<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03783533</url>
  </required_header>
  <id_info>
    <org_study_id>STUDY00002824</org_study_id>
    <secondary_id>P50MH115837</secondary_id>
    <nct_id>NCT03783533</nct_id>
  </id_info>
  <brief_title>Adapting Behavioral Activation to Technology Platform</brief_title>
  <official_title>Designing and Evaluating an Asynchronous Remote Communication Approach to Behavioral Activation With Clinicians and Adolescents At Risk for Depression</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Washington</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Institute of Mental Health (NIMH)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Washington</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      This project aims to use an asynchronous remote communities (ARC) approach both to discover&#xD;
      the design requirements for adapting Behavioral Activation (BA) to ARC as well as&#xD;
      design/build an ARC platform for administering BA. The investigators will test the&#xD;
      feasibility of our approach in a small feasibility observational study with clinicians and&#xD;
      adolescents.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      An estimated 3.1 million adolescents are diagnosed with depression (MDD) each year (SAMHSA,&#xD;
      2016), and adolescent onset MDD is associated with chronic physical, mental and psychosocial&#xD;
      disability (Birmaher et al., 1996). However, over 60% of adolescents with MDD do not receive&#xD;
      mental health care, and, among those who do, treatment engagement is low (SAMHSA, 2016;&#xD;
      Olfson et al., 2003). Behavioral Activation (BA) is an evidence-based psychosocial&#xD;
      intervention (EBPI) for individuals with MDD (Dimidjian et al., 2006). While BA holds promise&#xD;
      as an effective treatment with adolescents (McCauley et al., 2015, 2016), previous research&#xD;
      approaches have found that adolescents may be better reached and engaged through social&#xD;
      media, mobile technologies, and other technology platforms (Boyd, 2007; Park &amp; Calamaro,&#xD;
      2013). In addition, BA requires frequent interaction from patients over time, which can be&#xD;
      difficult and costly for clinicians to administer directly. Thus, there is an opportunity to&#xD;
      improve usability and engagement of EBPIs via new technology-based tools. Asynchronous Remote&#xD;
      Communities (ARC) is a promising technology-based approach for engaging adolescents that&#xD;
      capitalizes on the reach of technology while also providing support, social interactions, and&#xD;
      motivation to engage. ARCs are technology-mediated groups that use private online platforms&#xD;
      to deliver weekly tasks to participants and gather information about perceptions in a format&#xD;
      that is lightweight, accessible, usable, and low burden. The investigators aim to use ARC&#xD;
      both to discover the design requirements for adapting BA to ARC as well as design/build an&#xD;
      ARC platform for administering BA. The investigators will test the feasibility of our&#xD;
      approach in a small feasibility study with clinicians and adolescents. The investigators&#xD;
      propose the following specific aims:&#xD;
&#xD;
      Aim 1: Use the ARC approach with adolescents, primary care physicians, and mental health&#xD;
      specialists to discover target user needs, design constraints and to observe their experience&#xD;
      with ARC: The investigators will first use ARC to collect target user (i.e., primary care&#xD;
      providers (PCP) and mental health specialists, adolescents at risk for depression) data to&#xD;
      understand their needs and the facilitators and barriers to adapting BA to ARC.&#xD;
&#xD;
      Aim 2: Design &amp; build an ARC platform for BA delivery with adolescents: Once the&#xD;
      investigators have a strong understanding of the facilitators and barriers, the investigators&#xD;
      will design a platform to use the ARC approach for BA delivery via Slack. The investigators&#xD;
      will use an iterative design approach to understand the technical feasibility of the&#xD;
      approach, whether and how to automate parts of the BA intervention using chatbots and other&#xD;
      custom applications within Slack. The investigators will conduct small, informal usability&#xD;
      testing with target users during this stage.&#xD;
&#xD;
      Aim 3: Test feasibility and usability with small pilot groups of adolescent and clinician&#xD;
      target users: Once the investigators have a robust enough prototype of the ARC delivery&#xD;
      platform for BA, the investigators will conduct a small pilot study with adolescents at-risk&#xD;
      for depression and clinicians to assess the feasibility and usability of the approach. The&#xD;
      investigators will collect data on the feasibility, usability, user burden, acceptability,&#xD;
      and symptom outcomes.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">August 1, 2019</start_date>
  <completion_date type="Actual">December 31, 2020</completion_date>
  <primary_completion_date type="Actual">December 31, 2020</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Single Group Assignment</intervention_model>
    <primary_purpose>Treatment</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Patient Health Questionnaire-Adolescent (PHQ-8)</measure>
    <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
    <description>Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>User Burden Scale</measure>
    <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
    <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:&#xD;
Access Burden&#xD;
Emotional Burden&#xD;
Financial Burden&#xD;
Mental Burden&#xD;
Physical Burden&#xD;
Privacy Burden&#xD;
Social Burden&#xD;
Time Burden</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Acceptability of Intervention Measure</measure>
    <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
    <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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Appropriateness of Intervention Measure</measure>
    <time_frame>Measured within 3-week post BA App User Testing</time_frame>
    <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.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Feasibility of Intervention Measure</measure>
    <time_frame>Measured within 3-week post BA App User Testing</time_frame>
