Ignite Creation Date:
2025-12-25 @ 2:40 AM
Ignite Modification Date:
2026-02-22 @ 7:25 AM
Study NCT ID:
NCT03783533
Status:
COMPLETED
Last Update Posted:
2022-09-16
First Post:
2018-11-29
Is NOT Gene Therapy:
True
Has Adverse Events:
True
Brief Title:
Adapting Behavioral Activation to Technology Platform
Sponsor:
Organization:
Raw JSON
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BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood.", 'otherNumAtRisk': 11, 'deathsNumAtRisk': 11, 'otherNumAffected': 0, 'seriousNumAtRisk': 11, 'deathsNumAffected': 0, 'seriousNumAffected': 0}], 'frequencyThreshold': '0'}, 'outcomeMeasuresModule': {'outcomeMeasures': [{'type': 'PRIMARY', 'title': 'Patient Health Questionnaire-Adolescent (PHQ-8)', 'denoms': [{'units': 'Participants', 'counts': [{'value': '5', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Adolescents', 'description': "Adolescents with PHQ-9 scores between 5 and 20 who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings. 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BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). 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BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood."}], 'classes': [{'categories': [{'measurements': [{'value': '3.50', 'spread': '.71', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': 'Measured within 3-week post BA App User Testing', 'description': 'This is a survey measure that assesses the feasibility of the intervention adaptation with both clinician and adolescent participants. Scores range from 4 to 20 with higher scores indicating higher feasibility.', 'unitOfMeasure': 'units on a scale', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}, {'type': 'SECONDARY', 'title': 'Platform Engagement', 'denoms': [{'units': 'Participants', 'counts': [{'value': '5', 'groupId': 'OG000'}]}], 'groups': [{'id': 'OG000', 'title': 'Adolescents', 'description': "Adolescents with PHQ-9 scores between 5 and 20 who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings. The investigators will recruit new adolescents for each Aim to decrease bias in feedback and outcomes.\n\nBehavioral Activation: Intervention: Behavioral Activation (BA) therapy is based on a functional analytic model of depression that highlights the need for increased positive reinforcement (rewards) and decreased anhedonia, or diminished motivation to seek rewards, to maintain normal mood. BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood."}], 'classes': [{'categories': [{'measurements': [{'value': '52.13', 'spread': '45.53', 'groupId': 'OG000'}]}]}], 'paramType': 'MEAN', 'timeFrame': 'Measuring platform engagement across 35 days of platform use.', 'description': 'Platform mood-activity logging across 35 days of possible logging 3x/day', 'unitOfMeasure': 'Number of mood-activity logs', 'dispersionType': 'Standard Deviation', 'reportingStatus': 'POSTED'}]}, 'participantFlowModule': {'groups': [{'id': 'FG000', 'title': 'Adolescents', 'description': "Adolescents with PHQ-9 scores between 5 and 20 who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings. The investigators will recruit new adolescents for each Aim to decrease bias in feedback and outcomes.\n\nBehavioral Activation: Intervention: Behavioral Activation (BA) therapy is based on a functional analytic model of depression that highlights the need for increased positive reinforcement (rewards) and decreased anhedonia, or diminished motivation to seek rewards, to maintain normal mood. BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood."}], 'periods': [{'title': 'Overall Study', 'milestones': [{'type': 'STARTED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '11'}]}, {'type': 'COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '7'}]}, {'type': 'NOT COMPLETED', 'achievements': [{'groupId': 'FG000', 'numSubjects': '4'}]}]}], 'recruitmentDetails': "To recruit teens between February and March 2020, we advertised our study in online groups, sent messages and flyers to clinicians, and a mailing list of parents with teenagers. Interested participants filled out a screener with contact information and the PHQ-8. If the teen was experiencing PHQ-8 \\>15, we required that they had a current therapist. Participants were paid $10 for each week's activity and $20 for exit interviews. All study activities were conducted between May and August 2020."