The majority of people who die by suicide do so with firearms, and there were more firearm suicides in America in 2017 than there were homicides committed by any method. Combined.
Those shocking numbers from the FBI and American Foundation for Suicide Prevention are the impetus for two UC Merced professors from very different disciplines to join forces to try and predict who is most likely to commit suicide using a gun.
Professor Sidra Goldman-Mellor, a public health researcher with the School of Social Sciences, Humanities and Arts and the Health Sciences Research Institute, has teamed up with applied math Professor Harish Bhat with the School of Natural Sciences to sift through more than 44 million California hospital records, looking at patients’ basic demographics, visits, admissions and emergency-room visits and outcomes.
Funded by a $10,000, one-year grant from the UC Firearm Violence Prevention Research Center at UC Davis, the researchers aim to design an algorithm that can tell clinicians what to look for among potential at-risk patients and who to target for interventions.
The Centers for Disease Control found that national suicide rates have increased by 25 percent over the past 20 years, and 54 percent of all suicides are among people who had no known mental health condition. Often, those people were never diagnosed with such conditions, so they were never treated for them.
