Predicting Homelessness Among U.S. Army Soldiers No Longer on Active Duty

• Main Authors: Gildea, S.M (Author), Hwang, I. (Author), Kennedy, C.J (Author), Kessler, R.C (Author), King, A.J (Author), Koh, K.A (Author), Luedtke, A. (Author), Montgomery, A.E (Author), O'Brien, R.W (Author), Petriceks, A.H (Author), Petukhova, M.V (Author), Sampson, N.A (Author), Stein, M.B (Author), Ursano, R.J (Author)
• Format: Article
• Language: English
• Published: NLM (Medline) 2022
• Subjects: homeless person; Homeless Persons; human; Humans; Longitudinal Studies; longitudinal study; military personnel; Military Personnel; Prospective Studies; prospective study; risk assessment; Risk Assessment; United States
• Online Access: View Fulltext in Publisher
• ISBN: 18732607 (ISSN)
• DOI: 10.1016/j.amepre.2021.12.028

INTRODUCTION: The ability to predict and prevent homelessness has been an elusive goal. The purpose of this study was to develop a prediction model that identified U.S. Army soldiers at high risk of becoming homeless after transitioning to civilian life based on information available before the time of this transition. METHODS: The prospective cohort study consisted of observations from 16,589 soldiers who were separated or deactivated from service and who had previously participated in 1 of 3 baseline surveys of the Army Study to Assess Risk and Resilience in Servicemembers in 2011-2014. A machine learning model was developed in a 70% training sample and evaluated in the remaining 30% test sample to predict self-reported homelessness in 1 of 2 Longitudinal Study surveys administered in 2016-2018 and 2018-2019. Predictors included survey, administrative, and geospatial variables available before separation/deactivation. Analysis was conducted in November 2020-May 2021. RESULTS: The 12-month prevalence of homelessness was 2.9% (SE=0.2%) in the total Longitudinal Study sample. The area under the receiver operating characteristic curve in the test sample was 0.78 (SE=0.02) for homelessness. The 4 highest ventiles (top 20%) of predicted risk included 61% of respondents with homelessness. Self-reported lifetime histories of depression, trauma of having a loved one murdered, and post-traumatic stress disorder were the 3 strongest predictors of homelessness. CONCLUSIONS: A prediction model for homelessness can accurately target soldiers for preventive intervention before transition to civilian life. Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.