Firearm violence and associated factors among young adults presenting to emergency departments in three cities: Baseline results from Project SPARK.

Objective: Recent shifts in U.S. violence dynamics call for updated violence epidemiology among general emergency department (ED) samples of young adults. Using baseline data from a multi-site longitudinal study of firearm violence prediction, we describe violence rates and associated factors.

Methods: Staff approached age 18-24 entrants to Level-1 trauma centers in three cities (Flint, Seattle, Philadelphia; 7/2021-5/2023). Consenting participants completed a survey including validated measures of violence experience, firearm-related behaviors, substance use, mental health symptoms, peer/parental/familial behaviors, community violence, and attitudes/norms. We described the sample and examined factors associated with firearm assault (victimization/aggression, including threats).

Results: Across sites, 1506 participants enrolled (41.7. % Black; 33.6 % White; 61.4. % female). Half of participants self-reported past-six-month violent victimization and/or aggression; non-partner violence, and violent victimization were most common. Over half of participants self-reported high-risk substance use, and over half screened positive for post-traumatic stress disorder, depression, and/or anxiety. About 14.4 % self-reported past-six-month firearm assault, and 5.9 % self-reported firearm violence (excluding threats). Adjusted analysis showed community violence exposure was most strongly associated with firearm assault; each one-point-increase corresponded to a 13.7 % (95 %CI: 10.4 %-16.9 %) absolute increase in firearm assault prevalence. Drug misuse, mental health symptoms, firearm carrying, retaliatory attitudes, prosocial attitudes, and family conflict were also associated with firearm assault.

Conclusions: Violence, including firearm assault, is common among young adults entering urban EDs, and is associated with several psychosocial factors. High rates of substance use and mental health symptoms underscore this as a high-need population. Leveraging this information could help tailor interventions and optimize resource allocation.