}, 'baselineCharacteristicsModule': {'denoms': [{'units': 'Participants', 'counts': [{'value': '11', 'groupId': 'BG000'}]}], 'groups': [{'id': 'BG000', 'title': 'Adolescents', 'description': "Adolescents with PHQ-9 scores between 5 and 12 (Mild Range) who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings. The investigators will recruit new adolescents for each Aim to decrease bias in feedback and outcomes.\n\nBehavioral Activation: Intervention: Behavioral Activation (BA) therapy is based on a functional analytic model of depression that highlights the need for increased positive reinforcement (rewards) and decreased anhedonia, or diminished motivation to seek rewards, to maintain normal mood. BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood."}], 'measures': [{'title': 'Age, Categorical', 'classes': [{'categories': [{'title': '<=18 years', 'measurements': [{'value': '11', 'groupId': 'BG000'}]}, {'title': 'Between 18 and 65 years', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': '>=65 years', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Age, Continuous', 'classes': [{'categories': [{'measurements': [{'value': '15.83', 'spread': '2.14', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'unitOfMeasure': 'years', 'dispersionType': 'STANDARD_DEVIATION'}, {'title': 'Sex/Gender, Customized', 'classes': [{'title': 'Female', 'categories': [{'measurements': [{'value': '4', 'groupId': 'BG000'}]}]}, {'title': 'Male', 'categories': [{'measurements': [{'value': '4', 'groupId': 'BG000'}]}]}, {'title': 'Non-binary/Transgender', 'categories': [{'measurements': [{'value': '1', 'groupId': 'BG000'}]}]}, {'title': 'Unknown', 'categories': [{'measurements': [{'value': '2', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Ethnicity (NIH/OMB)', 'classes': [{'categories': [{'title': 'Hispanic or Latino', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Not Hispanic or Latino', 'measurements': [{'value': '6', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '5', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Race (NIH/OMB)', 'classes': [{'categories': [{'title': 'American Indian or Alaska Native', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Asian', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Native Hawaiian or Other Pacific Islander', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'Black or African American', 'measurements': [{'value': '0', 'groupId': 'BG000'}]}, {'title': 'White', 'measurements': [{'value': '5', 'groupId': 'BG000'}]}, {'title': 'More than one race', 'measurements': [{'value': '1', 'groupId': 'BG000'}]}, {'title': 'Unknown or Not Reported', 'measurements': [{'value': '5', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Region of Enrollment', 'classes': [{'title': 'United States', 'categories': [{'measurements': [{'value': '11', 'groupId': 'BG000'}]}]}], 'paramType': 'COUNT_OF_PARTICIPANTS', 'unitOfMeasure': 'Participants'}, {'title': 'Patient Health Questionnaire-8', 'classes': [{'categories': [{'measurements': [{'value': '14.44', 'spread': '3.94', 'groupId': 'BG000'}]}]}], 'paramType': 'MEAN', 'description': 'Measure of depression symptoms in the last 2 weeks. Scores range from 0 to 24 with higher scores indicating higher depression symptoms.', 'unitOfMeasure': 'units on a scale', 'dispersionType': 'STANDARD_DEVIATION'}]}}, 'documentSection': {'largeDocumentModule': {'largeDocs': [{'date': '2022-02-14', 'size': 3038665, 'label': 'Study Protocol, Statistical Analysis Plan, and Informed Consent Form', 'hasIcf': True, 'hasSap': True, 'filename': 'Prot_SAP_ICF_000.pdf', 'typeAbbrev': 'Prot_SAP_ICF', 'uploadDate': '2022-08-22T18:05', 'hasProtocol': True}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'TREATMENT', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 11}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2019-08-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2022-08', 'completionDateStruct': {'date': '2020-12-31', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2022-08-22', 'studyFirstSubmitDate': '2018-11-29', 'resultsFirstSubmitDate': '2022-07-22', 'studyFirstSubmitQcDate': '2018-12-19', 'lastUpdatePostDateStruct': {'date': '2022-09-16', 'type': 'ACTUAL'}, 'resultsFirstSubmitQcDate': '2022-08-22', 'studyFirstPostDateStruct': {'date': '2018-12-21', 'type': 'ACTUAL'}, 'resultsFirstPostDateStruct': {'date': '2022-09-16', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-12-31', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Patient Health Questionnaire-Adolescent (PHQ-8)', 'timeFrame': 'Measured within 3-weeks post BA App User Testing', 'description': 'Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms.'