Using the Multiphase Optimization Strategy to Adapt Cognitive Processing Therapy

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Background: One third of post-9/11 Veterans in VHA suffer from posttraumatic stress disorder (PTSD), and among those who initiate Cognitive Processing Therapy (CPT), up to 70% drop out before receiving an adequate dose of treatment. Unfortunately, Veterans who drop out prematurely may never receive the most effective components of CPT. Thus, there is an urgent need to use empirical approaches to identify the most effective components of CPT, so that CPT can be adapted into a briefer format. The long-term goal of this line of research is to adapt, test, and implement brief, evidence-based treatment for Veterans with PTSD. The overall objective of the current application is to adapt CPT into a brief, effective format. The rationale is that identifying the most effective intervention components and delivering only those components will make CPT deliverable in a shorter timeframe, thus improving efficiency, reducing drop-out related to poor treatment response, and ensuring that Veterans receive the most beneficial components of treatment, which will significantly improve their quality of life. Significance/Impact: Upon completion of this project, we expect to have produced an empirically-based, brief version of CPT. This contribution is likely to improve clinical practice for Veterans with PTSD by providing the most effective components at an earlier session, thus increasing the overall effectiveness of treatment and mitigating the negative consequences of untreated PTSD, such as lost productivity, substance use, later-life physical disability, reduced quality of life, and increased risk of suicide. Innovation: The status quo for PTSD treatment is lengthy psychotherapy in a specialty mental health setting, which is rarely delivered in its entirety. The proposed research is innovative because it will use a novel engineering-inspired framework, the multiphase optimization strategy (MOST), to adapt this effective psychotherapy into a brief format. Developing a brief, empirically-based version of CPT will open new horizons for PTSD treatment by expanding CPT access to treatment settings where lengthier treatments are not feasible. It will also provide effective options for Veterans who desire a briefer treatment course. Specific Aims: Specific Aim 1: Using a highly efficient experimental design, identify which of five CPT components contribute meaningfully to reduction in PTSD symptoms. We will test the effectiveness of each component and each two-way interaction between components. Specific Aim 2: Identify mediators of component effectiveness. We hypothesize that effects will be mediated by engagement/adherence and change in posttraumatic cognitions. Exploratory Aim 1: Identify moderators of component effectiveness. Methodology: The MOST is an innovative engineering-inspired framework that uses an optimization trial to assess the performance of individual intervention components within a multicomponent intervention such as CPT. Guided by the MOST framework, the goal of the proposed project is to empirically inform an abbreviated version of CPT via a highly efficient fractional factorial design. Veterans (N = 270) at two VAMCs with clinically significant PTSD symptoms who meet minimal inclusion/exclusion criteria will be randomized to receive one or more CPT components. This design will test the effectiveness of each component and each two-way interaction between components, as measured by PTSD symptom reduction on the Clinician-administered PTSD scale for DSM-5 (CAPS-5) across six months of follow-up. Implementation/Next Steps: Upon completion of these aims, our expected outcome is an adapted, abbreviated version of CPT that consists of the most effective elements of the intervention. The adapted intervention will be primed for a future large scale, fully powered effectiveness trial. The adapted intervention can be easily disseminated through the VA CPT training program and will have a positive impact on the health and wellbeing of Veterans with PTSD.