T.E.A.M. Feasibility and Efficacy Study 2.0

Depression, Anxiety

T.E.A.M. psychotherapy was developed by one of the founders of cognitive therapy, David Burns and builds on traditional CBT with an emphasis on T = Testing, E = Empathy, A = Agenda Setting (assessing and building motivation) and M = Methods (including cognitive and behavioral methods). Because TEAM therapy is a data-driven therapy, its delivery hinges on the use of symptom measures and measures of the therapeutic alliance at every session with every patient. These measures are now available for collection thru computerized forms, making their collection and review considerably more accessible and efficient for the patient and therapist. The following hypotheses will be tested: 1. TEAM psychotherapy using computerized measurement collection is safe and feasible. 2. TEAM psychotherapy using computerized measurement collection shows evidence of efficacy by exploratory non inferiority testing compared to benchmark studies with similar psychotherapeutic modalities 3. Evidence for efficacy is strong enough to justify pursuit of an experimental randomized controlled clinical trial of TEAM therapy for major depressive disorder versus treatment as usual.

A gap currently exists between the technology available for collecting psychotherapy data and the application of this technology to psychotherapeutic settings to enhance treatment outcomes. A novel integration of Cognitive Behavior Therapy (CBT) informed psychotherapy and digitized data collection systems called T.E.A.M. therapy exists that bridges this gap and has yet to be tested. The purpose of this study is to explore whether TEAM CBT appears safe and feasible and has results similar to comparable and similar benchmark studies. This outcome will provide pilot data and a rationale for whether to pursue a separate randomized controlled trial in the future. We will compare the results of TEAM therapy using electronic data collection to similar psychotherapeutic treatments for common psychiatric problems such as depression, anxiety, relationship conflicts and maladaptive behaviors. We will also explore the data for its use in predictive modeling. This study is part of a wider goal of developing best practices in dissemination of standardized measurement based psychotherapies that are effective and use technology via computerized delivery systems guided by therapists. It is hoped that with computer based measurement systems for psychotherapy, more accurate and frequent information for therapists is available to modify earlier and more effectively their approaches. The measurement based systems will also allow performance by psychotherapists to be measured accurately and enable a type of machine based learning environment with feedback systems in place to improve providers' patient care in a more precise and personalized way.

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