Mental health courts have recently emerged with goals to reduce recidivism and improve clinical outcomes for people with serious mental illness in the criminal justice system. The present study is a review of mental health court literature assessing their effectiveness in reducing recidivism and improving clinical outcomes for participants using meta-analytic techniques. A total of 20 studies that included sufficient information to compute the standardized mean difference effect size, focused on adult populations, and were within the United States were included in the analysis. Only experimental and quasi-experimental research designs were obtained. Using Cohen's d (1988) guidelines, mental health courts were found to have a small effect on reducing recidivism (0.32, p<.05) and a nonsignificant effect for improving clinical outcomes for participants. Several moderator analyses were conducted and indicated that the nature of the control group (whether they were a treatment as usual or participants who "opted-out") was found to be significant between groups (Q=22.33, p<.001) as a possible moderating effect.

Adults with mental illnesses are at an increased risk to be diagnosed with one or more comorbid physical illnesses compared to the general population. Much of the disparities faced by adults with serious mental illnesses (SMI) can be attributed to medication side effects, increased risk for metabolic diseases, inability to communicate about severity and monitor physical health symptoms, poor health behaviors, high rates of smoking, and poor quality health care. The rate of physical illnesses for adults with mental illnesses are even higher among those who have been involved with the criminal justice system. In order to understand the relationship between physical and mental illnesses, longitudinal study designs are needed. Longitudinal studies can provide greater understanding of the temporal relationship of physical and mental illnesses. Despite the benefits of longitudinal studies, there also are challenges, including missing data. The first manuscript of this dissertation explores the physical and mental health status of adults with mental illnesses. Secondary data were used from three different studies: a sample of adults with SMI enrolled in a mental health court jail diversion program (n=91); a sample of Medicaid enrollees with SMI in Florida (n=688) who were part of a larger Substance Abuse and Mental Health Services Administration (SAMHSA) study; and a sample of inpatient and outpatient adults with SMI from five different study sites (n=969). The samples were combined into two data sets, consisting of the jail diversion sample and the SAMHSA sample, and the jail diversion sample and the 5-site sample. Participants in these samples answered questions on the Short-Form Health Survey (SF-12), recent arrests, drug and alcohol use, socio-demographic information, and mental illness symptom severity (measured only in the criminal justice and 5-site samples). Overall, the mental and physical health status scores were significantly lower for all of the participants compared to the general population mean scores. The participants reporting a recent arrest had a higher physical health score compared to those who did not have a recent arrest, and in the jail diversion and 5-site sample, had a lower mental health status score than those without a recent arrest. After taking age, drug and alcohol use, and psychiatric symptom severity into account, arrest was no longer associated with the physical health status score in either of the data sets. In the jail diversion and 5-site data set, arrest was still significantly associated with mental health status score after controlling for age, drug and alcohol use, and psychiatric symptom severity. The second manuscript of this dissertation explores the analysis of missing data in a longitudinal study to determine the missing data mechanisms and missing data patterns, and subsequently, how to prepare the data for analysis by using multiple imputation or maximum likelihood estimation. Secondary data were drawn from the same jail diversion sample as in the first manuscript. Data were collected at baseline, three months, six months, and nine months. Only participants with the potential to have data collected at these time points were included (n=50). Analysis revealed missing data due to missing item-level information, missing participant data at one time point but complete data at a subsequent time point, and missing participant data for those who dropped out of the study completely. The missing data mechanism for the missing item-level data were missing completely at random, whereas the participant-level missing data were missing at random. Multiple imputation was used for the item-level data and for the participant-level missing data. Maximum likelihood estimation was also used for the participant-level missing data and compared to the multiple imputation results. Findings suggest that multiple imputation produced more accurate parameter estimates, possibly due to the small sample size. The findings from this study indicate that more research needs to be done to fully understand the physical illnesses experienced by adults with mental illnesses who are involved with the criminal justice system. Understanding mental and physical illness comorbidity is important in public health as it dictates appropriate treatments and training for behavioral health practitioners and staff. In addition, missing data in longitudinal studies cannot be ignored, as it can bias the results, and appropriate techniques for exploring the missing data must be used. When missing data is ignored in analyses, the subsequent results can be incorrect and unable to detect treatment effects, thereby preventing effective programs from receiving necessary funding. In addition, ignoring missing data can impact funding for behavioral health services by underestimating the prevalence and severity of mental illnesses. Future research should focus on exploring how mental and physical health are related in adults with a recent arrest compared to the general population, and ways to integrate services to address both mental and physical health.