Inmate characteristics and mental health services: An examination of service utilization and treatment effects

Many individuals incarcerated in the prison system suffer from mental health problems. As the inmate population grows, correctional mental health professionals are being overwhelmed with a population that is more likely than the general public to experience mental health problems (Fazel & Danesh, 2002). To maximize resources, it is important that treatment be offered to inmates who will receive the most benefit (e.g., Andrews, Zinger et al., 1990). Variables that have been found to impact treatment utilization and treatment outcome include demographic variables (e.g., Kessler et al., 2005), help-seeking attitudes, and client expectations (Grencavage & Norcross, 1990). For correctional mental health treatment, risk for recidivism is another variable that is predictive of treatment outcome (Andrews, Zinger et al., 1990). This study examined these variables aiming to gather information necessary to maximize treatment effectiveness. Participants consisted of 278 incarcerated adult offenders from the Kansas Department of Corrections. Inmates who received mental health services while incarcerated and those who have not were included in the study. Variables under investigation include sociodemographic variables (e.g., race, age, educational level, institutional security level, length of prison sentence), attitudes toward help seeking, expectations about mental health treatment, and risk for recidivism. Although several studies have examined inmate characteristics that affect mental health treatment (e.g., Deane et al., 1999; Morgan et al., 2004; Morgan et al., 2007; Williams et al., 2001), the impact of these characteristics on treatment effects remained uninvestigated. The objectives of this study were to identify sociodemographic variables that affect service utilization; identify if correctional mental health treatment impacts treatment outcome variables (improves institutional behavior, reduces risk for recidivism) and identify inmate characteristics (help-seeking attitudes, treatment fears, and client expectations) that impact treatment outcome variables; and identify if inmate characteristics impact treatment satisfaction. Logistic regression analysis identified security level as the most powerful predictor of mental health service utilization. Hierarchical linear regression analyses indicated that the amount of mental health treatment an inmate received was associated with institutional behavior (number and severity of disciplinary infractions). In addition, help-seeking attitudes was associated with institutional behavior and risk for recidivism. Results of standard multiple linear regression analyses indicated that treatment satisfaction was associated with inmate characteristics (i.e., help-seeking attitudes and client expectations). These results indicated that treatment utilization is impacted by sociodemographic variables. They also showed that certain outcome variables might be affected by the amount of mental health treatment and inmate characteristics. As a result, correctional psychologists may be better able to predict which inmates are more likely to utilize mental health services and which inmates will receive the most benefit from services. Findings and conclusions are discussed in light of limitations of the study.