}, {'measure': 'User Burden Scale', 'timeFrame': 'Measured within 3-weeks post BA App User Testing', 'description': 'Assesses the burden of the intervention adaptation with both clinician and adolescent participants across several domains and ranges from 0 to 80 for a total score with higher scores indicating higher burden. Scores were averaged across subscales including:\n\n* Access Burden\n* Emotional Burden\n* Financial Burden\n* Mental Burden\n* Physical Burden\n* Privacy Burden\n* Social Burden\n* Time Burden'}, {'measure': 'Acceptability of Intervention Measure', 'timeFrame': 'Measured within 3-weeks post BA App User Testing', 'description': 'This is a survey measure that assesses the acceptability of the intervention adaptation with both clinician and adolescent participants. Scores range from 4 to 20 with higher scores indicating higher acceptability.'}, {'measure': 'Appropriateness of Intervention Measure', 'timeFrame': 'Measured within 3-week post BA App User Testing', 'description': 'This is a survey measure that assesses the appropriateness of the intervention adaptation with both clinician and adolescent participants. Scores range from 4 to 20 with higher scores indicating higher appropriateness.'}, {'measure': 'Feasibility of Intervention Measure', 'timeFrame': 'Measured within 3-week post BA App User Testing', 'description': 'This is a survey measure that assesses the feasibility of the intervention adaptation with both clinician and adolescent participants. Scores range from 4 to 20 with higher scores indicating higher feasibility.'}], 'secondaryOutcomes': [{'measure': 'Platform Engagement', 'timeFrame': 'Measuring platform engagement across 35 days of platform use.', 'description': 'Platform mood-activity logging across 35 days of possible logging 3x/day'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Depression']}, 'descriptionModule': {'briefSummary': 'This project aims to use an asynchronous remote communities (ARC) approach both to discover the design requirements for adapting Behavioral Activation (BA) to ARC as well as design/build an ARC platform for administering BA. The investigators will test the feasibility of our approach in a small feasibility observational study with clinicians and adolescents.', 'detailedDescription': 'An estimated 3.1 million adolescents are diagnosed with depression (MDD) each year (SAMHSA, 2016), and adolescent onset MDD is associated with chronic physical, mental and psychosocial disability (Birmaher et al., 1996). However, over 60% of adolescents with MDD do not receive mental health care, and, among those who do, treatment engagement is low (SAMHSA, 2016; Olfson et al., 2003). Behavioral Activation (BA) is an evidence-based psychosocial intervention (EBPI) for individuals with MDD (Dimidjian et al., 2006). While BA holds promise as an effective treatment with adolescents (McCauley et al., 2015, 2016), previous research approaches have found that adolescents may be better reached and engaged through social media, mobile technologies, and other technology platforms (Boyd, 2007; Park \\& Calamaro, 2013). In addition, BA requires frequent interaction from patients over time, which can be difficult and costly for clinicians to administer directly. Thus, there is an opportunity to improve usability and engagement of EBPIs via new technology-based tools. Asynchronous Remote Communities (ARC) is a promising technology-based approach for engaging adolescents that capitalizes on the reach of technology while also providing support, social interactions, and motivation to engage. ARCs are technology-mediated groups that use private online platforms to deliver weekly tasks to participants and gather information about perceptions in a format that is lightweight, accessible, usable, and low burden. The investigators aim to use ARC both to discover the design requirements for adapting BA to ARC as well as design/build an ARC platform for administering BA. The investigators will test the feasibility of our approach in a small feasibility study with clinicians and adolescents. The investigators propose the following specific aims:\n\nAim 1: Use the ARC approach with adolescents, primary care physicians, and mental health specialists to discover target user needs, design constraints and to observe their experience with ARC: The investigators will first use ARC to collect target user (i.e., primary care providers (PCP) and mental health specialists, adolescents at risk for depression) data to understand their needs and the facilitators and barriers to adapting BA to ARC.