Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| P50MH115837 | U.S. NIH Grant/Contract | View source |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Class |
|---|---|
| National Institute of Mental Health (NIMH) | NIH |
Not provided
Not provided
Not provided
Not provided
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.
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Adolescent Target Users of Behavioral Activation (BA) App | Experimental | 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Behavioral Activation | Behavioral | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Patient Health Questionnaire-Adolescent (PHQ-8) | Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms. | Measured within 3-weeks post BA App User Testing |
| User Burden Scale | 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:
| Measured within 3-weeks post BA App User Testing |
| Acceptability of Intervention Measure | 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. | Measured within 3-weeks post BA App User Testing |
| Appropriateness of Intervention Measure | 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. | Measured within 3-week post BA App User Testing |
| Feasibility of Intervention Measure | 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. | Measured within 3-week post BA App User Testing |
| Measure | Description | Time Frame |
|---|---|---|
| Platform Engagement | Platform mood-activity logging across 35 days of possible logging 3x/day | Measuring platform engagement across 35 days of platform use. |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Washington | Seattle | Washington | 98115 | United States |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
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.
Not provided
| ID | Title | Description |
|---|---|---|
| FG000 | Adolescents | 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. 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. |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| BG000 | Adolescents | 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. 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. |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Categorical | Count of Participants |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Patient Health Questionnaire-Adolescent (PHQ-8) | Measures symptoms of adolescent depression; Scores range from 0 to 24 with higher scores indicating higher depression symptoms. | Posted | Mean | Standard Deviation | units on a scale | Measured within 3-weeks post BA App User Testing |
|
4 months
No differences in definition or additional information to provide
Not provided
| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Adolescents | 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. 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. |
Not provided
Not provided
Not provided
| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Jessica Jenness | University of Washington | 206-616-7967 | jennessj@uw.edu |
Not provided
| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP_ICF | Yes | Yes | Yes | Study Protocol, Statistical Analysis Plan, and Informed Consent Form | Feb 14, 2022 | Aug 22, 2022 | Prot_SAP_ICF_000.pdf |
Not provided
| ID | Term |
|---|---|
| D003863 | Depression |
| ID | Term |
|---|---|
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
|
| Participants |
|
| Age, Continuous | Mean | Standard Deviation | years |
|
| Sex/Gender, Customized | Count of Participants | Participants |
|
| Ethnicity (NIH/OMB) | Count of Participants | Participants |
|
| Race (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Count of Participants | Participants |
|
| Patient Health Questionnaire-8 | Measure of depression symptoms in the last 2 weeks. Scores range from 0 to 24 with higher scores indicating higher depression symptoms. | Mean | Standard Deviation | units on a scale |
|
|
|
| Primary | User Burden Scale | 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:
| Posted | Mean | Standard Deviation | units on a scale | Measured within 3-weeks post BA App User Testing |
|
|
|
| Primary | Acceptability of Intervention Measure | 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. | Posted | Mean | Standard Deviation | units on a scale | Measured within 3-weeks post BA App User Testing |
|
|
|
| Primary | Appropriateness of Intervention Measure | 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. | Posted | Mean | Standard Deviation | units on a scale | Measured within 3-week post BA App User Testing |
|
|
|
| Primary | Feasibility of Intervention Measure | 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. | Posted | Mean | Standard Deviation | units on a scale | Measured within 3-week post BA App User Testing |
|
|
|
| Secondary | Platform Engagement | Platform mood-activity logging across 35 days of possible logging 3x/day | Posted | Mean | Standard Deviation | Number of mood-activity logs | Measuring platform engagement across 35 days of platform use. |
|
|
|
| 0 |
| 11 |
| 0 |
| 11 |
| 0 |
| 11 |
Not provided
Not provided