Persons with serious mental illness are at significant risk for involvement with the criminal justice system. In a recent Massachusetts study, nearly 30% of a cohort of public mental health service recipients followed for roughly 10 years experienced at least one arrest, and among young cohort members, those between 18 and 25, the rate was 50%.1
Analyses of national data reinforce this point, indicating that persons with severe mental illness are 1.5 times more likely to be jailed than admitted to a psychiatric hospital.2
Efforts to reverse this trend have been substantial; in many locales across the nation, mental health and criminal justice agencies have collaborated in developing a range of prevention and diversion interventions, including a host of jail diversion mechanisms,3
specialized court sessions for defendants with mental illness,4
and re-entry services targeting the unique needs of individuals with serious psychiatric disorders returning to their communities following a period of incarceration.5
In an effort to improve the outcomes of persons with mental illness who have been involved with the justice system, standard evidence-based practices have been tailored to meet the special needs of these “forensically involved” individuals. These efforts have produced the most recent mental health system interventions for this population, in the form of Forensic Assertive Community Treatment (FACT) and Forensic Intensive Case Management (FICM) teams.6
Reviews of the outcomes of these efforts have not been encouraging. Even when highly touted evidence-based practices, such as Assertive Community Treatment, are specially recast as FACTs to address the needs of the so-called “forensic client,” justice system recidivism continues at a disappointing rate.2,7
Among the factors likely contributing to these outcomes are some of the assumptions underlying these programs' design, in particular the tendency of mental health providers and policy makers to ignore the criminal offending and recidivism patterns of justice-involved individuals with mental illness, focusing instead on clinical and service modalities aimed at reducing the psychiatric and substance abuse problems that are believed to be the main contributor to criminal justice involvement8,9
and to the lackluster performance of some re-entry programs.5
An issue often overlooked in this discussion is that instances of arrest experienced by persons with serious mental illness often are not simply a single episode but may instead be part of a larger pattern of criminal justice involvement spanning several years and possibly varying in intensity over that time. This fact is reflected in data from re-entry programs, which report serving the same individuals multiple times, as they cycle through periods of arrest, incarceration, re-entry, and rearrest,6
and reinforced by data from a 10-year longitudinal study of criminal justice involvement among mental service recipients, which found that 68% of those with any arrest were arrested more than once, and a small number of persons experienced at least one arrest in each of the calendar years during which the cohort was observed, with a maximum of 71.1
Understanding the temporal patterning of multiple arrests among offenders with mental illness has the potential to inform the development and implementation of diversion and other services at the interface of the mental health and criminal justice systems. To date, however, no such efforts have been undertaken. This paper demonstrates an approach to identifying such patterns, drawing on “trajectory analysis,” a methodology that has been used by criminological researchers to study long-term patterns of offending.9–11
This paper pursues two goals: the first is to describe the patterns of criminal justice involvement exhibited by a cohort of persons with serious mental illness over a multi-year period; the second is to demonstrate the utility of this modeling approach as a tool for categorizing arrest patterns exhibited by members of this population and, thus, better targeting needed services for them.
With a few exceptions (see Davis et al.12,13
), trajectory analysis has not been applied in mental health services research. For this reason, it is appropriate to review its history and underlying concepts. The technique originates within the developmental criminology community, whose members examine questions such as whether persons who become involved with the justice system as juveniles continue to offend as adults (i.e., “persist,”) or desist from offending. Illustrative examples of such work include research conducted by Sampson and Laub14,15
and Nagin and Land.11
Their research addresses two fundamental questions: First, what are the overall levels and patterns of desistence and persistence as individuals mature into adulthood? Second, in what ways do groups displaying different patterns differ from one another on key theoretically based or other factors?
Trajectory analysis was developed to address these questions, first by identifying mathematically a set of patterns that illustrate trends in persistence and desistence over time, and second by identifying groups of individuals displaying those trends in a way that would allow group membership to be modeled. In the latter respect, trajectory analysis, at least within the framework advanced by Nagin,9
has much in common with cluster analysis, in employing iterative algorithms to converge on a mathematically optimal solution—i.e., the number of groups that best fits the data. However, unlike cluster analysis, where individual characteristics of the unit of analysis are the basis for group membership, the groups identified with trajectory analysis include members' behaviors, such as criminal justice involvement patterns or other behaviors exhibited over an observation period, which are the most similar to one another. As with cluster analysis, group membership can be modeled as a function of predictor variables.
The present study applies the properties of trajectory analysis outlined above to identify such patterns in a large cohort of adults receiving services from a public mental health agency and to determine what service recipient characteristics and offense patterns, if any, differentiate the trajectory-based groups. Information from this analysis has the potential to inform the development of new programs that would better identify the people that would benefit from particular types of interventions at critical times along their life courses.