The use of propensity scores to control for pretreatment imbalances on observed variables in non-randomized or observational studies examining the causal effects of treatments or interventions has become widespread over the past decade. For settings with two conditions of interest such as a treatment and a control, inverse probability of treatment weighted (IPTW) estimation with propensity scores estimated via boosted models has been shown in simulation studies to yield causal effect estimates with desirable properties. There are tools (e.g., the twang package in R) and guidance for implementing this method with two treatments. However, there is not such guidance for analyses of three or more treatments. The goals of this paper are two-fold: (1) to provide step-by-step guidance for researchers who want to implement propensity score weighting for multiple treatments and (2) to propose the use of generalized boosted models (GBM) for estimation of the necessary propensity score weights. We define the causal quantities that may be of interest to studies of multiple treatments and derive weighted estimators of those quantities. We present a detailed plan for using GBM to estimate propensity scores and using those scores to estimate weights and causal effects. Tools for assessing balance and overlap of pretreatment variables among treatment groups in the context of multiple treatments are also provided. A case study examining the effects of three treatment programs for adolescent substance abuse demonstrates the methods.

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The authors reviewed 29 studies that provide prevalence estimates of posttraumatic stress disorder (PTSD) among service members previously deployed to Operations Enduring and Iraqi Freedom and their non-U.S. military counterparts. Studies vary widely, particularly in their representativeness and the way PTSD is defined. Among previously deployed personnel not seeking treatment, most prevalence estimates range from 5 to 20%. Prevalence estimates are generally higher among those seeking treatment: As many as 50% of veterans seeking treatment screen positive for PTSD, though much fewer receive a PTSD diagnosis. Combat exposure is the only correlate consistently associated with PTSD. When evaluating PTSD prevalence estimates among this population, researchers and policymakers should carefully consider the method used to define PTSD and the population the study sample represents.

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This review summarizes the epidemiology of posttraumatic stress disorder (PTSD) and related mental health problems among persons who served in the armed forces during the Iraq and Afghanistan conflicts, as reflected in the literature published between 2009 and 2014. One-hundred and sixteen research studies are reviewed, most of which are among non-treatment-seeking US service members or treatment-seeking US veterans. Evidence is provided for demographic, military, and deployment-related risk factors for PTSD, though most derive from cross-sectional studies and few control for combat exposure, which is a primary risk factor for mental health problems in this cohort. Evidence is also provided linking PTSD with outcomes in the following domains: physical health, suicide, housing and homelessness, employment and economic well-being, social well-being, and aggression, violence, and criminality. Also included is evidence about the prevalence of mental health service use in this cohort. In many instances, the current suite of studies replicates findings observed in civilian samples, but new findings emerge of relevance to both military and civilian populations, such as the link between PTSD and suicide. Future research should make effort to control for combat exposure and use longitudinal study designs; promising areas for investigation are in non-treatment-seeking samples of US veterans and the role of social support in preventing or mitigating mental health problems in this group.