T.E.A.M. Feasibility and Efficacy Study 2.0
Last updated on July 2021Recruitment
- Recruitment Status
- Active, not recruiting
- Estimated Enrollment
- Same as current
Summary
- Conditions
- Depression, Anxiety
- Type
- Observational
- Design
- Observational Model: Case-OnlyTime Perspective: Prospective
Participation Requirements
- Age
- Between 18 years and 125 years
- Gender
- Both males and females
Description
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 s...
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.
Tracking Information
- NCT #
- NCT03694106
- Collaborators
- Stanford University
- Investigators
- Principal Investigator: Maor Katz, MD Feeling Good Institute Principal Investigator: Alex Clarke, MD Feeling Good Institute
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