity.\n\nBehavioral activation is a well-established psychological approach that encourages individuals to take small, structured actions that align with their goals and values. In this study, participants receive daily prompts, activity suggestions, and personalized behavioral tasks through a mobile app. The app uses information from a wearable sensor-such as movement patterns, activity levels, and environmental cues-to help participants track progress and stay engaged with the program.\n\nA unique feature of this study is the use of decentralized data verification. Participants' activity logs and task completions are recorded in a secure, tamper-resistant system that allows them to maintain control over their own data while ensuring accuracy and transparency. This approach supports participant autonomy and strengthens the reliability of the study's outcome measures.\n\nThe study aims to understand whether combining behavioral activation with real-time sensor feedback and decentralized data verification can improve daily productivity, increase follow-through on planned tasks, and support healthier routines. Participants will use the mobile app and wearable device for the duration of the study and will complete periodic check-ins to share their experiences, challenges, and overall satisfaction with the program.\n\nThe research team will evaluate changes in daily activity patterns, task completion rates, self-reported productivity, and engagement with the behavioral activation tasks. Findings from this study may help inform future digital health tools that support motivation, routine-building, and personal productivity in everyday life.", 'detailedDescription': 'Daily functioning in modern environments is often affected by high cognitive load, fragmented attention, and inconsistent routines. Many adults experience difficulty initiating tasks, sustaining engagement, and maintaining productive habits. Behavioral Activation (BA), originally developed for mood-related conditions, provides a structured approach for increasing engagement in meaningful activities and reducing avoidance patterns. BA emphasizes that action precedes motivation and that small, achievable behaviors can create reinforcement cycles that improve daily functioning.\n\nMobile technology and wearable sensors now allow BA principles to be delivered in real time. Wearable devices can detect movement patterns, activity levels, sleep-related rhythms, and environmental cues. When paired with a mobile application, these data streams support adaptive prompts, personalized task suggestions, and real-time feedback. This integration enables interventions to occur in natural environments rather than relying solely on retrospective self-report.\n\nTo enhance transparency and participant autonomy, the study incorporates a decentralized verification layer. Traditional digital-health systems rely on centralized data storage controlled by the research team. In contrast, decentralized verification provides tamper-resistant logs, participant-controlled data review, and transparent audit trails. This approach supports data integrity and participant trust.\n\nThe study evaluates a mobile-integrated behavioral activation program supported by wearable sensors and a decentralized verification layer. The objective is to determine whether this combined approach can improve daily functioning, increase follow-through on planned tasks, and support healthier routines in adults seeking to enhance their productivity.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* Adults age 18 or older\n* Owns a compatible smartphone capable of running the study app\n* Willing to wear a lightweight activity sensor during waking hours (for applicable arms)\n* Able to read and understand study instructions in English\n* Willing to complete daily tasks and weekly check-ins through the mobile app\n* Provides informed consent\n\nExclusion Criteria:\n\n* Any condition that would prevent use of a mobile app or wearable sensor (e.g., inability to operate a smartphone)\n* Any condition that would interfere with participation in daily behavioral tasks as determined by the research team\n* Current participation in another digital-behavioral intervention study\n* Inability or unwillingness to comply with study procedures\n* Plans to travel or relocate in a way that would prevent consistent participation during the study period'}, 'identificationModule': {'nctId': 'NCT07382804', 'acronym': 'MBAP-X', 'briefTitle': 'Mobile Behavioral Activation Program With Wearable Sensors and Secure Activity Verification', 'organization': {'class': 'INDUSTRY', 'fullName': 'Truway Health, Inc.'}, 'officialTitle': 'A Mobile-Integrated Behavioral Activation Program Using Wearable Sensor Support and Optional Decentralized Data Verification to Enhance Daily Productivity in Healthy Adults', 'orgStudyIdInfo': {'id': 'TH-MBAP-2026-001'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Experimental - Mobile App Only', 'description': 'Participants use a mobile behavioral activation application that delivers daily tasks, reminders, and routine-building prompts. No wearable sensor or secure activity-verification layer is used in this arm.', 'interventionNames': ['Behavioral: Behavioral: Mobile Behavioral Activation App']}, {'type': 'EXPERIMENTAL', 'label': 'Experimental - Mobile App + Wearable Sensor', 'description': 'Participants use the same mobile behavioral activation app as Arm 1 and also wear a lightweight activity sensor that passively tracks movement and activity patterns. Sensor-derived activity data may inform the timing or intensity of app-delivered prompts.', 'interventionNames': ['Behavioral: Mobile App + Wearable Activity Sensor']}, {'type': 'EXPERIMENTAL', 'label': 'Experimental - Mobile App + Wearable Sensor + Secure Activity Verification', 'description': 'Participants use the mobile behavioral activation app and wearable activity sensor. Activity logs are additionally processed through a secure verification layer that provides participant-controlled, tamper-evident activity records used for engagement tracking and outcome analysis.', 'interventionNames': ['Behavioral: Mobile App + Wearable Sensor + Secure Activity Verification Layer']}], 'interventions': [{'name': 'Behavioral: Mobile Behavioral Activation App', 'type': 'BEHAVIORAL', 'description': 'Participants receive daily behavioral activation tasks, structured prompts, and routine-building cues delivered through the mobile app only.', 'armGroupLabels': ['Experimental - Mobile App Only']}, {'name': 'Mobile App + Wearable Activity Sensor', 'type': 'BEHAVIORAL', 'description': 'Participants receive behavioral activation tasks through the mobile app and wear an activity sensor that provides real-time movement data used to tailor prompts and support engagement.', 'armGroupLabels': ['Experimental - Mobile App + Wearable Sensor']}, {'name': 'Mobile App + Wearable Sensor + Secure Activity Verification Layer', 'type': 'BEHAVIORAL', 'description': 'Participants receive behavioral activation tasks, sensor-based feedback, and secure verification of activity logs through a tamper-resistant verification layer.', 'armGroupLabels': ['Experimental - Mobile App + Wearable Sensor + Secure Activity Verification']}]}, 'contactsLocationsModule': {'locations': [{'zip': '10016', 'city': 'New York', 'state': 'New York', 'country': 'United States', 'facility': 'Truway Health, Inc.', 'geoPoint': {'lat': 40.71427, 'lon': -74.00597}}], 'overallOfficials': [{'name': 'Gavin Solomon, CEO', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Truway Health, Inc.'}]}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Truway Health, Inc.', 'class': 'INDUSTRY'}, 'responsibleParty': {'type': 'SPONSOR'}}}}