\n\nAim 2: Design \\& build an ARC platform for BA delivery with adolescents: Once the investigators have a strong understanding of the facilitators and barriers, the investigators will design a platform to use the ARC approach for BA delivery via Slack. The investigators will use an iterative design approach to understand the technical feasibility of the approach, whether and how to automate parts of the BA intervention using chatbots and other custom applications within Slack. The investigators will conduct small, informal usability testing with target users during this stage.\n\nAim 3: Test feasibility and usability with small pilot groups of adolescent and clinician target users: Once the investigators have a robust enough prototype of the ARC delivery platform for BA, the investigators will conduct a small pilot study with adolescents at-risk for depression and clinicians to assess the feasibility and usability of the approach. The investigators will collect data on the feasibility, usability, user burden, acceptability, and symptom outcomes.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['CHILD'], 'maximumAge': '17 Years', 'minimumAge': '13 Years', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* Adolescents with PHQ-9 scores between 5 and 15 (Mild to Moderate Range) who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings.\n\nExclusion Criteria:\n\n* Current suicidal ideation or PHQ-9 scores that are below or above the cutoff described above for adolescents."}, 'identificationModule': {'nctId': 'NCT03783533', 'briefTitle': 'Adapting Behavioral Activation to Technology Platform', 'organization': {'class': 'OTHER', 'fullName': 'University of Washington'}, 'officialTitle': 'Designing and Evaluating an Asynchronous Remote Communication Approach to Behavioral Activation With Clinicians and Adolescents At Risk for Depression', 'orgStudyIdInfo': {'id': 'STUDY00002824'}, 'secondaryIdInfos': [{'id': 'P50MH115837', 'link': 'https://reporter.nih.gov/quickSearch/P50MH115837', 'type': 'NIH'}]}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Adolescent Target Users of Behavioral Activation (BA) App', 'description': "Adolescents with PHQ-9 scores between 5 and 12 (Mild Range) who do not report current suicidality (Pine et al., 1999) will be recruited from clinician target users' practice settings. The investigators will recruit new adolescents for each Aim to decrease bias in feedback and outcomes.", 'interventionNames': ['Behavioral: Behavioral Activation']}], 'interventions': [{'name': 'Behavioral Activation', 'type': 'BEHAVIORAL', 'description': "Intervention: Behavioral Activation (BA) therapy is based on a functional analytic model of depression that highlights the need for increased positive reinforcement (rewards) and decreased anhedonia, or diminished motivation to seek rewards, to maintain normal mood. BA is significantly more effective than Cognitive Behavioral Therapy and comparable to antidepressant medication in reducing depressive symptoms among depressed adults (Dimidjian et al., 2006). McCauley (senior mentor) et al. (2016) adapted BA for adolescents to target anhedonia, effective problem solving and avoidant behaviors with peers, family, and school. McCauley's findings and others show BA is a promising intervention for adolescent MDD (Chu et al., 2009; Cuijpers et al.,, 2007; McCauley et al., 2015; Ritschel et al., 2011). BA focuses on targeting ideographically identified avoidant behaviors and rewarding experiences that affect mood.", 'armGroupLabels': ['Adolescent Target Users of Behavioral Activation (BA) App']}]}, 'contactsLocationsModule': {'locations': [{'zip': '98115', 'city': 'Seattle', 'state': 'Washington', 'country': 'United States', 'facility': 'University of Washington', 'geoPoint': {'lat': 47.60621, 'lon': -122.33207}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'University of Washington', 'class': 'OTHER'}, 'collaborators': [{'name': 'National Institute of Mental Health (NIMH)', 'class': 'NIH'}], 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Acting Assistant Professor', 'investigatorFullName': 'Jessica Jenness', 'investigatorAffiliation': 'University of Washington'}}}}