    <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.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Platform Engagement</measure>
    <time_frame>Measuring platform engagement across 35 days of platform use.</time_frame>
    <description>Platform mood-activity logging across 35 days of possible logging 3x/day</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Actual">11</enrollment>
  <condition>Depression</condition>
  <arm_group>
    <arm_group_label>Adolescent Target Users of Behavioral Activation (BA) App</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <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.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>Behavioral Activation</intervention_name>
    <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.</description>
    <arm_group_label>Adolescent Target Users of Behavioral Activation (BA) App</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Adolescents with PHQ-9 scores between 5 and 15 (Mild to Moderate Range) who do not&#xD;
             report current suicidality (Pine et al., 1999) will be recruited from clinician target&#xD;
             users' practice settings.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Current suicidal ideation or PHQ-9 scores that are below or above the cutoff described&#xD;
             above for adolescents.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>13 Years</minimum_age>
    <maximum_age>17 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>University of Washington</name>
      <address>
        <city>Seattle</city>
        <state>Washington</state>
        <zip>98115</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>August 2022</verification_date>
  <study_first_submitted>November 29, 2018</study_first_submitted>
  <study_first_submitted_qc>December 19, 2018</study_first_submitted_qc>
  <study_first_posted type="Actual">December 21, 2018</study_first_posted>
  <results_first_submitted>July 22, 2022</results_first_submitted>
  <results_first_submitted_qc>August 22, 2022</results_first_submitted_qc>
  <results_first_posted type="Actual">September 16, 2022</results_first_posted>
  <last_update_submitted>August 22, 2022</last_update_submitted>
  <last_update_submitted_qc>August 22, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">September 16, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Washington</investigator_affiliation>
    <investigator_full_name>Jessica Jenness</investigator_full_name>
    <investigator_title>Acting Assistant Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Depression</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol, Statistical Analysis Plan, and Informed Consent Form</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>February 14, 2022</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/33/NCT03783533/Prot_SAP_ICF_000.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <recruitment_details>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 &gt;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.</recruitment_details>
      <group_list>
        <group group_id="P1">
          <title>Adolescents</title>
          <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.&#xD;
Behavioral 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.</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="11"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="7"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="4"/>
              </participants_list>
            </milestone>
          </milestone_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Adolescents</title>
          <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.&#xD;
Behavioral 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.</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="11"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>&lt;=18 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="11"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Between 18 and 65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>&gt;=65 years</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Age</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="15.83" spread="2.14"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex/Gender, Customized</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <title>Female</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="4"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Male</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="4"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Non-binary/Transgender</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
            <class>
              <title>Unknown</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="2"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Ethnicity (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Not Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="6"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="5"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Race (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>American Indian or Alaska Native</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Asian</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Native Hawaiian or Other Pacific Islander</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Black or African American</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                  </measurement_list>
                </category>
                <category>
                  <title>White</title>
                  <measurement_list>
                    <measurement group_id="B1" value="5"/>
                  </measurement_list>
                </category>
                <category>
                  <title>More than one race</title>
                  <measurement_list>
                    <measurement group_id="B1" value="1"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="5"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <title>United States</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="11"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Patient Health Questionnaire-8</title>
          <description>Measure of depression symptoms in the last 2 weeks. Scores range from 0 to 24 with higher scores indicating higher depression symptoms.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="14.44" spread="3.94"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Patient Health Questionnaire-Adolescent (PHQ-8)</title>
