With more than 13% of adolescents diagnosed with depressive disorders each year, prevention of depressive disorders has become a key priority for the NIMH. Unfortunately, we have no widely available interventions to reduce morbidity and mortality (e.g. public health impact). To address this need, we developed a multi-health system ?collaboratory? to develop and evaluate the primary care based-technology ?behavioral vaccine,? Competent Adulthood Transition with Cognitive-Behavioral Humanistic and Interpersonal Therapy (CATCH-IT) (14 adolescent, 4 parent modules). Using this health-system collaboratory model, CATCH-IT demonstrated evidence of efficacy in prevention of depressive episodes in phase-three clinical trials in the United States and China. However, like many ?package? interventions, CATCH-IT became larger and more complex across efficacy trials. Thus, adolescents and parents were less willing to complete all 18 modules, suggesting adolescent dose ?tolerability? issues (e.g. satisfaction, acceptability and resource use, ?time as cost?). Similarly, primary care practices have ?scalability? challenges (acceptability, feasibility, resource use, cost), resulting in declining REACH (percent of at-risk youth who complete intervention). To prepare for implementation studies and dissemination, we need to address adolescent tolerability and practice/health system scalability, while preserving efficacy. Multiphase Optimization Strategy (MOST) uses a systematic analytic approach and a factorial randomized clinical trial design to address efficacy, tolerability, and scalability, simultaneously. We will use a MOST approach to optimize CATCH-IT for the prevention of depression (indicated prevention, i.e., elevated symptoms of depression) in practices and health systems representative of US geography and population. The theoretically grounded components of CATCH-IT selected for study and optimization are: behavioral activation, cognitive therapy, interpersonal psychotherapy, and parent program. We will use a 4-factor (2x2x2x2) fully crossed factorial design with N=16 cells (20 per cell, 15% dropout) to evaluate the contribution of each component. We propose to randomize N=378 (N=189) from each health system site. The at-risk youth will be high school students 13 through 18 years old, not currently experiencing a mood disorder, but with subsyndromal symptoms of depression (moderate to high risk). Using the efficient factorial design, we can assess the contribution to prevention efficacy of each component. Thus, the MOST study design will enable us to eliminate non-contributing components while preserving efficacy and to optimize CATCH-IT by strengthening tolerability and scalability by reducing ?resource use.? By reducing resource use, we anticipate satisfaction and acceptability will also increase, preparing the way for an implementation trial and eventual US Preventive Services Task Force endorsement to support dissemination. Thus, our primary question is whether one component, or perhaps two, can demonstrate an equivalent effect to combinations of other components in terms of efficacy, whilst also demonstrating superior adolescent/family tolerability scalability over a 12-month follow-up.

Public Health Relevance

Prevention of depressive disorders has become a key priority for the NIMH, but we have no widely available public health strategy to reduce morbidity and mortality. To address this need, we developed and evaluated the primary care based-technology ?behavioral vaccine,? Competent Adulthood Transition with Cognitive-Behavioral Humanistic and Interpersonal Therapy (CATCH- IT). We will engage N=4 health systems representative of the United States health care system, and conduct a factorial design study to optimize the intervention in preparation for an implementation study and eventual dissemination.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
Project #
Application #
Study Section
Special Emphasis Panel (ZMH1)
Program Officer
Reider, Eve
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Illinois at Chicago
Schools of Medicine
United States
Zip Code