ORCID
0000-0002-8159-428X
Date of Award
Spring 2025
Language
English
Embargo Period
4-29-2026
Document Type
Dissertation
Degree Name
Doctor of Public Health (DrPH)
College/School/Department
School of Public Health
Program
Public Health
First Advisor
Melissa Tracy
Committee Members
Rachael de Long, Lindsey Disney, Daphney Zois
Keywords
mental health, refugee, agent-based modeling, multi-tier intervention, intervention, simulation
Abstract
Increasing numbers of people are fleeing political violence and becoming refugees who resettle all around the world.Compared to the general population in the countries where they resettle, refugees disproportionately suffer from depression and higher trauma-related mental health symptoms including post-traumatic stress disorder (PTSD) due to the experiences that led to their refugee status, as well as post-migration stressors, disadvantages in multiple social determinants of health, and lack of social support. New York City has received refugees from over 50 countries and may require policy and infrastructure changes to meet refugee mental health needs, especially in face of the recent surge in migrant admissions.Previous mental health interventions for refugees have usually focused on only individual, interpersonal, or community factors, have not examined potential positive changes after traumatic events, have targeted clinical populations, and have lacked sustainability in their effects. Complex multi-tier interventions that incorporate social determinants of health, trauma-informed and culture-informed care, along with medical interventions are recommended. However, not enough information is known about the effectiveness of these complex systemic interventions on decreasing depression and PTSD and increasing post-traumatic growth (PTG), given limited program evaluation data.
For this dissertation, I conducted a systematic review and meta-analysis of the existing interventions for refugee mental health in the U.S. following the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. Informed by findings from the systematic review and meta-analysis, I further developed an agent-based simulation model to: 1) simulate the most relevant risk and protective factors of depression, PTSD, and PTG for refugees aged 15-64 years who resettled in NYC in 2019 to 2023, 2) simulate the relevant existing resources and infrastructure in NYC for refugee mental health, and 3) compare population-level mental health outcomes under the status quo model versus seven intervention schemes. The resulting ABM successfully replicated the refugee population, the influence of key mental health factors, and the patterns of refugee mental health outcomes.
Findings from the systematic review and meta-analysis indicated that most existing interventions in the U.S. were community-based educational programs or trauma-focused psychotherapies. Psychotherapies were more effective in improving refugee mental health compared to other interventions, while multi-level interventions were understudied. Overall, interventions significantly decreased PTSD (SMD= -1.08, 95% CI= -1.70, -0.47; I2= 70%) and depression (SMD= -0.51, 95%CI= -0.9, -0.13, I2=69%) while also increasing social support and mental health service use among refugees. Findings from the ABM experiments suggested that combining a 200% increase in referral rate with a 100% increase in the number of service programs and a 50% increase in mental health service effectiveness resulted in a significant 8.8% decrease in depression prevalence (to 22.4%, 95% CrI: 19.7%, 25.1%) and a significant 13.7% decrease in PTSD prevalence (to 27.2%, 95% CrI: 24.2%, 30.3%). Combined interventions to increase mental health service referrals, support and mental health service availability, and mental health service effectiveness can achieve more to reduce refugee depression and PTSD prevalence than any intervention implemented in isolation. According to our agent-based model, increasing referral rates alone, even if with a maximum increase, was not capable of significantly reducing population depression or PTSD prevalence. Considering resources, time, and cost, public health practitioners could use simulated results to plan multi-tier intervention schemes to address specific goals in refugee mental health. This dissertation has employed an innovative approach that introduced a systems methodology to refugee mental health research and laid the groundwork for future policy experiments for improving refugee mental health in NYC.
License
This work is licensed under the University at Albany Standard Author Agreement.
Recommended Citation
Huang, Bishan, "Simulating a Multi-tier Intervention for Refugee Mental Health Using Agent-based Modeling" (2025). Electronic Theses & Dissertations (2024 - present). 169.
https://scholarsarchive.library.albany.edu/etd/169
