A systems framework and modeling approach to predict and manage the mental health effects of a military conflict

Combat-related Post-Traumatic Stress Disorder (PTSD) poses complex challenges for policymakers that systems analysis could help elucidate. True population prevalence and future clinical need are highly uncertain, because individuals' PTSD symptomatology may fluctuate in time. Though we increasingly measure policy outcomes, outcome metrics often address direct, short-term effects, so the impact on long-term prevalence is unclear. The PTSD burden involves a diverse set of actors across domains who independently make decisions based on incomplete information. Systems analysis can indicate how these local aspects of the PTSD burden jointly impact long-term prevalence and identify leverage points for PTSD mitigation. This thesis presents a systems framework and stochastic modeling approach to predict PTSD prevalence and clinical demand over the decades following the current Operations Enduring Freedom (OEF) and Iraqi Freedom (OIF). The system developed in this study incorporates the literature on PTSD symptom dynamics and social factors governing its recognition and treatment in order to identify the structure and dynamics of the PTSD burden. The simulation results indicate the extent to which PTSD is chronic, prevalent, and resistant to treatment. The best-case model predicts that 11-16% of OEF/OIF combat veterans will maintain a long-term need for PTSD services, and as many as 23% of OEF/OIF combat veterans will seek PTSD-related health care at least once in their lives. By controlling for symptom dynamics, model results account for a large component of the variation in empirically observed prevalence rates. Sensitivity and policy analyses show that care-seeking factors tend to have the most significant effect on long-term PTSD prevalence. Model limitations and assumptions are documented, particularly regarding symptom and care-seeking dynamics and parameter interactions, to provide the basis for future empirical and analytical work to elaborate systemic complexities underlying military mental health. The current study specifically addresses OEF/OIF combat-related PTSD, however this approach may be generalized to other populations and mental health concerns. This study has three main policymaking implications. First, study predictions regarding long-term PTSD prevalence and clinical demand can be used for clinical planning and resource allocation over time. Second, baseline model results indicate the long-term limits of current best practice PTSD mitigation efforts. Third, the study identifies effective policy levers by indicating the factors with the greatest direct impact on long-term PTSD prevalence.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2015

Author dc:creator

• Fingerhut, Henry Alan

Advisor dc:contributor.advisor

• Richard C. Larson.

• Institute for Data, Systems, and Society.
• Engineering Systems Division.
• Technology and Policy Program.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/103570

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/103570