The New England Journal of Statistics in Data Science

In this paper, we present the U.S. Mental Health Dashboard, an R Shiny web application that facilitates exploratory data analysis of U.S. mental health data collected through national surveys. Mental health affects almost every aspect of people’s lives including their social relationships, substance use, academic success, professional productivity, and physical wellness. Even so, mental illnesses are often perceived as less legitimate or serious than physical diseases, and as a result of this stigmatization, many people suffer in silence without access to proper treatment. To address the lack of accessible healthcare information related to mental illness, the U.S. Mental Health Dashboard presents dynamic visualizations, tables, and choropleth maps of the prevalence and geographic distribution of key mental health metrics based on data from the National Survey on Drug Use and Health (NSDUH) and Behavioral Risk Factor Surveillance System (BRFSS). National and state-level estimates are provided for the civilian, non-institutionalized adult population of the United States as well as within relevant demographic subpopulations. By demonstrating the pervasiveness of mental illness and stark health inequities between demographic groups, this application aims to raise mental health awareness and reduce self-blame and stigmatization, especially for individuals that may inherently be at high risk. The U.S. Mental Health Dashboard has a wide variety of potential use cases: to illustrate to individuals suffering from mental illness and those in close proximity to them that they are not alone, identify subpopulations with the biggest need for mental health care, and help epidemiologists planning studies identify the target population for specific mental illness symptoms.