ABSTRACT
Youth experiencing homelessness (YEH) face many significant risks that are detrimental to their long-term well-
being and survival, including engaging in negative coping behaviors such as alcohol and drug use. 89% of YEH
report lifetime alcohol use, 77% marijuana use, and 48% report methamphetamine use. Drug and alcohol use
prevalence rates are 2 to 3 times higher among YEH than in their housed peers, leading to poorer mental health
and HIV outcomes for this population. Proximal risk factors for substance use in YEH include street victimization:
39% and 94% have been sexually or physically victimized, respectively; poor mental health: 80% and 74% meet
diagnostic criteria for PTSD and depression, respectively; and risky social networks: 62% of YEH report drug
use with a network member. Another risk factor for substance is affect regulation. Studies of general population
youth find that those with greater negative affect have higher rates of substance use. The role of affect regulation
has rarely been examined for YEH; thus, mediating mechanisms are unclear. It is possible that proximal risk
factors increase negative affect, leading to greater substance use among YEH. Understanding these linkages is
key to developing predictive models of coping. This project uses a socio-ecological framework to examine
linkages between Proximal risk factors, Affect regulation, and Coping behaviors. Specifically, we will identify
factors that influence positive vs. negative coping behavior for YEH to develop a data-driven intervention that: 1)
is relevant to this vulnerable population, and provides individualized support, and 2) can be sustainable outside
the research setting. Our team has pioneered the use of cellphones for ecological momentary assessment (EMA)
in public health research (Khan), and with YEH (Tyler and Olson). Increased cellphone ownership among YEH
alongside growth in urban WiFi hotspot coverage together create a public health opportunity leveraged in this
project's aims: 1) determine whether affect regulation mediates the relationship between YEHs’ proximal risk
factors and coping behaviors, achieved by analyzing survey data and EMA data on Proximal risk factors, Affect
regulation, and Coping behaviors collected via app-based responsive EMA (rEMA) in an observational cohort
study of N=300 YEH over 60 days; 2) develop a data-driven app-based just-in-time personal support intervention
(JIT-PSI) that delivers responsive messaging to mitigate negative coping in favor of positive coping. This aim is
achieved by developing predictive models of coping behavior based on machine learning analyses of Aim 1’s
survey and rEMA data; and conducting focus groups with N=30 YEH and meetings with N=15 agency staff to
design intervention messaging content responsive to a range of coping behaviors; 3) test the feasibility and
acceptability of the JIT-PSI, achieved by an observational cohort study of N=300 YEH over 60 days, using
surveys, alongside cellphone based rEMA, and JIT intervention delivery. Leveraging growing number of public
free WiFi hotspots and shrinking cellphone hardware costs, this project will yield significant public health impacts
by developing a sustainable, JIT behavioral intervention for the prevention of drug use among YEH.