        <description>Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms.</description>
        <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>Patient Health Questionnaire-Adolescent (PHQ-8)</title>
          <description>Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="9.60" spread="6.27"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>User Burden Scale</title>
        <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:&#xD;
Access Burden&#xD;
Emotional Burden&#xD;
Financial Burden&#xD;
Mental Burden&#xD;
Physical Burden&#xD;
Privacy Burden&#xD;
Social Burden&#xD;
Time Burden</description>
        <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>User Burden Scale</title>
          <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:&#xD;
Access Burden&#xD;
Emotional Burden&#xD;
Financial Burden&#xD;
Mental Burden&#xD;
Physical Burden&#xD;
Privacy Burden&#xD;
Social Burden&#xD;
Time Burden</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value=".60" spread=".21"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Acceptability of Intervention Measure</title>
        <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.</description>
        <time_frame>Measured within 3-weeks post BA App User Testing</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>Acceptability of Intervention Measure</title>
          <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.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3.55" spread=".51"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Appropriateness of Intervention Measure</title>
        <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.</description>
        <time_frame>Measured within 3-week post BA App User Testing</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>Appropriateness of Intervention Measure</title>
          <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.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3.4" spread=".55"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Feasibility of Intervention Measure</title>
        <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.</description>
        <time_frame>Measured within 3-week post BA App User Testing</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>Feasibility of Intervention Measure</title>
          <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.</description>
          <units>units on a scale</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="3.50" spread=".71"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Secondary</type>
        <title>Platform Engagement</title>
        <description>Platform mood-activity logging across 35 days of possible logging 3x/day</description>
        <time_frame>Measuring platform engagement across 35 days of platform use.</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Adolescents</title>
            <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.&#xD;
Behavioral 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.</description>
          </group>
        </group_list>
        <measure>
          <title>Platform Engagement</title>
          <description>Platform mood-activity logging across 35 days of possible logging 3x/day</description>
          <units>Number of mood-activity logs</units>
          <param>Mean</param>
          <dispersion>Standard Deviation</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="5"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="52.13" spread="45.53"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>4 months</time_frame>
      <desc>No differences in definition or additional information to provide</desc>
      <group_list>
        <group group_id="E1">
          <title>Adolescents</title>
          <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.&#xD;
Behavioral 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.</description>
        </group>
      </group_list>
      <serious_events>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="11"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="11"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>0</frequency_threshold>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="0" subjects_at_risk="11"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>Dr. Jessica Jenness</name_or_title>
      <organization>University of Washington</organization>
      <phone>206-616-7967</phone>
      <email>jennessj@uw.edu</email>
    </point_of_contact>
  </clinical_results>
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03783533
org study id: STUDY00002824
secondary id: P50MH115837
nct id: NCT03783533
lead sponsor: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
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:

      Aim 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.

      Aim 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.

      Aim 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.
allocation: N/A
intervention model: Single Group Assignment
primary purpose: Treatment
masking: None (Open Label)
measure: Patient Health Questionnaire-Adolescent (PHQ-8)
time frame: 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
time frame: 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:
Access Burden
Emotional Burden
Financial Burden
Mental Burden
Physical Burden
Privacy Burden
Social Burden
Time Burden
measure: Acceptability of Intervention Measure
time frame: 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
time frame: 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
time frame: 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.
measure: Platform Engagement
time frame: Measuring platform engagement across 35 days of platform use.
description: Platform mood-activity logging across 35 days of possible logging 3x/day
arm group label: Adolescent Target Users of Behavioral Activation (BA) App
arm group type: Experimental
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.
intervention type: Behavioral
intervention name: Behavioral Activation
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.
arm group label: Adolescent Target Users of Behavioral Activation (BA) App
criteria: 
gender: All
minimum age: 13 Years
maximum age: 17 Years
healthy volunteers: No
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Washington
investigator full name: Jessica Jenness
investigator title: Acting Assistant Professor
mesh term: Depression
sharing ipd: No
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 