LAUSR

Homelessness is a public health crisis both nationally, in the United States, and internationally. Nevertheless, due to the hidden vulnerabilities of persons who are without shelter, little is known about their experiences during periods of homelessness. The present research adopts a network approach that conceptualizes how the major risk factors of homelessness interact, namely substance abuse problems, poor mental health, disability, and exposure to physical or sexual violence by an intimate partner. Our analysis draws on a large demographic survey of over 5,000 unsheltered homeless persons conducted in 2017 by the Los Angeles Homeless Services Authority. We estimated a network structure for 12 survey items tapping individual risk using the graphical least absolute shrinkage and selection operator algorithm. We then examined network centrality metrics and implemented a community detection algorithm to detect communities in the network. Our results indicated that mental illness and intimate partner violence (IPV) are central measures that connect all other mental and physical health variables together and that post-traumatic stress disorder and IPV are both highly affected by changes in any part of the network and, in turn, affect changes in other parts of the network. A community detection analysis derived four communities characterized by disability, sexual victimization and health, substance use, and mental health issues. Finally, a directed acyclic graph revealed that drug abuse and physical disability were key drivers of the overall system. We conclude with a discussion of the major implications of our findings and suggest how our results might inform programs aimed at homelessness prevention and intervention.