Effectiveness Research for Common Mental Disorders in Low and Middle Income Countries: A sequential, multiple assignment randomized trial for non-specialist treatment strategies in Kenya

Project Abstract Mental disorders are a leading cause of global disability, driven primarily by depression and anxiety. Most of the disease burden is in Low and Middle Income Countries LMICs, where 75 percent of adults with mental disorders have no service access. Despite nearly 15 years of efficacy studies showing that local non-specialists can provide evidence-based care for depression and anxiety in LMICs, few studies have advanced to the critical next step identifying how non-specialists might best apply treatments with proven efficacy in the real world using existing delivery platforms and responding to common clinical dilemmas, such as what treatment to start with, and how and when to modify treatment. Our research team has worked in western Kenya for 5 years with a UCSF-Kenya collaboration Family AIDS Care and Education Services FACES that supports integrated HIV services at over 70 primary healthcare facilities in Kisumu County. Primary care populations in Kenya have high prevalence of Major Depressive Disorder MDD 26 percent and Posttraumatic Stress Disorder PTSD 35 percent 2 and 4 times higher than in the U.S., respectively. Given the need for personalized treatment to achieve remission cure or absence of disease and the scarcity of mental health specialists in LMICs, successful reduction of population-level disability caused by depression and anxiety requires 1 evidence-based strategies for first-line and second-line non-remitter treatment delivered by non-specialists, and 2 identification of patient-level moderators of treatment outcome to inform personalized, resource-efficient non-specialist treatment algorithms. To address these needs, we propose to partner with local and national mental health stakeholders in Kenya to identify 1 evidence-based strategies for first-line and second-line treatment delivered by non-specialists integrated with primary care Aim 1, and investigate 2 presumed mediators of treatment outcome Aim 2 and determine 3 patient-level moderators of treatment effect to inform personalized, resource-efficient non-specialist treatment algorithms Aim 3. We will use a Sequential, Multiple Assignment Randomized Trial SMART in which 2,710 participants with MDD, PTSD, or both will be randomized to non-specialist-delivered Interpersonal Psychotherapy IPT or to fluoxetine non-remitters will be re-randomized to switch treatment or to combination therapy. The results of this research will be significant in three ways 1 they will determine the effectiveness of non-specialist delivered first- and second-line treatment for MDD and or PTSD in LMICs, 2 they will investigate presumed mechanisms of action for IPT and fluoxetine in a large population, 3 they will produce predictive algorithms essential for optimal sequencing of treatment for MDD and or PTSD in low resource settings a critical barrier for addressing a leading global cause of disability.