DESCRIPTION (provided by applicant): The burden of mental illness and addictions in the population served by safety net medical facilities is substantial, and cannot be accommodated by specialty mental health facilities. Despite the urgent need to develop effective approaches to organizing, financing, and delivering mental health and addiction services integrated with medical care in this setting, there is a paucity of trained researchers with the necessary skills, training, and background knowledge to both conduct relevant, high impact research, while at the same time understanding the administrative, fiscal, policy, and community stakeholder perspectives needed to translate these findings into clinical practice. This post-doctoral training program aims to increase the number of early career investigators trained in mental health and addictions services research with a safety net medical setting focus, using an interdisciplinary approach embedded in an academic-public sector partnership that has existed for several decades. The proposed fellowship program will select 3 postdoctoral investigators each year to receive 2 years of mentored training for a total of 15 fellows over the 5 year period. The interdisciplinary training would involve faculty from the Departments of Psychiatry and Medicine in the School of Medicine, and from the Schools of Social Work, Nursing, and Public Health. Mentored research activities and safety-net clinical, administrative and policy exposures form the core experience of the program, and will be embedded in, and facilitated by, individually tailored didactics and mentored instruction designed to impart crucially important knowledge and skills.

PUBLIC HEALTH RELEVANCE: By addressing a critical shortfall in investigators, the proposed program will increase translational research designed to bring evidence-based findings to the community of safety net service providers and, hopefully, have a long range impact in improving the delivery of mental health and addictions care in these settings.