Topic: Behavioral Health Stigma: Breaking the Code with Stigma Index
Speaker: Farah Tokmic
Abstract: Social labeling of people with behavioral health disorders falls under the umbrella of “stigma”, a fundamental cause of population health inequalities that plays a key role in limiting the access to behavioral healthcare. Currently, the U.S. spends an estimated $201B on behavioral health disorders making it the number one most expensive medical condition. In any given year, 43.8M Americans experience a behavioral health disorder. More than half of them receive no treatment mainly because of their fear of being socially disgraced or stigmatized against. This research proposes a novel computational model that demonstrates the potential for using machine learning classification to measure population-level stigma, as a complement to traditional research methods. The research goal is to develop the stigma index, an easy-to-administer shared measurement system that (1) provides data-driven insights on the prevalence of stigma, and (2) assists healthcare decision-makers in improving both the health of populations and the patient experience of care.