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Building A Longitudinal Mental Health Tracking System

Ruzanna Harutyunyan's picture

Building a longitudinal mental health tracking system is a new initiative, that will leverage the power of existing household surveys on behavioral health by embedding detailed modules assessing psychopathology, functioning, and service use.

Several very large longitudinal epidemiologic surveillance programs conduct 70,000 to 250,000 surveys on an ongoing basis in the U.S. general population annually. These programs include the Centers for Disease Control and Prevention’s National Health Interview Survey and Behavioral Risk Factor Surveillance System and the Substance Abuse and Mental Health Administration’s National Survey on Drug Use and Health program.

NIMH can leverage the information gained from these large programs in a cost-efficient manner by over-sampling respondents who screen positive for mental disorders and following up with more detailed modules assessing psychopathology, comorbidities, functioning, service use, and treatment costs. The longitudinal nature of these data would give NIMH the ability to track, over time, the prevalence, incidence, severity, and correlates of mental disorders, and enable analysis of trajectories and trends of disorders, service use, and outcomes. In addition, important subgroups (e.g., racial/ethnic populations, people with autism) and smaller geographic areas (e.g., states and counties) could be over-sampled to provide timely information on health disparities. Such data are critical for targeting future research activities and providing quality assurance that delivered interventions are beneficial.

The longitudinal tracking system is clearly aligned with the NIMH Strategic Plan, specifically Strategic Objective 4: Strengthen the Public Health Impact of NIMH-Supported Research, as well as Strategic Objective 2: Chart Mental Illness Trajectories to Determine When, Where, and How to Intervene. This initiative might include DNA collection from well-phenotyped cases and controls that could help identify genetic variants associated with mental disorders. Following respondents over time could also facilitate translational research to identify risk architecture and trajectories of illness. Likewise, ongoing data collection could assess the impact of salient events (e.g. natural or other disasters, financial shocks, reintegration of returning veterans) on mental health. Finally, a longitudinal tracking system could help NIMH document the impact of the Strategic Plan, and inform Federal, state and local policy.

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Scientific areas of interest include:

* Infrastructure to provide timely data on the prevalence, severity and age of onset of mental disorders and their correlates; overall and across time, geography and life course

* Assessing patterns of mental health service use, quality and outcomes of care, and disparities among diverse populations

* Identifying risk factors for mental illness and trajectories of disorders

* Studying the impact of natural disasters, financial crises, and other events on people with specific mental disorders

* Identifying genetic variants and environmental factors that may contribute to understanding the pathophysiology of mental disorders